Objective: To investigate the current status of benefit finding among young and middle-aged patients with type 2 diabetes mellitus (T2DM) and analyze its influencing factors, so as to provide a reference for improving the level of benefit finding in this population. Methods: From November 2022 to May 2023, young and middle-aged patients with T2DM aged 18-59 years hospitalized in the endocrinology departments of 2 tertiary hospitals in Hengyang City, Hunan Province were selected as survey subjects by a convenience sampling method. Basic demographic information was collected using a general questionnaire survey. Benefit finding, resourcefulness, and stigma were evaluated using the Benefit Finding Scale, the Chinese Version of the Resourcefulness Scale, and the Type 2 Diabetes Stigma Assessment Scale, respectively. A multiple linear regression model was used to analyze the influencing factors of benefit finding among young and middle-aged patients with T2DM. Results: A total of 305 young and middle-aged patients with T2DM were investigated, including 222 males (72.79%) and 83 females (27.21%). There were 231 cases aged 45-59 years, accounting for 75.74%. The scores for benefit finding, resourcefulness, and stigma were (42.86±6.06), (75.12±11.30), and (41.20±10.10), respectively. Multiple linear regression analysis showed that young and middle-aged patients with T2DM who were male (β′=0.088), aged 18-<45 years (β′=0.083), absence of diabetes complications (β′=0.124), and had higher resourcefulness scores (β′=0.679) had higher levels of benefit finding, while patients with higher stigma scores (β′=-0.097) had lower levels of benefit finding. Conclusion The level of benefit finding among young and middle-aged patients with T2DM was moderate, and was related to gender, age, diabetes complications, resourcefulness, and stigma.

Objective To systematically evaluate the effectiveness and acceptability of antidepressant drugs in the treatment of postpartum depression(PPD).Methods The PubMed,Cochrane Library,Embase,Web of Science,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Journals of Chinese Scienc were searched,and Chinese Biomedical Literature Service System(SinoMed)database until November 2023.Screen randomized controlled trials(RCTs)of antidepressant drugs for the treatment of PPD.The treatment group was given antidepressant drugs,and the control group was given placebo or another antidepressant drug.Meta-analysis of effectiveness and acceptability is performed using Stata 17.0 software.Results A total of 27 RCTs with a total of 2 202 patients were included.The results of meta-analysis showed:The top three efficacy relative to placebo were mirtazapine[odds ratio(OR)=2.25,95％confidence interval(CI)=(1.20-3.30),P＜0.05],nortriptyline[OR=1.50,95％CI=(0.55-2.44),P＞0.05],venlafaxine[OR=1.35,95％CI=(0.13-2.56),P＞0.05].Acceptability is compared with placebo in the top three Chinese herbal medicine[OR=0.47,95％CI=(-0.72-1.66),P＞0.05],nortriptyline[OR=-0.08,95％CI=(-1.16-1.33),P＞0.05],venlafaxine[OR=-0.12,95％CI=(-1.47-1.24),P＞0.05].Conclusion Nortriptyline,venlafaxine,trazodone,and duloxetine are effective in treating PPD without obvious adverse drug reactions.

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.

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 To systematically evaluate the effectiveness and acceptability of antidepressant drugs in the treatment of postpartum depression(PPD).Methods The PubMed,Cochrane Library,Embase,Web of Science,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Journals of Chinese Scienc were searched,and Chinese Biomedical Literature Service System(SinoMed)database until November 2023.Screen randomized controlled trials(RCTs)of antidepressant drugs for the treatment of PPD.The treatment group was given antidepressant drugs,and the control group was given placebo or another antidepressant drug.Meta-analysis of effectiveness and acceptability is performed using Stata 17.0 software.Results A total of 27 RCTs with a total of 2 202 patients were included.The results of meta-analysis showed:The top three efficacy relative to placebo were mirtazapine[odds ratio(OR)=2.25,95％confidence interval(CI)=(1.20-3.30),P＜0.05],nortriptyline[OR=1.50,95％CI=(0.55-2.44),P＞0.05],venlafaxine[OR=1.35,95％CI=(0.13-2.56),P＞0.05].Acceptability is compared with placebo in the top three Chinese herbal medicine[OR=0.47,95％CI=(-0.72-1.66),P＞0.05],nortriptyline[OR=-0.08,95％CI=(-1.16-1.33),P＞0.05],venlafaxine[OR=-0.12,95％CI=(-1.47-1.24),P＞0.05].Conclusion Nortriptyline,venlafaxine,trazodone,and duloxetine are effective in treating PPD without obvious adverse drug reactions.

AIM:To investigate the effects of macrophage galactose-type lectin 1(Mgl1)gene deletion on he-matopoietic stem/progenitor cells(HSPCs)under steady-state conditions and inflammation.METHODS:Mice were di-vided into a control group(wild-type)and an experimental group(Mgl1 gene-deleted).Flow cytometry was used to ana-lyze the proportions of various hematopoietic cell lineages in the peripheral blood and bone marrow of both groups,assess-ing the impact of Mgl1 gene deletion on steady-state hematopoiesis(n=3～4).Transplantation and colony-forming assays were utilized to evaluate the effects of Mgl1 gene deletion onthe repopulation capacity and colony-forming ability of HSPCs(n=5).The LPS-induced inflammation model was employed to examine the effects of Mgl1 gene deletion on the inflamma-tory response of HSPCs both in vitro and in vivo(n=5～8).Western blot and RT-qPCR were conducted to analyze the alter-ations in signaling pathways regulated by Mgl1 in the inflammatory response of HSPCs(n=3).RESULTS:(1)Mgl1 gene deletion had no significant effecton steady-state hematopoiesis(P>0.05).(2)Mgl1 gene deletion promoted inflam-mation-induced cell differentiation of HSPCs(P<0.01).(3)Mgl1 gene deletion accelerated the exhaustion of HSPCs un-der prolonged inflammatory conditions(P<0.01).(4)Mgl1 was found to regulate the inflammatory response of HSPCs via the NF-κB signaling pathway.CONCLUSION:Mgl1 gene deletion enhances the inflammatory response of HSPCs via the NF-κB signaling pathway.

