Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.

Fusarium head blight (FHB), caused by Fusarium graminearum, not only leads to severe yield losses but also poses a threat to food safety due to the mycotoxins produced by the pathogen. Since this disease is preventable but not curable, the current control mainly relies on chemical fungicides, the long-term use of which may lead to pathogen resistance and environmental pollution. To develop green control methods, we screened 13 biocontrol strains from the rhizosphere soil of wheat, among which strain No. 12 (identified as Pythium aphanidermatum) showed significant antifungal effects. In the plate confrontation test, this strain reduced the colony diameter of the pathogen by 69.2% (1.47 mm vs. 4.78 mm in the control group), with an inhibition rate of 77% (P < 0.01). Microscopic observation revealed obvious deformations in the pathogen hyphae, suggesting a lysing effect. The coleoptile experiment further confirmed that the pre-treatment with this strain reduced the incidence rate to 0. These findings provide new candidate strains for the biocontrol of FHB and offer a scientific basis for reducing the use of chemical fungicides and promoting sustainable agricultural development.
Triticum/growth & development* ; Fusarium/growth & development* ; Plant Diseases/prevention & control* ; Soil Microbiology ; Pest Control, Biological/methods* ; Pythium/physiology* ; Biological Control Agents ; Rhizosphere ; Fungicides, Industrial

Objective:To explore the high-risk factors affecting the severity of neonatal necrotizing enterocolitis (NEC).Methods:This study involved 153 NEC patients admitted to the Neonatology Department of the Children's Hospital of Soochow University from January 1, 2017, to December 30, 2023. Based on the severity of NEC determined by Bell's criteria, these patients were divided into two groups: mild group (Bell stage Ⅱ, n=70) and severe group (Bell stage Ⅲ, n=83). Clinical data including general conditions, clinical treatment and disease status before the onset of NEC, laboratory test results, and perinatal conditions of the mothers were retrospectively collected. Univariate analysis (rank-sum test and Chi-square test) and multivariate analysis (logistic regression analysis) were used to explore the risk factors affecting the severity of NEC. Results:The proportion of infants with gestational age<37 weeks or birth weight<1 500 g, the rate of antibiotic usage, sepsis or shock were higher in the severe group than in the mild group [91.6% (76/83) vs. 75.7% (53/70); 55.4% (46/83) vs. 34.3% (24/70); 85.5% (71/83) vs. 71.4% (50/70); 55.4% (46/83) vs. 17.1% (12/70); 30.1% (25/83) vs. 8.6% (6/70); with χ 2 values of 7.22, 6.84, 4.57, 23.64, and 10.91, respectively, all P<0.05]. Furthermore, the severe group had a late initiation of breastfeeding and longer durations of peripherally inserted central catheter (PICC) placement and parenteral nutrition [2.00 d (1.00-2.00 d) vs. 1.00 d (1.00-2.00 d); 0.00 d (0.00-18.00 d) vs. 0.00 d (0.00-7.50 d); 14.00 d (5.00-21.00 d) vs. 10.50 d (0.00-18.25 d), with Z values of -2.90, -1.98, and -2.09, respectively, all P<0.05]. (2) Within 48 h before the onset, the severe group had higher proportions of infants with decreased white blood cell count, decreased platelet count, electrolyte imbalance, and metabolic acidosis than the mild group [53.0% (44/83) vs. 14.3% (10/70); 49.4% (41/83) vs. 10.0% (7/70); 38.6% (32/83) vs. 14.3% (10/70); 37.3% (31/83) vs. 14.3% (10/70), with χ2 values of 24.94, 27.38, 11.23, and 10.30, respectively, all P<0.05]. Besides, the levels of procalcitonin and C-reactive protein were higher in the severe group than in the mild group [2.31 ng/ml (0.26-11.71 ng/ml) vs. 0.22 ng/ml (0.00-2.19 ng/ml); 58.50 mg/L (14.34-125.25 mg/L) vs. 8.20 mg/L (0.23-34.56 mg/L), with Z values of -3.88 and -5.02, respectively, both P<0.05]. (3) Multivariate logistic regression analysis showed that prolonged duration of PICC placement, decreased platelet count, electrolyte imbalance, metabolic acidosis, and concurrent sepsis were independent risk factors affecting the severity of NEC [ OR (95% CI) values were 1.104 (1.020-1.196), 5.364 (1.667-17.253), 4.047 (1.171-13.986), 4.333 (1.290-14.556), and 3.290 (1.005-10.774), respectively, with all P<0.05]. Conclusions:Prolonged duration of PICC placement, concurrent sepsis, decreased platelet count, electrolyte imbalance, and metabolic acidosis in NEC patients are more likely to lead to severe cases. In clinical practice, attention should be paid to relevant indicators, and abnormal changes should be identified and intervened in a timely manner to reduce the occurrence of severe NEC.

