Objective To assess the stability of the molluscicidal activity of the fermentation broth supernatant of Bacillus indicus F19, so as to provide insights into development of novel molluscicides derived from this isolate. Methods Healthy Oncomelania hupensis snails free from Schistosoma japonicum infections and acclimated in the laboratory for 7 days were selected. The fermentation broth supernatant of B. indicus F19 was prepared. For each treatment condition, four experimental groups and one control group were established, with 10 mL of the fermentation broth supernatant each group. O. hupensis snails were exposed to different pH values (3, 6, 9 and 12), temperatures (40, 60, 80 °C and 100 °C), and ultraviolet (UV) exposure durations (1, 2, 3 h and 4 h). Then, the supernatant was diluted with dechlorinated water to concentrations of 50%, 10%, and 5% (v/v), and 10 mL of each dilution solution was added to three separate tubes, with an equal volume of dechlorinated water as a blank control. Twenty O. hupensis snails were transferred to each tube, immersed for 48 h and 72 h, and collected for viability assessment using the shell-tapping method. The mortality of O. hupensis snails was calculated and compared among dilution groups and the blank control group to evaluate the molluscicidal activity of the fermentation broth supernatant of B. indicus F19. Results There was a significant difference in the mortality of O. hupensis snails immersed in 5% fermentation broth supernatants of B. indicus F19 for 48 h at various pH levels (χ² = 11.556, P < 0.05), and the mortality reduced to 13.33% (8/60) in the experimental groups at a pH value of 12, which was significantly lower than in the blank control group [33.33% (20/60)] (χ² = 6.708, P < 0.05). There was a significant difference in the mortality of O. hupensis snails immersed in 10% fermentation broth supernatants of B. indicus F19 for 72 h at various pH levels (χ² = 31.691, P < 0.001), and the mortality reduced to 71.67% (43/60) and 65.00% (39/60) in the experimental group at pH values of 9 and 12, which was significantly lower than in the blank control group [100.00% (60/60)] (χ² = 8.571 and 12.110, both P values < 0.01). The mortality of O. hupensis snails both reduced to 23.33% (14/60) following immersion in 5% fermentation broth supernatants of B. indicus F19 heated in a water bath at 80 °C and 100 °C for 48 h, which was lower than that of unheated O. hupensis snails [33.33% (20/60)] and snails heated in a water bath at 40 °C [35.00% (21/60)] and 60 °C [33.33% (20/60)], and there was no significant difference in the mortality of O. hupensis snails among groups (χ² = 3.898, P > 0.05). The mortality of O. hupensis snails was 68.33% (41/60), 66.67% (40/60), 65.00% (39/60), and 68.33% (41/60) following immersion in fermentation broth supernatants heated in a water bath at 40, 60, 80 °C and 100 °C for 72 h, which was all lower than that of snails in the control group [71.70% (43/60)]; however, there was no significant difference seen in the snail mortality among groups (χ² = 0.674, P > 0.05). The mortality of O. hupensis snails was 73.33% (44/60), 71.67% (43/60), 71.67% (43/60), and 75.00% (45/60) following 48 h immersion in 10% fermentation broth supernatants of B. indicus F19 irradiated by UV for 1, 2, 3 h and 4 h, 33.33% (20/60), 31.67% (19/60), 35.00% (21/60), and 33.33% (20/60) following 48 h immersion in 10% fermentation broth supernatants of B. indicus F19 irradiated by UV for 1, 2, 3 h and 4 h, and 71.67% (43/60) and 33.33% (20/60) following 48 h immersion in 10% fermentation broth supernatants of B. indicus F19 without UV irradiation, and no significant differences were found among groups (χ² = 0.229 and 0.150, both P values > 0.05). In addition, the mortality of O. hupensis snails was 76.67% (46/60), 71.67% (43/60), 70.00% (42/60), and 76.67% (46/60) following 72 h immersion in 5% fermentation broth supernatants of B. indicus F19 irradiated by UV for 1, 2, 3 h and 4 h, and 71.67% (43/60) in the control group, and there was no significant difference in the snail mortality among groups (χ² = 1.193, P > 0.05). Conclusion The molluscicidal action of the fermentation broth supernatants of B. indicus F19 is tolerant to high temperature and UV irradiation; however, the activity is attenuated under alkaline conditions.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

