Structural optimization of lead compounds is a crucial step in drug discovery.One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties.One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules,thereby accelerating the molecular optimization process.Deep molecular diffusion generative models simulate a gradual process that creates novel,chemically feasible molecules from noise.However,the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules,leading to challenges in modifying the scaffold-based molecular structures,and creates limitations in the stability and diversity of the generated molecules.To address these challenges,we propose a deep molecular diffusion generative model,the three-dimensional(3D)equivariant diffusion-driven molecular generation(3D-EDiffMG)model.The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder(dual-SWLEE)is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions.Addi-tionally,a gate multilayer perceptron(gMLP)block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies.The experimental results show that 3D-EDiffMG effectively generates unique,novel,stable,and diverse drug-like molecules,highlighting its potential for lead optimization and accelerating drug discovery.

Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.

Objective This research aims to establish a scientific research performance evaluation indicator system for public hospital staff,providing evaluation standards and assessment criteria for their research performances.Methods An indica-tor pool was developed through literature review.The indicators were determined through two rounds of Delphi expert consultations.Analytic Hierarchy Process(AHP)was used to calculate their weights and thus establish an indicator system.Results The indica-tor system consists of 8 primary indicators-research projects(0.193 3),talent cultivation(0.264 3),patents(0.046 2),publica-tions(0.118 5),monographs(0.068 1),awards(0.147 2),standards(0.094 3),and research errors(0.068 1)-encompassing 29 secondary indicators.The response rate of the second-round expert consultation was 0.85;the authority coefficient was 0.94;the importance rating of indicators was 4.44,and Kendall's coefficient was 0.260(P＜0.05).The consistency index(CI)and consistency ratio(CR)values were＜0.1,indicating good results.Conclusion The indicator system demonstrates scientifically good validity and feasibility.Thus it can be used to evaluate the research performances of public hospital staff,providing decision support for resource allocation and the optimization of incentive mechanisms.

Purpose To evaluate the predictive performance of mean apparent propagator-magnetic resonance imaging(MAP-MRI)combined with habitat analysis for determining O6-methylguanine-DNA methyltransferase(MGMT)promoter methylation status in glioma.Materials and Methods This retrospective study analyzed MRI and clinical data from 55 patients with surgically confirmed glioma at Fujian Medical University Union Hospital from January 2019 to December 2023.All patients underwent structural and diffusion-weighted imaging.Three-dimensional volumes of interest were delineated in the tumor solid region using ImageJ software.The nn-FAE tool was used to segment the tumor solid region into two habitat subregions based on mean diffusivity(MD)maps:high-MD and low-MD habitats.Average diffusion parameter values were extracted from the entire tumor solid region and each habitat subregion.Differences in parameters between methylated and unmethylated groups were compared,and the area under the curve was calculated.Results Among 55 patients,significant differences were observed in all MAP-MRI parameters and MD in the tumor solid region and low-MD habitat,as well as all parameters in the high-MD habitat between methylated and unmethylated groups(t/Z=-3.780-3.153,all P<0.05).The return-to-origin probability(RTOP)in the low-MD habitat demonstrated the highest diagnostic performance,with the area under the curve improving from 0.771 before habitat analysis to 0.827 after habitat analysis.In the high-grade subgroup,significant differences were observed in return-to-axis probability(RTAP)and RTOP in the tumor solid region;RTOP,non-Gaussianity,non-Gaussianity axial,and RTAP in the low-MD habitat;and non-Gaussianity in the high-MD habitat(t/Z=-2.820--1.976,all P<0.05).RTOP in the low-MD habitat again showed optimal diagnostic efficacy(the area under the curve 0.725 before habitat analysis,0.798 after).Multivariate analysis identified RTAP and RTOP in the tumor solid region and low-MD habitat as independent predictors of MGMT methylation.Conclusion MAP-MRI diffusion parameters demonstrate the ability to predict MGMT promoter methylation status in glioma,with superior performance compared with diffusion tensor imaging.Habitat imaging further enhances the predictive efficacy of MAP-MRI parameters for MGMT promoter methylation.

Purpose To evaluate the predictive performance of mean apparent propagator-magnetic resonance imaging(MAP-MRI)combined with habitat analysis for determining O6-methylguanine-DNA methyltransferase(MGMT)promoter methylation status in glioma.Materials and Methods This retrospective study analyzed MRI and clinical data from 55 patients with surgically confirmed glioma at Fujian Medical University Union Hospital from January 2019 to December 2023.All patients underwent structural and diffusion-weighted imaging.Three-dimensional volumes of interest were delineated in the tumor solid region using ImageJ software.The nn-FAE tool was used to segment the tumor solid region into two habitat subregions based on mean diffusivity(MD)maps:high-MD and low-MD habitats.Average diffusion parameter values were extracted from the entire tumor solid region and each habitat subregion.Differences in parameters between methylated and unmethylated groups were compared,and the area under the curve was calculated.Results Among 55 patients,significant differences were observed in all MAP-MRI parameters and MD in the tumor solid region and low-MD habitat,as well as all parameters in the high-MD habitat between methylated and unmethylated groups(t/Z=-3.780-3.153,all P<0.05).The return-to-origin probability(RTOP)in the low-MD habitat demonstrated the highest diagnostic performance,with the area under the curve improving from 0.771 before habitat analysis to 0.827 after habitat analysis.In the high-grade subgroup,significant differences were observed in return-to-axis probability(RTAP)and RTOP in the tumor solid region;RTOP,non-Gaussianity,non-Gaussianity axial,and RTAP in the low-MD habitat;and non-Gaussianity in the high-MD habitat(t/Z=-2.820--1.976,all P<0.05).RTOP in the low-MD habitat again showed optimal diagnostic efficacy(the area under the curve 0.725 before habitat analysis,0.798 after).Multivariate analysis identified RTAP and RTOP in the tumor solid region and low-MD habitat as independent predictors of MGMT methylation.Conclusion MAP-MRI diffusion parameters demonstrate the ability to predict MGMT promoter methylation status in glioma,with superior performance compared with diffusion tensor imaging.Habitat imaging further enhances the predictive efficacy of MAP-MRI parameters for MGMT promoter methylation.

Objective This research aims to establish a scientific research performance evaluation indicator system for public hospital staff,providing evaluation standards and assessment criteria for their research performances.Methods An indica-tor pool was developed through literature review.The indicators were determined through two rounds of Delphi expert consultations.Analytic Hierarchy Process(AHP)was used to calculate their weights and thus establish an indicator system.Results The indica-tor system consists of 8 primary indicators-research projects(0.193 3),talent cultivation(0.264 3),patents(0.046 2),publica-tions(0.118 5),monographs(0.068 1),awards(0.147 2),standards(0.094 3),and research errors(0.068 1)-encompassing 29 secondary indicators.The response rate of the second-round expert consultation was 0.85;the authority coefficient was 0.94;the importance rating of indicators was 4.44,and Kendall's coefficient was 0.260(P＜0.05).The consistency index(CI)and consistency ratio(CR)values were＜0.1,indicating good results.Conclusion The indicator system demonstrates scientifically good validity and feasibility.Thus it can be used to evaluate the research performances of public hospital staff,providing decision support for resource allocation and the optimization of incentive mechanisms.

Objective: To evaluate the preventive effect of implementing the free influenza vaccination policy on school absence among primary and secondary school students, so as to provide a reference for formulating and adjusting vaccination strategies. Methods: Among primary and secondary school students aged 6 to 18 in Longgang District, Shenzhen, they were divided into a vaccinated group (265 996 students) and an unvaccinated group (122 513 students) according to their influenza vaccination history during November 2023. Propensity score matching was used to conduct a 1∶1 match between the two groups to balance covariates. The number of absences per month was set as the dependent variable to construct a difference in differences model, and Poisson regression was employed to analyze the overall and multi time point effects. Results: Vaccination against influenza was associated with low rate of absenteeism among primary and secondary school students, with an overall preventive effect of 26.52% (95% CI = 23.47% -29.45%). The preventive effects in November (the month of vaccination) and December 2023, January and March 2024 were 42.12%, 40.12%, 30.33% and 20.91%, respectively. The preventive effect of the influenza vaccine on absenteeism among primary school students (26.39%) was not significantly different from that among secondary school students ( 27.97% ) ( P >0.05). The regression coefficient for class vaccination rates ranged from 0.998 to 0.999 ( P <0.01), indicating that for every 10% increase in influenza vaccination rates, absenteeism could be reduced by 1.5% to 2.2%. Conclusion Implementing free influenza vaccination for primary and secondary school students might help to reduce the risk of absenteeism, yielding significant socioeconomic benefits.

Recent studies on male infertility reveal a growing worry: more infertile men are dealing with inflammation in the testis. Analyzing testicular biopsies from infertile men highlights a significant presence of inflammation. This connection, supported by clinical and pathological evidence, emphasizes that testicular inflammation hampers sperm production, leading to lasting declines in sperm count and quality. However, the exact reasons behind male infertility due to orchitis, a type of testicular inflammation, are still uncertain. Understanding these fundamental aspects of molecular signals and cellular mechanisms in testicular inflammation is crucial. Our review delves into recent literature with a dual objective: elucidating potential mechanisms involving immune cells, non-immune cells, and cytokines that link orchitis to male infertility, while also paving the way for precise interventions and solutions to address the challenges of male infertility.

Recent studies on male infertility reveal a growing worry: more infertile men are dealing with inflammation in the testis. Analyzing testicular biopsies from infertile men highlights a significant presence of inflammation. This connection, supported by clinical and pathological evidence, emphasizes that testicular inflammation hampers sperm production, leading to lasting declines in sperm count and quality. However, the exact reasons behind male infertility due to orchitis, a type of testicular inflammation, are still uncertain. Understanding these fundamental aspects of molecular signals and cellular mechanisms in testicular inflammation is crucial. Our review delves into recent literature with a dual objective: elucidating potential mechanisms involving immune cells, non-immune cells, and cytokines that link orchitis to male infertility, while also paving the way for precise interventions and solutions to address the challenges of male infertility.

Recent studies on male infertility reveal a growing worry: more infertile men are dealing with inflammation in the testis. Analyzing testicular biopsies from infertile men highlights a significant presence of inflammation. This connection, supported by clinical and pathological evidence, emphasizes that testicular inflammation hampers sperm production, leading to lasting declines in sperm count and quality. However, the exact reasons behind male infertility due to orchitis, a type of testicular inflammation, are still uncertain. Understanding these fundamental aspects of molecular signals and cellular mechanisms in testicular inflammation is crucial. Our review delves into recent literature with a dual objective: elucidating potential mechanisms involving immune cells, non-immune cells, and cytokines that link orchitis to male infertility, while also paving the way for precise interventions and solutions to address the challenges of male infertility.