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.

Plant-derived nanovesicles have gained attention given their similarity to mammalian exosomes and advantages such as low cost, sustainability, and tissue targeting. Thus, they hold promise for disease treatment and drug delivery. In this study, we proposed a time-efficient method, PEG 8000 combined with sucrose density gradient centrifugation to prepare ginger-derived nanovesicles (GDNVs). Subsequently, curcumin (CUR) was loaded onto GDNV by ultrasonic incubation. The optimum conditions for ginger-derived nanovesicles loaded with curcumin (CG) were ultrasound time of 3 min, a carrier-to-drug ratio (GDNV:CUR) of 1:1. The study achieved a high loading capacity (94.027% ± 0.094%) and encapsulation efficiency (89.300% ± 0.344%). Finally, the drugs' in vivo distribution and anti-colitis activity were investigated in mice. CG was primarily distributed in the colon after oral administration. Compared to CUR and GDNV, CG was superior in improving disease activity, colon length, liver and spleen coefficients, myeloperoxidase activity, and biochemical factor levels in ulcerative colitis (UC) mice. In addition, CG plays a protective role against UC by modulating serum metabolite levels and gut flora. In summary, our study demonstrated that GDNV can be used for CUR delivery with enhanced therapeutic potential.

OBJECTIVE:To establish a method for the contents determination of psoralen,isopsoralen,psoralenoside and isop-soralenoside in Danzhi qing’e tablet. METHODS:HPLC performed on the column of Eclipse XDB-C18 with mobile phase of metha-nol-water(51∶49,V/V)(isocratic elution,for psoralen and isopsoralen)and acetonitrile-0.1% formic acid(12∶88,V/V)(isocratic elution,for psoralenoside and isopsoralenoside)at a flow rate of 1.0 ml/min,the detection wavelength was 246 nm,column tem-perature was 30℃,and injection volume was 10 μl. RESULTS:The linear range was 3.138-200.8 μg/ml for psoralen(r=0.999 9), 3.175-203.2μg/ml for isopsoralen(r=0.999 9),3.181-101.8μg/ml for psoralenoside(r=0.999 9)and 3.169-101.4μg/ml for isopso-ralenoside (r=0.999 9);RSDs of precision,stability and reproducibility tests were lower than 2%;limits of quantitation were 0.627 5 ng,0.635 0 ng,3.181 0 ng and 3.169 0 ng,the limits of detection were 0.251 0 ng,0.254 0 ng,1.273 0 ng and 1.268 0 ng;recoveries were 95.68%-102.80%(RSD=2.4%,n=6),95.91%-102.10%(RSD=2.3%,n=6),98.64%-99.13%(RSD=0.23%,n=6) and 100.20%-101.70%(RSD=0.69%,n=6),respectively. CONCLUSIONS:The method is simple and accurate, and can be used for the simultaneous determination of psoralen,isopsoralen,psoralenoside and isopsoralenoside in Danzhi qing’e tablet.

Objective To study the correlation between the occurrence of encephaledema and the target dose-volume after the low dose stereotactic radiosurgery of epilepsy.Methods Totally 136 epilepsy patients treated by low dose stereotactic radiosurgery with Novalis System were analysed retrospectively.The target doses and volumes of the patients were analysed by drawing out the scatterplot and conducting the binary Logistic regression to all of the data.An equation was obtained to predict the occurrence of radiation induced encephaledema in certain range of target volume and dose.Results Among all of 136 patients,different degree of local encephaledema occurred in 19 cases after the radiosurgery.Higher occurrence of radiation induced encephaledema was observed when the target central dose (i.e.90％ isodose circling the target)was more than 18 Gy or the target volume more than 30 cm3.Moreover,in patients with multitargets the doses of different targets devoted to each other,which could lead to the occurrence of local encephaledema.The equation to predict the occurrence probability was obtained by regression analysis.By testing this equation in all of 136 patients the coincidence percentage was 94.7％.Conclusions The target dose and volume could be effective parameters in certain range to predict the occurrence probability of radiation induced encephaledema.This equation would help to establish and optimize the therapeutic planning system.So it could finally reduce the side-effect of low dose stereotactic radiosurgey in epilepsy patients.The equation has some clinical value.

Objective To explore the possible effects of methyl methanesulfonate sensitive 2(MMS2)in the process of angiotensin Ⅱ inducing differentiation of neural stem cells (NSCs) into dopaminegic phenotype neurons. Methods NSCs were isolated from the brain of newborn rats and were cultured in the serum-free medium.Identification of neural precursor cells was done by Nestin immunocyt ochemical staining. Then the second generation of NSCs was divided into the following six groups: A, control; B, AⅡ; C, AT1 antagonist ZD7155; D, ZD7155+AⅡ; E, AT2 antagonist PD123319; F, PD123319+AⅡ. The detection of expression of MMS2 and TH mRNA level was done by real-time PCR. The silence of the expression of MMS2 in NSCs was brought about via the transfection of MMS2-siRNA, and then the NSCs were induced to differentiate into dopaminegic neurons. The expression of TH mRNA level in the cells of the groups after transfection was detected by real-time PCR. Results Nestin-positive cells were observed in suspended growth in the medium.Real-Time PCR revealed that the MMS2 and TH mRNA expression of group B and D were significantly higher than that of the control group(P<0.05), There was no significant difference in MMS2 and TH mRNA expression between group C, E, F and the control, respectively. Conclusion AⅡ increased the expression of MMS2 mRNA in NSCs and induced the differentiation of NSCs into DA neurons via AT2 recepter. MMS2 may play important roles in the process of angiotensin Ⅱ inducing NSCs to differentiate into dopaminergic neurons.

Objective To develop a HPLC fingerprints of Glycyrrhiza uralensis Fisch.in Inner Mongolia.Methods The RP-HPLC method was adopted on Phenomenex C18(4.6?250 mm,5 ?m)analytical column by gradient elution with acetonitrile and acetic acid buffer solution as mobile phase.The gradient wavelength data acquisition was employed.The analysis time was 60 minutes and the flow rate was 1 mL/min.Results The HPLC standard fingerprints chromatography of Glycyrrhiza uralensis Fisch.consists of 10 common characteristic peaks.The results of method validation accorded with the technical standard of fingerprints.Conclusion This method is stable,accurate,reliable,and can provide a scientific basis for the quality control of Glycyrrhiza uralensis Fisch..