Cardiotoxicity is a critical issue in drug development that poses serious health risks, including potentially fatal arrhythmias. The human ether-à-go-go related gene (hERG) potassium channel, as one of the primary targets of cardiotoxicity, has garnered widespread attention. Traditional cardiotoxicity testing methods are expensive and time-consuming, making computational virtual screening a suitable alternative. In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. Our models demonstrated advanced predictive performance. The best machine learning model, XGBoost Morgan, achieved an accuracy (ACC) value of 0.84, and the deep learning model, Transformer_Morgan, achieved the best ACC value of 0.85, showing a high ability to distinguish between toxic and non-toxic compounds. On an external independent validation set, it achieved the best area under the curve (AUC) value of 0.93, surpassing ADMETlab3.0, Cardpred, and CardioDPi. In addition, we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods, such as voting and stacking, provided slight improvements in model stability. Furthermore, the SHapley Additive exPlanations (SHAP) explanations revealed the relationship between benzene rings, fluorine-containing groups, NH groups, oxygen in ether groups, and cardiotoxicity, highlighting the importance of these features. This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment. Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.

Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the pri-mary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alter-native.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Trans-former models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.

Objective To protect the economic benefits of the hospital by improving the medical record quality,quality control ability,and standardising the filling of the medical insurance settlement list.Methods Re-quality control of previous malignant tumour cases,with the help of the intelligent health insurance case collaboration system,compare the changes in case entry and benchmark costs after the revision of errors,analyse the results caused by different errors,and summarise the correct experience.Results Erroneous disease diagnoses can lead to losses or suspected fraud in health insurance billing,affecting the economic operation of healthcare organisations.Conclusion The improvement of the quality of the medical insurance settlement list not only needs to improve the quality of case writing,coding level,but also needs to read the connotation of the policy through extensive study.

Objective:To observe and evaluate the clinical efficacy and safety of albumin-bound paclitaxel as first-line treatment for patients with advanced pancreatic cancer in China, and to explore the prognosis-related molecules in pancreatic cancer based on next-generation sequencing (NGS) of tumor tissues.Methods:From December 2018 to December 2020, patients with locally advanced or metastatic pancreatic cancer were recruited to accept albumin-bound paclitaxel as first-line treatment in the oncology departments of 24 hospitals in East China. The primary endpoints were overall survival (OS) and treatment related adverse events, and the secondary endpoint was progression-free survival (PFS). Adverse effects were graded using Common Terminology Criteria for Adverse Events 5.0 (CTCAE 5.0). NGS sequencing on the primary or metastatic tissue samples of pancreatic cancer obtained through surgical resection or biopsy was performed.Results:This study recruited 229 patients, including 70 patients with locally advanced pancreatic cancer (LAPC) and 159 patients with metastatic pancreatic cancer (mPC). The disease control rate was 79.9% and the objective response rate is 36.3%.The common adverse effects during treatment were anaemia (159 cases), leucopenia (170 cases), neutropenia (169 cases), increased aminotransferases (110 cases), and thrombocytopenia (95 cases), and the incidence of grade 3-4 neutropenia is 12.2% (28/229). The median follow-up time was 21.2 months (95% CI: 18.5-23.1 months). The median PFS (mPFS) was 5.3 months (95% CI: 4.37-4.07 months) and the median OS (mOS) was 11.2 months (95% CI: 9.5-12.9 months). The mPFS of patients with LAPC was 7.4 months (95% CI: 6.6-11.2 months), and their mOS was 15.5 months (95% CI: 12.6-NA months). The mPFS of patients with mPC was 3.9 months (95% CI: 3.4-5.1 months), and their mOS was 9.3 months (95% CI: 8.0-10.8 months). Multivariate Cox regression analysis showed that clinical stage ( HR=1.47, 95% CI: 1.06-2.04), primary tumor site ( HR=0.64, 95% CI: 0.48-0.86), Eastern Cooperative Oncology Group Performance Status (ECOG PS) score ( HR=2.66, 95% CI: 1.53-4.65), and whether to combine radiotherapy ( HR=0.65, 95% CI: 0.42-1.00) were independent influencing factors for the PFS of these patients. The primary tumor site ( HR=0.68, 95% CI: 0.48-0.95), ECOG score ( HR=5.82, 95% CI: 3.14-10.82), and whether to combine radiotherapy ( HR=0.58, 95% CI: 0.35-0.96) were independent influencing factors of the OS of these patients. The most frequent gene mutations in these advanced stage pancreatic patients were KRAS (89.66%), TP53 (77.01%), CDKN2A (32.18%), and SMAD4 (21.84%) by NGS of tumor tissues from 87 pancreatic cancer patients with sufficient specimens. Further analysis revealed that mutations in CDKN2B, PTEN, FGF6, and RBBP8 genes were significantly associated with an increased risk of death ( P＜0.05). Conclusion:Albumin-bound paclitaxel as first-line treatment demonstrated feasible anti-tumor efficacy and manageable safety for patients with advanced pancreatic cancer in China.

