Core Insights - The research presents a comprehensive human proteome profile across a 50-year lifespan, revealing aging trajectories and signatures [2][3][21] - It identifies a significant aging turning point around the age of 50, with blood vessels being the earliest and most affected tissue [4][12][21] - The study highlights the decline in protein homeostasis as a core mechanism of aging, with implications for chronic inflammatory diseases and conditions like Alzheimer's [9][10][22] Group 1: Research Methodology - The study utilized ultra-sensitive mass spectrometry combined with machine learning algorithms to construct a proteomic aging map across seven physiological systems and 13 key tissues [3][21] - A total of 516 samples from 76 individuals aged 14-68 were collected, covering various organs such as the heart, aorta, lungs, and muscles [6][21] - The research identified 12,771 proteins, establishing organ-specific protein expression characteristics [7][21] Group 2: Key Findings on Aging - The research found that the correlation between mRNA and its translated proteins significantly decreases with age, particularly in the spleen, muscles, and lymph nodes [7][21] - Aging leads to a collapse of protein homeostasis, characterized by decreased synthesis capabilities, impaired folding and transport, and accumulation of amyloid proteins and immunoglobulins [9][21] - Blood vessels are identified as a "senohub," driving systemic aging processes through the expression of pro-aging proteins like GAS6 [14][15][21] Group 3: Implications for Anti-Aging Strategies - The study suggests potential anti-aging interventions targeting pro-aging proteins, such as developing CAR-T cell therapies against membrane proteins like GPNMB and neutralizing circulating proteins like GAS6 [18][21] - It emphasizes the importance of early intervention before the age of 50 to protect blood vessels and potentially delay systemic aging [18][21] - The findings provide a new paradigm for understanding systemic aging mechanisms through the lens of protein homeostasis imbalance and vascular aging [22]

Group 1 - The core point of the article is that Zhejiang China Commodity City Group Co., Ltd. is expanding its financial services by establishing offshore subsidiaries in Hong Kong to enhance its cross-border financial capabilities through its YiwuPay platform [1][2] - The company plans to invest HKD 50 million to set up a wholly-owned offshore subsidiary, and an additional HKD 10 million for another subsidiary to apply for the TCSP license, which will allow it to legally conduct trust and company services in Hong Kong [1] - YiwuPay has developed a global service network covering over 160 countries and regions, becoming a crucial financial infrastructure in China's foreign trade [2] Group 2 - YiwuPay has partnered with major banks to innovate its services, including the establishment of the first digital RMB B2B cross-border settlement platform and real-time settlement services between UAE Dirham and RMB [2] - The company has reported a significant increase in its cross-border collection volume, exceeding USD 4 billion in 2024, representing a 233% year-on-year growth, and a net profit of CNY 61.04 million, up 274.67% [2] - In addition to payment services, the company is also involved in credit information and factoring services, creating a comprehensive financial service system that supports cross-border financial business [3]

Core Insights - A breakthrough technology has been developed by the Institute of Software Research, Chinese Academy of Sciences, in collaboration with the First Hospital of Hebei Medical University, which efficiently identifies emotional disorders such as anxiety and depression through eye movement analysis during natural viewing of table tennis matches [1][2] - This technology offers a non-invasive and convenient new solution for mental health monitoring, with results published in the prestigious journal "Frontiers in Neurology" [1] Summary by Sections Technology Development - The research team utilized dynamic sports videos, specifically table tennis matches, as natural visual stimuli combined with virtual reality (VR) technology and machine learning algorithms to collect eye movement data without the need for active participation from subjects [1] - The study involved 25 participants, including 12 emotional disorder patients and 13 healthy controls, who watched table tennis and tennis match videos while their eye movement characteristics were recorded using the EyeKnow eye-tracking system [1] Research Findings - Significant testing and machine learning analysis revealed that 11 eye movement features from the table tennis videos effectively distinguished emotional disorders, with "Gaze Entropy" achieving an accuracy rate of 88% [2] - A decision tree model trained on all significant features reached an overall accuracy of 92% and an area under the ROC curve of 0.94, outperforming traditional assessment scales [2] - The tennis video showed weaker distinguishing effects due to lower familiarity among participants, but some indicators still demonstrated potential for adaptation to new content as a biological marker for emotional disorders [2] Future Applications - The core advantage of this technology lies in its "natural and unobtrusive" nature, requiring no active cooperation or professional guidance, allowing for detection simply through watching everyday videos [2] - Future integration into smart TVs and mobile devices is anticipated, enabling at-home mental health monitoring [2] - The research leader, Professor Tian Feng, emphasized that this method integrates disease screening into daily life, providing a low-cost and highly compliant long-term monitoring tool, particularly useful for tracking medication effects and relapse warnings [2]

