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.

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 describe and analyze suicide risk of patients with schizophrenia,major depressive disorder,and bipolar disorder.Methods:A total of 2 016 patients with schizophrenia,903 patients with major de-pressive disorder,and 381 patients with bipolar disorder from inpatients,clinics,or communities who met the diag-nostic criteria of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition were recruited.All patients were interviewed by psychiatrists using the Mini International Neuropsychiatric Interview to diagnose mental disor-ders and assess suicide risk,as well as Clinical-Rated Dimensions of Psychosis Symptom Severity(CRDPSS)to as-sess symptoms.Differences and risk factors of suicide risk among three types of mental disorders were explored u-sing multivariate logistic regression analysis.Results:In the past one month,37 patients with schizophrenia(1.8％),516 patients with major depressive disorder(57.1％),and 102 patients with bipolar disorder(26.8％)had suicide risk.Compared with patients with schizophrenia,suicide risk in patients with major depressive disorder(OR=36.50)and bipolar disorder(OR=20.10)increased.Female(OR=1.87),smoking(OR=1.76),family history of suicide(OR=5.09),higher score of CRDPSS hallucination(OR=1.80),and higher score of CRDPSS depression(OR=1.54)were risk factors of suicide risk of patients.Conclusions:Suicide risk of patients with ma-jor depressive disorder and bipolar disorder is higher than that of patients with schizophrenia.In clinical practice,it is important to regularly assess suicide risk of patients.Patients who experience symptoms of hallucination and de-pression should be paid more attention to.

Objective:To evaluate direct and indirect costs for schizophrenia,major depressive disorder(MDD)and bipolar disorder,and to compare their differences of cost composition,and to explore the drivers of the total costs.Methods:A total of 3 175 inpatients with schizophrenia,MDD,and bipolar disorder were recruited.In-patient's self-report total direct of medical costs outpatient and inpatient,out-of-pocket costs,and direct non-medical costs were regarded as direct costs.Productivity loss and other loss caused by damaging properties were defined as indirect costs.The perspectives of this study included individual and societal levels.Multivariate regression analysis was applied for detecting the factors influencing disease costs.Results:The total cost of schizophrenia was higher than those of MDD and bipolar disorder at individual and societal levels.The indirect costs of three mental disorders were higher than the direct costs,and the indirect cost ratio of bipolar disorder was higher than those of schizophre-nia and MDD.Age,gender,working condition and marital status(P＜0.05)were the important drivers of total costs.Conclusion:The economic burden of the three mental disorders is relatively heavy.Schizophrenia has heaviest disease burden,and the productivity loss due to mental disorders is the driving force of the soaring disease cost

Objective:To explore the clinical characteristics and related socio-demographic factors of schizo-phrenia patients with different ages of onset.Methods:Totally 2 016 patients with schizophrenia aged 15 to 70 were selected according to the diagnostic criteria for schizophrenia in the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition.All of the patients were interviewed by psychiatrists using the Mini International Neuropsy-chiatric Interview to diagnose schizophrenia,Clinical-Rated Dimensions of Psychosis Symptom Severity(CRDPSS)and the Positive and Negative Syndrome Scale(PANSS)to assess symptoms.The cut-off points were 18 and 25 years old for three age groups,i.e.early onset(EOS),youth onset(YOS)and adult onset(AOS).Statistical analy-ses were performed by analysis of variance Pearson correlation analysis,and multivariate linear regression.Results:The early-onset patients had the highest total PANSS score(73.8±28.0)and CRDPSS score(11.7±5.4).Fe-male gender,high education level,Han ethnicity,early onset age,and slower onset of illness were negatively corre-lated with the total and dimension score of PANSS scale and CRDPSS scale(standardized regression coefficient:0.04-0.47),and income level and smoking were negatively correlated with those score(standardized regression coefficient:-0.04--0.14).Conclusion:Early-onset schizophrenia patients have more severe symptoms,and fe-male,high education level,early-onset disease,and chronic onset are the risk factors of symptom severity in patients with schizophrenia.