AIM:To investigate the effects of macrophage galactose-type lectin 1(Mgl1)gene deletion on he-matopoietic stem/progenitor cells(HSPCs)under steady-state conditions and inflammation.METHODS:Mice were di-vided into a control group(wild-type)and an experimental group(Mgl1 gene-deleted).Flow cytometry was used to ana-lyze the proportions of various hematopoietic cell lineages in the peripheral blood and bone marrow of both groups,assess-ing the impact of Mgl1 gene deletion on steady-state hematopoiesis(n=3～4).Transplantation and colony-forming assays were utilized to evaluate the effects of Mgl1 gene deletion onthe repopulation capacity and colony-forming ability of HSPCs(n=5).The LPS-induced inflammation model was employed to examine the effects of Mgl1 gene deletion on the inflamma-tory response of HSPCs both in vitro and in vivo(n=5～8).Western blot and RT-qPCR were conducted to analyze the alter-ations in signaling pathways regulated by Mgl1 in the inflammatory response of HSPCs(n=3).RESULTS:(1)Mgl1 gene deletion had no significant effecton steady-state hematopoiesis(P>0.05).(2)Mgl1 gene deletion promoted inflam-mation-induced cell differentiation of HSPCs(P<0.01).(3)Mgl1 gene deletion accelerated the exhaustion of HSPCs un-der prolonged inflammatory conditions(P<0.01).(4)Mgl1 was found to regulate the inflammatory response of HSPCs via the NF-κB signaling pathway.CONCLUSION:Mgl1 gene deletion enhances the inflammatory response of HSPCs via the NF-κB signaling pathway.

Purpose: Chronic low-grade inflammation is linked to the biology of aging; however, evidence supporting a causal relationship between periodontitis—a dysbiotic biofilminitiated inflammatory disease—and accelerated aging remains limited. This study investigated the causality between periodontitis and biological aging and identified potentially shared genomic loci, genes, and pathways. Methods: We conducted a 2-sample Mendelian randomization (MR) analysis to explore the causality of periodontitis on age acceleration measures (DNAm PhenoAge acceleration, GrimAge acceleration, Hannum age acceleration, and intrinsic epigenetic age acceleration) using a dataset from genome-wide association studies of European ancestry populations.Independent genetic variants associated with each trait were used as instrumental variables.The inverse variance-weighted (IVW) method served as the primary MR approach, supplemented by sensitivity testing. We also performed additional statistical genetic analyses to identify pleiotropic loci, shared functional genes, and potential biological pathways, integrating large-scale expression quantitative trait loci data from blood samples. Results: The MR analysis indicated a causal relationship between periodontitis and DNAm PhenoAge acceleration (IVW β=0.308; 95% confidence interval, 0.056–0.561; P=0.017), a finding corroborated by sensitivity analyses. There was a significant genetic overlap between periodontitis and age acceleration. Pleiotropic analysis revealed 24 shared SNPs associated with 242 genes, predominantly involved in immune functions and pathways related to cellular processes. Further integration analysis showed that 91 of these pleiotropic genes were causally linked to both conditions, with C6orf183 identified as a potential mediator. Conclusions This study presents compelling genetic evidence supporting a causal relationship between periodontitis and accelerated aging. Further research is required to validate these findings and investigate the underlying mechanisms.

Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.

Objective:To analyze the clinical features and genetic etiology of 17 Chinese pedigrees affected with X-linked intellectual disability (XLID).Methods:Seventeen pedigrees affected with unexplained intellectual disability which had presented at Henan Provincial People′s Hospital from May 2021 to May 2023 were selected as the study subjects. Clinical data of the probands and their pedigree members were collected. Trio-whole exome sequencing (Trio-WES), Sanger sequencing and X chromosome inactivation (XCI) analysis were carried out. Pathogenicity of candidate variants was predicted based on the guidelines from the American College of Medical Genetics and Genomics and co-segregation analysis.Results:The 17 probands, including 9 males and 8 females with an age ranging from 0.6 to 8 years old, had all shown mental retardation and developmental delay. Fourteen variants were detected by genetic testing, which included 4 pathogenic variants ( MECP2: c. 502C>T, MECP2: c. 916C>T/c.806delG, IQSEC2: c.1417G>T), 4 likely pathogenic variants ( MECP2: c. 1157_1197del/c.925C>T, KDM5C: c. 2128A>T, SLC6A8: c. 1631C>T) and 6 variants of uncertain significance ( KLHL15: c. 26G>C, PAK3: c. 970A>G/c.1520G>A, GRIA3: c. 2153C>G, TAF1: c. 2233T>G, HUWE1: c. 10301T>A). The PAK3: c.970A>G, GRIA3: c. 2153C>G and TAF1: c. 2233T>G variants were considered as the genetic etiology for pedigrees 12, 14 and 15 by co-segregation analysis, respectively. The proband of pedigree 13 was found to have non-random XCI (81: 19). Therefore, the PAK3: c. 1520G>A variant may underlie its pathogenesis. Conclusion:Trio-WES has attained genetic diagnosis for the 17 XLID pedigrees. Sanger sequencing and XCI assay can provide auxiliary tests for the diagnosis of XLID.