The precise and rapid monitoring of multiple organ dysfunction is crucial in drug discovery. Traditional methods, such as pathological analysis, are often time-consuming and inefficient. Here, we developed a multiplexed near-infrared window two (NIR-II) fluorescent bioimaging method that allows for real-time, rapid, and quantitative assessment of multiple organ dysfunctions. Given that existing probes did not fully meet requirements, we synthesized a range of NIR-II hemicyanine dyes (HDs) with varying absorption and emission wavelengths. By modifying these dyes, we achieved high spatial and temporal resolution imaging of the liver, kidneys, stomach, and intestines. This method was further applied to investigate disorders induced by cisplatin, a drug known to cause gastric emptying issues along with liver and kidney injuries. By monitoring the metabolic rate of the dyes in these organs, we accurately quantified multi-organ dysfunction, which was also confirmed by gold-standard pathological analysis. Additionally, we evaluated the effects of five aristolochic acids (AAs) on multiple organ dysfunction. For the first time, we identified that AA-I and AA-II could cause gastric emptying disorders, which was further validated through transcriptomics analysis. Our study introduces a novel approach for the simultaneous monitoring of multi-organ dysfunction, which may significantly enhance the evaluation of drug side effects.

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Objective:To explore the efficacy and safety of olverembatinib in treatment of chronic myeloid leukemia (CML) progressed to acute lymphoblastic leukemia with D241E mutation.Methods:The diagnosis and treatment of a patient with D241E mutant CML progressed to acute lymphoblastic leukemia admitted to the Fourth People's Hospital of Jinan in December 2018 were retrospectively analyzed, and relevant literature was reviewed.Results:The patient was a 47-year-old female, and her blood test result was abnormal during physical examination. She was diagnosed as CML and received treatment with imatinib and dasatinib for 2 years. The disease progressed to philadelphia chromosome (Ph)-positive acute B-lymphoblastic leukemia with BCR-ABL mutation (a D241E mutation). After 3 courses of chemotherapy combined with a targeted drug (ponatinib), the patient achieved complete remission, while the minimal residual disease continued to be positive. The patient received 1 course of chemotherapy combined with olverembatinib from the 4th course of treatment. After olverembatinib monotherapy maintenance therapy for 36 months, the patient achieved molecular complete remission with minimal residual disease. The patient developed complications such as skin pigmentation and elevated lipid levels, but all complications were tolerable.Conclusions:The application of olverembatinib in D241E mutant CML progressed to acute lymphoblastic leukemia can help patients obtain sustained molecular biological remission and good safety.

Computational analysis can accurately detect drug-gene interactions(DGIs)cost-effectively.However,transductive learning models are the hotspot to reveal the promising performance for unknown DGIs(both drugs and genes are present in the training model),without special attention to the unseen DGIs(both drugs and genes are absent in the training model).In view of this,this study,for the first time,proposed an inductive learning-based model for the precise identification of unseen DGIs.In our study,by integrating disease nodes to avoid data sparsity,a multi-relational drug-disease-gene(DDG)graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions.Following the extraction of graph features by utilizing graph embedding algorithms,our next step was the retrieval of the attributes of individual gene and drug nodes.In this way,a hybrid feature charac-terization was represented by integrating graph features and node attributes.Machine learning(ML)models were built,enabling the fulfillment of transductive predictions of unknown DGIs.To realize inductive learning,this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights,enabling inductive predictions for the unseen DGIs.Consequently,the final model was superior to existing models,with significant improvement in predicting both external unknown and unseen DGIs.The practical feasibility of our model was further confirmed through case study and molecular docking.In summary,this study establishes an efficient data-driven approach through the proposed modeling,suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Objective:To retrieve, evaluate and summarize relevant evidence on communication strategies for families with perinatal loss, and to provide an evidence-based basis for communication practice among clinical health professionals.Methods:The system searches for evidence related to the loss of family doctor-patient communication strategies during the perinatal period in computer decision support systems such as UpToDate, BMJ Best Clinical Practice, International Guidelines Network, UK National Institute for Health and Clinical Excellence, PubMed, Web of Science, CINAHL, China National Knowledge Infrastructure, Wanfang Data, as well as in Chinese and English databases and related websites.The search was conducted between January 2012 and December 2022. The literature ′s quality and extracted evidence were independently evaluated by two researchers according to professional judgement. Results:A total of 13 articles were included, including 1 clinical decision, 2 guidelines, 4 national standards, 2 expert consensus, and 4 systematic reviews. 30 pieces of evidence have been summarized across five aspects, comprising communication environment, communication skills, timing and key points of communication, communication for special populations, and system-level communication support.Conclusions:This study summarizes the relevant evidence on communication strategies for family doctor-patient communication strategies for perinatal loss. Clinical professionals should carefully select and apply relevant evidence based on available medical resources and parental preferences, Develop and implement practical standards for family doctor-patient communication strategies for perinatal loss at the system level, further harmonize communication behaviors, and improve communication quality.

