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*

OBJECTIVE: Poxviruses are zoonotic pathogens that infect humans, mammals, vertebrates, and arthropods. However, the specific role of ticks in transmission and evolution of these viruses remains unclear. METHODS: Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses. Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences. RESULTS: Fifty-eight poxvirus species, representing two subfamilies and 20 genera, were identified, with 212 poxviral sequences assembled. A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes. These genomic sequences contained fragments originating from rodents, archaea, and arthropods. CONCLUSION Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses. These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer, gene recombination, and gene mutations, thereby promoting co-existence and co-evolution with their hosts. This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
Animals ; Poxviridae/physiology* ; Ticks/virology* ; Phylogeny ; Transcriptome ; Evolution, Molecular ; Poxviridae Infections/virology* ; Genome, Viral

Objective:To investigate the efficacy and safety of darolutamide in the treatment of patients with metastatic hormone-sensitive prostate cancer.Methods:A retrospective analysis was conducted on 17 cases of prostate cancer patients who received treatment with darolutamide in combination with ADT at our hospital from January to December 2022. The median age was 70 (range: 56 to 92) years old. The median pre-treatment prostate-specific antigen (PSA) level was 63.50 (range: 29.16 to 700.74) ng/ml. Sixteen cases had a Gleason score of 8 or above, and 11 cases were classified as high tumor burden (with four or more bone metastases and/or visceral metastases). The patients were treated with darolutamide in combination with goserelin (10.8 mg, subcutaneous injection, every 12 weeks). The decrease in PSA levels was observed at 2 weeks and at 1, 2, 3, and 6 months post-treatment. The time to achieve a 50% decrease in PSA level (PSA50), a 90% decrease (PSA90), and a PSA level of ≤0.2 ng/ml was recorded.Adverse drug reactions were also documented.Results:All the 17 patients were followed up and continued to receive darolutamide at our center without any loss to follow-up. The median follow-up time was 11.4(8.9, 15.3)months. It showed a median PSA decrease from baseline of 83.33% at 2 weeks, 95.37% at 1 month, 96.71% at 2 months, 97.22% at 3 months, and 99.10% at 6 months. The median time to achieve PSA50, PSA90, and PSA ≤ 0.2 ng/ml were 1.3 (0.9, 1.7)months, 1.7 (1.2, 2.4)months, and 3.6 (2.9, 4.5)months respectively. Six patients with bone metastases experienced relief of metastatic lesions after treatment. Only one patient developed papules on the left upper limb, which were assessed as grade 1 rash, and the rash disappeared after three days treatment of topical application of hydrocortisone cream.Conclusions:Darolutamide could rapidly control and significantly reduce PSA levels in prostate cancer patients, with a favorable safety profile.