Objective:To study the correlation between serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) level and echocardiographic parameters in patients with chronic Keshan disease, providing reference for diagnosis and prognosis evaluation of chronic Keshan disease.Methods:Ninety-nine patients with chronic Keshan disease who received standardized treatment at Jingchuan County People's Hospital in Pingliang City, Gansu Province from January to December 2020 were selected. Among them, 16 patients were classified as cardiac function grade Ⅱ according to New York Heart Association (NYHA), 69 as grade Ⅲ and 14 as grade Ⅳ. The patients underwent echocardiography and their serum NT-proBNP level was measured using fluorescence immunochromatography. The differences in serum NT-proBNP levels among patients with different cardiac function grades were compared, and the correlation between cardiac function grades, serum NT-proBNP level and echocardiographic parameters was analyzed.Results:The serum NT-proBNP levels in patients with cardiac function grades Ⅱ, Ⅲ, and Ⅳ were (1 107.26 ± 268.03), (2 125.98 ± 293.02), and (8 268.59 ± 2 659.50) pg/ml, respectively. The differences among the three groups were statistically significant ( F = 13.94, P < 0.001). The serum NT-proBNP level was positively correlated with cardiac function grades ( r = 0.44, P < 0.001), left ventricular end-diastolic diameter, left ventricular end-systolic diameter, and left atrial diameter ( r = 0.45, 0.52, 0.38, P < 0.001), and negatively correlated with fractional shortening and left ventricular ejection fraction ( r = - 0.39, - 0.46, P < 0.001). Conclusions:The serum NT-proBNP level in patients with chronic Keshan disease with different cardiac function grades is different, and is positively correlated with echocardiographic parameters reflecting the degree of cardiac structural and functional impairment. The NT-proBNP level may become an early diagnostic, grading, and prognostic indicator for chronic Keshan disease.

Objective:To investigate the intelligence status of children aged 10 - 12 in rural areas of Linxia Hui Autonomous Prefecture (referred to as Linxia) in Gansu Province.Methods:From September to November 2019, a cross-sectional study was carried out to investigate the intelligence status of children aged 10 to 12 in 8 counties (cities) of Linxia. Chinese Raven's Progressive Matrices (rural version) was used for intelligence test and children's intelligence quotient (IQ) was calculated by regular mold to evaluate children's intelligence level.Results:A total of 1 721 children in Linxia were tested for intelligence, with an average IQ of 103.2. Among them, low intelligence (≤69) accounted for 1.0% (18/1 721), borderline (70 - 79) accounted for 3.0% (52/1 721), middle and lower (80 - 89) accounted for 8.4% (144/1 721), moderate (90 - 109) accounted for 56.6% (974/1 721), middle and upper (110 - 119) accounted for 21.9% (377/1 721), excellent (120 - 129) accounted for 7.8% (135/1 721), extremely excellent (≥130) accounted for 1.2% (21/1 721). There were 635, 598 and 488 children aged 10, 11 and 12, respectively, with an average IQ of 106.1, 103.3 and 99.2. There were 919 males and 802 females, with an average IQ of 102.9 and 103.4, respectively.Conclusion:In 2019, the intelligence of children aged 10 to 12 in rural areas of Linxia has reached the moderate level.

Objective:To evaluate the value of left echography (LVO) in the diagnosis of false ventricular aneurysm complicated with mural thrombus.Methods:The clinical data of 10 patients with suspected pseudoventricular aneurysm examined by thoracic echocardiography (TTE) in Wuhan Asian Heart Hospital from January 2018 to March 2024 were retrospectively analyzed. All patients underwent LVO examination to further diagnose pseudoventricular tumor and whether it was complicated with mural thrombosis. Computed tomography angiography (CTA) or cardiac magnetic resonance (CMR) examination was used as the gold standard to analyze the diagnostic value of LVO in the diagnosis of pseudoventricular tumor.Results:Among the 10 suspected pseudoventricular tumors examined by TTE, LVO detected 6 cases of left ventricular pseudoaneurysm and 1 case of right ventricular pseudoaneurysm; CTA confirmed that 6 cases of left ventricular pseudoaneurysm detected by LVO were correctly diagnosed, 1 case of right ventricular pseudoaneurysm was misdiagnosed, CMR diagnosed right ventricular diverticula, LVO diagnosis accuracy was 6/7, and 4 cases of thrombi were detected. The detection rate was 4/4. The maximum transverse diameter of the tumor body of the communicating mouth/false ventricular aneurysm was 0.46±0.04. 1 patient underwent coronary artery bypass grafting and resection of false ventricular aneurysm. 1 patient underwent coronary artery interventional stent surgery; 4 routine conservative drug treatment, follow-up observation; One case of right ventricular diverticulum did not require special treatment.Conclusions:LVO contrast agent can clearly show the tumor body and location, measure the tumor entrance and size, and show mural thrombus. It is the first choice for the identification of false ventricular tumor. The diverticula was similar to the image of false ventricular aneurysm, and the sensitivity and specificity of right ventricular wall motion were higher in CMR than in LVO.