OBJECTIVE To explore and establish the working mechanism for prevention and control of hospital-as-sociated infections in regional oral medical institutions so as to standardize the prevention and control of the hospi-tal-associated infections in the regional oral medical institutions.METHODS Taking an administrative division of Chongqing as example,the matrix evaluation was carried out based on the quality control mode for management of hospital-associated infections in oral medical institutions' action planning,training guidance,quality control super-vision,summary review' organically in combination with'quality control plus law enforcement',a color-co-ded management of the oral medical institutions in the region was implemented,and the effectiveness of improved work in infection control was examined.RESULTS From the perspective of the grade of medical institution,the qualified rates of hospital infection management system construction,architectural layout and process,cleaning,disinfection and sterilization of oral instruments,environmental cleaning and disinfection,isolation,safe injection,use of occupational protection supplies and disposal of medical waste of the primary and unrated medical institu-tions were respectively 26.51％,49.40％,24.10％,37.35％,31.33％,46.99％,67.47％and 51.81％before the improvement and were respectively increased to 67.47％,63.86％,45.78％,66.27％,63.86％,73.49％,84.34％and 66.27％after the improvement,and there were significant differences(P＜0.05).From the perspec-tive of the property of the medical institution,the qualified rates of the above items of the private medical institu-tions were respectively 24.66％,47.95％,21.92％,34.25％,31.51％,45.21％,69.86％and 50.68％before the improvement and were respectively increased to 65.75％,61.64％,42.47％,64.38％,63.01％,71.23％,84.93％and 63.01％after the improvement,and there were significant differences(P＜0.05).CONCLUSION The working mechanism on prevention and control of hospital-associated infections in regional oral medical institu-tions that is established based on'quality control plus law enforcement'with the introduction of social credit can effectively raise the qualified rates of the infection prevention and control measures,which achieves more remarka-ble improvement effectiveness in grass-roots oral medical institutions such as the private,primary and unrat-ed medical institutions.

Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures.Nonetheless,they also form a major source of prediction error in structure-activity relationship(SAR)models.To date,several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs.In this paper,we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet,tailored for ACs.Through extensive comparison with multiple baseline models on 30 benchmark datasets,the results showed that ACtriplet was significantly better than those deep learning(DL)models without pre-training.In addition,we explored the effect of pre-training on data representation.Finally,the case study demonstrated that our model's interpretability module could explain the prediction results reasonably.In the dilemma that the amount of data could not be increased rapidly,this innovative framework would better make use of the existing data,which would propel the potential of DL in the early stage of drug discovery and optimization.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective:To apply the Timed Up and Go Test(TUGT)to investigate the correlation between motor function, emotional state, cognitive function, and sleep quality among elderly individuals in the Chinese community.Methods:A cross-sectional study was conducted, involving 739 subjects aged 60 to 90 years, who were randomly recruited from December 2021 to August 2023 across Beijing, Tianjin, Zhejiang, Guangdong, and Hainan Provinces in China.Basic demographic information was collected, and the TUGT was utilized to assess motor function.Based on the TUGT time(t), the subjects were divided into three groups: normal motor function group, mild motor abnormality group, and significant motor abnormality group.Cognitive function was evaluated using the Chinese Revised Mini-Mental State Examination(MMSE), while the Patient Health Questionnaire Depression Scale(PHQ-9)was employed to measure the degree of depression.Additionally, the Epworth Sleepiness Scale(ESS)was used to assess excessive daytime sleepiness.The correlation between subjects' motor function and their cognitive abilities, mood, and sleep was subsequently analyzed.Results:Systolic blood pressure, heart rate, PHQ-9, MMSE, and ESS scores were identified as significant factors influencing TUGT time.Specifically, TUGT time was positively correlated with PHQ-9 and ESS scores, while exhibiting negative correlations with systolic blood pressure, heart rate, and MMSE scores.Additionally, TUGT time was negatively correlated with the MMSE subcomponents of orientation, immediate memory, and verbal ability.All observed differences were statistically significant(all P<0.05).Logistic regression analysis indicated that an increase in the PHQ-9 score was associated with an odds ratio( OR)of 1.099(95% CI: 1.045-1.155, P<0.001)(mild motor abnormality group)and 1.150(95% CI: 1.066-1.242, P<0.001)(Significant motor abnormality group).Additionally, a reduction in the MMSE score was observed, with an OR of 0.939(95% CI: 0.886-0.995, P<0.001)(mild motor abnormality group)and 0.793(95% CI: 0.729-0.862, P<0.001)(Significant motor abnormality group).Furthermore, an increase in the ESS score was noted, with ORs of 1.139(95% CI: 1.094-1.186, P<0.001)(mild motor abnormality group)and 1.203(95% CI: 1.132-1.279, P<0.001)(Significant motor abnormality group).These findings suggest that these variables are independently related to decreased motor function. Conclusions:Depression, cognitive impairment, and excessive daytime sleepiness are independent risk factors for motor dysfunction among elderly individuals in community settings.The Timed Up and Go Test TUGT can be utilized for the early screening of motor function decline in this population.

Objective:To evaluate the efficacy and safety of obinutuzumab combined with glucocorticoid-based therapy in patients with relapsed immune thrombotic thrombocytopenic purpura (iTTP).Methods:This study analyzed the efficacy and adverse reactions of four patients with relapsed iTTP who were treated with a combination of obinutuzumab and glucocorticoids to assess the effectiveness and safety of the treatment.Results:All four patients had a history of multiple relapses and had previously undergone treatment with rituximab and bortezomib. Three patients exhibited additional autoantibodies. Following the combined therapy, all patients achieved clinical remission, with ADAMTS13 activity returning to normal levels and inhibitors testing negative. During a median follow-up period of 11 months (range: 3–17 months), all patients maintained sustained remission. No severe adverse events were reported during treatment or follow-up.Conclusion:The combination of obinutuzumab and glucocorticoid-based therapy is effective and safe for treating relapsed iTTP.

Sepsis is defined as a severe organ dysfunction caused by an imbalanced immune response to infection, making it a common life-threatening critical condition in clinical practice. With the rapid advancement of precision and personalized medicine, along with a deeper understanding of the pathophysiology of sepsis, immune dysfunction has increasingly been recognized as a major factor contributing to poor outcomes in sepsis patients. This article discusses the mechanisms of immune dysfunction, methods of immune monitoring, and patient stratification in sepsis, highlighting the importance of achieving immune balance in sepsis treatment. It aims to explore new strategies for immunotherapy in sepsis.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.