Tsinghua University

HELSINKI, May 20, 2025 /PRNewswire/ -- From May 14 to 17, 2025, the 57th Annual Meeting of the European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) was held in Helsinki, Finland. At the meeting, Yili presented twelve of its latest key findings on breast milk, covering HMOs, lactoferrin, and the optimal balance of dietary fatty acids. Yili also hosted a dedicated seminar during the conference, drawing considerable attention from international delegates. Continue Reading Yili attends the 57th ESPGHAN Annual Meeting Among the more than 1,500 abstracts submitted to ESPGHAN 2025, a collaborative study by Yili, the team of Dr. Ai Zhao at Tsinghua University, and the National Center of Technology Innovation for Dairy in China stood out by receiving one of the highest scores. This was the first study to apply machine learning to uncover the nutritional complexity of breast milk. This study revealed that a targeted combination of DHA, EPA, and DSLNT can precisely modulate the gut microbiota of both mothers and infants, providing a novel theoretical framework for precise nutritional interventions in maternal and infant health. Other groundbreaking discoveries presented by Yili, in collaboration with Tsinghua University, Nanchang University, China Agricultural University, and other institutions, were also a major highlight of the annual meeting. These studies revealed new insights into: how a mother's postpartum emotional state affects infant gut microbiota and early brain development; how a balanced dietary fatty acid profile can enhance lipid metabolism and cognitive function through gut microbiota modulation; and the potential of human milk fat substitutes (HMFS) to regulate gut microbiota, reduce fat accumulation, and support healthy physical development in infants. At the seminar themed "Promoting Healthy Infant Development: Insights from Breast Milk, Gut Microbiota, and Nutritional Research," Dr. Ignatius Szeto, Assistant President of Yili Group, unveiled Yili's latest research findings on HMOs, highlighting their significant role in fostering infant gut health, immune function, nutrient absorption, and cognitive development. During the roundtable forum, Professor Zhang Yumei, tenured professor at the School of Public Health of Peking University, elaborated on the four aspects of breast milk research, emphasizing the synergistic benefits of key components such as HMOs, lactoferrin, and nucleotides in supporting the immune, intestinal, nervous, and metabolic systems of infants. She commended Yili for proposing this comprehensive view of breast milk's health effects, taking the lead in establishing an AI-driven research and development paradigm for maternal and infant nutrition, and opening new frontiers in precision infant nutrition research. From a clinical trial perspective, Professor Marc Benning of Amsterdam University Medical Centre emphasized the importance of incorporating gut health biomarkers as key outcome measures in infant nutrition research. To date, Pro-Kido, Yili's infant formula brand has launched a wide range of specialized nutritional solutions for infants worldwide, including ZhenHu, Aronurish, Seine Mouiller, and UITSTEKEND GEITENMELK. Looking ahead, Yili will rely on its 15 global innovation centers to advance full value chain innovation and international collaboration in key areas of dairy research, aiming to better serve consumers worldwide. SOURCE Yili Group WANT YOUR COMPANY'S NEWS FEATURED ON PRNEWSWIRE.COM? 440k+ Newsrooms & Influencers 9k+ Digital Media Outlets 270k+ Journalists Opted In GET STARTED