Objective:To observe and evaluate the clinical efficacy and safety of albumin-bound paclitaxel as first-line treatment for patients with advanced pancreatic cancer in China, and to explore the prognosis-related molecules in pancreatic cancer based on next-generation sequencing (NGS) of tumor tissues.Methods:From December 2018 to December 2020, patients with locally advanced or metastatic pancreatic cancer were recruited to accept albumin-bound paclitaxel as first-line treatment in the oncology departments of 24 hospitals in East China. The primary endpoints were overall survival (OS) and treatment related adverse events, and the secondary endpoint was progression-free survival (PFS). Adverse effects were graded using Common Terminology Criteria for Adverse Events 5.0 (CTCAE 5.0). NGS sequencing on the primary or metastatic tissue samples of pancreatic cancer obtained through surgical resection or biopsy was performed.Results:This study recruited 229 patients, including 70 patients with locally advanced pancreatic cancer (LAPC) and 159 patients with metastatic pancreatic cancer (mPC). The disease control rate was 79.9% and the objective response rate is 36.3%.The common adverse effects during treatment were anaemia (159 cases), leucopenia (170 cases), neutropenia (169 cases), increased aminotransferases (110 cases), and thrombocytopenia (95 cases), and the incidence of grade 3-4 neutropenia is 12.2% (28/229). The median follow-up time was 21.2 months (95% CI: 18.5-23.1 months). The median PFS (mPFS) was 5.3 months (95% CI: 4.37-4.07 months) and the median OS (mOS) was 11.2 months (95% CI: 9.5-12.9 months). The mPFS of patients with LAPC was 7.4 months (95% CI: 6.6-11.2 months), and their mOS was 15.5 months (95% CI: 12.6-NA months). The mPFS of patients with mPC was 3.9 months (95% CI: 3.4-5.1 months), and their mOS was 9.3 months (95% CI: 8.0-10.8 months). Multivariate Cox regression analysis showed that clinical stage ( HR=1.47, 95% CI: 1.06-2.04), primary tumor site ( HR=0.64, 95% CI: 0.48-0.86), Eastern Cooperative Oncology Group Performance Status (ECOG PS) score ( HR=2.66, 95% CI: 1.53-4.65), and whether to combine radiotherapy ( HR=0.65, 95% CI: 0.42-1.00) were independent influencing factors for the PFS of these patients. The primary tumor site ( HR=0.68, 95% CI: 0.48-0.95), ECOG score ( HR=5.82, 95% CI: 3.14-10.82), and whether to combine radiotherapy ( HR=0.58, 95% CI: 0.35-0.96) were independent influencing factors of the OS of these patients. The most frequent gene mutations in these advanced stage pancreatic patients were KRAS (89.66%), TP53 (77.01%), CDKN2A (32.18%), and SMAD4 (21.84%) by NGS of tumor tissues from 87 pancreatic cancer patients with sufficient specimens. Further analysis revealed that mutations in CDKN2B, PTEN, FGF6, and RBBP8 genes were significantly associated with an increased risk of death ( P＜0.05). Conclusion:Albumin-bound paclitaxel as first-line treatment demonstrated feasible anti-tumor efficacy and manageable safety for patients with advanced pancreatic cancer in China.

