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.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Humans ; Fasciitis/pathology* ; Fibroma/pathology* ; Gene Rearrangement ; Proto-Oncogene Proteins/genetics* ; Ubiquitin Thiolesterase

Objective: To analyze the prevalence and the risk factors of fungal sepsis in 25 neonatal intensive care units (NICU) among preterm infants in China, and to provide a basis for preventive strategies of fungal sepsis. Methods: This was a second-analysis of the data from the "reduction of infection in neonatal intensive care units using the evidence-based practice for improving quality" study. The current status of fungal sepsis of the 24 731 preterm infants with the gestational age of <34⁺⁰ weeks, who were admitted to 25 participating NICU within 7 days of birth between May 2015 and April 2018 were retrospectively analyzed. These preterm infants were divided into the fungal sepsis group and the without fungal sepsis group according to whether they developed fungal sepsis to analyze the incidences and the microbiology of fungal sepsis. Chi-square test was used to compare the incidences of fungal sepsis in preterm infants with different gestational ages and birth weights and in different NICU. Multivariate Logistic regression analysis was used to study the outcomes of preterm infants with fungal sepsis, which were further compared with those of preterm infants without fungal sepsis. The 144 preterm infants in the fungal sepsis group were matched with 288 preterm infants in the non-fungal sepsis group by propensity score-matched method. Univariate and multivariate Logistic regression analysis were used to analyze the risk factors of fungal sepsis. Results: In all, 166 (0.7%) of the 24 731 preterm infants developed fungal sepsis, with the gestational age of (29.7±2.0) weeks and the birth weight of (1 300±293) g. The incidence of fungal sepsis increased with decreasing gestational age and birth weight (both P<0.001). The preterm infants with gestational age of <32 weeks accounted for 87.3% (145/166). The incidence of fungal sepsis was 1.0% (117/11 438) in very preterm infants and 2.0% (28/1 401) in extremely preterm infants, and was 1.3% (103/8 060) in very low birth weight infants and 1.7% (21/1 211) in extremely low birth weight infants, respectively. There was no fungal sepsis in 3 NICU, and the incidences in the other 22 NICU ranged from 0.7% (10/1 397) to 2.9% (21/724), with significant statistical difference (P<0.001). The pathogens were mainly Candida (150/166, 90.4%), including 59 cases of Candida albicans and 91 cases of non-Candida albicans, of which Candida parapsilosis was the most common (41 cases). Fungal sepsis was independently associated with increased risk of moderate to severe bronchopulmonary dysplasia (BPD) (adjusted OR 1.52, 95%CI 1.04-2.22, P=0.030) and severe retinopathy of prematurity (ROP) (adjusted OR 2.55, 95%CI 1.12-5.80, P=0.025). Previous broad spectrum antibiotics exposure (adjusted OR=2.50, 95%CI 1.50-4.17, P<0.001), prolonged use of central line (adjusted OR=1.05, 95%CI 1.03-1.08, P<0.001) and previous total parenteral nutrition (TPN) duration (adjusted OR=1.04, 95%CI 1.02-1.06, P<0.001) were all independently associated with increasing risk of fungal sepsis. Conclusions: Candida albicans and Candida parapsilosis are the main pathogens of fungal sepsis among preterm infants in Chinese NICU. Preterm infants with fungal sepsis are at increased risk of moderate to severe BPD and severe ROP. Previous broad spectrum antibiotics exposure, prolonged use of central line and prolonged duration of TPN will increase the risk of fungal sepsis. Ongoing initiatives are needed to reduce fungal sepsis based on these risk factors.
Infant ; Infant, Newborn ; Humans ; Birth Weight ; Intensive Care Units, Neonatal ; Retrospective Studies ; Tertiary Care Centers ; Infant, Extremely Low Birth Weight ; Gestational Age ; Infant, Extremely Premature ; Sepsis/epidemiology* ; Retinopathy of Prematurity/epidemiology* ; Bronchopulmonary Dysplasia/epidemiology*

OBJECTIVE: To investigate the effect of Yinlai Decoction (YD) on the microstructure of colon, and activity of D-lactic acid (DLA) and diamine oxidase (DAO) in serum of pneumonia mice model fed with high-calorie and high-protein diet (HCD). METHODS: Sixty male Kunming mice were randomly divided into 6 groups by the random number table method: normal control, pneumonia, HCD, HCD with pneumonia (HCD-P), YD (229.2 mg/mL), and dexamethasone (15.63 mg/mL) groups, with 10 in each group. HCD mice were fed with 52% milk solution by gavage. Pneumonia mice was modeled with lipopolysaccharide inhalation and was fed by gavage with either the corresponding therapeutic drugs or saline water, twice daily, for 3 days. After hematoxylin-eosin staining, the changes in the colon structure were observed under light microscopy and transmission electron microscope, respectively. Enzyme-linked immunosorbent assay was used to detect the protein levels of DLA and DAO in the serum of mice. RESULTS: The colonic mucosal structure and ultrastructure of mice in the normal control group were clear and intact. The colonic mucosal goblet cells in the pneumonia group tended to increase, and the size of the microvilli varied. In the HCD-P group, the mucosal goblet cells showed a marked increase in size with increased secretory activity. Loose mucosal epithelial connections were also observed, as shown by widened intercellular gaps with short sparse microvilli. These pathological changes of intestinal mucosa were significantly reduced in mouse models with YD treatment, while there was no significant improvement after dexamethasone treatment. The serum DLA level was significantly higher in the pneumonia, HCD, and HCD-P groups as compared with the normal control group (P<0.05). Serum DLA was significantly lower in the YD group than HCD-P group (P<0.05). Moreover, serum DLA level significantly increased in the dexamethasone group as compared with the YD group (P<0.01). There was no statistical significance in the serum level of DAO among groups (P>0.05). CONCLUSIONS YD can protect function of intestinal mucosa by improving the tissue morphology of intestinal mucosa and maintaining integrity of cell connections and microvilli structure, thereby reducing permeability of intestinal mucosa to regulate the serum levels of DLA in mice.
Mice ; Male ; Animals ; Lactic Acid/pharmacology* ; Intestinal Mucosa ; Colon/pathology* ; Dexamethasone/pharmacology* ; Diet, High-Protein ; Pneumonia/pathology*

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

External apical root resorption is among the most common risks of orthodontic treatment, and it cannot be completely avoided and predicted. Risk factors causing orthodontic root resorption can generally be divided into patient- and treatment-related factors. Root resorption that occurs during orthodontic treatment is usually detected by radiographical examination. Mild or moderate root absorption usually does no obvious harm, but close attention is required. When severe root resorption occurs, it is generally recommended to suspend the treatment for 3 months for the cementum to be restored. To unify the risk factors of orthodontic root resorption and its clinical suggestions, we summarized the theoretical knowledge and clinical experience of more than 20 authoritative experts in orthodontics and related fields in China. After discussion and summarization, this consensus was made to provide reference for orthodontic clinical practice.
Humans ; Tooth Movement Techniques/adverse effects* ; Root Resorption/etiology* ; Consensus ; Dental Cementum ; Risk Factors