BEIJING, China I March 24, 2025 I SineuGene Therapeutics Co., Ltd. (“SineuGene”), a clinical-stage biotech company pioneering innovative therapies for neurological disorders, today announced that the U.S. Food and Drug Administration (FDA) has cleared its Investigational New Drug (IND) application for SNUG01 — a first-in-class TRIM72 (Tripartite Motif Protein 72)-targeted gene therapy candidate for amyotrophic lateral sclerosis (ALS). The clearance authorizes a global Phase I/IIa clinical trial designed to evaluate SNUG01’s safety, tolerability, and preliminary efficacy in adults with ALS through a dose-escalation and expansion study. ALS is a rapidly progressive neurodegenerative disorder marked by motor neuron degeneration in the brain and spinal cord, leading to muscle weakness, atrophy, and eventually respiratory failure. Median survival time post-diagnosis is 3–5 years. Despite being the most prevalent adult-onset motor neuron disease, existing therapies offer limited clinical benefits, slowing progression only marginally and leaving no curative options for patients. SNUG01 leverages groundbreaking research carried out by Dr. Yichang Jia’s laboratory at Tsinghua University, whose team identified TRIM72 as a multifunctional neuroprotectant. The therapy utilizes a recombinant adeno-associated virus serotype 9 (rAAV9) capsid to deliver the human TRIM72 gene via intrathecal administration. Preclinical studies demonstrate TRIM72’s ability to counteract ALS pathogenesis through several synergistic mechanisms such as reducing oxidative stress by scavenging reactive oxygen species (ROS), restoring mitochondrial homeostasis, suppressing stress granule dysregulation, inhibiting neuroinflammatory cascades, and enhancing neuronal membrane repair capacity In an investigator-initiated trial (IIT) at Peking University Third Hospital, SNUG01 demonstrated a favorable safety and tolerability profile, along with early efficacy signals in both functional clinical assessments and key biomarkers of neurodegeneration. These results enhance the translational validation of TRIM72, bridging target discovery, preclinical models, and human proof-of-concept. Unlike mutation-targeting gene therapies, SNUG01 leverages multiple neuroprotective mechanisms, offering a critical advantage for over 90% of ALS patients with sporadic (non-familial) disease. This unique multi-target approach positions SNUG01 as a first-in-class candidate for the majority of ALS cases, addressing an urgent unmet need in this underserved population. SineuGene will partner with a leading global consortium of academic and clinical institutions to conduct a multi-regional clinical trial, expediting validation of SNUG01’s safety and therapeutic efficacy profile across a diverse ALS patient populations. About SineuGene SineuGene Therapeutics Co., Ltd., often referred to as “SineuGene,” is a biotechnology company focused on developing innovative therapies for neurological diseases. Established in late 2021, the company builds on over a decade of scientific research conducted by Dr. Yichang Jia’s team from School of Medicine, Tsinghua University. SineuGene uses advanced technologies such as adeno-associated virus (AAV) vector-mediated gene delivery and editing and antisense oligonucleotide (ASO)- based gene expression regulation. The company has created a diverse pipeline that targets major neurological diseases, including Amyotrophic Lateral Sclerosis (ALS), stroke, Parkinson’s disease, Alzheimer’s disease, Spinocerebellar Ataxia type 3, and Huntington’s disease. SineuGene is dedicated to transforming groundbreaking research into effective treatments, aiming to meet the unmet medical needs in the field of neurology. Website: www.sineugene.com SOURCE: SineuGene Therapeutics

A project in China that is developing an autonomous and self-evolving virtual healthcare setting is targeted to go public next year. This is confirmed to Healthcare IT News by Yang Liu, a professor at Tsinghua University's Department of Computer Science and Technology and co-research head of the Agent Hospital project. The virtual hospital concept, developed by researchers at the university's Institute for AI Industry Research (AIR), simulates the real-world cycle of the hospital treatment process, from disease onset to follow-up. The institute claims the concept as the first of its kind globally. Findings from this research were first published in May in arXiv, Cornell University's open-access online research paper repository. WHY IT MATTERS All virtual actors in Agent Hospital, including patients, nurses, and doctors, are generated via a large language model (LLM). These AI characters will represent real people once the system goes live in public by the first half of 2025. A public pilot, to be conducted by AIR's spinoff startup Tairex, will begin sometime in the first quarter, said Prof Yang. For the virtual hospital concept, researchers proposed a design method called MedAgent-Zero, which enables AI doctors to continuously learn and improve and become accurate in performing clinical tasks by interacting with patients, reviewing medical literature, and accumulating experience from handling both successful and unsuccessful cases. Their research findings showed that through this novel method, AI doctors achieved 88%, 95.6%, and 77.6% accuracy in examining, diagnosing, and treating patients, respectively. "The doctor agent is able to complete the diagnosis and treatment of tens of thousands of patients within a few days, which would typically take at least two years for a human doctor," the researchers also noted. Meanwhile, an AI doctor also showed up to 93% accuracy in answering a subset of the MedQA dataset – mostly based on the competitive United States Medical Licensing Examination, covering questions on major respiratory diseases. As part of the concept's development, researchers plan to expand its range of disease coverage and extension in more medical departments. The virtual platform currently features 42 AI doctors in 21 medical departments, including emergency, respiratory, and cardiology. They also plan to incorporate more features, including medical position promotions, changes in disease distribution with time, and historical patient medical records. There is also a plan to optimise the selection and implementation of the base LLM. OpenAI's ChatGPT model versions 3.5 and 4 are currently utilised in their research. "We will use the latest and most advanced LLM," Prof Yang said. THE LARGER TREND Other research initiatives in China have also developed medical LLMs for clinical decision support. A project at the Tongji University School of Medicine built a model called MedGo , which was trained using 6,000 medical textbooks and has since been integrated and utilised at the affiliated Shanghai East Hospital. An AI-focused institute under the Chinese Academy of Sciences – one of China's national research centres – introduced early this year the CARES Copilot chatbot based on Meta's Llama 2 LLM, which assists doctors in making medical diagnoses and treatments.