University of Aberdeen

在一项新的研究中，来自阿伯丁大学和埃克塞特大学等研究机构的研究人员聚焦于免疫细胞是如何感知它们的周围环境。这种感知行为会引发微妙平衡的反应，以防止疾病和感染，并减少可能损害细胞的炎症。特别地，他们报告了一种名为MICL的受体的行为及其在预防炎症和抵御感染方面的作用。 相关研究结果于2024年8月14日在线发表在Nature期刊上，论文标题为“Recognition and control of neutrophil extracellular trap formation by MICL”。 论文的第一作者、埃克塞特大学的 Mariano Malamud 博士表示：“我们发现 MICL 是一种关键受体，当其功能发生改变时会导致严重的炎症性疾病。这为开发针对 MICL 的新疗法以减轻炎症性疾病的严重程度并防止感染开辟了道路。” 通常，免疫系统中的大多数受体都会感知周围环境，并向细胞发送信号，指示它们激活以应对感染或组织损伤等情况。然而，这项新研究揭示 MICL 的作用恰恰相反，它能抑制细胞的激活。这其实是一个重要的功能，因为如果任由细胞过度激活，会导致细胞损伤和自身免疫性疾病的发生。 研究团队进一步证实了 MICL 在调节严重 COVID-19 炎症、关节炎以及其他自身免疫性疾病中的重要角色。这项研究主要在小鼠身上进行，并且在患者身上也得到了验证。研究重点放在了一种最常见的免疫细胞——中性粒细胞表面的 MICL 功能上。 当遇到自身免疫性疾病或感染时，中性粒细胞会经历称为 NETosis 的程序性细胞死亡，这是一种控制感染的关键机制，但也容易引发炎症。研究团队发现 MICL 能够检测这种状态，并通过其抑制活性来阻止更多中性粒细胞以这种方式死亡。 NETosis 与多种人类炎症性疾病有关，例如红斑狼疮、类风湿性关节炎和严重的 COVID-19。这些炎症性疾病会导致产生与 MICL 结合的抗体，从而阻碍其抑制功能，使疾病恶化。与此相反的是，通过阻断 MICL 的功能来增加 NETosis 可以帮助预防感染，比如真菌感染。 MICL是控制中性粒细胞反应所必需的 图片来自Nature, 2024, doi:10.1038/s41586-024-07820-3 研究团队在患有关节炎的小鼠身上发现，遗传性 MICL 缺陷会导致中性粒细胞胞外陷阱（Neutrophil extracellular traps, NETs）过度形成，从而使疾病更为严重。给正常小鼠施加靶向 MICL 的抗体同样会导致更严重的疾病。实际上，携带靶向 MICL 抗体的人类关节炎患者也会出现更严重的疾病，研究团队在实验室中直接证实了这些患者的抗体加剧了炎症反应。 论文的通讯作者、埃克塞特大学的 Gordon Brown 教授表示：“过去 20 多年来，我们一直在研究免疫细胞如何感知周围环境。这一突破确实令人兴奋，它揭示了抑制炎症过程是如何在控制感染和自身免疫疾病发展之间达到微妙平衡的。” 参考资料： Mariano Malamud et al. Recognition and control of neutrophil extracellular trap formation by MICL. Nature, 2024, doi:10.1038/s41586-024-07820-3. 本文仅用于学术分享，转载请注明出处。若有侵权，请联系微信：bioonSir 删除或修改！ 点击下方「阅读原文」，前往生物谷官网查询更多生物相关资讯~

ABERDEEN, UK I July 01, 2024 I TauRx Pharmaceuticals Ltd, a global leader in tau-based research in Alzheimer’s disease (AD), has announced the submission of a UK Marketing Authorisation Application (MAA) for hydromethylthionine mesylate (HMTM) for treatment of mild cognitive impairment (MCI-AD) and mild to moderate stages of dementia due to Alzheimer’s disease. HMTM has been designated by the UK’s Medicines and Healthcare products Regulatory Agency (MHRA) for the Innovative Licensing and Access Pathway (ILAP). If successful, the UK could be the first country in which an accessible, safe, oral treatment, which targets the hallmark tau pathology of the disease, becomes available to patients. The MAA is based on the totality of evidence available from the recently released 24-month Phase 3 LUCIDITY data and two earlier Phase 3 trials in mild to moderate AD. These studies have been consistent in showing benefit on measures of decline in cognition, ability to perform normal activities of daily living, and reduction in the rate of brain shrinkage. Tau aggregation is strongly correlated with the rate and severity of cognitive decline, brain atrophy, and the damage to neurons responsible for the characteristic neurodegeneration of the disease. HMTM acts by selectively inhibiting the aggregation of tau-protein in brain nerve cells. It also has a second mode of action which results in enhancement of brain functioning. Commenting on the submission, Professor Claude Wischik, Executive Chairman of TauRx, said: “This is a significant milestone for TauRx and is an important step in potentially bringing a new type of treatment and a new hope to patients and families who carry the burden of this terrible disease.” NOTES ABOUT HMTM Hydromethylthionine mesylate (HMTM) has been developed as a potential oral treatment for AD targeting tau aggregation. It also has a secondary tau-independent mode of action which increases acetylcholine levels in the hippocampus. The global Phase 3 clinical trial LUCIDITY has recently completed and the data were presented at the AD/PD™ 2024 Alzheimer’s & Parkinson’s Diseases Conference in Lisbon, Portugal, on 7 March. With over 3,000 subjects studied, HMTM has a strong safety profile and could be delivered with minimal patient and physician burden. Neurofilament Light Chain (NfL) is an established biomarker for neurodegeneration. LUCIDITY showed a significant reduction in the change of NfL, in the randomised double-blind portion of the study at 12 months. Clinical measures of cognition showed improvement over baseline levels that was sustained over 18 months in MCI, as diagnosed in the LUCIDITY trial. Patients who were in the control group were unable to catch up in terms of cognitive function despite transitioning to 16mg per day HMTM (target dose) in the open-label phase after 12 months. This emphasises the importance of early intervention with effective therapies in AD. ABOUT TAURx PHARMACEUTICALS LTD TauRx was founded in 2002 in Singapore, with primary research facilities and operations based in Aberdeen, UK. In collaboration with the University of Aberdeen, the company has dedicated the past two decades to developing treatments and diagnostics for Alzheimer’s and other neurodegenerative diseases due to pathological aggregation of tau and other proteins. AD is a leading cause of disability and death throughout the world and is one of the most important global public health issues. TauRx will contribute to addressing this urgent unmet need with data from the totality of evidence available from LUCIDITY and the earlier AD trials in pursuit of regulatory approvals starting in UK. TauRx’s hope is to make HMTM available for people living with Alzheimer’s as soon as possible. Future research is planned for other related neurodegenerative diseases. https://taurx.com/ SOURCE: TAURx Pharmaceuticals