Objective:To retrieve, evaluate and summarize relevant evidence on communication strategies for families with perinatal loss, and to provide an evidence-based basis for communication practice among clinical health professionals.Methods:The system searches for evidence related to the loss of family doctor-patient communication strategies during the perinatal period in computer decision support systems such as UpToDate, BMJ Best Clinical Practice, International Guidelines Network, UK National Institute for Health and Clinical Excellence, PubMed, Web of Science, CINAHL, China National Knowledge Infrastructure, Wanfang Data, as well as in Chinese and English databases and related websites.The search was conducted between January 2012 and December 2022. The literature ′s quality and extracted evidence were independently evaluated by two researchers according to professional judgement. Results:A total of 13 articles were included, including 1 clinical decision, 2 guidelines, 4 national standards, 2 expert consensus, and 4 systematic reviews. 30 pieces of evidence have been summarized across five aspects, comprising communication environment, communication skills, timing and key points of communication, communication for special populations, and system-level communication support.Conclusions:This study summarizes the relevant evidence on communication strategies for family doctor-patient communication strategies for perinatal loss. Clinical professionals should carefully select and apply relevant evidence based on available medical resources and parental preferences, Develop and implement practical standards for family doctor-patient communication strategies for perinatal loss at the system level, further harmonize communication behaviors, and improve communication quality.

Poria cocos is a classic Chinese medicine with homology of food and medicine,which is beneficial to water infiltration,spleen and stomach,calming the heart and calming the mind,etc.It is known as"nine Poria cocos in ten prescriptions".Poria cocos contains polysaccharide,triterpenoids and steroids,among them polysaccharide and triterpenoid are considered as the main active components.Modern studies have shown that Poria cocos polysaccharide triterpenes display pharmacological activities such as anti-tumor,immunomodulatory and anti-oxidation.The dissolution rate of poria cocos and triterpenes was low in the traditional decocting process,and the oral absorption rate of poria cocos was low,but the activity of poria cocos and triterpenes was still very good,indicating the high activity of poria cocos and triterpenes.Therefore,this paper systematically reviews the extraction and separation,structural identification,content determination,structural modification,biosynthesis,pharmacological activity and potential product development value of Poria cocos polysaccharide and triterpenoids,in order to provide literature reference for the development of Poria cocos grand health industry.

Objective:To explore the current status and the influencing factors of protracted postpartum urinary retention(P-PUR) in women with labor analgesia, so as to provide evidences for early diagnosis and timely intervention for P-PUR.Methods:A total of 41 995 women who were given vaginal delivery under labor analgesia from January 2017 to October 2020 in Women′s Hospital of Nanjing Medical University were chosen as the research objects. A retrospective analysis was performed for the clinical data of 62 women with P-PUR, and a 1∶4 matching case control study was conducted. Logistic regression analysis was used to analyze the variables with statistical difference in univariate analysis, so as to explore the independent influencing factors of P-PUR in women with labor analgesia.Results:Among 41 995 women with labor analgesia, 62 women suffered from P-PUR, and the incidence was about 0.15% (62/41 995). The Logistic regression model showed that nulliparity ( OR=121.80, 95% CI 8.59-1 727.40, P<0.05), forceps delivery ( OR=13.41, 95% CI 2.21-81.58, P<0.05),Ⅱdegree porineal iaceration ( OR=0.04, 95% CI 0.01-0.11, P<0.05), episiotomy ( OR=0.13, 95% CI 0.04-0.47, P<0.05) and perineotomy with perineal laceration ( OR=0.20, 95% CI 0.06-0.63, P<0.05) were the independent risk factors. Conclusions:For primiparas with labor analgesia, interventions should be taken to reduce perineal injury, and indications of forceps delivery should be strictly controlled, so as to reduce P-PUR and adverse urinary tract complications.

Isopentenyl flavonoids are a class of characteristic components in Sophora flavescens Ait. (S. flavescens). They have biological activities such as anti-tumor, anti-bacteria, anti-inflammol/ Lation and anti-oxidation. In this paper, the structural types, toxicology and pharmacological effects of isopentenyl flavonoids from S. flavescens were briefly reviewed. Furthermore, the worth of further study on pharmacokinetics, pharmacodynamics, toxicology, action targets, molecular mechanisms and structure-function relationships of isopentenyl flavonoids were proposed. The deep exploration on functional characterastics of isopentenyl flavonoids of S. flavescens and their application on development of innovative drugs are of great significance to further improve the added value of isopentenyl flavonoids and expand their application fields.

Cholangiocarcinoma is a malignant tumor originating from the bile duct epithelium, with the increasing incidence year by year. Its early symptoms are atypical and the diagnosis rate is low. Most of the patients are already in advanced stage when they are diagnosed, losing the best surgery period. Currently, the conservative treatments for unresectable extrahepatic cholangiocarcinoma include stent placement, radiofrequency ablation, radiotherapy and chemotherapy, targeted and immunotherapy and other systemic treatments. But due to the high malignancy of biliary tract tumors, the tendency to develop drug resistance and the limited population benefited from the emerging treatment modalities, we urgently need to explore new treatment strategies to break this bottleneck. As a new treatment for cholangiocarcinoma, photodynamic therapy has attracted much attention for its clinical application and therapeutic effects. In this paper, we summarize the principles of photodynamic therapy, the combination of photodynamic and other therapeutic modalities, especially the combination of photodynamic with emerging immune and targeted therapies, and describe the current hotspot directions of photodynamic therapy research at home and abroad to provide reference for clinical treatment and research.