The interactions between microorganisms and medicinal plants are crucial to the quality improvement of medicinal plants. Medicinal plants attract microorganisms to colonize by secreting specific compounds and provide niche and nutrient support for these microorganisms, with a symbiotic network formed. These microorganisms grow in the rhizosphere, phyllosphere, and endophytic tissues of plants and significantly improve the growth performance and medicinal component accumulation of medicinal plants by promoting nutrient uptake, enhancing disease resistance, and regulating the synthesis of secondary metabolites. Microorganisms are also widely used in the ecological planting of medicinal plants, and the growth conditions of medicinal plants are optimized by simulating the microbial effects in the natural environment. The interactions between microorganisms and medicinal plants not only significantly improve the yield and quality of medicinal plants but also enhance their geoherbalism, which is in line with the concept of green agriculture and eco-friendly development. This study reviewed the research results on the interactions between medicinal plants and microorganisms in recent years and focused on the analysis of the great potential of microorganisms in optimizing the growth environment of medicinal plants, regulating the accumulation of secondary metabolites, inducing systemic resistance, and promoting the ecological planting of medicinal plants. It provides a scientific basis for the research on the interactions between medicinal plants and microorganisms, the research and development of microbial agents, and the application of microorganisms in the ecological planting of medicinal plants and is of great significance for the quality improvement of medicinal plants and the green and sustainable development of TCM resources.
Plants, Medicinal/metabolism* ; Bacteria/genetics* ; Symbiosis

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

Objective:To observe the clinical efficacy of Chinese materia medica soaking therapy combined with cervical rotation-traction manipulation in the treatment of cervical spondylotic radiculopathy (CSR).Methods:A randomized controlled trial was conducted. Totally 84 CSR patients from the Orthopedics Department of Shunyi Hospital, Beijing Traditional Chinese Medicine Hospital from April 2023 to May 2024 were selected as the observation subjects. They were divided into two groups using a random number table method, with 42 patients in each group. The treatment for both groups lasted for 14 d. VAS scale was used to assess pain levels before and after treatment, OASTCSR was used to evaluate cervical function, and NDI was used to assess cervical functional status; adverse reactions during treatment were observed and recorded, and clinical efficacy was evaluated.Results:The total effective rate was 95.24% (40/42) in the treatment group and 80.95% (34/42) in the control group, with statistical significance ( χ2=4.36, P=0.029). After treatment, the VAS score (1.60±1.21 vs. 2.91±1.12, t=-1.89), the OASTCSR score (5.17±2.14 vs. 9.31±3.82, t=-11.57), and the NDI score (9.17±2.13 vs. 13.36±3.45, t=-10.82) in the treatment group were lower than those in the control group ( P<0.001 or P<0.05). During the treatment period, neither group experienced any adverse reactions. Conclusion:The combination of Chinese materia medica soaking therapy and cervical rotation-traction manipulation can significantly improve the clinical symptoms and quality of life of patients with CSR, and its efficacy is superior to the use of cervical rotation-traction manipulation alone.

Objective To analyze the clinical characteristics,treatment,and prognosis of immune checkpoint inhibitor-related diabetes mellitus(ICI-DM).Methods The clinical characteristics,laboratory examinations,treatment regimens,and follow-up outcomes of 10 ICI-DM patients who were diagnosed and treated in the First Medical Center of Chinese PLA General Hospital between July 2019 and December 2024 were retrospectively analyzed.Relevant literatures were retrieved from domestic and foreign databases such as PubMed,CNKI,and VIP.The clinical characteristics of ICI-DM were summarized based on the literature results.Results All 10 patients were PD-1 inhibitor users,including 5 males and 5 females,with a median age of 54.5(51.3,64.0)years and a body mass index(BMI)of(22.0±2.15)kg/m2.Among them,9 cases(90.0%)were fulminant type 1 diabetes mellitus(FT1DM);9 cases(90.0%)had a severity of adverse events reaching grade 3-4 according to the Common Terminology Criteria for adverse events(CTCAE).The median time from PD-1 inhibitor treatment to the occurrence of the classic diabetes symptoms referred to as"three more and one less"(polyuria,polydipsia,polyphagia,and weight loss)in all patients was 145.5(110.5,204.8)days,and the medication duration was 6.0(4.3,7.8)cycles.The average blood glucose level of the 10 patients at the time of consultation was 25.3(10.0-41.4)mmol/L,and the glycated hemoglobin(HbA1c)level was 8.0%(6.6%-10.9%).Eight patients had fasting and 2-hour C-peptide levels<0.1 ng/ml(fasting C-peptide from<0.010 to 0.067 ng/ml,2-hour C-peptide from<0.010 to 0.077 ng/ml).Nine of the 10 patients were negative for diabetes autoantibodies,while 1 was not tested.All 10 patients were successfully treated with insulin and other therapies.During the follow-up after discharge,all patients still relied on insulin treatment,and no significant recovery of pancreatic islet β cell function was observed compared with that at discharge.Literature review revealed that ICI-DM was more common in PD-1 inhibitor users,with clinical mainly manifested as diabetic ketoacidosis(DKA)(65.4%)and diabetic ketosis(13.1%).Patients had severely impaired pancreatic islet function and required long-term insulin treatment,and some cases were complicated by thyroid or pituitary dysfunction.Conclusions ICI-DM typically presents as FT1DM,often manifesting with DKA or diabetic ketosis at onset.It is characterized by severe and irreversible loss of pancreatic islet function,necessitating lifelong insulin therapy.To enable early detection and prompt treatment,close monitoring of blood glucose is essential during ICI treatment.