Core Viewpoint - The FDA approval of the Jewel Patch-WCD wearable defibrillator marks a significant advancement in providing a non-invasive solution for high-risk patients facing sudden cardiac arrest (SCA) [1][3]. Group 1: Product Features - Jewel Patch-WCD is designed with a low-profile, waterproof patch that allows for continuous ECG monitoring without disrupting daily activities, including sleep and showering [3][6]. - The device is intended for temporary high-risk patients, including those recovering from myocardial infarction or with severe cardiovascular diseases, with an estimated 500,000 patients in the US and Europe benefiting annually [6][9]. - The device has demonstrated high compliance, with an average daily wear time exceeding 23 hours during clinical trials, successfully identifying and treating arrhythmias without any reported deaths or serious complications [6][9]. Group 2: Technology and Innovation - Jewel Patch-WCD utilizes a machine learning-based arrhythmia recognition system, achieving a low inappropriate shock rate of 0.36 per 100 patients per month, significantly better than many similar devices [7][9]. - The device integrates with the Jewel mobile app for near real-time data transmission to healthcare providers, facilitating remote monitoring and personalized cardiovascular care [7][9]. Group 3: Company Background - Element Science, founded by Dr. Uday Kumar in 2011, focuses on developing next-generation wearable technologies for high-risk cardiac patients, particularly in preventing SCA [8]. - The company has raised $145 million in Series C funding, positioning itself as one of the fastest-growing startups in the wearable medical device sector [8].

Core Findings - An international research team, including Israeli researchers, discovered that psychological stress during pregnancy can "reprogram" key molecular pathways in fetuses, affecting newborns' stress response systems in different ways based on gender [1][2] - The study involved over 120 mother-infant pairs recruited in Germany from 2016 to 2018, focusing on pregnant women with high perceived stress levels, which often go unmonitored [2][3] - The research highlighted significant molecular changes in female infants, particularly the near-complete disappearance of choline tRNA fragments, which regulate genes responsible for synthesizing acetylcholine, a neurotransmitter [1] - Male infants exhibited higher levels of acetylcholinesterase, an enzyme that breaks down acetylcholine, indicating an imbalance in their stress response systems from birth [1] - Machine learning algorithms were utilized to analyze choline tRNA fragment characteristics in newborn girls, achieving up to 95% accuracy in determining exposure to maternal stress during pregnancy, paving the way for early diagnostic and intervention tools [1] Research Implications - The study emphasizes the importance of maternal mental health during pregnancy, particularly for women who perceive high stress but are not diagnosed with depression or anxiety, as their stress can still impact both themselves and their newborns [2] - The findings suggest potential avenues for early diagnosis and support for pregnant women experiencing high levels of stress [2]

Core Insights - A machine learning algorithm developed by a team at Columbia University can infer the atomic structure of materials by observing patterns produced by nanocrystals, addressing a century-old challenge in materials science [1] Group 1: Implications for Drug Development - The breakthrough in nanocrystal structure analysis is expected to accelerate new drug development processes [1] Group 2: Clean Energy Materials - The new algorithm may also facilitate the development of clean energy materials, potentially impacting the renewable energy sector positively [1] Group 3: Cultural Heritage Research - This advancement could enhance research in cultural heritage, providing new methods for analyzing and preserving historical materials [1]

作者｜冬梅 字节 Top Seed 启动 2026 届招聘，瞄准顶尖博士 4 月 27 日，字节跳动 Seed 在其官微上发布了一则招聘启示，宣布正式启动 2026 届 Top Seed 大模型顶尖人才校招计划， 研究课题包括大语言模型、机器学习算法和系统、多模态生成、多模态理解、语音等方向，基本覆盖大模型研究各个领域， 计划招募约 30 位顶尖应届博士。 值得一提的是，本届 Top Seed 强调不限专业背景，更关注研究潜力，希望寻找具有极强技术信仰与热情、具备出色研究能 力、富有好奇心和驱动力的年轻研究者。 值得注意的是，字节跳动在此次招聘启事中还透露了几位刚毕业的同学已经做出了一些有影响力的研究。 比如，Z 同学构建并开源了首个多语言代码修复基准 Multi-SWE-bench，在 SWE-bench 基础上，首次覆盖 Python 之外的 Java、TypeScript、C、C++、Go、Rust 和 JavaScript 七种编程语言，1632 个真实修复任务，是真正面向"全栈工程"的评测 基准，其数据均来自 GitHub issue，历时近一年构建，以尽可能准确测评和提高大模型高阶编程智能水平。 ...

Group 1 - The core point of the article is that Zhejiang Jinke Tom Cat (300459) has signed a capital increase agreement to invest in Aurion11 Limited, aiming to expand its mobile internet programmatic advertising business [1][2] - Outfit7 will hold 60% of Aurion11 Limited after the investment, with the remaining 40% held by four founding shareholders from the original Outfit7 team [1] - Aurion11 Limited focuses on the commercialization of mobile internet advertising technology services, utilizing AI, machine learning algorithms, and big data analysis to enhance advertising value for third parties [1] Group 2 - The company has over 14 years of experience in programmatic advertising technology since the early development of mobile internet [1] - The investment aims to leverage Outfit7's accumulated knowledge, experience, technical reserves, and client resources to explore providing advertising technology services to third-party mobile application companies [1] - The company has established a strong competitive edge in programmatic advertising monetization and has long-term partnerships with major global advertising service providers such as Google, Meta, and TikTok [2]