Drug repurposing offers a promising alternative to traditional drug development and significantly re-duces costs and timelines by identifying new therapeutic uses for existing drugs.However,the current approaches often rely on limited data sources and simplistic hypotheses,which restrict their ability to capture the multi-faceted nature of biological systems.This study introduces adaptive multi-view learning(AMVL),a novel methodology that integrates chemical-induced transcriptional profiles(CTPs),knowledge graph(KG)embeddings,and large language model(LLM)representations,to enhance drug repurposing predictions.AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning(MVL),matrix factorization,and ensemble optimization techniques to integrate heterogeneous multi-source data.Comprehensive evaluations on benchmark datasets(Fdata-set,Cdataset,and Ydataset)and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art(SOTA)methods,achieving superior accuracy in predicting drug-disease associations across multiple metrics.Literature-based validation further confirmed the model's predictive capabilities,with seven out of the top ten predictions corroborated by post-2011 evidence.To promote transparency and reproducibility,all data and codes used in this study were open-sourced,providing resources for pro-cessing CTPs,KG,and LLM-based similarity calculations,along with the complete AMVL algorithm and benchmarking procedures.By unifying diverse data modalities,AMVL offers a robust and scalable so-lution for accelerating drug discovery,fostering advancements in translational medicine and integrating multi-omics data.We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Drug repurposing offers a promising alternative to traditional drug development and significantly reduces costs and timelines by identifying new therapeutic uses for existing drugs. However, the current approaches often rely on limited data sources and simplistic hypotheses, which restrict their ability to capture the multi-faceted nature of biological systems. This study introduces adaptive multi-view learning (AMVL), a novel methodology that integrates chemical-induced transcriptional profiles (CTPs), knowledge graph (KG) embeddings, and large language model (LLM) representations, to enhance drug repurposing predictions. AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning (MVL), matrix factorization, and ensemble optimization techniques to integrate heterogeneous multi-source data. Comprehensive evaluations on benchmark datasets (Fdataset, Cdataset, and Ydataset) and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art (SOTA) methods, achieving superior accuracy in predicting drug-disease associations across multiple metrics. Literature-based validation further confirmed the model's predictive capabilities, with seven out of the top ten predictions corroborated by post-2011 evidence. To promote transparency and reproducibility, all data and codes used in this study were open-sourced, providing resources for processing CTPs, KG, and LLM-based similarity calculations, along with the complete AMVL algorithm and benchmarking procedures. By unifying diverse data modalities, AMVL offers a robust and scalable solution for accelerating drug discovery, fostering advancements in translational medicine and integrating multi-omics data. We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Chronic liver disease remains a severe threat to human health. Furthermore, if left untreated promptly and effectively, it may gradually develop into end-stage liver disease, including decompensated cirrhosis and liver failure. Currently, mesenchymal stem cell technology is acting as a kind of an emerging treatment method, and multiple clinical trials have confirmed its promising application prospects in the treatment of decompensated cirrhosis and liver failure. Hence, stem cell therapy may offer a novel therapeutic option for these patients. This article summarizes the clinical research progress of stem cell therapy for decompensated cirrhosis and liver failure and analyzes present challenges and application prospects.

Chronic liver disease remains a severe threat to human health. Furthermore, if left untreated promptly and effectively, it may gradually develop into end-stage liver disease, including decompensated cirrhosis and liver failure. Currently, mesenchymal stem cell technology is acting as a kind of an emerging treatment method, and multiple clinical trials have confirmed its promising application prospects in the treatment of decompensated cirrhosis and liver failure. Hence, stem cell therapy may offer a novel therapeutic option for these patients. This article summarizes the clinical research progress of stem cell therapy for decompensated cirrhosis and liver failure and analyzes present challenges and application prospects.

End-stage liver disease includes liver failure and decompensated cirrhosis resulting from various etiologies and often leads to patient mortality due to complications and clinical symptoms such as severe jaundice, ascites, hepatic encephalopathy, coagulopathy, and hepatorenal syndrome. Liver transplantation is currently regarded as the most effective treatment, but its clinical application is limited by the shortage of donors, elevated expenses, and post-transplant rejection. Stem cells are a group of cells with multidirectional differentiation potential and self-renewal ability, which can improve the clinical indicator outcomes through mechanisms such as immunoregulation and promotion of tissue repair in patients with end-stage liver disease. Clinical trials of stem cell therapy have achieved a series of results for end-stage liver disease, proving the safety and effectiveness of stem cell therapy. This article reviews the clinical studies that have been registered and published at home and abroad and provides a reference for the clinical plan on stem cell therapy for end-stage liver disease.