Dr Gerald Lip, Clinical Director of Breast Screening, North West Scotland, oversaw the AI breast cancer screening programme. (Photo courtesy of Kheiron Medical Technologies). Kheiron Medical Technologies' AI tool trialled by NHS in Scotland identified 11 cases of early-stage breast cancer that were missed by clinicians An AI tool tested by the UK’s National Health Service (NHS) in Scotland has identified ultra-early signs of breast cancer in 11 women that had been missed by clinicians. The tool, called Mia, was piloted alongside NHS Grampian doctors, and analysed the mammograms of over 10,000 women. Mia is developed by London-based Kheiron Medical Technologies , and the solution is supported by Microsoft’s Azure Cloud. Most of the cases were cancer-free, but Mia successfully flagged all of those with symptoms, as well as an extra 11 the doctors did not identify, because at very early stages cancers can be extremely small and hard to spot. Yet crucially, breast cancer patients with tumours smaller than 15mm at the time of discovery have a 90% five-year survival rate. Another factor affecting detection is that on average cancer shows up in just six-in-a-thousand scans. This is why in the UK and in Europe two specialists read every mammogram. Yet occasionally, so-called ‘interval’ cancers are missed at the time of screening, or occur after screening. Kheiron Medical Technologies says that, over a three-year period, Mia could be expected to pick up 47 cases (33.8%) of interval cancers that would be missed by clinicians. AI cancer-scan tools 'have high detection rate' The company adds that, over the same period: Two specialists reading mammograms would detect 303 cancers A single specialist reading would detect 261 Mia reading scans alone would pick up 271 instances of cancer Kheiron says that because it works instantly the tool, and others like it, can also reduce waiting times for results from 14 days to three. This is crucial, not only for hospitals in the UK but also worldwide, where the pandemic has caused major screening backlogs. In the UK, more than two million women have a breast cancer screening each year but the pandemic, coupled with staff pressures, mean there are long waiting lists and a backlog of mammograms to be read. The Grampian NHS Trust hopes to show that using an AI alongside a highly trained radiologist will cut waiting times both for screenings and the results. It is also normal practice for two radiologists to study each scan. The hope now is that Mia, and tools like it, can halve workloads by replacing one radiologist. Sarah Kerruish , Chief Strategy Officer of Kheiron Medical Technologies, reveals that it took six years to build and train Mia, and that it was trained on “millions of mammograms from women all over the world”. She added: “AI tools are generally pretty good at spotting symptoms of a specific disease, if they are trained on enough data to enable them to be identified. “This means feeding the programme with as many different anonymised images of those symptoms as possible, from as diverse a range of people as possible. "I think the most important thing I've learned is that when you're developing AI for a healthcare situation, you have to build in inclusivity from day one." Unlike clinicians, AI 'not prone to exhaustion' The clinician in charge of the trial, Dr Gerald Lip – Clinical Director of Breast Screening, North West Scotland – told the BBC that of the 10,889 women who took part in the trial, just 81 did not want the AI tool to review their scans. He added that part of the power of AI is it’s not prone to exhaustion or distraction. With breast cancer doctors reading around 5,000 breast scans a year, and as many as 100 in a single session there “is an element of fatigue",  said Dr Lip. He added: "You also get disruptions. Someone's coming in, someone's chatting in the background. There are lots of things that can throw you off your regular routine." Dr Lip added that he hoped one day, AI tech like Mia one day would “free me up to spend more time patients”. "I see Mia as a friend and an augmentation to my practice," he added. “Mia isn't perfect. It had no access to patient history so would flag cysts that had already been identified by previous scans and designated harmless.” He also revealed that because of UK health regulation, the machine learning element of Mia was disabled, which means it could not learn on the job, or evolve during its use. The University of Aberdeen independently validated Grampian NHS Trust’s research, but the results are yet to be peer reviewed. The Royal College of Radiologists, meanwhile, says the tech has “potential”. Mia is just one way in which AI technology is changing how healthcare is being delivered .