Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol

Identifying and Assessing Physiological... | F1000Research "use strict";function _typeof(t){return(_typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}!function(){var t=function(){var t,e,o=[],n=window,r=n;for(;r;){try{if(r.frames.__tcfapiLocator){t=r;break}}catch(t){}if(r===n.top)break;r=r.parent}t||(!function t(){var e=n.document,o=!!n.frames.__tcfapiLocator;if(!o)if(e.body){var r=e.createElement("iframe");r.style.cssText="display:none",r.name="__tcfapiLocator",e.body.appendChild(r)}else setTimeout(t,5);return!o}(),n.__tcfapi=function(){for(var t=arguments.length,n=new Array(t),r=0;r 3&&2===parseInt(n[1],10)&&"boolean"==typeof n[3]&&(e=n[3],"function"==typeof n[2]&&n[2]("set",!0)):"ping"===n[0]?"function"==typeof n[2]&&n[2]({gdprApplies:e,cmpLoaded:!1,cmpStatus:"stub"}):o.push(n)},n.addEventListener("message",(function(t){var e="string"==typeof t.data,o={};if(e)try{o=JSON.parse(t.data)}catch(t){}else o=t.data;var n="object"===_typeof(o)&&null!==o?o.__tcfapiCall:null;n&&window.__tcfapi(n.command,n.version,(function(o,r){var a={__tcfapiReturn:{returnValue:o,success:r,callId:n.callId}};t&&t.source&&t.source.postMessage&&t.source.postMessage(e?JSON.stringify(a):a,"*")}),n.parameter)}),!1))};"undefined"!=typeof module?module.exports=t:t()}(); dataLayer = dataLayer || []; // Standard GTM initialization - Google Consent Mode handles consent automatically (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl+ '>m_auth=hzk0Vc3qFsQYhCrIoHz68A>m_preview=env-1>m_cookies_win=x';f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-MWFK8L5J'); ;window.NREUM||(NREUM={});NREUM.init={distributed_tracing:{enabled:true},privacy:{cookies_enabled:true},ajax:{deny_list:["bam.nr-data.net"]}}; ;NREUM.loader_config={accountID:"438030",trustKey:"438030",agentID:"772317073",licenseKey:"97f8f67f26",applicationID:"772317073"} ;NREUM.info={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net",licenseKey:"97f8f67f26",applicationID:"772317073",sa:1} ;/*! For license information please see nr-loader-spa-1.236.0.min.js.LICENSE.txt */ (()=>{"use strict";var e,t,r={5763:(e,t,r)=>{r.d(t,{P_:()=>l,Mt:()=>g,C5:()=>s,DL:()=>v,OP:()=>T,lF:()=>D,Yu:()=>y,Dg:()=>h,CX:()=>c,GE:()=>b,sU:()=>_});var n=r(8632),i=r(9567);const o={beacon:n.ce.beacon,errorBeacon:n.ce.errorBeacon,licenseKey:void 0,applicationID:void 0,sa:void 0,queueTime:void 0,applicationTime:void 0,ttGuid:void 0,user:void 0,account:void 0,product:void 0,extra:void 0,jsAttributes:{},userAttributes:void 0,atts:void 0,transactionName:void 0,tNamePlain:void 0},a={};function s(e){if(!e)throw new Error("All info objects require an agent identifier!");if(!a[e])throw new Error("Info for ".concat(e," was never set"));return a[e]}function c(e,t){if(!e)throw new Error("All info objects require an agent identifier!");a[e]=(0,i.D)(t,o),(0,n.Qy)(e,a[e],"info")}var u=r(7056);const d=()=>{const e={blockSelector:"[data-nr-block]",maskInputOptions:{password:!0}};return{allow_bfcache:!0,privacy:{cookies_enabled:!0},ajax:{deny_list:void 0,enabled:!0,harvestTimeSeconds:10},distributed_tracing:{enabled:void 0,exclude_newrelic_header:void 0,cors_use_newrelic_header:void 0,cors_use_tracecontext_headers:void 0,allowed_origins:void 0},session:{domain:void 0,expiresMs:u.oD,inactiveMs:u.Hb},ssl:void 0,obfuscate:void 0,jserrors:{enabled:!0,harvestTimeSeconds:10},metrics:{enabled:!0},page_action:{enabled:!0,harvestTimeSeconds:30},page_view_event:{enabled:!0},page_view_timing:{enabled:!0,harvestTimeSeconds:30,long_task:!1},session_trace:{enabled:!0,harvestTimeSeconds:10},harvest:{tooManyRequestsDelay:60},session_replay:{enabled:!1,harvestTimeSeconds:60,sampleRate:.1,errorSampleRate:.1,maskTextSelector:"*",maskAllInputs:!0,get blockClass(){return"nr-block"},get ignoreClass(){return"nr-ignore"},get maskTextClass(){return"nr-mask"},get blockSelector(){return e.blockSelector},set blockSelector(t){e.blockSelector+=",".concat(t)},get maskInputOptions(){return e.maskInputOptions},set maskInputOptions(t){e.maskInputOptions={...t,password:!0}}},spa:{enabled:!0,harvestTimeSeconds:10}}},f={};function l(e){if(!e)throw new Error("All configuration objects require an agent identifier!");if(!f[e])throw new Error("Configuration for ".concat(e," was never set"));return f[e]}function h(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");f[e]=(0,i.D)(t,d()),(0,n.Qy)(e,f[e],"config")}function g(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");var r=l(e);if(r){for(var n=t.split("."),i=0;i {r.d(t,{D:()=>i});var n=r(50);function i(e,t){try{if(!e||"object"!=typeof e)return(0,n.Z)("Setting a Configurable requires an object as input");if(!t||"object"!=typeof t)return(0,n.Z)("Setting a Configurable requires a model to set its initial properties");const r=Object.create(Object.getPrototypeOf(t),Object.getOwnPropertyDescriptors(t)),o=0===Object.keys(r).length?e:r;for(let a in o)if(void 0!==e[a])try{"object"==typeof e[a]&&"object"==typeof t[a]?r[a]=i(e[a],t[a]):r[a]=e[a]}catch(e){(0,n.Z)("An error occurred while setting a property of a Configurable",e)}return r}catch(e){(0,n.Z)("An error occured while setting a Configurable",e)}}},6818:(e,t,r)=>{r.d(t,{Re:()=>i,gF:()=>o,q4:()=>n});const n="1.236.0",i="PROD",o="CDN"},385:(e,t,r)=>{r.d(t,{FN:()=>a,IF:()=>u,Nk:()=>f,Tt:()=>s,_A:()=>o,il:()=>n,pL:()=>c,v6:()=>i,w1:()=>d});const n="undefined"!=typeof window&&!!window.document,i="undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self.navigator instanceof WorkerNavigator||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis.navigator instanceof WorkerNavigator),o=n?window:"undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis),a=""+o?.location,s=/iPad|iPhone|iPod/.test(navigator.userAgent),c=s&&"undefined"==typeof SharedWorker,u=(()=>{const e=navigator.userAgent.match(/Firefox[/\s](\d+\.\d+)/);return Array.isArray(e)&&e.length>=2?+e[1]:0})(),d=Boolean(n&&window.document.documentMode),f=!!navigator.sendBeacon},1117:(e,t,r)=>{r.d(t,{w:()=>o});var n=r(50);const i={agentIdentifier:"",ee:void 0};class o{constructor(e){try{if("object"!=typeof e)return(0,n.Z)("shared context requires an object as input");this.sharedContext={},Object.assign(this.sharedContext,i),Object.entries(e).forEach((e=>{let[t,r]=e;Object.keys(i).includes(t)&&(this.sharedContext[t]=r)}))}catch(e){(0,n.Z)("An error occured while setting SharedContext",e)}}}},8e3:(e,t,r)=>{r.d(t,{L:()=>d,R:()=>c});var n=r(2177),i=r(1284),o=r(4322),a=r(3325);const s={};function c(e,t){const r={staged:!1,priority:a.p[t]||0};u(e),s[e].get(t)||s[e].set(t,r)}function u(e){e&&(s[e]||(s[e]=new Map))}function d(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"feature";if(u(e),!e||!s[e].get(t))return a(t);s[e].get(t).staged=!0;const r=[...s[e]];function a(t){const r=e?n.ee.get(e):n.ee,a=o.X.handlers;if(r.backlog&&a){var s=r.backlog[t],c=a[t];if(c){for(var u=0;s&&u {let[t,r]=e;return r.staged}))&&(r.sort(((e,t)=>e[1].priority-t[1].priority)),r.forEach((e=>{let[t]=e;a(t)})))}function f(e,t){var r=e[1];(0,i.D)(t[r],(function(t,r){var n=e[0];if(r[0]===n){var i=r[1],o=e[3],a=e[2];i.apply(o,a)}}))}},2177:(e,t,r)=>{r.d(t,{c:()=>f,ee:()=>u});var n=r(8632),i=r(2210),o=r(1284),a=r(5763),s="nr@context";let c=(0,n.fP)();var u;function d(){}function f(e){return(0,i.X)(e,s,l)}function l(){return new d}function h(){u.aborted=!0,u.backlog={}}c.ee?u=c.ee:(u=function e(t,r){var n={},c={},f={},g=!1;try{g=16===r.length&&(0,a.OP)(r).isolatedBacklog}catch(e){}var p={on:b,addEventListener:b,removeEventListener:y,emit:v,get:x,listeners:w,context:m,buffer:A,abort:h,aborted:!1,isBuffering:E,debugId:r,backlog:g?{}:t&&"object"==typeof t.backlog?t.backlog:{}};return p;function m(e){return e&&e instanceof d?e:e?(0,i.X)(e,s,l):l()}function v(e,r,n,i,o){if(!1!==o&&(o=!0),!u.aborted||i){t&&o&&t.emit(e,r,n);for(var a=m(n),s=w(e),d=s.length,f=0;fn,p:()=>i});var n=r(2177).ee.get("handle");function i(e,t,r,i,o){o?(o.buffer([e],i),o.emit(e,t,r)):(n.buffer([e],i),n.emit(e,t,r))}},4322:(e,t,r)=>{r.d(t,{X:()=>o});var n=r(5546);o.on=a;var i=o.handlers={};function o(e,t,r,o){a(o||n.E,i,e,t,r)}function a(e,t,r,i,o){o||(o="feature"),e||(e=n.E);var a=t[o]=t[o]||{};(a[r]=a[r]||[]).push([e,i])}},3239:(e,t,r)=>{r.d(t,{bP:()=>s,iz:()=>c,m$:()=>a});var n=r(385);let i=!1,o=!1;try{const e={get passive(){return i=!0,!1},get signal(){return o=!0,!1}};n._A.addEventListener("test",null,e),n._A.removeEventListener("test",null,e)}catch(e){}function a(e,t){return i||o?{capture:!!e,passive:i,signal:t}:!!e}function s(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;window.addEventListener(e,t,a(r,n))}function c(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;document.addEventListener(e,t,a(r,n))}},4402:(e,t,r)=>{r.d(t,{Ht:()=>u,M:()=>c,Rl:()=>a,ky:()=>s});var n=r(385);const i="xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx";function o(e,t){return e?15&e[t]:16*Math.random()|0}function a(){const e=n._A?.crypto||n._A?.msCrypto;let t,r=0;return e&&e.getRandomValues&&(t=e.getRandomValues(new Uint8Array(31))),i.split("").map((e=>"x"===e?o(t,++r).toString(16):"y"===e?(3&o()|8).toString(16):e)).join("")}function s(e){const t=n._A?.crypto||n._A?.msCrypto;let r,i=0;t&&t.getRandomValues&&(r=t.getRandomValues(new Uint8Array(31)));const a=[];for(var s=0;s {r.d(t,{Bq:()=>n,Hb:()=>o,oD:()=>i});const n="NRBA",i=144e5,o=18e5},7894:(e,t,r)=>{function n(){return Math.round(performance.now())}r.d(t,{z:()=>n})},7243:(e,t,r)=>{r.d(t,{e:()=>o});var n=r(385),i={};function o(e){if(e in i)return i[e];if(0===(e||"").indexOf("data:"))return{protocol:"data"};let t;var r=n._A?.location,o={};if(n.il)t=document.createElement("a"),t.href=e;else try{t=new URL(e,r.href)}catch(e){return o}o.port=t.port;var a=t.href.split("://");!o.port&&a[1]&&(o.port=a[1].split("/")[0].split("@").pop().split(":")[1]),o.port&&"0"!==o.port||(o.port="https"===a[0]?"443":"80"),o.hostname=t.hostname||r.hostname,o.pathname=t.pathname,o.protocol=a[0],"/"!==o.pathname.charAt(0)&&(o.pathname="/"+o.pathname);var s=!t.protocol||":"===t.protocol||t.protocol===r.protocol,c=t.hostname===r.hostname&&t.port===r.port;return o.sameOrigin=s&&(!t.hostname||c),"/"===o.pathname&&(i[e]=o),o}},50:(e,t,r)=>{function n(e,t){"function"==typeof console.warn&&(console.warn("New Relic: ".concat(e)),t&&console.warn(t))}r.d(t,{Z:()=>n})},2587:(e,t,r)=>{r.d(t,{N:()=>c,T:()=>u});var n=r(2177),i=r(5546),o=r(8e3),a=r(3325);const s={stn:[a.D.sessionTrace],err:[a.D.jserrors,a.D.metrics],ins:[a.D.pageAction],spa:[a.D.spa],sr:[a.D.sessionReplay,a.D.sessionTrace]};function c(e,t){const r=n.ee.get(t);e&&"object"==typeof e&&(Object.entries(e).forEach((e=>{let[t,n]=e;void 0===u[t]&&(s[t]?s[t].forEach((e=>{n?(0,i.p)("feat-"+t,[],void 0,e,r):(0,i.p)("block-"+t,[],void 0,e,r),(0,i.p)("rumresp-"+t,[Boolean(n)],void 0,e,r)})):n&&(0,i.p)("feat-"+t,[],void 0,void 0,r),u[t]=Boolean(n))})),Object.keys(s).forEach((e=>{void 0===u[e]&&(s[e]?.forEach((t=>(0,i.p)("rumresp-"+e,[!1],void 0,t,r))),u[e]=!1)})),(0,o.L)(t,a.D.pageViewEvent))}const u={}},2210:(e,t,r)=>{r.d(t,{X:()=>i});var n=Object.prototype.hasOwnProperty;function i(e,t,r){if(n.call(e,t))return e[t];var i=r();if(Object.defineProperty&&Object.keys)try{return Object.defineProperty(e,t,{value:i,writable:!0,enumerable:!1}),i}catch(e){}return e[t]=i,i}},1284:(e,t,r)=>{r.d(t,{D:()=>n});const n=(e,t)=>Object.entries(e||{}).map((e=>{let[r,n]=e;return t(r,n)}))},4351:(e,t,r)=>{r.d(t,{P:()=>o});var n=r(2177);const i=()=>{const e=new WeakSet;return(t,r)=>{if("object"==typeof r&&null!==r){if(e.has(r))return;e.add(r)}return r}};function o(e){try{return JSON.stringify(e,i())}catch(e){try{n.ee.emit("internal-error",[e])}catch(e){}}}},3960:(e,t,r)=>{r.d(t,{K:()=>a,b:()=>o});var n=r(3239);function i(){return"undefined"==typeof document||"complete"===document.readyState}function o(e,t){if(i())return e();(0,n.bP)("load",e,t)}function a(e){if(i())return e();(0,n.iz)("DOMContentLoaded",e)}},8632:(e,t,r)=>{r.d(t,{EZ:()=>u,Qy:()=>c,ce:()=>o,fP:()=>a,gG:()=>d,mF:()=>s});var n=r(7894),i=r(385);const o={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net"};function a(){return i._A.NREUM||(i._A.NREUM={}),void 0===i._A.newrelic&&(i._A.newrelic=i._A.NREUM),i._A.NREUM}function s(){let e=a();return e.o||(e.o={ST:i._A.setTimeout,SI:i._A.setImmediate,CT:i._A.clearTimeout,XHR:i._A.XMLHttpRequest,REQ:i._A.Request,EV:i._A.Event,PR:i._A.Promise,MO:i._A.MutationObserver,FETCH:i._A.fetch}),e}function c(e,t,r){let i=a();const o=i.initializedAgents||{},s=o[e]||{};return Object.keys(s).length||(s.initializedAt={ms:(0,n.z)(),date:new Date}),i.initializedAgents={...o,[e]:{...s,[r]:t}},i}function u(e,t){a()[e]=t}function d(){return function(){let e=a();const t=e.info||{};e.info={beacon:o.beacon,errorBeacon:o.errorBeacon,...t}}(),function(){let e=a();const t=e.init||{};e.init={...t}}(),s(),function(){let e=a();const t=e.loader_config||{};e.loader_config={...t}}(),a()}},7956:(e,t,r)=>{r.d(t,{N:()=>i});var n=r(3239);function i(e){let t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2?arguments[2]:void 0,i=arguments.length>3?arguments[3]:void 0;return void(0,n.iz)("visibilitychange",(function(){if(t)return void("hidden"==document.visibilityState&&e());e(document.visibilityState)}),r,i)}},1214:(e,t,r)=>{r.d(t,{em:()=>v,u5:()=>N,QU:()=>S,_L:()=>I,Gm:()=>L,Lg:()=>M,gy:()=>U,BV:()=>Q,Kf:()=>ee});var n=r(2177);const i="nr@original";var o=Object.prototype.hasOwnProperty,a=!1;function s(e,t){return e||(e=n.ee),r.inPlace=function(e,t,n,i,o){n||(n="");var a,s,c,u="-"===n.charAt(0);for(c=0;c 2?n-2:0),o=2;o {r(A[T],e,w),r(E[T],e,w)})),r(l._A,"fetch",y),t.on(y+"end",(function(e,r){var n=this;if(r){var i=r.headers.get("content-length");null!