End-stage liver disease includes liver failure and decompensated cirrhosis resulting from various etiologies and often leads to patient mortality due to complications and clinical symptoms such as severe jaundice, ascites, hepatic encephalopathy, coagulopathy, and hepatorenal syndrome. Liver transplantation is currently regarded as the most effective treatment, but its clinical application is limited by the shortage of donors, elevated expenses, and post-transplant rejection. Stem cells are a group of cells with multidirectional differentiation potential and self-renewal ability, which can improve the clinical indicator outcomes through mechanisms such as immunoregulation and promotion of tissue repair in patients with end-stage liver disease. Clinical trials of stem cell therapy have achieved a series of results for end-stage liver disease, proving the safety and effectiveness of stem cell therapy. This article reviews the clinical studies that have been registered and published at home and abroad and provides a reference for the clinical plan on stem cell therapy for end-stage liver disease.

Objective To review the experience on screening,diagnosis and treatment for neonatal congenital hypothyroidism (CH)in Xuancheng City,Anhui Province.MethodsFrom Jan 2008 to Dec 2014,peripheral blood samples from the heel were collected among 83787 neonates and the blood samples were sent to the screening center to test the level of thyroid stimulating hormone (TSH).Neonates with abnormal level of TSH were admitted to our hospital for further TSH and free tetraiodothyronine (FT4 )tests. Neonates with CH diagnosis were given standard treatments of levothyroxine and their thyroid function, physical and intelligence development were evaluated on a routine basis.Results Among the 106 neonates with abnormal TSH level ,68 were diagnosed CH.The prevalence of CH in Xuancheng City was 0.8 ‰.All 68 patients with CH received levothyroxine treatment and 6 cases were lost during follow-up.44 patients received physical examination and their bone ages were normal. 53 patients received intelligence assessment.Only 1 of them was diagnosed of mental retardation, and 3 with suspicious mental retardation.Conclusion Neonatal screening is necessary for the early diagnosis and treatment of CH. Neonates with CH can have normal physical and mental development if they receive standard treatment as early as possible and followed up regularly.

OBJECTIVEUse HPLC to study the permeation of ingredients of Shuanghuanglian injection powder (SHL) through placental barriers of rats at different stages of pregnancy.

METHODThe pregnant rats were administered SHL for 5 d through caudalis vena at different stages of pregnancy. Plasma and embryonic tissues were obtained 12 h after the final administration of SHL. The componds in biological specimen were identified by HPLC.

RESULTBaicalin, luteolin and wogonoside were the main compounds in plasma. Wogonoside retained in first trimester embryonic tissues, and baicalin retained in the embryonic tissues of different pregnant stages.

CONCLUSIONBaicalin is the main compound of SHL through placental barriers of rats. Embryotoxicity of baicalin should be considered as the key point to evaluate the safety of SHL.

Animals ; Drugs, Chinese Herbal ; administration & dosage ; analysis ; metabolism ; Female ; Humans ; Injections ; Male ; Models, Animal ; Permeability ; Placenta ; drug effects ; metabolism ; Pregnancy ; Rats ; Rats, Wistar

OBJECTIVETo identify the compounds in fruits of Psoralea corylifolia by high performance liquid chromatography-mass spectrometry.

METHODThe chromatographic separation was carried out at 30 degrees C on a Diamonsil C18 column (4.6 mm x 250 mm, 5 microm) eluted in the gradient program. The mobile phase consisted of acetonitrile (A) and water containing 0.05% formic acid (B). The detection wavelength was at 246 nm and the on-line UV spectra was recorded in the range of 190-400 nm. The mass spectra were obtained by Finnigan LCQ Deca XP(plus) ion trap mass spectrometer in the positive ion mode with ion spray voltage 4.5 kV, sheath gas (N2), 60 arbitrary units, auxiliary gas (N2), 20 arbitrary units; capillary temperature, 350 degrees C, capillary voltage 19 V, tube lens offset voltage 25 V, mass range recorded, m/z 90-800.

RESULTTwo coumarin glycosides, three coumarins, eight flavonoids and one meroterpene were identified by HPLC-MS method.

CONCLUSIONThe method is simple and rapid for the identification and quality control for the fruits of P. corylifolia.

Chromatography, High Pressure Liquid ; methods ; Fruit ; chemistry ; Mass Spectrometry ; methods ; Plant Extracts ; chemistry ; Psoralea ; chemistry