. * * window.aa needs to exist and be usable by ANY module's script, * however early it runs - main-nav's script, for one, runs near * the top of

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, well before the real search-insights.js * so the download * begins as early as before. Repeat calls share the same downloads, a * failed load is retried on the next call, and the versions / SRI * hashes live only here. * * Algolia Insights is unaffected: window.aa above is still created in * on every page and queues events until search-insights loads. * * window.loadAlgoliaLibs({ priority: 'high' }) (Oct 2026): used by the * /search page, where the first results wait on these libraries. Chrome * gives async scripts low priority, behind images and fonts; this asks * for high instead (fetchpriority). Only the first call for a library * sets its priority - later calls share that download. */ (function (win, doc) { var LIBS = [ { ready: function () { return !!win['algoliasearch/lite']; }, src: 'https://cdn.jsdelivr.net/npm/algoliasearch@5.52.1/dist/lite/builds/browser.umd.js', integrity: 'sha256-I2oYUIvhx1g6l4lTP+yoERbzLIHKzw4AKaBRQPwIeDY=' }, { ready: function () { return !!win.instantsearch; }, src: 'https://cdn.jsdelivr.net/npm/instantsearch.js@4.98.0/dist/instantsearch.production.min.js', integrity: 'sha256-ngmqZk4WBxUw257aMYZayyNBd983INngagv0jI6Ecfs=' } ]; function loadOne(lib, options) { if (lib.ready()) return Promise.resolve(); // One download per library, shared by every caller; reset on // failure so the next call retries just the library that failed. if (lib.pending) return lib.pending; lib.pending = new Promise(function (resolve, reject) { var script = doc.createElement('script'); script.src = lib.src; script.integrity = lib.integrity; script.crossOrigin = 'anonymous'; script.async = true; if (options && options.priority === 'high') script.setAttribute('fetchpriority', 'high'); script.onload = function () { lib.ready() ? resolve() : reject(new Error('Loaded but not available: ' + lib.src)); }; script.onerror = function () { script.remove(); reject(new Error('Could not load ' + lib.src)); }; doc.head.appendChild(script); }); lib.pending.catch(function () { lib.pending = null; }); return lib.pending; } win.loadAlgoliaLibs = function (options) { return Promise.all(LIBS.map(function (lib) { return loadOne(lib, options); })); }; })(window, document); . */ window.hsConversationsSettings = window.hsConversationsSettings || {}; window.hsConversationsSettings.loadImmediately = false; (function (win) { var EVENTS = ['pointerdown', 'keydown', 'touchstart', 'scroll', 'mousemove', 'wheel']; var done = false; /* 19 Oct 2026 - chat widget layout shift (field CLS). Phones fail Core Web Vitals on CLS (p75 ~0.2 site-wide in CrUX for months). Biggest cause found: HubSpot's chat container is fixed to the bottom-right corner and changes size - 100x96 launcher to 282x253 when the welcome message pops up (~5 s after load), and to full screen when a visitor opens the chat. Its top-left corner moves, so Chrome scores it as a layout shift: 0.088 per page view at 360x640 (0.044 at 412x850), on every page. Taps happen inside the chat iframe, so the parent page never sees the input and the open/close shifts count too. Fix: whenever the container's size changes it is made transparent for 400 ms (Chrome doesn't score shifts of invisible elements), then shown again at its new size. Tested on live io1001 at 360x640 in a cookie-less frame: the 0.088 shift no longer appears. The chat itself is unchanged - it just appears 0.4 s later at each resize. Relies on HubSpot's container id; if that changes this does nothing (no error). */ function cloakChatResizes() { var ID = 'hubspot-messages-iframe-container'; function watch(c) { if (c.getAttribute('data-bb-cloak')) return; c.setAttribute('data-bb-cloak', '1'); var last = c.offsetWidth + 'x' + c.offsetHeight, timer = null; new MutationObserver(function () { var size = c.offsetWidth + 'x' + c.offsetHeight; if (size === last) return; last = size; c.style.setProperty('opacity', '0', 'important'); clearTimeout(timer); timer = setTimeout(function () { c.style.removeProperty('opacity'); }, 400); }).observe(c, { attributes: true, attributeFilter: ['style', 'class'], subtree: true, childList: true }); } var found = document.getElementById(ID); if (found) { watch(found); return; } if (!document.body || !('MutationObserver' in win)) return; var mo = new MutationObserver(function () { var c = document.getElementById(ID); if (c) { mo.disconnect(); watch(c); } }); mo.observe(document.body, { childList: true }); setTimeout(function () { mo.disconnect(); }, 30000); } function loadWidget() { var api = win.HubSpotConversations; if (api && api.widget && api.widget.status && api.widget.status().loaded) return; try { cloakChatResizes(); } catch (e) {} if (api && api.widget) api.widget.load(); } function onFirstInteraction() { if (done) return; done = true; EVENTS.forEach(function (type) { win.removeEventListener(type, onFirstInteraction, { passive: true }); }); var start = function () { if (win.HubSpotConversations) loadWidget(); else (win.hsConversationsOnReady = win.hsConversationsOnReady || []).push(loadWidget); }; if ('requestIdleCallback' in win) win.requestIdleCallback(start, { timeout: 1500 }); else setTimeout(start, 200); } EVENTS.forEach(function (type) { win.addEventListener(type, onFirstInteraction, { passive: true }); }); })(window);

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Generating publishable neuroscience research in 12 weeks with ioGlutamatergic Neurons
Case study

Generating publishable neuroscience research in 12 weeks with ioGlutamatergic Neurons

This case study showcases the research of Professor Deepak Srivastava's lab at King鈥檚 College London, and their use of cutting-edge human iPSC-derived cells to optimise their experimental timelines in their recent publication identifying schizophrenia risk factors.
Generating publishable neuroscience research in 12 weeks with ioGlutamatergic Neurons

Professor Deepak Srivastava

Professor of Molecular Neuroscience and Group Leader, MRC Centre for Developmental Disorders

King鈥檚 College London 

Generating publishable neuroscience research in 12 weeks with ioGlutamatergic Neurons
This case study showcases the research of Professor Deepak Srivastava's lab at King鈥檚 College London, and their use of cutting-edge human iPSC-derived cells to optimise their experimental timelines in their recent publication identifying schizophrenia risk factors.
Generating publishable neuroscience research in 12 weeks with ioGlutamatergic Neurons

Professor Deepak Srivastava

Professor of Molecular Neuroscience and Group Leader, MRC Centre for Developmental Disorders

King鈥檚 College London 

It took Professor Deepak Srivastava鈥檚 lab at King鈥檚 College London just 12 weeks to generate publishable data on schizophrenia risk factors. This dramatically short research timeline was driven by the lab鈥檚 push to maximise the value of their students鈥� time at the bench and was achieved by adopting precision reprogrammed human iPSC-derived glutamatergic neurons in their experiments.

In this case study, you will learn:

  • About Professor Srivastava鈥檚 research on the molecular mechanisms that impact cognitive function, and his focus on Schizophrenia.
  • How his lab use hiPSC-derived excitatory neurons to model key triggers that may impact an individual鈥檚 propensity to develop schizophrenia during their lifetime.
  • How the use of opti-ox powered human iPSC-derived cells has enabled his lab to optimise their time at the bench.

V2

2024

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