==i&&(n.rxSize=i),t.emit(y+"done",[null,r],n)}else t.emit(y+"done",[e],n)})),t}const O={},j=["pushState","replaceState"];function S(e){const t=function(e){return(e||n.ee).get("history")}(e);return!l.il||O[t.debugId]++||(O[t.debugId]=1,s(t).inPlace(window.history,j,"-")),t}var P=r(3239);const C={},R=["appendChild","insertBefore","replaceChild"];function I(e){const t=function(e){return(e||n.ee).get("jsonp")}(e);if(!l.il||C[t.debugId])return t;C[t.debugId]=!0;var r=s(t),i=/[?&](?:callback|cb)=([^&#]+)/,o=/(.*)\.([^.]+)/,a=/^(\w+)(\.|$)(.*)$/;function c(e,t){var r=e.match(a),n=r[1],i=r[3];return i?c(i,t[n]):t[n]}return r.inPlace(Node.prototype,R,"dom-"),t.on("dom-start",(function(e){!function(e){if(!e||"string"!=typeof e.nodeName||"script"!==e.nodeName.toLowerCase())return;if("function"!=typeof e.addEventListener)return;var n=(a=e.src,s=a.match(i),s?s[1]:null);var a,s;if(!n)return;var u=function(e){var t=e.match(o);if(t&&t.length>=3)return{key:t[2],parent:c(t[1],window)};return{key:e,parent:window}}(n);if("function"!=typeof u.parent[u.key])return;var d={};function f(){t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}function l(){t.emit("jsonp-error",[],d),t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}r.inPlace(u.parent,[u.key],"cb-",d),e.addEventListener("load",f,(0,P.m$)(!1)),e.addEventListener("error",l,(0,P.m$)(!1)),t.emit("new-jsonp",[e.src],d)}(e[0])})),t}var k=r(5763);const H={};function L(e){const t=function(e){return(e||n.ee).get("mutation")}(e);if(!l.il||H[t.debugId])return t;H[t.debugId]=!0;var r=s(t),i=k.Yu.MO;return i&&(window.MutationObserver=function(e){return this instanceof i?new i(r(e,"fn-")):i.apply(this,arguments)},MutationObserver.prototype=i.prototype),t}const z={};function M(e){const t=function(e){return(e||n.ee).get("promise")}(e);if(z[t.debugId])return t;z[t.debugId]=!0;var r=n.c,o=s(t),a=k.Yu.PR;return a&&function(){function e(r){var n=t.context(),i=o(r,"executor-",n,null,!1);const s=Reflect.construct(a,[i],e);return t.context(s).getCtx=function(){return n},s}l._A.Promise=e,Object.defineProperty(e,"name",{value:"Promise"}),e.toString=function(){return a.toString()},Object.setPrototypeOf(e,a),["all","race"].forEach((function(r){const n=a[r];e[r]=function(e){let i=!1;[...e||[]].forEach((e=>{this.resolve(e).then(a("all"===r),a(!1))}));const o=n.apply(this,arguments);return o;function a(e){return function(){t.emit("propagate",[null,!i],o,!1,!1),i=i||!e}}}})),["resolve","reject"].forEach((function(r){const n=a[r];e[r]=function(e){const r=n.apply(this,arguments);return e!==r&&t.emit("propagate",[e,!0],r,!1,!1),r}})),e.prototype=a.prototype;const n=a.prototype.then;a.prototype.then=function(){var e=this,i=r(e);i.promise=e;for(var a=arguments.length,s=new Array(a),c=0;c e())),t};function m(e,t){i.inPlace(t,["onreadystatechange"],"fn-",E)}function b(){var e=this,t=r.context(e);e.readyState>3&&!t.resolved&&(t.resolved=!0,r.emit("xhr-resolved",[],e)),i.inPlace(e,f,"fn-",E)}if(function(e,t){for(var r in e)t[r]=e[r]}(o,p),p.prototype=o.prototype,i.inPlace(p.prototype,J,"-xhr-",E),r.on("send-xhr-start",(function(e,t){m(e,t),function(e){h.push(e),a&&(y?y.then(A):u?u(A):(w=-w,x.data=w))}(t)})),r.on("open-xhr-start",m),a){var y=c&&c.resolve();if(!u&&!c){var w=1,x=document.createTextNode(w);new a(A).observe(x,{characterData:!0})}}else t.on("fn-end",(function(e){e[0]&&e[0].type===d||A()}));function A(){for(var e=0;e {r.d(t,{t:()=>n});const n=r(3325).D.ajax},6660:(e,t,r)=>{r.d(t,{A:()=>i,t:()=>n});const n=r(3325).D.jserrors,i="nr@seenError"},3081:(e,t,r)=>{r.d(t,{gF:()=>o,mY:()=>i,t9:()=>n,vz:()=>s,xS:()=>a});const n=r(3325).D.metrics,i="sm",o="cm",a="storeSupportabilityMetrics",s="storeEventMetrics"},4649:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageAction},7633:(e,t,r)=>{r.d(t,{Dz:()=>i,OJ:()=>a,qw:()=>o,t9:()=>n});const n=r(3325).D.pageViewEvent,i="firstbyte",o="domcontent",a="windowload"},9251:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageViewTiming},3614:(e,t,r)=>{r.d(t,{BST_RESOURCE:()=>i,END:()=>s,FEATURE_NAME:()=>n,FN_END:()=>u,FN_START:()=>c,PUSH_STATE:()=>d,RESOURCE:()=>o,START:()=>a});const n=r(3325).D.sessionTrace,i="bstResource",o="resource",a="-start",s="-end",c="fn"+a,u="fn"+s,d="pushState"},7836:(e,t,r)=>{r.d(t,{BODY:()=>A,CB_END:()=>E,CB_START:()=>u,END:()=>x,FEATURE_NAME:()=>i,FETCH:()=>_,FETCH_BODY:()=>v,FETCH_DONE:()=>m,FETCH_START:()=>p,FN_END:()=>c,FN_START:()=>s,INTERACTION:()=>l,INTERACTION_API:()=>d,INTERACTION_EVENTS:()=>o,JSONP_END:()=>b,JSONP_NODE:()=>g,JS_TIME:()=>T,MAX_TIMER_BUDGET:()=>a,REMAINING:()=>f,SPA_NODE:()=>h,START:()=>w,originalSetTimeout:()=>y});var n=r(5763);const i=r(3325).D.spa,o=["click","submit","keypress","keydown","keyup","change"],a=999,s="fn-start",c="fn-end",u="cb-start",d="api-ixn-",f="remaining",l="interaction",h="spaNode",g="jsonpNode",p="fetch-start",m="fetch-done",v="fetch-body-",b="jsonp-end",y=n.Yu.ST,w="-start",x="-end",A="-body",E="cb"+x,T="jsTime",_="fetch"},5938:(e,t,r)=>{r.d(t,{W:()=>o});var n=r(5763),i=r(2177);class o{constructor(e,t,r){this.agentIdentifier=e,this.aggregator=t,this.ee=i.ee.get(e,(0,n.OP)(this.agentIdentifier).isolatedBacklog),this.featureName=r,this.blocked=!1}}},9144:(e,t,r)=>{r.d(t,{j:()=>m});var n=r(3325),i=r(5763),o=r(5546),a=r(2177),s=r(7894),c=r(8e3),u=r(3960),d=r(385),f=r(50),l=r(3081),h=r(8632);function g(){const e=(0,h.gG)();["setErrorHandler","finished","addToTrace","inlineHit","addRelease","addPageAction","setCurrentRouteName","setPageViewName","setCustomAttribute","interaction","noticeError","setUserId"].forEach((t=>{e[t]=function(){for(var r=arguments.length,n=new Array(r),i=0;i 1?r-1:0),i=1;i {e.exposed&&e.api[t]&&o.push(e.api[t](...n))})),o.length>1?o:o[0]}(t,...n)}}))}var p=r(2587);function m(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},m=arguments.length>2?arguments[2]:void 0,v=arguments.length>3?arguments[3]:void 0,{init:b,info:y,loader_config:w,runtime:x={loaderType:m},exposed:A=!0}=t;const E=(0,h.gG)();y||(b=E.init,y=E.info,w=E.loader_config),(0,i.Dg)(e,b||{}),(0,i.GE)(e,w||{}),(0,i.sU)(e,x),y.jsAttributes??={},d.v6&&(y.jsAttributes.isWorker=!0),(0,i.CX)(e,y),g();const T=function(e,t){t||(0,c.R)(e,"api");const h={};var g=a.ee.get(e),p=g.get("tracer"),m="api-",v=m+"ixn-";function b(t,r,n,o){const a=(0,i.C5)(e);return null===r?delete a.jsAttributes[t]:(0,i.CX)(e,{...a,jsAttributes:{...a.jsAttributes,[t]:r}}),x(m,n,!0,o||null===r?"session":void 0)(t,r)}function y(){}["setErrorHandler","finished","addToTrace","inlineHit","addRelease"].forEach((e=>h[e]=x(m,e,!0,"api"))),h.addPageAction=x(m,"addPageAction",!0,n.D.pageAction),h.setCurrentRouteName=x(m,"routeName",!0,n.D.spa),h.setPageViewName=function(t,r){if("string"==typeof t)return"/"!==t.charAt(0)&&(t="/"+t),(0,i.OP)(e).customTransaction=(r||"http://custom.transaction")+t,x(m,"setPageViewName",!0)()},h.setCustomAttribute=function(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if("string"==typeof e){if(["string","number"].includes(typeof t)||null===t)return b(e,t,"setCustomAttribute",r);(0,f.Z)("Failed to execute setCustomAttribute.\nNon-null value must be a string or number type, but a type of was provided."))}else(0,f.Z)("Failed to execute setCustomAttribute.\nName must be a string type, but a type of was provided."))},h.setUserId=function(e){if("string"==typeof e||null===e)return b("enduser.id",e,"setUserId",!0);(0,f.Z)("Failed to execute setUserId.\nNon-null value must be a string type, but a type of was provided."))},h.interaction=function(){return(new y).get()};var w=y.prototype={createTracer:function(e,t){var r={},i=this,a="function"==typeof t;return(0,o.p)(v+"tracer",[(0,s.z)(),e,r],i,n.D.spa,g),function(){if(p.emit((a?"":"no-")+"fn-start",[(0,s.z)(),i,a],r),a)try{return t.apply(this,arguments)}catch(e){throw p.emit("fn-err",[arguments,this,"string"==typeof e?new Error(e):e],r),e}finally{p.emit("fn-end",[(0,s.z)()],r)}}}};function x(e,t,r,i){return function(){return(0,o.p)(l.xS,["API/"+t+"/called"],void 0,n.D.metrics,g),i&&(0,o.p)(e+t,[(0,s.z)(),...arguments],r?null:this,i,g),r?void 0:this}}function A(){r.e(439).then(r.bind(r,7438)).then((t=>{let{setAPI:r}=t;r(e),(0,c.L)(e,"api")})).catch((()=>(0,f.Z)("Downloading runtime APIs failed...")))}return["actionText","setName","setAttribute","save","ignore","onEnd","getContext","end","get"].forEach((e=>{w[e]=x(v,e,void 0,n.D.spa)})),h.noticeError=function(e,t){"string"==typeof e&&(e=new Error(e)),(0,o.p)(l.xS,["API/noticeError/called"],void 0,n.D.metrics,g),(0,o.p)("err",[e,(0,s.z)(),!1,t],void 0,n.D.jserrors,g)},d.il?(0,u.b)((()=>A()),!0):A(),h}(e,v);return(0,h.Qy)(e,T,"api"),(0,h.Qy)(e,A,"exposed"),(0,h.EZ)("activatedFeatures",p.T),T}},3325:(e,t,r)=>{r.d(t,{D:()=>n,p:()=>i});const n={ajax:"ajax",jserrors:"jserrors",metrics:"metrics",pageAction:"page_action",pageViewEvent:"page_view_event",pageViewTiming:"page_view_timing",sessionReplay:"session_replay",sessionTrace:"session_trace",spa:"spa"},i={[n.pageViewEvent]:1,[n.pageViewTiming]:2,[n.metrics]:3,[n.jserrors]:4,[n.ajax]:5,[n.sessionTrace]:6,[n.pageAction]:7,[n.spa]:8,[n.sessionReplay]:9}}},n={};function i(e){var t=n[e];if(void 0!==t)return t.exports;var o=n[e]={exports:{}};return r[e](o,o.exports,i),o.exports}i.m=r,i.d=(e,t)=>{for(var r in t)i.o(t,r)&&!i.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:t[r]})},i.f={},i.e=e=>Promise.all(Object.keys(i.f).reduce(((t,r)=>(i.f[r](e,t),t)),[])),i.u=e=>(({78:"page_action-aggregate",147:"metrics-aggregate",242:"session-manager",317:"jserrors-aggregate",348:"page_view_timing-aggregate",412:"lazy-feature-loader",439:"async-api",538:"recorder",590:"session_replay-aggregate",675:"compressor",733:"session_trace-aggregate",786:"page_view_event-aggregate",873:"spa-aggregate",898:"ajax-aggregate"}[e]||e)+"."+{78:"ac76d497",147:"3dc53903",148:"1a20d5fe",242:"2a64278a",317:"49e41428",348:"bd6de33a",412:"2f55ce66",439:"30bd804e",538:"1b18459f",590:"cf0efb30",675:"ae9f91a8",733:"83105561",786:"06482edd",860:"03a8b7a5",873:"e6b09d52",898:"998ef92b"}[e]+"-1.236.0.min.js"),i.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),e={},t="NRBA:",i.l=(r,n,o,a)=>{if(e[r])e[r].push(n);else{var s,c;if(void 0!==o)for(var u=document.getElementsByTagName("script"),d=0;d {s.onerror=s.onload=null,clearTimeout(h);var i=e[r];if(delete e[r],s.parentNode&&s.parentNode.removeChild(s),i&&i.forEach((e=>e(n))),t)return t(n)},h=setTimeout(l.bind(null,void 0,{type:"timeout",target:s}),12e4);s.onerror=l.bind(null,s.onerror),s.onload=l.bind(null,s.onload),c&&document.head.appendChild(s)}},i.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.j=364,i.p="https://js-agent.newrelic.com/",(()=>{var e={364:0,953:0};i.f.j=(t,r)=>{var n=i.o(e,t)?e[t]:void 0;if(0!==n)if(n)r.push(n[2]);else{var o=new Promise(((r,i)=>n=e[t]=[r,i]));r.push(n[2]=o);var a=i.p+i.u(t),s=new Error;i.l(a,(r=>{if(i.o(e,t)&&(0!==(n=e[t])&&(e[t]=void 0),n)){var o=r&&("load"===r.type?"missing":r.type),a=r&&r.target&&r.target.src;s.message="Loading chunk "+t+" failed.\n("+o+": "+a+")",s.name="ChunkLoadError",s.type=o,s.request=a,n[1](s)}}),"chunk-"+t,t)}};var t=(t,r)=>{var n,o,[a,s,c]=r,u=0;if(a.some((t=>0!==e[t]))){for(n in s)i.o(s,n)&&(i.m[n]=s[n]);if(c)c(i)}for(t&&t(r);u {i.r(o);var e=i(3325),t=i(5763);const r=Object.values(e.D);function n(e){const n={};return r.forEach((r=>{n[r]=function(e,r){return!1!==(0,t.Mt)(r,"".concat(e,".enabled"))}(r,e)})),n}var a=i(9144);var s=i(5546),c=i(385),u=i(8e3),d=i(5938),f=i(3960),l=i(50);class h extends d.W{constructor(e,t,r){let n=!(arguments.length>3&&void 0!==arguments[3])||arguments[3];super(e,t,r),this.auto=n,this.abortHandler,this.featAggregate,this.onAggregateImported,n&&(0,u.R)(e,r)}importAggregator(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};if(this.featAggregate||!this.auto)return;const r=c.il&&!0===(0,t.Mt)(this.agentIdentifier,"privacy.cookies_enabled");let n;this.onAggregateImported=new Promise((e=>{n=e}));const o=async()=>{let t;try{if(r){const{setupAgentSession:e}=await Promise.all([i.e(860),i.e(242)]).then(i.bind(i,3228));t=e(this.agentIdentifier)}}catch(e){(0,l.Z)("A problem occurred when starting up session manager. This page will not start or extend any session.",e)}try{if(!this.shouldImportAgg(this.featureName,t))return void(0,u.L)(this.agentIdentifier,this.featureName);const{lazyFeatureLoader:r}=await i.e(412).then(i.bind(i,8582)),{Aggregate:o}=await r(this.featureName,"aggregate");this.featAggregate=new o(this.agentIdentifier,this.aggregator,e),n(!0)}catch(e){(0,l.Z)("Downloading and initializing ".concat(this.featureName," failed..."),e),this.abortHandler?.(),n(!1)}};c.il?(0,f.b)((()=>o()),!0):o()}shouldImportAgg(r,n){return r!==e.D.sessionReplay||!1!==(0,t.Mt)(this.agentIdentifier,"session_trace.enabled")&&(!!n?.isNew||!!n?.state.sessionReplay)}}var g=i(7633),p=i(7894);class m extends h{static featureName=g.t9;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];if(super(r,n,g.t9,i),("undefined"==typeof PerformanceNavigationTiming||c.Tt)&&"undefined"!=typeof PerformanceTiming){const n=(0,t.OP)(r);n[g.Dz]=Math.max(Date.now()-n.offset,0),(0,f.K)((()=>n[g.qw]=Math.max((0,p.z)()-n[g.Dz],0))),(0,f.b)((()=>{const t=(0,p.z)();n[g.OJ]=Math.max(t-n[g.Dz],0),(0,s.p)("timing",["load",t],void 0,e.D.pageViewTiming,this.ee)}))}this.importAggregator()}}var v=i(1117),b=i(1284);class y extends v.w{constructor(e){super(e),this.aggregatedData={}}store(e,t,r,n,i){var o=this.getBucket(e,t,r,i);return o.metrics=function(e,t){t||(t={count:0});return t.count+=1,(0,b.D)(e,(function(e,r){t[e]=w(r,t[e])})),t}(n,o.metrics),o}merge(e,t,r,n,i){var o=this.getBucket(e,t,n,i);if(o.metrics){var a=o.metrics;a.count+=r.count,(0,b.D)(r,(function(e,t){if("count"!