Objective:To understand and compare the clinical characteristics of children and adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant BA.5 and BA.2 subtypes in Shanghai City.Methods:The clinical data of 524 children hospitalized with coronavirus disease 2019(COVID-19) at the Children′s Hospital of Fudan University during the period of BA.5 predominance from December 1, 2022 to January 20, 2023 were collected, which included age, gender, clinical symptoms and laboratory examination results. And the clinical data of household close contacts were also collected. The clinical data of children and their household contacts infected with Omicron BA.2 subtypes during the period of BA.2 predominance from April 4 to April 30, 2022 were collected and compared.The clinical characteristic of critical and non-critical cases, child and adult cases during the period of BA.5 predominance were compared.Statistical analyses were conducted using independent samples t-test, Mann-Whitney U test, chi-square test or Fisher′s exact test. Results:The age of 524 hospitalized children was five days to 16 years old. Among them, 301(57.4%) were male and 223(42.6%) were female. Additionally, there were 29 critical cases (5.5%) and 495 non-critical cases (94.5%). Critical cases had significantly higher fever peak, more shortness of breath occurrence, more pneumonia and underlying diseases compared to non-critical cases, with statistically significant differences ( t=12.06, χ2=34.90, 10.04 and 31.10, respectively, all P<0.05). Regarding laboratory examinations, critical cases exhibited significantly higher frequencies of decreased lymphocyte count, elevated levels of C-reactive protein, procalcitonin and interleukin-6, abnormal liver function and kidney function, and abnormal creatine kinase isoenzyme compared to non-critical cases, with statistically significant differences ( χ2=8.18, Z=-4.61, Z=-4.28, Z=-5.13, χ2 =195.90, Fisher′s exact test and χ2=136.13, respectively, all P<0.05). Non-critical children cases infected with Omicron variant BA.5 subtype exhibited a higher proportion of symptomatic infections compared to adults. Among children, the occurrence rates of fever and gastrointestinal symptoms (nausea, vomiting, diarrhea) were higher, whereas among adults, the occurrence rate of cough was higher. The differences were statistically significant ( χ2=11.16, 11.83, 8.50 and 28.14, respectively, all P<0.05).From December 1, 2022 to January 20, 2023, a total of 588 children cases and 791 adult cases were collected, while from April 4 to April 30, 2022, a total of 355 children cases and 755 adult cases were collected.In the children group, the occurrence rates of cough, convulsions and critical cases were higher in BA.5 subtype-infected children compared to those infected with the BA.2 subtype, with statistically significant differences ( χ2=37.95, 40.78 and 15.54, respectively, all P<0.001).In the adult group, BA.5 subtype-infected individuals had higher fever peak, longer duration of fever, and higher occurrence of fever, cough and gastrointestinal symptoms, compared to those infected with the BA.2 subtype.The differences were statistically significant ( t=-4.40, Z=-9.64, χ2=47.29, 124.09 and 29.90, respectively, all P<0.001). Conclusions:During the peak periods of BA.5 subtype of the Omicron variant in Shanghai City, critical cases have severe systemic symptoms and a higher prevalence of underlying diseases compared to non-critical cases. Among non-critical cases infected with BA.5 subtype, the proportion of symptomatic infections in children is higher than adults, with fever and gastrointestinal symptoms more common than adults, while cough symptoms are more common seen in adults.The occurrence rate of convulsions and critical cases is higher in children infected with variant BA.5 subtype compared to those infected with BA.2 subtype.The systemic symptoms are more severe in adults infected with BA.5 subtype compared to those infected with BA.2 subtype.