Objective:To compare the clinical efficacy of autologous bone grafting or bioceramic bone grafting combined with locking compression plate (LCP) internal fixation in the treatment of Schatzker type II and III tibial plateau fractures.Methods:A retrospective analysis was conducted on 104 patients with Schatzker type II and III tibial plateau fractures who underwent surgical treatment at the Department of Orthopedics, PLA Central Theater Command General Hospital from January 2010 to December 2021. The cohort comprised 55 males and 49 females, with an average age of 49.13±13.80 years (range 18-73 years). All fractures were unilateral: 55 on the left and 49 on the right. According to the Schatzker classification, 59 were Type II and 45 were Type III. Causes of injury included traffic accidents (48 cases), falls from height (3 cases), sprains or falls (45 cases), and other causes (8 cases). During surgery, bioceramic material or allograft bone tissue was implanted into the collapsed tibial plateau region to restore articular surface flatness. Based on graft type, patients were divided into the allograft bone group (63 cases) and the bioceramic group (41 cases). All cases underwent proximal lateral tibial LCP internal fixation. The two groups were compared in terms of operative time, intraoperative blood loss, bone graft volume, length of hospital stay, fracture healing time, and postoperative complications. The Rasmussen radiographic collapse score was used to evaluate fracture reduction, and the Hospital for Special Surgery (HSS) score system was used to assess knee joint function.Results:All patients were followed up for 12(12, 13) months (range 12-16 months). The fracture healing time in the allograft bone group was 13.70±1.36 weeks (range 11-16 weeks), which was significantly shorter than that in the bioceramic group: 14.59±1.73 weeks (range 11-19 weeks) ( t=2.911, P=0.004). The time to full weight-bearing in the allograft group was 15.0(14.0, 17.0) weeks (range 13-23 weeks), which was shorter than the 16.0 (15.5, 18.5) weeks (range 12-24 weeks) in the bioceramic group, showing a statistically significant difference ( Z=-3.019, P=0.002). At 12 months postoperatively, the Rasmussen radiographic collapse score was 1(0, 1) in the bioceramic group, significantly lower than the 1(1, 2) score in the allograft group ( Z=-2.083, P=0.037). No statistically significant differences were observed between the two groups in bone graft volume, surgical duration, intraoperative blood loss, hospitalization duration, or HSS scores at 6 and 12 months postoperatively ( P>0.05). The complication rate was 6.3% (4/63) in the allograft group and 2.4% (1/41) in the bioceramic group, with no statistically significant difference (χ 2=0.830, P=0.362). Conclusions:For Schatzker type II and III tibial plateau fractures, the use of allograft bone or bioceramic combined with LCP internal fixation can achieve good results. Allograft bone has advantages in terms of fracture healing speed and early weight-bearing recovery, while bioceramic is more effective in maintaining joint surface stability.

Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94～0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.

Objective:To compare the clinical efficacy of autologous bone grafting or bioceramic bone grafting combined with locking compression plate (LCP) internal fixation in the treatment of Schatzker type II and III tibial plateau fractures.Methods:A retrospective analysis was conducted on 104 patients with Schatzker type II and III tibial plateau fractures who underwent surgical treatment at the Department of Orthopedics, PLA Central Theater Command General Hospital from January 2010 to December 2021. The cohort comprised 55 males and 49 females, with an average age of 49.13±13.80 years (range 18-73 years). All fractures were unilateral: 55 on the left and 49 on the right. According to the Schatzker classification, 59 were Type II and 45 were Type III. Causes of injury included traffic accidents (48 cases), falls from height (3 cases), sprains or falls (45 cases), and other causes (8 cases). During surgery, bioceramic material or allograft bone tissue was implanted into the collapsed tibial plateau region to restore articular surface flatness. Based on graft type, patients were divided into the allograft bone group (63 cases) and the bioceramic group (41 cases). All cases underwent proximal lateral tibial LCP internal fixation. The two groups were compared in terms of operative time, intraoperative blood loss, bone graft volume, length of hospital stay, fracture healing time, and postoperative complications. The Rasmussen radiographic collapse score was used to evaluate fracture reduction, and the Hospital for Special Surgery (HSS) score system was used to assess knee joint function.Results:All patients were followed up for 12(12, 13) months (range 12-16 months). The fracture healing time in the allograft bone group was 13.70±1.36 weeks (range 11-16 weeks), which was significantly shorter than that in the bioceramic group: 14.59±1.73 weeks (range 11-19 weeks) ( t=2.911, P=0.004). The time to full weight-bearing in the allograft group was 15.0(14.0, 17.0) weeks (range 13-23 weeks), which was shorter than the 16.0 (15.5, 18.5) weeks (range 12-24 weeks) in the bioceramic group, showing a statistically significant difference ( Z=-3.019, P=0.002). At 12 months postoperatively, the Rasmussen radiographic collapse score was 1(0, 1) in the bioceramic group, significantly lower than the 1(1, 2) score in the allograft group ( Z=-2.083, P=0.037). No statistically significant differences were observed between the two groups in bone graft volume, surgical duration, intraoperative blood loss, hospitalization duration, or HSS scores at 6 and 12 months postoperatively ( P>0.05). The complication rate was 6.3% (4/63) in the allograft group and 2.4% (1/41) in the bioceramic group, with no statistically significant difference (χ 2=0.830, P=0.362). Conclusions:For Schatzker type II and III tibial plateau fractures, the use of allograft bone or bioceramic combined with LCP internal fixation can achieve good results. Allograft bone has advantages in terms of fracture healing speed and early weight-bearing recovery, while bioceramic is more effective in maintaining joint surface stability.

Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94～0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.

Objective:To investigate the efficacy and safety of darolutamide in the treatment of patients with metastatic hormone-sensitive prostate cancer.Methods:A retrospective analysis was conducted on 17 cases of prostate cancer patients who received treatment with darolutamide in combination with ADT at our hospital from January to December 2022. The median age was 70 (range: 56 to 92) years old. The median pre-treatment prostate-specific antigen (PSA) level was 63.50 (range: 29.16 to 700.74) ng/ml. Sixteen cases had a Gleason score of 8 or above, and 11 cases were classified as high tumor burden (with four or more bone metastases and/or visceral metastases). The patients were treated with darolutamide in combination with goserelin (10.8 mg, subcutaneous injection, every 12 weeks). The decrease in PSA levels was observed at 2 weeks and at 1, 2, 3, and 6 months post-treatment. The time to achieve a 50% decrease in PSA level (PSA50), a 90% decrease (PSA90), and a PSA level of ≤0.2 ng/ml was recorded.Adverse drug reactions were also documented.Results:All the 17 patients were followed up and continued to receive darolutamide at our center without any loss to follow-up. The median follow-up time was 11.4(8.9, 15.3)months. It showed a median PSA decrease from baseline of 83.33% at 2 weeks, 95.37% at 1 month, 96.71% at 2 months, 97.22% at 3 months, and 99.10% at 6 months. The median time to achieve PSA50, PSA90, and PSA ≤ 0.2 ng/ml were 1.3 (0.9, 1.7)months, 1.7 (1.2, 2.4)months, and 3.6 (2.9, 4.5)months respectively. Six patients with bone metastases experienced relief of metastatic lesions after treatment. Only one patient developed papules on the left upper limb, which were assessed as grade 1 rash, and the rash disappeared after three days treatment of topical application of hydrocortisone cream.Conclusions:Darolutamide could rapidly control and significantly reduce PSA levels in prostate cancer patients, with a favorable safety profile.

[Abstract] [Objective] To explore the risk factors of blood transfusion in patients with isolated traumatic brain injury (iTBI) based on multiple machine learning methods, so as to establish a predictive model to provide reasonable guidance for blood transfusion in patients with iTBI. [Methods] A total of 2 273 patients with iTBI from the First Affiliated Hospital of Nanchang University from January 1, 2015 to June 30, 2021 were included to compare and analyze the differences in variables such as vital signs, clinical indicators and laboratory testing indicators between transfusion and non transfusion patients. Furthermore, six machine learning models were established to compare the performance of different models through cross validation, accuracy, specificity, recall, f1 value and area under the ROC curve. The SHAP plot was used to explain the influencing factors of blood transfusion in iTBI patients. [Results] This study included 2 273 iTBI patients, with a total of 301 patients receiving blood transfusions. There were significant differences (P<0.05) in gender, age, HR, clinical diagnosis, skull fracture, treatment methods, hemorrhagic shock, GCS, K, Ca, PT, APTT, INR, RBC, Hct, Hb and Plt between transfusion and non transfusion patients; Moreover, the LOS, incidence of complications, mechanical ventilation rate, ICU admission rate, readmission rate within 90 days and in-hospital mortality rate of transfusion patients were all higher than those of the non transfusion group (P<0.05). Six machine learning algorithms were used for model construction, and the validation results on the test set showed that the CatBoost model performed the best with an AUC of 0.911. Furthermore, the SHAP framework was used to explain and visualize the optimal model CatBoost, showing that surgical treatment, lower GCS, higher INR, lower Hct, lower K, lower Ca, age ≥60 years, skull fractures and hemorrhagic shock increase the risk of blood transfusion in patients. [Conclusion] This study established a machine learning model for predicting blood transfusion in iTBI patients, and the CatBoost model performed the best. This model may be useful and beneficial for identifying transfusion risks in this population, making clinical transfusion decisions and monitoring progress.