==e){var n=a[e],i=r[e];i&&!i.c?a[e]=w(i.t,n):a[e]=function(e,t){if(!t)return e;t.c||(t=x(t.t));return t.min=Math.min(e.min,t.min),t.max=Math.max(e.max,t.max),t.t+=e.t,t.sos+=e.sos,t.c+=e.c,t}(i,a[e])}}))}else o.metrics=r}storeMetric(e,t,r,n){var i=this.getBucket(e,t,r);return i.stats=w(n,i.stats),i}getBucket(e,t,r,n){this.aggregatedData[e]||(this.aggregatedData[e]={});var i=this.aggregatedData[e][t];return i||(i=this.aggregatedData[e][t]={params:r||{}},n&&(i.custom=n)),i}get(e,t){return t?this.aggregatedData[e]&&this.aggregatedData[e][t]:this.aggregatedData[e]}take(e){for(var t={},r="",n=!1,i=0;i t.max&&(t.max=e),e 2&&void 0!==arguments[2])||arguments[2];super(e,r,j.t,n),c.il&&((0,t.OP)(e).initHidden=Boolean("hidden"===document.visibilityState),(0,N.N)((()=>(0,s.p)("docHidden",[(0,p.z)()],void 0,j.t,this.ee)),!0),(0,O.bP)("pagehide",(()=>(0,s.p)("winPagehide",[(0,p.z)()],void 0,j.t,this.ee))),this.importAggregator())}}var P=i(3081);class C extends h{static featureName=P.t9;constructor(e,t){let r=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(e,t,P.t9,r),this.importAggregator()}}var R,I=i(2210),k=i(1214),H=i(2177),L={};try{R=localStorage.getItem("__nr_flags").split(","),console&&"function"==typeof console.log&&(L.console=!0,-1!==R.indexOf("dev")&&(L.dev=!0),-1!==R.indexOf("nr_dev")&&(L.nrDev=!0))}catch(e){}function z(e){try{L.console&&z(e)}catch(e){}}L.nrDev&&H.ee.on("internal-error",(function(e){z(e.stack)})),L.dev&&H.ee.on("fn-err",(function(e,t,r){z(r.stack)})),L.dev&&(z("NR AGENT IN DEVELOPMENT MODE"),z("flags: "+(0,b.D)(L,(function(e,t){return e})).join(", ")));var M=i(6660);class B extends h{static featureName=M.t;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(r,n,M.t,i),this.skipNext=0;try{this.removeOnAbort=new AbortController}catch(e){}const o=this;o.ee.on("fn-start",(function(e,t,r){o.abortHandler&&(o.skipNext+=1)})),o.ee.on("fn-err",(function(t,r,n){o.abortHandler&&!n[M.A]&&((0,I.X)(n,M.A,(function(){return!0})),this.thrown=!0,(0,s.p)("err",[n,(0,p.z)()],void 0,e.D.jserrors,o.ee))})),o.ee.on("fn-end",(function(){o.abortHandler&&!this.thrown&&o.skipNext>0&&(o.skipNext-=1)})),o.ee.on("internal-error",(function(t){(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,o.ee)})),this.origOnerror=c._A.onerror,c._A.onerror=this.onerrorHandler.bind(this),c._A.addEventListener("unhandledrejection",(t=>{const r=function(e){let t="Unhandled Promise Rejection: ";if(e instanceof Error)try{return e.message=t+e.message,e}catch(t){return e}if(void 0===e)return new Error(t);try{return new Error(t+(0,D.P)(e))}catch(e){return new Error(t)}}(t.reason);(0,s.p)("err",[r,(0,p.z)(),!1,{unhandledPromiseRejection:1}],void 0,e.D.jserrors,this.ee)}),(0,O.m$)(!1,this.removeOnAbort?.signal)),(0,k.gy)(this.ee),(0,k.BV)(this.ee),(0,k.em)(this.ee),(0,t.OP)(r).xhrWrappable&&(0,k.Kf)(this.ee),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}onerrorHandler(t,r,n,i,o){"function"==typeof this.origOnerror&&this.origOnerror(...arguments);try{this.skipNext?this.skipNext-=1:(0,s.p)("err",[o||new F(t,r,n),(0,p.z)()],void 0,e.D.jserrors,this.ee)}catch(t){try{(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,this.ee)}catch(e){}}return!1}}function F(e,t,r){this.message=e||"Uncaught error with no additional information",this.sourceURL=t,this.line=r}let U=1;const q="nr@id";function G(e){const t=typeof e;return!e||"object"!==t&&"function"!==t?-1:e===c._A?0:(0,I.X)(e,q,(function(){return U++}))}function V(e){if("string"==typeof e&&e.length)return e.length;if("object"==typeof e){if("undefined"!=typeof ArrayBuffer&&e instanceof ArrayBuffer&&e.byteLength)return e.byteLength;if("undefined"!=typeof Blob&&e instanceof Blob&&e.size)return e.size;if(!("undefined"!=typeof FormData&&e instanceof FormData))try{return(0,D.P)(e).length}catch(e){return}}}var X=i(7243);class W{constructor(e){this.agentIdentifier=e,this.generateTracePayload=this.generateTracePayload.bind(this),this.shouldGenerateTrace=this.shouldGenerateTrace.bind(this)}generateTracePayload(e){if(!this.shouldGenerateTrace(e))return null;var r=(0,t.DL)(this.agentIdentifier);if(!r)return null;var n=(r.accountID||"").toString()||null,i=(r.agentID||"").toString()||null,o=(r.trustKey||"").toString()||null;if(!n||!i)return null;var a=(0,_.M)(),s=(0,_.Ht)(),c=Date.now(),u={spanId:a,traceId:s,timestamp:c};return(e.sameOrigin||this.isAllowedOrigin(e)&&this.useTraceContextHeadersForCors())&&(u.traceContextParentHeader=this.generateTraceContextParentHeader(a,s),u.traceContextStateHeader=this.generateTraceContextStateHeader(a,c,n,i,o)),(e.sameOrigin&&!this.excludeNewrelicHeader()||!e.sameOrigin&&this.isAllowedOrigin(e)&&this.useNewrelicHeaderForCors())&&(u.newrelicHeader=this.generateTraceHeader(a,s,c,n,i,o)),u}generateTraceContextParentHeader(e,t){return"00-"+t+"-"+e+"-01"}generateTraceContextStateHeader(e,t,r,n,i){return i+"@nr=0-1-"+r+"-"+n+"-"+e+"----"+t}generateTraceHeader(e,t,r,n,i,o){if(!("function"==typeof c._A?.btoa))return null;var a={v:[0,1],d:{ty:"Browser",ac:n,ap:i,id:e,tr:t,ti:r}};return o&&n!==o&&(a.d.tk=o),btoa((0,D.P)(a))}shouldGenerateTrace(e){return this.isDtEnabled()&&this.isAllowedOrigin(e)}isAllowedOrigin(e){var r=!1,n={};if((0,t.Mt)(this.agentIdentifier,"distributed_tracing")&&(n=(0,t.P_)(this.agentIdentifier).distributed_tracing),e.sameOrigin)r=!0;else if(n.allowed_origins instanceof Array)for(var i=0;i 2&&void 0!==arguments[2])||arguments[2];super(r,n,Z.t,i),(0,t.OP)(r).xhrWrappable&&(this.dt=new W(r),this.handler=(e,t,r,n)=>(0,s.p)(e,t,r,n,this.ee),(0,k.u5)(this.ee),(0,k.Kf)(this.ee),function(r,n,i,o){function a(e){var t=this;t.totalCbs=0,t.called=0,t.cbTime=0,t.end=E,t.ended=!1,t.xhrGuids={},t.lastSize=null,t.loadCaptureCalled=!1,t.params=this.params||{},t.metrics=this.metrics||{},e.addEventListener("load",(function(r){_(t,e)}),(0,O.m$)(!1)),c.IF||e.addEventListener("progress",(function(e){t.lastSize=e.loaded}),(0,O.m$)(!1))}function s(e){this.params={method:e[0]},T(this,e[1]),this.metrics={}}function u(e,n){var i=(0,t.DL)(r);i.xpid&&this.sameOrigin&&n.setRequestHeader("X-NewRelic-ID",i.xpid);var a=o.generateTracePayload(this.parsedOrigin);if(a){var s=!1;a.newrelicHeader&&(n.setRequestHeader("newrelic",a.newrelicHeader),s=!0),a.traceContextParentHeader&&(n.setRequestHeader("traceparent",a.traceContextParentHeader),a.traceContextStateHeader&&n.setRequestHeader("tracestate",a.traceContextStateHeader),s=!0),s&&(this.dt=a)}}function d(e,t){var r=this.metrics,i=e[0],o=this;if(r&&i){var a=V(i);a&&(r.txSize=a)}this.startTime=(0,p.z)(),this.listener=function(e){try{"abort"!==e.type||o.loadCaptureCalled||(o.params.aborted=!0),("load"!==e.type||o.called===o.totalCbs&&(o.onloadCalled||"function"!=typeof t.onload)&&"function"==typeof o.end)&&o.end(t)}catch(e){try{n.emit("internal-error",[e])}catch(e){}}};for(var s=0;s 1?e[1]=i:e.push(i)}else e[0]&&e[0].headers&&s(e[0].headers,n)&&(this.dt=n);function s(e,t){var r=!1;return t.newrelicHeader&&(e.set("newrelic",t.newrelicHeader),r=!0),t.traceContextParentHeader&&(e.set("traceparent",t.traceContextParentHeader),t.traceContextStateHeader&&e.set("tracestate",t.traceContextStateHeader),r=!0),r}}function x(e,t){this.params={},this.metrics={},this.startTime=(0,p.z)(),this.dt=t,e.length>=1&&(this.target=e[0]),e.length>=2&&(this.opts=e[1]);var r,n=this.opts||{},i=this.target;"string"==typeof i?r=i:"object"==typeof i&&i instanceof Y?r=i.url:c._A?.URL&&"object"==typeof i&&i instanceof URL&&(r=i.href),T(this,r);var o=(""+(i&&i instanceof Y&&i.method||n.method||"GET")).toUpperCase();this.params.method=o,this.txSize=V(n.body)||0}function A(t,r){var n;this.endTime=(0,p.z)(),this.params||(this.params={}),this.params.status=r?r.status:0,"string"==typeof this.rxSize&&this.rxSize.length>0&&(n=+this.rxSize);var o={txSize:this.txSize,rxSize:n,duration:(0,p.z)()-this.startTime};i("xhr",[this.params,o,this.startTime,this.endTime,"fetch"],this,e.D.ajax)}function E(t){var r=this.params,n=this.metrics;if(!this.ended){this.ended=!0;for(var o=0;o 2&&void 0!==arguments[2])||arguments[2];super(e,t,we.t,r),this.importAggregator()}}new class{constructor(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:(0,_.ky)(16);c._A?(this.agentIdentifier=t,this.sharedAggregator=new y({agentIdentifier:this.agentIdentifier}),this.features={},this.desiredFeatures=new Set(e.features||[]),this.desiredFeatures.add(m),Object.assign(this,(0,a.j)(this.agentIdentifier,e,e.loaderType||"agent")),this.start()):(0,l.Z)("Failed to initial the agent. Could not determine the runtime environment.")}get config(){return{info:(0,t.C5)(this.agentIdentifier),init:(0,t.P_)(this.agentIdentifier),loader_config:(0,t.DL)(this.agentIdentifier),runtime:(0,t.OP)(this.agentIdentifier)}}start(){const t="features";try{const r=n(this.agentIdentifier),i=[...this.desiredFeatures];i.sort(((t,r)=>e.p[t.featureName]-e.p[r.featureName])),i.forEach((t=>{if(r[t.featureName]||t.featureName===e.D.pageViewEvent){const n=function(t){switch(t){case e.D.ajax:return[e.D.jserrors];case e.D.sessionTrace:return[e.D.ajax,e.D.pageViewEvent];case e.D.sessionReplay:return[e.D.sessionTrace];case e.D.pageViewTiming:return[e.D.pageViewEvent];default:return[]}}(t.featureName);n.every((e=>r[e]))||(0,l.Z)("".concat(t.featureName," is enabled but one or more dependent features has been disabled (").concat((0,D.P)(n),"). This may cause unintended consequences or missing data...")),this.features[t.featureName]=new t(this.agentIdentifier,this.sharedAggregator)}})),(0,T.Qy)(this.agentIdentifier,this.features,t)}catch(e){(0,l.Z)("Failed to initialize all enabled instrument classes (agent aborted) -",e);for(const e in this.features)this.features[e].abortHandler?.();const r=(0,T.fP)();return delete r.initializedAgents[this.agentIdentifier]?.api,delete r.initializedAgents[this.agentIdentifier]?.[t],delete this.sharedAggregator,r.ee?.abort(),delete r.ee?.get(this.agentIdentifier),!1}}}({features:[J,m,S,class extends h{static featureName=oe;constructor(t,r){if(super(t,r,oe,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;const n=this.ee;let i;(0,k.QU)(n),this.eventsEE=(0,k.em)(n),this.eventsEE.on(se,(function(e,t){this.bstStart=(0,p.z)()})),this.eventsEE.on(ae,(function(t,r){(0,s.p)("bst",[t[0],r,this.bstStart,(0,p.z)()],void 0,e.D.sessionTrace,n)})),n.on(ce+ne,(function(e){this.time=(0,p.z)(),this.startPath=location.pathname+location.hash})),n.on(ce+ie,(function(t){(0,s.p)("bstHist",[location.pathname+location.hash,this.startPath,this.time],void 0,e.D.sessionTrace,n)}));try{i=new PerformanceObserver((t=>{const r=t.getEntries();(0,s.p)(te,[r],void 0,e.D.sessionTrace,n)})),i.observe({type:re,buffered:!0})}catch(e){}this.importAggregator({resourceObserver:i})}},C,xe,B,class extends h{static featureName=de;constructor(e,r){if(super(e,r,de,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;if(!(0,t.OP)(e).xhrWrappable)return;try{this.removeOnAbort=new AbortController}catch(e){}let n,i=0;const o=this.ee.get("tracer"),a=(0,k._L)(this.ee),s=(0,k.Lg)(this.ee),u=(0,k.BV)(this.ee),d=(0,k.Kf)(this.ee),f=this.ee.get("events"),l=(0,k.u5)(this.ee),h=(0,k.QU)(this.ee),g=(0,k.Gm)(this.ee);function m(e,t){h.emit("newURL",[""+window.location,t])}function v(){i++,n=window.location.hash,this[ve]=(0,p.z)()}function b(){i--,window.location.hash!==n&&m(0,!0);var e=(0,p.z)();this[pe]=~~this[pe]+e-this[ve],this[ye]=e}function y(e,t){e.on(t,(function(){this[t]=(0,p.z)()}))}this.ee.on(ve,v),s.on(be,v),a.on(be,v),this.ee.on(ye,b),s.on(ge,b),a.on(ge,b),this.ee.buffer([ve,ye,"xhr-resolved"],this.featureName),f.buffer([ve],this.featureName),u.buffer(["setTimeout"+le,"clearTimeout"+fe,ve],this.featureName),d.buffer([ve,"new-xhr","send-xhr"+fe],this.featureName),l.buffer([me+fe,me+"-done",me+he+fe,me+he+le],this.featureName),h.buffer(["newURL"],this.featureName),g.buffer([ve],this.featureName),s.buffer(["propagate",be,ge,"executor-err","resolve"+fe],this.featureName),o.buffer([ve,"no-"+ve],this.featureName),a.buffer(["new-jsonp","cb-start","jsonp-error","jsonp-end"],this.featureName),y(l,me+fe),y(l,me+"-done"),y(a,"new-jsonp"),y(a,"jsonp-end"),y(a,"cb-start"),h.on("pushState-end",m),h.on("replaceState-end",m),window.addEventListener("hashchange",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("load",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("popstate",(function(){m(0,i>1)}),(0,O.m$)(!0,this.removeOnAbort?.signal)),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}}],loaderType:"spa"})})(),window.NRBA=o})(); window.jQuery || document.write(' ') CKEDITOR_BASEPATH='https://f1000research.com/js/vendor/ckeditor/' window.reactTheme = 'research'; window.MathJax = { CommonHTML: { linebreaks: { automatic: true } }, 'HTML-CSS': { linebreaks: { automatic: true } }, SVG: { linebreaks: { automatic: true } }, AuthorInit: function() { MathJax.Hub.Register.MessageHook('End Process', function () { let timeout = false; // holder for timeout id const delay = 250; // delay after event is "complete" to run callback const reflowMath = function() { const dispFormulas = document.querySelectorAll('.disp-formula.panel'); if (!dispFormulas) { return; } for (const dispFormula of dispFormulas) { const child = dispFormula.querySelector('.MathJax_Preview').nextSibling.firstChild; const isMultiline = MathJax.Hub.getAllJax(dispFormula)[0].root.isMultiline; if (dispFormula.offsetWidth < child.offsetWidth || isMultiline) { MathJax.Hub.Queue(['Rerender', MathJax.Hub, dispFormula]); } } }; window.addEventListener('resize', function() { clearTimeout(timeout); // clear the timeout timeout = setTimeout(reflowMath, delay); // start timing for event "completion" }); }); }, }; if (window.location.hash == '#_=_'){ window.location = window.location.href.split('#')[0] } !function(f,b,e,v,n,t,s){if(f.fbq)return;n=f.fbq=function() {n.callMethod? n.callMethod.apply(n,arguments):n.queue.push(arguments)} ;if(!f._fbq)f._fbq=n; n.push=n;n.loaded=!0;n.version='2.0';n.queue=[];t=b.createElement(e);t.async=!0; t.src=v;s=b.getElementsByTagName(e)[0];s.parentNode.insertBefore(t,s)}(window, document,'script','https://connect.facebook.net/en_US/fbevents.js'); fbq('init', '1641728616063202'); fbq('track', "PixelInitialized", {}); (function(h,o,t,j,a,r){ h.hj=h.hj||function(){(h.hj.q=h.hj.q||[]).push(arguments)}; h._hjSettings={hjid:2318163,hjsv:6}; a=o.getElementsByTagName('head')[0]; r=o.createElement('script');r.async=1; r.src=t+h._hjSettings.hjid+j+h._hjSettings.hjsv; a.appendChild(r); })(window,document,'https://static.hotjar.com/c/hotjar-','.js?sv='); search file_upload Submit your research search menu close search Browse Gateways & Collections How to Publish Submit your Research My Submissions Article Guidelines Article Guidelines (New Versions) Open Data, Software and Code Guidelines Open Data and Accessible Source Materials Guidelines (HSS) Open Data, Software and Code Guidelines (PSE) Prepublication Checks Production Process Posters and Slides Guidelines Document Guidelines Article Processing Charges Peer Review Finding Article Reviewers About How it Works For Reviewers Our Advisors Policies Glossary FAQs For Developers Newsroom Contact My Research Submissions Content and Tracking Alerts My Details Sign In file_upload Submit your research { "@context": "https://schema.org", "@type": "ScholarlyArticle", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://f1000research.com/articles/13-1358" }, "headline": "Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with...", "datePublished": "2024-11-13T17:39:17", "dateModified": "2025-04-03T17:47:32", "author": [ { "@type": "Person", "name": "Jiaying Zhou" }, { "@type": "Person", "name": "Mayue Shi" }, { "@type": "Person", "name": "Mingzhu Cai" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": " Background Traditional dietary assessments are often inaccurate and prone to self-reporting biases. Tracking the physiological responses associated with eating and digestion events via wearable technologies may provide an effective approach for continuously monitoring food intake and estimating energy consumption. Eating and digestion are accompanied by a series of changes in the heart rate, skin temperature, blood oxygen saturation, and blood pressure. These changes can be tracked by wearable devices, such as smartwatches, which have been widely accepted in the market. This systematic review is the first to evaluate the effectiveness of tracking such physiological biomarkers in differentiating between high- and low-calorie meals, potentially paving the way for more accurate dietary monitoring. Methods Following the PRISMA-P guidelines, we will conduct a systematic literature search through MEDLINE, EMBASE, and PubMed for clinical trials that investigated physiological responses following meal intake in healthy subjects. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. This will be followed by data extraction and quality assessment of the included studies. Statistical analyses, including meta-analyses, will be performed using R Studio software. Our primary outcome will be the comparison of physiological biomarkers before and after meal intake, while secondary outcomes will include comparisons of physiological biomarkers between high- and low-calorie meal consumption and the correlation between the caloric content of consumed meals and postprandial physiological changes. Discussion This systematic review and meta-analysis will identify physiological indicators for eating events and inform the design of wearable sensors that estimate food intake in healthy subjects. Systematic Review Registration PROSPERO Registration ID: CRD42024544353 " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/13-1358/v2", "name": "Identifying and Assessing Physiological Biomarkers for Food and Energy..." } } ] } Home Browse Identifying and Assessing Physiological Biomarkers for Food and Energy... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Zhou J, Shi M and Cai M. Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.12688/f1000research.157875.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Study Protocol Revised Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] Jiaying Zhou https://orcid.org/0009-0009-4937-1834 1 , Mayue Shi 2 , Mingzhu Cai https://orcid.org/0000-0002-1474-0224 1 Jiaying Zhou https://orcid.org/0009-0009-4937-1834 1 , Mayue Shi 2 , Mingzhu Cai https://orcid.org/0000-0002-1474-0224 1 PUBLISHED 03 Apr 2025 Author details Author details 1 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, England, UK 2 Department of Electrical and Electronic Engineering, Imperial College London, London, England, UK Jiaying Zhou Roles: Methodology, Writing – Original Draft Preparation Mayue Shi Roles: Conceptualization, Supervision, Writing – Review & Editing Mingzhu Cai Roles: Conceptualization, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Background Traditional dietary assessments are often inaccurate and prone to self-reporting biases. Tracking the physiological responses associated with eating and digestion events via wearable technologies may provide an effective approach for continuously monitoring food intake and estimating energy consumption. Eating and digestion are accompanied by a series of changes in the heart rate, skin temperature, blood oxygen saturation, and blood pressure. These changes can be tracked by wearable devices, such as smartwatches, which have been widely accepted in the market. This systematic review is the first to evaluate the effectiveness of tracking such physiological biomarkers in differentiating between high- and low-calorie meals, potentially paving the way for more accurate dietary monitoring. Methods Following the PRISMA-P guidelines, we will conduct a systematic literature search through MEDLINE, EMBASE, and PubMed for clinical trials that investigated physiological responses following meal intake in healthy subjects. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. This will be followed by data extraction and quality assessment of the included studies. Statistical analyses, including meta-analyses, will be performed using R Studio software. Our primary outcome will be the comparison of physiological biomarkers before and after meal intake, while secondary outcomes will include comparisons of physiological biomarkers between high- and low-calorie meal consumption and the correlation between the caloric content of consumed meals and postprandial physiological changes. Discussion This systematic review and meta-analysis will identify physiological indicators for eating events and inform the design of wearable sensors that estimate food intake in healthy subjects. Systematic Review Registration PROSPERO Registration ID: CRD42024544353 READ ALL READ LESS Keywords Dietary behaviour, food intake, physiological biomarkers, heart rate, blood pressure wearable sensor Corresponding Author(s) Mayue Shi ( [email protected] ) Mingzhu Cai ( [email protected] ) Close Corresponding authors: Mayue Shi, Mingzhu Cai Competing interests: No competing interests were disclosed. Grant information: This work was supported by the Dame Julia Higgins Postdoc Collaborative Research Fund. The sponsor had no role in composing the study design, collection, management, analysis, and interpretation of data. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2025 Zhou J et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Zhou J, Shi M and Cai M. Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.12688/f1000research.157875.2 ) First published: 13 Nov 2024, 13 :1358 ( https://doi.org/10.12688/f1000research.157875.1 ) Latest published: 03 Apr 2025, 13 :1358 ( https://doi.org/10.12688/f1000research.157875.2 ) Revised Amendments from Version 1 This revised version addresses all peer review comments. We clarified that the manuscript is a study protocol for a systematic review and meta-analysis, highlighting its role as secondary research. Redundancies in the “Study Design and Context” section were removed for clarity. The primary and secondary outcomes now more clearly define the physiological biomarkers of interest—heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose—which will be assessed before and after meals, and across high- and low-calorie conditions. An “Expected Results/Findings” section has been added, outlining anticipated postprandial physiological changes and potential dose-response relationships with caloric intake. We also expanded the data extraction section to include planned comparisons between wearable devices and traditional clinical methods, where data are available. This revised version addresses all peer review comments. We clarified that the manuscript is a study protocol for a systematic review and meta-analysis, highlighting its role as secondary research. Redundancies in the “Study Design and Context” section were removed for clarity. The primary and secondary outcomes now more clearly define the physiological biomarkers of interest—heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose—which will be assessed before and after meals, and across high- and low-calorie conditions. An “Expected Results/Findings” section has been added, outlining anticipated postprandial physiological changes and potential dose-response relationships with caloric intake. We also expanded the data extraction section to include planned comparisons between wearable devices and traditional clinical methods, where data are available. See the authors' detailed response to the review by Faiza Jan Iftikhar READ REVIEWER RESPONSES Background Diet is essential for human health, and understanding what people eat in their daily lives is a fundamental challenge. Traditional dietary assessments rely on self-reporting and present high levels of subjectivity and recall biases. These limitations have driven the development of objective and reliable tools for dietary monitoring. Recent advances in metabolomic techniques, combined with bioinformatics analysis, have opened new avenues for developing dietary biomarkers. These approaches aim to identify blood or urine metabolites as biomarkers of food intake (BFIs) that reflect the consumption of specific foods or dietary patterns ( Cuparencu et al., 2024 ; Maruvada et al., 2020 ). However, this approach is limited by laboratory analysis and does not enable continuous dietary monitoring. Wearable sensor-based methods have also been proposed for continuous dietary monitoring. Various wearable sensors function by tracking the oral phase of digestion (capturing bites, chewing, and swallowing actions) and hand gestures to identify eating episodes ( Burrows & Rollo, 2019 ). However, they often fall short of providing contextual meal information, such as energy intake estimates ( Vu et al., 2017 ). Camera-based systems have also been proposed, with the ability to estimate meal energy by measuring food volume and categorizing food types. However, these systems have significant privacy concerns, particularly when personal images are involved ( Doulah et al., 2022 ). To date, a widely accessible, user-friendly tool for real-time monitoring of food and energy intake is still lacking. Tracking the physiological responses associated with eating and digestion events via wearable technologies may provide a solution for the continuous monitoring of food intake. Physiological changes after food consumption, such as increased heart rate, elevated skin temperature, and decreased blood oxygen saturation, have been well documented ( De Aguiar Cassiani et al., 2011 ; Sit & Chou, 1984 ; Westerterp, 2004 ). Heart rate changes showed a strong correlation with meal size, suggesting that physiological responses could serve as valuable indicators of both food consumption and energy intake ( Sidery & Macdonald, 1994 ). Despite this, there remains no consensus on whether monitoring physiological responses can serve as reliable indicators of energy intake. This systematic review aims to identify and evaluate physiological biomarkers associated with food and energy intake. The specific objectives are: (1) to investigate physiological responses, such as heart rate, blood pressure, skin temperature, and blood oxygen saturation, following the consumption of high-caloric versus low-calorie meals through meta-analysis; and (2) to assess whether there is a dose-response relationship between these physiological changes and the caloric content of meals using meta-regression analysis. This can inform the design of new dietary monitoring tools and whether tracking such changes can effectively differentiate between high- and low-calorie intake. Methods This protocol will follow the PRISMA-P Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines to ensure a systematic and transparent process ( Moher et al., 2015 ; Shamseer et al., 2015 ). We will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake. Outcomes Primary outcomes Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters. Secondary outcomes Our secondary outcomes