Coronavirus,a major pathogen infecting humans,mammals,and birds,causes primarily respiratory diseases af-ter infecting humans.Seven coronaviruses have been found to infect humans and subsequently cause varying degrees of respira-tory symptoms.From 2019 to 2023,millions of people died from severe acute respiratory syndrome coronavirus 2 infections,and the virus continues to mutate.Therefore,drug screening research must urgently be expanded to develop more effective,broad-spectrum anti-coronavirus drugs.In-depth research has indicated that the coronavirus 3C-like protease and RNA polymer-ase are necessary for viral reproduction and are highly conserved among strains,and consequently are anti-virus targets of great interest.This article summarizes the enzymes encoded by coronaviruses and drug screening methods,to provide a reference for coronavirus prevention and control.

Coronavirus,a major pathogen infecting humans,mammals,and birds,causes primarily respiratory diseases af-ter infecting humans.Seven coronaviruses have been found to infect humans and subsequently cause varying degrees of respira-tory symptoms.From 2019 to 2023,millions of people died from severe acute respiratory syndrome coronavirus 2 infections,and the virus continues to mutate.Therefore,drug screening research must urgently be expanded to develop more effective,broad-spectrum anti-coronavirus drugs.In-depth research has indicated that the coronavirus 3C-like protease and RNA polymer-ase are necessary for viral reproduction and are highly conserved among strains,and consequently are anti-virus targets of great interest.This article summarizes the enzymes encoded by coronaviruses and drug screening methods,to provide a reference for coronavirus prevention and control.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

OBJECTIVE: To assess the efficacy of Qingda Granule (QDG) in ameliorating hypertension-induced cardiac damage and investigate the underlying mechanisms involved. METHODS: Twenty spontaneously hypertensive rats (SHRs) were used to develope a hypertension-induced cardiac damage model. Another 10 Wistar Kyoto (WKY) rats were used as normotension group. Rats were administrated intragastrically QDG [0.9 g/(kg•d)] or an equivalent volume of pure water for 8 weeks. Blood pressure, histopathological changes, cardiac function, levels of oxidative stress and inflammatory response markers were measured. Furthermore, to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertension-induced cardiac injury, a network pharmacology study was conducted. Predicted results were validated by Western blot, radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction, respectively. RESULTS: The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs (P<0.01). Histological examinations, including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac damage. Furthermore, echocardiography demonstrated that QDG improved hypertension-associated cardiac dysfunction. Enzyme-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum (P<0.01). CONCLUSIONS Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertension-induced cardiac damage by regulating the angiotensin converting enzyme (ACE)/angiotensin II (Ang II)/Ang II receptor type 1 axis and ACE/Ang II/Ang II receptor type 2 axis.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/pathology* ; Renin-Angiotensin System/drug effects* ; Rats, Inbred SHR ; Oxidative Stress/drug effects* ; Male ; Rats, Inbred WKY ; Blood Pressure/drug effects* ; Myocardium/pathology* ; Rats ; Inflammation/pathology*

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective:To explore the diagnostic value of serum human mammaglobin (hMAM),human epidermal growth factor receptor 2 (HER2) and ubiquitin conjugating enzyme 2C (UBE2C) for axillary lymph node metastasis of breast cancer. Methods:Ninety patients with breast cancer admitted to Army 81st Group Hospital from March 2022 to March 2024 were col-lected and separated into metastatic group (n=40) and non-metastatic group (n=50) according to the pathological examination results. General clinical data were collected and analyzed. Multivari-ate logistic regression was used to analyze the influencing factors of axillary lymph node metasta-sis in breast cancer patients. ROC curve was drawn to analyze the diagnostic value of hMAM,HER2,UBE2C for axillary lymph node metastasis in breast cancer patients. Pearson method was applied to analyze the correlation between hMAM,HER2,UBE2C and tumor markers. Results:The proportion of T3+T4 stage and tumor diameter>3 cm in the metastatic group was higher than that in the non-metastatic group (P<0.05). The serum levels of cytokeratin-19 (CK19) and car-cinoembryonic antigen (CEA) in the metastatic group were higher than those in the non-metastatic group (P<0.05). Compared with the non-metastatic group,the serum hMAM,HER2,and UBE2C levels in the metastatic group were greatly increased (P<0.05). Elevated levels of CEA,hMAM,HER2 and UBE2C were all risk factors for axillary lymph node metastasis in breast cancer patients (P<0.05). ROC curve results showed that the AUC predicted by hMAM,HER2,and UBE2C for axillary lymph node metastasis in breast cancer patients was 0.821,0.815,and 0.819,respectively. The AUC of the combination of the three was greatly higher than that of hMAM (Z=2.070,P=0.038),HER2 (Z=2.072,P=0.038),and UBE2C (Z=1.987,P=0.047) diagnosed alone. HMAM,HER2,UBE2C were all positively correlated with tumor detection markers (P<0.05),and the three were also positively correlated with each other (P<0.05). Conclusion:The serum levels of hMAM,HER2 and UBE2C in patients with axillary lymph node metastasis of breast cancer are elevated. The combination of the three has a certain auxiliary predictive value for axillary lymph node metastasis of breast cancer,and may be used as a potential biomarker for axillary lymph node metastasis of breast cancer.

AP2 transcription factors belong to the AP2/ERF superfamily and are involved in the regula-tion of various biological processes in plant growth and development,as well as in response to biotic and abiotic stresses.However,studies on the AP2 transcription factor family of Perilla frutescens have not been reported.In this study,totally 18 AP2 family members were identified from the Perilla frutescens ge-nome and analyzed for gene structure,conserved motifs,and cis-acting elements using bioinformatics.WRINKLED1(WRI1)is a key regulator of lipid biosynthesis in many plant species and plays an impor-tant role in the regulation of lipid synthesis.Sequence comparison revealed that one member of WRI1 is highly homologous to AtWRI1 and contains two conserved AP2 domains,named PfWRI1.The expression levels of PfAP2 family genes were analyzed in different tissues of Perilla frutescens and at different stages of seed development in conjunction with the transcriptome data,and the results showed that PfWRI1 is highly expressed only in the seeds of Perilla frutescens,suggesting that PfWRI1 may be related to the de-velopmental process of the seeds.The overexpression vector of plant pCAMBIA1303-PfWRI1 was con-structed,and wild-type(Col)and mutant(wri1-1)Arabidopsis thaliana were transformed by Agrobacte-rium tumefaciens to obtain overexpression and complementation lines,respectively.The results showed that the expression of P fWRI1 led to an increase in oil content of Arabidopsis seeds by 8.90％-13.57％compared with Col,and promoted the accumulation of oleic acid(C18:1)and linoleic acid(18:2)and reduced the accumulation of palmitic acid(C16:0),arachidonic acid(C20:0),and cis-11-Eicosenoic acid(C20:1)in transgenic Arabidopsis seeds.In addition,PfWRI1 gene expression increased the ex-pression of glycolysis and fatty acid biosynthesis-related genes AtPKP-α,AtPKP-β1,AtBCCP2,AtSUS2,and AtLIP1.Taken together,PfWRI1 may promote lipid accumulation by increasing unsaturated fatty acid content through interaction with the above genes.