Objective:To analyze the patterns of dynamic functional connectivity(dFC) at rest in different obsessive-compulsive disorder(OCD) subtypes based on gray matter volume, and explore the relationship between abnormal gray matter volume and dFC patterns and clinical symptoms in different OCD subtypes.Methods:Clinical data were prospectively collected from a total of 48 patients with OCD from inpatient and outpatient departments of the Fourth Affiliated Hospital of Qiqihar Medical College(20 cases) and Qiqihar Mental Health Center(28 cases) from September 2013 to March 2020. There were 33 males and 15 females, aged 18 to 42(27.1±6.7) years. During the same period, 39 age-matched healthy controls were also recruited, including 31 males and 8 females, aged 18 to 43(28.5±8.6) years. Structural and resting-state functional magnetic resonance imaging scans were performed on 48 OCD patients(OCD group) who met the ICD-10 diagnostic criteria and 39 healthy controls(control group). Using voxel-based morphometry(VBM) and semi-supervised machine learning methods, the patient group was characterized by gray matter volume to perform subtype analysis, and brain regions with abnormal gray matter volume were selected as regions of interest for whole-brain voxel-wise dFC analysis. Correlations between abnormal gray matter volume and dFC and clinical symptoms in OCD patients were analyzed.Results:Based on gray matter volume, OCD patients were computed into two subtypes, of which subtype 1 increased gray matter volume in the right central posterior gyrus(809 voxels; t=4.31; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed), and subtype 2 showed reduced gray matter volume in the left superior temporal gyrus(1 118 voxels; t=-4.37; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed). In subtype 1, the dFC between the right central posterior gyrus and left medial superior frontal gyrus was significantly reduced(187 voxels; t=-4.42; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed); in subtype 2, dFC between the left superior temporal gyrus and left hippocampus, and left central opercular cortex was significantly reduced(272 voxels、99 voxels; t=-4.69, -5.01; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed). In subtype 1, dFC between the right central posterior gyrus and left medial superior frontal gyrus was negatively correlated with illness duration( r=-0.579; P=0.002, uncorrected). In subtype 2, dFC between the left superior temporal gyrus and left hippocampus was positively correlated with illness duration( r=0.578; P=0.003, uncorrected). Conclusions:In the resting state, patients with different subtypes of OCD may have different patterns of dFC abnormalities based on gray matter volume.

Objective:To analyze the patterns of dynamic functional connectivity(dFC) at rest in different obsessive-compulsive disorder(OCD) subtypes based on gray matter volume, and explore the relationship between abnormal gray matter volume and dFC patterns and clinical symptoms in different OCD subtypes.Methods:Clinical data were prospectively collected from a total of 48 patients with OCD from inpatient and outpatient departments of the Fourth Affiliated Hospital of Qiqihar Medical College(20 cases) and Qiqihar Mental Health Center(28 cases) from September 2013 to March 2020. There were 33 males and 15 females, aged 18 to 42(27.1±6.7) years. During the same period, 39 age-matched healthy controls were also recruited, including 31 males and 8 females, aged 18 to 43(28.5±8.6) years. Structural and resting-state functional magnetic resonance imaging scans were performed on 48 OCD patients(OCD group) who met the ICD-10 diagnostic criteria and 39 healthy controls(control group). Using voxel-based morphometry(VBM) and semi-supervised machine learning methods, the patient group was characterized by gray matter volume to perform subtype analysis, and brain regions with abnormal gray matter volume were selected as regions of interest for whole-brain voxel-wise dFC analysis. Correlations between abnormal gray matter volume and dFC and clinical symptoms in OCD patients were analyzed.Results:Based on gray matter volume, OCD patients were computed into two subtypes, of which subtype 1 increased gray matter volume in the right central posterior gyrus(809 voxels; t=4.31; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed), and subtype 2 showed reduced gray matter volume in the left superior temporal gyrus(1 118 voxels; t=-4.37; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed). In subtype 1, the dFC between the right central posterior gyrus and left medial superior frontal gyrus was significantly reduced(187 voxels; t=-4.42; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed); in subtype 2, dFC between the left superior temporal gyrus and left hippocampus, and left central opercular cortex was significantly reduced(272 voxels、99 voxels; t=-4.69, -5.01; GRF corrected voxel P<0.001, cluster P<0.05 two-tailed). In subtype 1, dFC between the right central posterior gyrus and left medial superior frontal gyrus was negatively correlated with illness duration( r=-0.579; P=0.002, uncorrected). In subtype 2, dFC between the left superior temporal gyrus and left hippocampus was positively correlated with illness duration( r=0.578; P=0.003, uncorrected). Conclusions:In the resting state, patients with different subtypes of OCD may have different patterns of dFC abnormalities based on gray matter volume.

BACKGROUND AND OBJECTIVES: To reveal the detail mechanism of miR-484 on myocardial ischemia-reperfusion (MI/R) injury.METHODS: Rats model of MI/R injury was established based on control (Con; sham operate) group, ischemia-reperfusion (I/R) group, miR-484 treatment (miR) group, and I/R-negative control (IR-C) group, followed by pathological and interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-1β expression evaluation. Then the myocardial apoptosis, as well as the expression of miR-484, caspase-3, and caspase-9 in myocardium were examined. Finally, the regulatory relation between miR-484 and SMAD family member 7 (SMAD7) was predicated, followed by verification analysis.RESULTS: Compared with Con group, the expression of miR-484 in I/R and IR-C group was decreased. Compared with I/R and IR-C group, the expression of miR-484 was increased in miR group. Compared with Con group, the expression levels of IL-6, TNF-α, and IL-1β in cardiac myocytes of I/R group and IR-C group were increased. Compared with Con group, the apoptotic index, membrane potential of I/R, and the expression of caspase-3/9 were increased in IR-C group. Compared with the I/R and IR-C groups, the apoptotic index of myocardial cells in the ischemic region was decreased, the membrane potential was increased, and the expression of caspase-3/9 was decreased significantly in the miR group. SMAD7 was the target gene of miR-484.CONCLUSIONS: MiR-484 protected myocardial cells from I/R injury by suppressing caspase-3 and caspase-9 expression during cardiomyocyte apoptosis. MiR-484 reduced the expression of IL-6, TNF-α, and IL-1β in MI/R. MiR-484 might alleviate the decreasing of mitochondrial membrane potential in MI/R cells.
Animals ; Apoptosis ; Caspase 3 ; Caspase 9 ; Humans ; Interleukin-6 ; Interleukins ; Membrane Potential, Mitochondrial ; Membrane Potentials ; Myocardium ; Myocytes, Cardiac ; Rats ; Reperfusion Injury ; Tumor Necrosis Factor-alpha

BACKGROUND AND OBJECTIVES: To reveal the detail mechanism of miR-484 on myocardial ischemia-reperfusion (MI/R) injury. METHODS: Rats model of MI/R injury was established based on control (Con; sham operate) group, ischemia-reperfusion (I/R) group, miR-484 treatment (miR) group, and I/R-negative control (IR-C) group, followed by pathological and interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-1β expression evaluation. Then the myocardial apoptosis, as well as the expression of miR-484, caspase-3, and caspase-9 in myocardium were examined. Finally, the regulatory relation between miR-484 and SMAD family member 7 (SMAD7) was predicated, followed by verification analysis. RESULTS: Compared with Con group, the expression of miR-484 in I/R and IR-C group was decreased. Compared with I/R and IR-C group, the expression of miR-484 was increased in miR group. Compared with Con group, the expression levels of IL-6, TNF-α, and IL-1β in cardiac myocytes of I/R group and IR-C group were increased. Compared with Con group, the apoptotic index, membrane potential of I/R, and the expression of caspase-3/9 were increased in IR-C group. Compared with the I/R and IR-C groups, the apoptotic index of myocardial cells in the ischemic region was decreased, the membrane potential was increased, and the expression of caspase-3/9 was decreased significantly in the miR group. SMAD7 was the target gene of miR-484. CONCLUSIONS MiR-484 protected myocardial cells from I/R injury by suppressing caspase-3 and caspase-9 expression during cardiomyocyte apoptosis. MiR-484 reduced the expression of IL-6, TNF-α, and IL-1β in MI/R. MiR-484 might alleviate the decreasing of mitochondrial membrane potential in MI/R cells.

Objective To compare the characteristics of the tremor of multiple system atrophy Parkinsonism type (MSA-P) with Parkinson's disease (PD), and improvement after acute levodopa challenge test. Methods From Match to September 2017, 70 patients with PD and 23 patients with probable MSA-P were included. All the patients were required of rest or postural tremor in at least one extremity or head, and accepted acute levodopa challenge test and analysis for dominant tremor frequency, amplitude and rhythm under resting state, posturing and holding 1000 g state, respectively.Results The score of Unified Parkinson Diease Rating Scale Part III was higher in MSA-P patients than in PD patients (t=-2.098, P<0.05), with less improvement after acute levodopa challenge test (Z=-9.446, P<0.01), while the tremor score and improvement were not significantly different between two groups (P>0.05). There were more frequence with non-alternating or synchronic tremor rhythm (χ2=8.756, P<0.01) and small irregular tremor in rest tremor (χ2=4.788, P<0.05) in MSA-P patients than in PD patients, as well as the high frequency tremor (>6 Hz) in postural tremor (χ2=11.312, P<0.01). The frequency of rest tremor was higher in MSA-P patients than in PD patients (t=-2.119, P<0.05), as well as the frequency of postural tremor with 1000 g (t=-2.274, P<0.05). Both PD and MSA-P patients showed, the lower frequency the postural tremor was, the higher the tremor scores were. There were 25% PD patients with head tremor, while none in MSA-P patients. Tremor score improved more than 30% after acute levodopa challenge test in 22.7% MSA-P patients, but none improved in UPDRS score. The frequence of tremor score improvement was more in female MSA-P patients than in males (P<0.05).Conclusion The features of the tremor are similar in PD and MSA-P, with some differences that MSA-P tend to higher frequency in rest or postural tremor, more non-alternating or synchronic tremor rhythm in rest tremor, and fewer has tremor besides limbs. Some MSA-P patients improve after acute levodopa challenge test, and women may improve more than men.