will focus on two key areas:: • Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes. • Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring. Eligibility criteria for including studies The eligibility criteria for this review are structured according to the PICO framework to clearly define the target population, interventions, comparators, outcomes, and study context. This framework is essential for identifying physiological biomarkers that reflect dietary behaviors and evaluating their applications in wearable sensing technology for food intake monitoring. Population Inclusion criteria: • Healthy participants included individuals who are underweight, overweight, or of normal weight, provided that they are otherwise in good health. Exclusion criteria: • Patients diagnosed with diabetes, cardiovascular disease, or any other type of chronic condition. • Animal studies. Intervention Inclusion criteria: • Meal intake with adequate nutrient and calorie information, regardless of meal form (liquid, solid, or mixed) • Monitoring physiological biomarkers before and after dietary intake. Key physiological biomarkers included heart rate, body temperature, oxygen consumption, cardiac output, blood pressure, blood flow, and blood glucose through a continuous glucose monitor. Exclusion criteria: • Studies investigating the impacts of water consumption, drug effects, long-term dietary consequences, and specific types of food or exercise • Studies lacking sufficient information to calculate the test meal’s caloric content Comparator Inclusion criteria: • Comparing the pre- and postprandial changes in physiological biomarkers. • Comparing the physiological biomarkers changes after consuming meals of different calories content. • Comparing wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. Outcomes Inclusion criteria: • Pre- and post-meal monitoring of heart rate, skin temperature, blood oxygen saturation, cardiac output, blood pressure, and intestinal blood flow measured using wearable or traditional devices. • Pre- and post-meal blood glucose monitoring using wearable devices, such as continuous glucose monitors (CGMs). • If measured using wearable devices, the performance metrics include accuracy, specificity, precision, recall, and F1-score. Exclusion criteria: • Articles without reported results from empirical research. Study design and context Inclusion criteria: • Experiential studies involving human participants in either controlled or real-life environments. • Randomised or non-randomised trial, including single-arm studies. • English-language articles in peer-reviewed journals. Exclusion criteria: • Review articles, commentaries, and protocols. • Studies without human involvement. • A publication cutoff date of February 7, 2024, will be applied. Information sources and search strategy Literature searches will be conducted across the MEDLINE, EMBASE, and PubMed databases following pre-defined eligibility criteria. We will use search strategies that incorporate both Medical Subject Headings (MeSH) and a suite of keywords pertinent to wearable sensors and their applications in monitoring eating behaviors. The selection of keywords will include terms such as ‘eating,’ ‘energy intake,’ ‘caloric intake,’ ‘postprandial period,’ ‘postprandial state,’ ‘oxygen consumption,’ ‘heart rate,’ ‘blood pressure,’ ‘cardiac output,’ ‘body temperature,’ ‘regional blood flow,’ and ‘blood glucose’ to ensure broad yet relevant coverage. For detailed insights into the search strategy employed for each database, please refer to Supplementary Table 1 (Appendix). Screen and selection process The literature search results will be uploaded to Covidence, a web-based tool for systematic review and management. The duplicates will be automatically removed upon uploading. Our team will create and refine screening questions and forms, aligning them with predetermined inclusion and exclusion criteria. The selection process will start with all three authors independently reviewing the titles and abstracts to check if they met the inclusion criteria. Titles that seem to fit these criteria or whose eligibility is not clear will be selected for a full-report review to confirm that they comply with the inclusion criteria. Conflicts on Covidence will be resolved through discussions in review team meetings, and the reasons for excluding texts will be recorded. The flow diagram of the article selection process for Covidence will be shown in the PRISMA flow diagram Supplementary Figure 1. Supplementary Figure 1 (Refer extended data) PRISMA Flow Diagram of the Article Screening Process. Data extraction J.Z. will independently extract specified characteristics from selected studies into a designated Excel spreadsheet for data extraction. Subsequently, M.C. and M.S. will independently assessed the extracted data. Any discrepancies identified during the review will b resolved through team meetings. Given the diversity of the data items to be extracted and the varied focus across papers, it is expected that not all papers will contain every piece of desired information. Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.Pre-defined study characteristics and outcome measures will be recorded in a standardized data extraction Excel spreadsheet, which will include the following information: Study design: randomised trials or non-randomised studies. Population: 1. Participant characteristics including age, gender, BMI, ethnicity, and healthy status. 2. Sample size: number of participants enrolled and analysed in the study. Intervention: 3. Meal content: Food items, nutritional, and calorie information. Calorie intake will be either extracted directly or calculated using reported nutritional information. 4. Timing and length of meal consumption 5. Fasting duration before interventions Comparisons: 6. Definition of ‘control’ groups (e.g., pre-meal vs. post-meal; high-calorie vs. low-calorie meal) Outcomes: 7. Quantitative data on physiological biomarkers: Time-series changes in heart rate, skin temperature, blood oxygen saturation, cardiac output, blood pressure, and intestinal blood flow before and after meals 8. Measurement instrument and intervals: Indicate whether outcomes are measured using traditional or wearable devices. If wearable devices are used, the performance metrics (e.g., accuracy, specificity, precision, recall, and F1-score) of the wearable sensors will be extracted, where applicable. 8. In addition to extracting predefined data fields, we anticipate comparing wearable sensor-derived measurements with traditional clinical methods where possible. As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available. Risk of bias assessment In this systematic review, a comprehensive assessment of the risk of bias in individual studies will b conducted to ensure the reliability and validity of our findings. We will follow the structured guidelines provided in Chapter 25 of the Cochrane Handbook for Systematic Reviews of Interventions, utilizing specific tools tailored to the type of study under review ( Higgins et al., 2019 ). • Risk of Bias In Non-randomized Studies-of Interventions (ROBINS-I) tool: for non-randomized studies, evaluating domains such as confounding, selection of participants, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes, and selection of reported results ( Sterne, Jonathan AC et al., 2016 ). • Risk of Bias (RoB) 2 tool: for randomized studies, examining domains including the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results ( Sterne, Jonathan A. C. et al., 2019 ). Risk of bias assessment will be carried out at both the study and outcome levels to identify biases that could impact the overall study or specific outcomes. The results of these assessments will b crucial to the data synthesis process. • Categorization of Studies: Each study will be categorized based on its assessed risk of bias: low, moderate, high, or critical. This categorization directly influenced the weight of each study contributing to the synthesis. • Interpretation of Findings: Categorization will also play a vital role in interpreting the review’s findings, especially when integrating results from studies with high or critical risk of bias. Visualization of bias assessment The results of the risk of bias assessments will be visualized using Robvis, a tool that generates high-quality publication-ready figures summarizing these assessments for systematic reviews ( McGuinness & Higgins, 2021 ). This visualization tool allows for customization according to the specific assessment tools used, such as RoB 2 or ROBINS-I, ensuring that our review’s risk-of-bias visualization is both informative and tailored to our specific methodology. These visualizations will aid in transparent reporting and a detailed discussion of the biases inherent in the included studies. Data synthesis This systematic review will integrate quantitative data from studies that examine physiological changes in postprandial status. Given the anticipated variation in study designs, populations, and measurement methods, we will initially perform a narrative synthesis to summarize and interpret the findings across different studies. A meta-analysis will be considered if the data extracted from the included studies demonstrate sufficient homogeneity in terms of the study design, intervention types, and reported outcomes. Our meta-analytic process willinclude the following steps. 1. Software for Data Synthesis: Statistical analyses, including meta-analysis, will be conducted using R Studio with the ‘metafor’ package, supporting fixed and random-effects models, heterogeneity assessment, subgroup, and sensitivity analyses. 2. Models for Meta-Analysis: We will select the meta-analytic model based on the data characteristics; a fixed-effects model will be used if the studies are sufficiently similar. Otherwise, a random-effects model will be employed to account for variability both within and across studies, if significant heterogeneity was detected. 3. Heterogeneity and Sensitivity Analysis: Heterogeneity will be assessed using the Q test and quantified using the I 2 statistic, which indicates the proportion of variance due to actual differences rather than chance, with values over 50% indicating substantial heterogeneity. Sensitivity analyses will be conducted by systematically excluding each study to check for significant changes in heterogeneity and overall results, ensuring that no single study disproportionately influences the effect sizes. 4. Subgroup Analyses and Meta-Regression: Subgroup analyses will be conducted to investigate whether moderators, such as high- and low-calorie meals, influence physiological biomarker changes differently. Meta-regression was performed to assess whether a dose-response relationship exists. 5. Assessment of Reporting Biases: To investigate potential publication biases, funnel plots will be used for visual examination and Egger’s test will be used to statistically determine the likelihood of bias influencing the reported results. Handling missing and incomplete data Where caloric information is missing, it will be calculated based on the macronutrient composition of the meal. Alternatively, the authors of the original study will be contacted. Where necessary, we will calculate standard deviations from the provided sample size and standard error mean or consider estimation methods if original data cannot be retrieved, adhering to the Cochrane guidelines ( Higgins et al., 2019 ). Expected results/ findings Based on previous literature and physiological mechanisms, we anticipate the following outcomes: • Transient increases in heart rate and blood pressure post-meal , with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements. • Variations in blood glucose and metabolic markers , influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels. • A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals , potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake. Confidence in cumulative evidence We used the GRADE framework to assess the quality of the evidence. Adjustments to the quality ratings will be made based on several factors: (i) Risk of Bias (RoB) across studies, (ii) indirect evidence, (iii) inconsistency of results, (iv) imprecision in data, and (v) Potential for Publication Bias. Evidence levels will be categorized as “high”, “moderate”, or “low”. Each reason for potential downgrade will be evaluated as “none,” “serious,” or “very serious.” Discussion Wearable devices have shown promise for monitoring eating episodes by capturing eating gestures or food images. Integrating physiological parameters, such as heart rate, blood pressure, and skin temperature, may enhance the estimation of food and energy intake. A systematic review is needed to consolidate the current evidence on the relationship between these physiological parameters and dietary intake and to assess the potential for tracking these changes in differentiating high- and low-calorie intake. This protocol is designed in strict adherence to the PRISMA-P guidelines to ensure the execution of a high-quality systematic review and meta-analysis. To our knowledge, this review is the first to systematically investigate the changes in key physiological biomarkers from pre- to post-meal states and their relationships with energy intake. The planned systematic review will enhance our understanding of physiological responses following dietary intake and may inform new wearable technologies for more accurate and real-time monitoring of food consumption. Declarations Ethics and dissemination This systematic review does not require ethical approval as it relies on previously published studies that contain non-identifiable data. The outcomes of the review will be shared through publication in a peer-reviewed journal, and presentations at conferences and seminars. Patient consent for publication Not required. Author’s contributions M.C. and M.S. designed and directed the project; M.C. and M.S. acquired funding as co-PIs; J.Z., M.C., and M.S. wrote this protocol. Data availability Underlying data No data are associated with this article. Extended data Figshare: Extended data for ‘Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol’. DOI: https://doi.org/10.6084/m9.figshare.27303741.v1 ( Zhou et al., 2024 ). The project contains the following extended data: • Data file 2: Search Strategy Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Reporting guidelines Figshare: Extended data for ‘Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol’. DOI: https://doi.org/10.6084/m9.figshare.27303741.v1 ( Zhou et al., 2024 ). The project contains the following Reporting guidelines: • Data file 1: PRISMA Flow Chart • Data file 3: PRISMA-P Checklist Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). References Burrows TL, Rollo ME: Advancement in Dietary Assessment and Self-Monitoring Using Technology. Nutrients. 2019; 11 (7): 1648. PubMed Abstract | Publisher Full Text | Free Full Text Cuparencu C, Bulmuş-Tüccar T, Stanstrup J, et al. : Towards nutrition with precision: unlocking biomarkers as dietary assessment tools. Nat. Metab. 2024; 6 (8): 1438–1453. PubMed Abstract | Publisher Full Text De Aguiar Cassiani R, Manfredi C, Santos JA, et al. : Arterial oxygen saturation and heart rate during a meal in chronic obstructive pulmonary disease.2011. Doulah A, Ghosh T, Hossain D, et al. : Energy intake estimation using a novel wearable sensor and food images in a laboratory (pseudo-free-living) meal setting: quantification and contribution of sources of error. Springer Science and Business Media LLC; 2022. Higgins JPT, Thomas J, Chandler J, et al. : Cochrane Handbook for Systematic Reviews of Interventions. Wiley Cochrane Series. 2nd ed.Newark: John Wiley & Sons, Ltd; 2019. Maruvada P, Lampe JW, Wishart DS, et al. : Perspective: Dietary Biomarkers of Intake and Exposure—Exploration with Omics Approaches. Adv. Nutr. 2020; 11 (2): 200–215. PubMed Abstract | Publisher Full Text | Free Full Text McGuinness LA, Higgins JPT: Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res. Synth. Methods. 2021; 12 (1): 55–61. PubMed Abstract | Publisher Full Text Moher D, Shamseer L, Clarke M, et al. : Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015; 4 (1). PubMed Abstract | Publisher Full Text | Free Full Text Shamseer L, Moher D, Clarke M, et al. : Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015; 349 (jan02 1): 7647. PubMed Abstract | Publisher Full Text Sidery MB, Macdonald IA: The effect of meal size on the cardiovascular responses to food ingestion. Br. J. Nutr. 1994; 71 (6): 835–848. PubMed Abstract | Publisher Full Text Sit SP, Chou CC: Time course of jejunal blood flow, O2 uptake, and O2 extraction during nutrient absorption. Am. J. Physiol. Heart Circ. Physiol. 1984; 247 (3): H395–H402. PubMed Abstract | Publisher Full Text Sterne JAC, Savović J, Page MJ, et al. : RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ (Online). 2019; 366 : l4898. Publisher Full Text Sterne JA, Hernán MA, Reeves BC, et al. : ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ (Online). 2016; 355 : i4919. PubMed Abstract | Publisher Full Text | Free Full Text Vu T, Lin F, Alshurafa N, et al. : Wearable Food Intake Monitoring Technologies: A Comprehensive Review. Computers (Basel). 2017; 6 (1): 4. Publisher Full Text Westerterp KR: Diet induced thermogenesis. Nutr. Metab. 2004; 1 (1): 5. PubMed Abstract | Publisher Full Text | Free Full Text Zhou J, Shi M, Cai M: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol. Dataset. figshare. 2024. Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 13 Nov 2024 ADD YOUR COMMENT Comment Author details Author details 1 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, England, UK 2 Department of Electrical and Electronic Engineering, Imperial College London, London, England, UK Jiaying Zhou Roles: Methodology, Writing – Original Draft Preparation Mayue Shi Roles: Conceptualization, Supervision, Writing – Review & Editing Mingzhu Cai Roles: Conceptualization, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This work was supported by the Dame Julia Higgins Postdoc Collaborative Research Fund. The sponsor had no role in composing the study design, collection, management, analysis, and interpretation of data. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (2) version 2 Revised Published: 03 Apr 2025, 13:1358 https://doi.org/10.12688/f1000research.157875.2 version 1 Published: 13 Nov 2024, 13:1358 https://doi.org/10.12688/f1000research.157875.1 Copyright © 2025 Zhou J et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Zhou J, Shi M and Cai M. Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.12688/f1000research.157875.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 03 Apr 2025 Revised Views 0 Cite How to cite this report: Iftikhar FJ. Reviewer Report For: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.5256/f1000research.179800.r375418 ) The direct URL for this report is: https://f1000research.com/articles/13-1358/v2#referee-response-375418 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 05 May 2025 Faiza Jan Iftikhar , National University of Technology (NUTECH), Islamabad, Pakistan Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.179800.r375418 Avoid using first person (plural) pronouns 2. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. What is meant by reviewer here? 3. Our primary outcome ... Continue reading READ ALL Avoid using first person (plural) pronouns 2. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. What is meant by reviewer here? 3. Our primary outcome will be the comparison of physiological biomarkers: mention the physiological biomarkers here 4. Intestinal blood flow measured using wearable or traditional devices: what wearables are used to detect intestinal blood flow. The intestinal flow is mentioned only twice and it seems it is added as an afterthought. Please check. 5. The results section shows no graphs. Is that normal when publishing a study protocol? Competing Interests: No competing interests were disclosed. Reviewer Expertise: Bio sensor /chemical sensors including wearable sensor. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Iftikhar FJ. Reviewer Report For: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.5256/f1000research.179800.r375418 ) The direct URL for this report is: https://f1000research.com/articles/13-1358/v2#referee-response-375418 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 13 Nov 2024 Views 0 Cite How to cite this report: Iftikhar FJ. Reviewer Report For: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.5256/f1000research.173392.r343907 ) The direct URL for this report is: https://f1000research.com/articles/13-1358/v1#referee-response-343907 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 27 Jan 2025 Faiza Jan Iftikhar , National University of Technology (NUTECH), Islamabad, Pakistan Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.173392.r343907 The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. It aims to assess the effectiveness of wearable technologies by tracking physiological biomarkers pre- and postprandial. It is ... Continue reading READ ALL The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. It aims to assess the effectiveness of wearable technologies by tracking physiological biomarkers pre- and postprandial. It is contended that the wearable devices are able to monitor the changes in heart rate, oxygen level, skin temperature etc., in a more accurate and continuous manner. This study aims to study these biomarkers that results due to high and low calories meals. It should be made clear that it is a secondary research. The PICO method is not explained and the different PICOs are given though with some repetition Different frameworks are being referred to but not explained. The expected results of the methods used is not given. Hence outcomes are not clear. They should include measurable results expected from the test It looks more like writing a review but expected results and findings extracted from secondary research is not given It says: Comparing wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. Mention what are the traditional methods that will be compared with. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Partly Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Bio sensor /chemical sensors including wearable sensor. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Iftikhar FJ. Reviewer Report For: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.5256/f1000research.173392.r343907 ) The direct URL for this report is: https://f1000research.com/articles/13-1358/v1#referee-response-343907 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 03 Apr 2025 Jiaying Zhou , 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK 03 Apr 2025 Author Response Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, ... Continue reading Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail. Response to Specific Comments: Journal Focus Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. Response: As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope. Clarifying that this is a secondary research study and improving PICO explanation Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition. Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation: We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study. The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72. Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below: “Study Design and Context Inclusion Criteria: Experiential studies involving human participants in either controlled or real-life environments. Randomized or non-randomized trials, including single-arm studies. English-language articles published in peer-reviewed journals. Exclusion Criteria: Review articles, commentaries, and protocols. Studies without human involvement. A publication cutoff date of February 7, 2024 , will be applied.” Explanation of Different Frameworks Reviewer Comment: Different frameworks are being referred to but not explained. Response: We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows: The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43. The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72. The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319. Expected Results and Measurable Outcomes Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test. Response: We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’: “Primary Outcomes Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters. Secondary Outcomes Our secondary outcomes will focus on two key areas: Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes. Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.” Expected Findings from Secondary Research Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given. Response: This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.” For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.” We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added: “Expected Results/Findings Based on previous literature and physiological mechanisms, we anticipate the following outcomes: Transient increases in heart rate and blood pressure post-meal , with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements. Variations in blood glucose and metabolic markers , influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels. A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals , potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.” Comparison with Traditional Methods for Monitoring Physiological Biomarkers Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared. Response: To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “ As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.” Sincerely, Jiaying Zhou Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail. Response to Specific Comments: Journal Focus Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. Response: As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope. Clarifying that this is a secondary research study and improving PICO explanation Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition. Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation: We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study. The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72. Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below: “Study Design and Context Inclusion Criteria: Experiential studies involving human participants in either controlled or real-life environments. Randomized or non-randomized trials, including single-arm studies. English-language articles published in peer-reviewed journals. Exclusion Criteria: Review articles, commentaries, and protocols. Studies without human involvement. A publication cutoff date of February 7, 2024 , will be applied.” Explanation of Different Frameworks Reviewer Comment: Different frameworks are being referred to but not explained. Response: We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows: The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43. The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72. The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319. Expected Results and Measurable Outcomes Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test. Response: We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’: “Primary Outcomes Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters. Secondary Outcomes Our secondary outcomes will focus on two key areas: Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes. Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.” Expected Findings from Secondary Research Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given. Response: This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.” For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.” We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added: “Expected Results/Findings Based on previous literature and physiological mechanisms, we anticipate the following outcomes: Transient increases in heart rate and blood pressure post-meal , with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements. Variations in blood glucose and metabolic markers , influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels. A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals , potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.” Comparison with Traditional Methods for Monitoring Physiological Biomarkers Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared. Response: To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “ As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.” Sincerely, Jiaying Zhou Competing Interests: The authors declare no competing interests. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 03 Apr 2025 Jiaying Zhou , 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK 03 Apr 2025 Author Response Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, ... Continue reading Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail. Response to Specific Comments: Journal Focus Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. Response: As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope. Clarifying that this is a secondary research study and improving PICO explanation Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition. Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation: We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study. The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72. Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below: “Study Design and Context Inclusion Criteria: Experiential studies involving human participants in either controlled or real-life environments. Randomized or non-randomized trials, including single-arm studies. English-language articles published in peer-reviewed journals. Exclusion Criteria: Review articles, commentaries, and protocols. Studies without human involvement. A publication cutoff date of February 7, 2024 , will be applied.” Explanation of Different Frameworks Reviewer Comment: Different frameworks are being referred to but not explained. Response: We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows: The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43. The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72. The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319. Expected Results and Measurable Outcomes Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test. Response: We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’: “Primary Outcomes Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters. Secondary Outcomes Our secondary outcomes will focus on two key areas: Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes. Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.” Expected Findings from Secondary Research Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given. Response: This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.” For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.” We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added: “Expected Results/Findings Based on previous literature and physiological mechanisms, we anticipate the following outcomes: Transient increases in heart rate and blood pressure post-meal , with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements. Variations in blood glucose and metabolic markers , influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels. A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals , potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.” Comparison with Traditional Methods for Monitoring Physiological Biomarkers Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared. Response: To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “ As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.” Sincerely, Jiaying Zhou Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail. Response to Specific Comments: Journal Focus Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. Response: As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope. Clarifying that this is a secondary research study and improving PICO explanation Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition. Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation: We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study. The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72. Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below: “Study Design and Context Inclusion Criteria: Experiential studies involving human participants in either controlled or real-life environments. Randomized or non-randomized trials, including single-arm studies. English-language articles published in peer-reviewed journals. Exclusion Criteria: Review articles, commentaries, and protocols. Studies without human involvement. A publication cutoff date of February 7, 2024 , will be applied.” Explanation of Different Frameworks Reviewer Comment: Different frameworks are being referred to but not explained. Response: We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows: The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43. The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72. The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319. Expected Results and Measurable Outcomes Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test. Response: We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’: “Primary Outcomes Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters. Secondary Outcomes Our secondary outcomes will focus on two key areas: Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes. Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.” Expected Findings from Secondary Research Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given. Response: This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.” For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.” We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added: “Expected Results/Findings Based on previous literature and physiological mechanisms, we anticipate the following outcomes: Transient increases in heart rate and blood pressure post-meal , with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements. Variations in blood glucose and metabolic markers , influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels. A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals , potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.” Comparison with Traditional Methods for Monitoring Physiological Biomarkers Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared. Response: To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “ As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.” Sincerely, Jiaying Zhou Competing Interests: The authors declare no competing interests. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 13 Nov 2024 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 Version 2 (revision) 03 Apr 25 read Version 1 13 Nov 24 read Faiza Jan Iftikhar , National University of Technology (NUTECH), Islamabad, Pakistan Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Iftikhar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 05 May 2025 | for Version 2 Faiza Jan Iftikhar , National University of Technology (NUTECH), Islamabad, Pakistan 0 Views copyright © 2025 Iftikhar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Avoid using first person (plural) pronouns 2. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. What is meant by reviewer here? 3. Our primary outcome will be the comparison of physiological biomarkers: mention the physiological biomarkers here 4. Intestinal blood flow measured using wearable or traditional devices: what wearables are used to detect intestinal blood flow. The intestinal flow is mentioned only twice and it seems it is added as an afterthought. Please check. 5. The results section shows no graphs. Is that normal when publishing a study protocol? Competing Interests No competing interests were disclosed. Reviewer Expertise Bio sensor /chemical sensors including wearable sensor. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Iftikhar FJ. Peer Review Report For: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.5256/f1000research.179800.r375418) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-1358/v2#referee-response-375418 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Iftikhar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 27 Jan 2025 | for Version 1 Faiza Jan Iftikhar , National University of Technology (NUTECH), Islamabad, Pakistan 0 Views copyright © 2025 Iftikhar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. It aims to assess the effectiveness of wearable technologies by tracking physiological biomarkers pre- and postprandial. It is contended that the wearable devices are able to monitor the changes in heart rate, oxygen level, skin temperature etc., in a more accurate and continuous manner. This study aims to study these biomarkers that results due to high and low calories meals. It should be made clear that it is a secondary research. The PICO method is not explained and the different PICOs are given though with some repetition Different frameworks are being referred to but not explained. The expected results of the methods used is not given. Hence outcomes are not clear. They should include measurable results expected from the test It looks more like writing a review but expected results and findings extracted from secondary research is not given It says: Comparing wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. Mention what are the traditional methods that will be compared with. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Partly Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Bio sensor /chemical sensors including wearable sensor. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 03 Apr 2025 Jiaying Zhou, 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK Dear Reviewer, We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail. Response to Specific Comments: Journal Focus Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. Response: As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope. Clarifying that this is a secondary research study and improving PICO explanation Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition. Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation: We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study. The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72. Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below: “Study Design and Context Inclusion Criteria: Experiential studies involving human participants in either controlled or real-life environments. Randomized or non-randomized trials, including single-arm studies. English-language articles published in peer-reviewed journals. Exclusion Criteria: Review articles, commentaries, and protocols. Studies without human involvement. A publication cutoff date of February 7, 2024 , will be applied.” Explanation of Different Frameworks Reviewer Comment: Different frameworks are being referred to but not explained. Response: We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows: The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43. The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72. The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319. Expected Results and Measurable Outcomes Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test. Response: We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’: “Primary Outcomes Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters. Secondary Outcomes Our secondary outcomes will focus on two key areas: Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes. Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.” Expected Findings from Secondary Research Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given. Response: This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.” For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.” We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added: “Expected Results/Findings Based on previous literature and physiological mechanisms, we anticipate the following outcomes: Transient increases in heart rate and blood pressure post-meal , with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements. Variations in blood glucose and metabolic markers , influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels. A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals , potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.” Comparison with Traditional Methods for Monitoring Physiological Biomarkers Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared. Response: To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “ As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.” Sincerely, Jiaying Zhou View more View less Competing Interests The authors declare no competing interests. reply Respond Report a concern Iftikhar FJ. Peer Review Report For: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations] . F1000Research 2025, 13 :1358 ( https://doi.org/10.5256/f1000research.173392.r343907) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-1358/v1#referee-response-343907 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Stay Updated Sign up for content alerts and receive a weekly or monthly email with all newly published articles Register with F1000Research Already registered? Sign in Not now, thanks close PLEASE NOTE If you are an AUTHOR of this article, please check that you signed in with the account associated with this article otherwise we cannot automatically identify your role as an author and your comment will be labelled as a “User Comment”. If you are a REVIEWER of this article, please check that you have signed in with the account associated with this article and then go to your account to submit your report, please do not post your review here. If you do not have access to your original account, please contact us . All commenters must hold a formal affiliation as per our Policies . The information that you give us will be displayed next to your comment. User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions . Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available. I accept the User Comment Terms and Conditions Please confirm that you accept the User Comment Terms and Conditions. Affiliation ✕ refresh Please enter your institution. Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered. ✕ refresh Country/Region * USA UK Canada China France Germany Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Cook Islands Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Democratic Republic of the Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands Faroe Islands Federated States of Micronesia Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Kosovo (Serbia and Montenegro) Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Minor Outlying Islands of the United States Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island North Korea North Macedonia Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Is South Korea South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand The Gambia The Netherlands Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu UK USA Uganda Ukraine United Arab Emirates United States Virgin Islands Uruguay Uzbekistan Vanuatu Venezuela Vietnam Wallis and Futuna West Bank and Gaza Strip Western Sahara Yemen Zambia Zimbabwe Please select your country/region. You must enter a comment. Competing Interests Please disclose any competing interests that might be construed to influence your judgment of the article's or peer review report's validity or importance. Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Please state your competing interests The comment has been saved. An error has occurred. Please try again. Cancel Post var lTitle = "Identifying and Assessing Physiological Biomarkers...".replace("'", ''); var linkedInUrl = "http://www.linkedin.com/shareArticle?url=https://f1000research.com/articles/13-1358/v2" + "&title=" + encodeURIComponent(lTitle) + "&summary=" + encodeURIComponent('Read the article by '); var deliciousUrl = "https://del.icio.us/post?url=https://f1000research.com/articles/13-1358/v2&title=" + encodeURIComponent(lTitle); var redditUrl = "http://reddit.com/submit?url=https://f1000research.com/articles/13-1358/v2" + "&title=" + encodeURIComponent(lTitle); linkedInUrl += encodeURIComponent('Zhou J et al.'); var offsetTop = /chrome/i.test( navigator.userAgent ) ? 4 : -10; var addthis_config = { ui_offset_top: offsetTop, services_compact : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_expanded : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_custom : [ { name: "LinkedIn", url: linkedInUrl, icon:"/img/icon/at_linkedin.svg" }, { name: "Mendeley", url: "http://www.mendeley.com/import/?url=https://f1000research.com/articles/13-1358/v2/mendeley", icon:"/img/icon/at_mendeley.svg" }, { name: "Reddit", url: redditUrl, icon:"/img/icon/at_reddit.svg" }, ] }; var addthis_share = { url: "https://f1000research.com/articles/13-1358", templates : { twitter : "Identifying and Assessing Physiological Biomarkers for Food and.... Zhou J et al., published by " + "@F1000Research" + ", https://f1000research.com/articles/13-1358/v2" } }; if (typeof(addthis) != "undefined"){ addthis.addEventListener('addthis.ready', checkCount); addthis.addEventListener('addthis.menu.share', checkCount); } $(".f1r-shares-twitter").attr("href", "https://twitter.com/intent/tweet?text=" + addthis_share.templates.twitter); $(".f1r-shares-facebook").attr("href", "https://www.facebook.com/sharer/sharer.php?u=" + addthis_share.url); $(".f1r-shares-linkedin").attr("href", addthis_config.services_custom[0].url); $(".f1r-shares-reddit").attr("href", addthis_config.services_custom[2].url); $(".f1r-shares-mendelay").attr("href", addthis_config.services_custom[1].url); function checkCount(){ setTimeout(function(){ $(".addthis_button_expanded").each(function(){ var count = $(this).text(); if (count !== "" && count != "0") $(this).removeClass("is-hidden"); else $(this).addClass("is-hidden"); }); }, 1000); } close How to cite this report {{reportCitation}} Cancel Copy Citation Details $(function(){R.ui.buttonDropdowns('.dropdown-for-downloads');}); $(function(){R.ui.toolbarDropdowns('.toolbar-dropdown-for-downloads');}); $.get("/articles/acj/157875/179800") new F1000.Clipboard(); new F1000.ThesaurusTermsDisplay("articles", "article", "179800"); $(document).ready(function() { $( "#frame1" ).on('load', function() { var mydiv = $(this).contents().find("div"); var h = mydiv.height(); console.log(h) }); var tooltipLivingFigure = jQuery(".interactive-living-figure-label .icon-more-info"), titleLivingFigure = tooltipLivingFigure.attr("title"); tooltipLivingFigure.simpletip({ fixed: true, position: ["-115", "30"], baseClass: 'small-tooltip', content:titleLivingFigure + " " }); tooltipLivingFigure.removeAttr("title"); $("body").on("click", ".cite-living-figure", function(e) { e.preventDefault(); var ref = $(this).attr("data-ref"); $(this).closest(".living-figure-list-container").find("#" + ref).fadeIn(200); }); $("body").on("click", ".close-cite-living-figure", function(e) { e.preventDefault(); $(this).closest(".popup-window-wrapper").fadeOut(200); }); $(document).on("mouseup", function(e) { var metricsContainer = $(".article-metrics-popover-wrapper"); if (!metricsContainer.is(e.target) && metricsContainer.has(e.target).length === 0) { $(".article-metrics-close-button").click(); } }); var articleId = $('#articleId').val(); if($("#main-article-count-box").attachArticleMetrics) { $("#main-article-count-box").attachArticleMetrics(articleId, { articleMetricsView: true }); } }); var figshareWidget = $(".new_figshare_widget"); if (figshareWidget.length > 0) { window.figshare.load("f1000", function(Widget) { // Select a tag/tags defined in your page. In this tag we will place the widget. _.map(figshareWidget, function(el){ var widget = new Widget({ articleId: $(el).attr("figshare_articleId") //height:300 // this is the height of the viewer part. [Default: 550] }); widget.initialize(); // initialize the widget widget.mount(el); // mount it in a tag that's on your page // this will save the widget on the global scope for later use from // your JS scripts. This line is optional. //window.widget = widget; }); }); } close Error Close Add Reset F1000.MICROSERVICES.AFFILIATION = ''; $(document).ready(function () { $('.js-affiliations-form').each((index, form) => { new AffiliationForm({ formId: form.id, institutionErrorSelector: '.comment-enter-institution', departmentErrorSelector: '.comment-enter-department', placeSelector: '.js-add-comment-place', stateSelector: '.js-add-comment-state', zipCodeSelector: '.js-add-comment-zipcode', countrySelector: '.js-add-comment-country', countryErrorSelector: '.comment-enter-country', }); }); }); $(document).ready(function () { var reportIds = { "364556": 0, "364553": 0, "364552": 0, "364555": 0, "364554": 0, "385301": 0, "385300": 0, "385303": 0, "385302": 0, "385297": 0, "385299": 0, "385298": 0, "380701": 0, "380700": 0, "380703": 0, "380702": 0, "380697": 0, "385305": 0, "385304": 0, "380699": 0, "380698": 0, "385306": 0, "348455": 0, "380705": 0, "380704": 0, "380706": 0, "348461": 0, "348460": 0, "348463": 0, "348462": 0, "348457": 0, "348456": 0, "348459": 0, "348458": 0, "348464": 0, "359749": 0, "359751": 0, "359750": 0, "383309": 0, "383311": 0, "383310": 0, "383317": 0, "383316": 0, "383318": 0, "383313": 0, "383312": 0, "383315": 0, "383314": 0, "378205": 0, "343901": 0, "378204": 0, "343900": 0, "378207": 0, "343903": 0, "378206": 0, "343902": 0, "378201": 0, "378203": 0, "378202": 0, "343909": 0, "343908": 0, "378209": 0, "343905": 0, "378208": 0, "343904": 0, "343907": 17, "378210": 0, "343906": 0, "390013": 0, "390012": 0, "390015": 0, "390014": 0, "390011": 0, "390010": 0, "375418": 3, "390017": 0, "390016": 0, "390019": 0, "390018": 0, "370322": 0, "387749": 0, "375973": 0, "375972": 0, "387751": 0, "375975": 0, "387750": 0, "375974": 0, "387757": 0, "375981": 0, "340909": 0, "387756": 0, "375980": 0, "340908": 0, "340911": 0, "387758": 0, "340910": 0, "387753": 0, "375977": 0, "340905": 0, "387752": 0, "375976": 0, "387755": 0, "375979": 0, "340907": 0, "387754": 0, "375978": 0, "340906": 0, "340913": 0, "340912": 0, "340914": 0, "354493": 0, "354492": 0, "354495": 0, "354494": 0, "368056": 0, "354491": 0, "354490": 0, "354497": 0, "354496": 0, "354499": 0, "354498": 0, }; $(".referee-response-container,.js-referee-report").each(function(index, el) { var reportId = $(el).attr("data-reportid"), reportCount = reportIds[reportId] || 0; $(el).find(".comments-count-container,.js-referee-report-views").html(reportCount); }); var uuidInput = $("#article_uuid"), oldUUId = uuidInput.val(), newUUId = "715e1263-4663-4432-9a75-6a4a311f5a90"; uuidInput.val(newUUId); $("a[href*='article_uuid=']").each(function(index, el) { var newHref = $(el).attr("href").replace(oldUUId, newUUId); $(el).attr("href", newHref); }); }); An innovative open access publishing platform offering rapid publication and open peer review, whilst supporting data deposition and sharing. Browse Gateways Collections How it Works Contact For Developers Cookie Notice Privacy Notice RSS Submit Your Research Follow us © 2012-2026 F1000 Research Ltd. ISSN 2046-1402 | Legal | Partner of Research4Life • CrossRef • ORCID • FAIRSharing R.templateTests.simpleTemplate = R.template(' $text $text $text $text $text '); R.templateTests.runTests(); var F1000platform = new F1000.Platform({ name: "f1000research", displayName: "F1000Research", hostName: "f1000research.com", id: "1", editorialEmail: "[email protected]", infoEmail: "[email protected]", usePmcStats: true }); $(function(){R.ui.dropdowns('.dropdown-for-authors, .dropdown-for-about, .dropdown-for-myresearch');}); // $(function(){R.ui.dropdowns('.dropdown-for-referees');}); $(document).ready(function () { if ($(".cookie-warning").is(":visible")) { $(".sticky").css("margin-bottom", "35px"); $(".devices").addClass("devices-and-cookie-warning"); } $(".cookie-warning .close-button").click(function (e) { $(".devices").removeClass("devices-and-cookie-warning"); $(".sticky").css("margin-bottom", "0"); }); $("#tweeter-feed .tweet-message").each(function (i, message) { var self = $(message); self.html(linkify(self.html())); }); $(".partner").on("mouseenter mouseleave", function() { $(this).find(".gray-scale, .colour").toggleClass("is-hidden"); }); }); Sign In Remember me Forgotten your password? Sign In Cancel Email or password not correct. Please try again Please wait... $(function(){ // Note: All the setup needs to run against a name attribute and *not* the id due the clonish // nature of facebox... $("a[id=googleSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("GOOGLE"); $("form[id=oAuthForm]").submit(); }); $("a[id=facebookSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("FACEBOOK"); $("form[id=oAuthForm]").submit(); }); $("a[id=orcidSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("ORCID"); $("form[id=oAuthForm]").submit(); }); }); If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Email address not valid, please try again You registered with F1000 via Google, so we cannot reset your password. To sign in, please click here . If you still need help with your Google account password, please click here . You registered with F1000 via Facebook, so we cannot reset your password. To sign in, please click here . If you still need help with your Facebook account password, please click here . Code not correct, please try again Reset password Cancel Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password. If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance. Please wait... Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });