Abnormal activation of the Janus kinase/signal transducer and activator of transcription （JAK/STAT） signaling pathway is involved in the pathogenesis of diffuse large B-cell lymphoma （DLBCL）. In recent years， inhibitors targeting JAK2 and STAT3 have emerged as promising therapeutic candidates in DLBCL. This review summarizes the efficacy and safety profiles of JAK2 inhibitors （e.g.， ruxolitinib） and STAT3 inhibitors （direct small-molecule inhibitors， the antisense oligonucleotide， and proteolysis targeting chimeras， etc.） in preclinical models and clinical trials. Accumulating evidence indicates that JAK2 and STAT3 inhibitors exhibit antitumor activity and are generally well tolerated in a subset of DLBCL patients. Meanwhile， the development of novel drug delivery systems has significantly enhanced the stability， bioavailability， and targeting ability of the compounds. Furthermore， JAK2 and STAT3 inhibitors may exhibit synergistic effects when combined with other therapy strategies （such as combinations with B-cell receptor signaling pathway inhibitors， immunomodulators， or other targeted drugs）. However， current clinical applications are still in their early stages. Future research should concentrate on precision treatment strategies based on the genetic subtyping of DLBCL， and further refine the delivery systems for inhibitors as well as combination drug regimens to improve clinical outcomes.

Objective To establish a highly efficient and sensitive technical system for the identification and analysis of platycodin-type saponins, systematically compare the differences in platycodin-type saponins among Platycodon grandiflorum from different producing areas, and provide scientific references for the screening of high-quality Platycodon grandiflorum resources, authenticity evaluation, and construction of standardized quality control systems. Methods A total of 45 batches of P. grandiflorum medicinal materials from 3 producing areas （Anhui, Henan, and Jilin, with 15 batches per area） were selected as research objects. Qualitative identification and semi-quantitative analysis of saponin components were performed based on ultra-high performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry （UHPLC-Q-TOF/MS） technology. Meanwhile, two multivariate statistical methods, principal component analysis （PCA） and partial least squares-discriminant analysis （PLS-DA）, were combined to analyze the differences in platycodin-type saponins of Platycodon grandiflorus from different producing areas. Results A total of 28 saponin components were identified from Platycodon grandiflorus of the three producing areas. PCA results showed that there were minor differences in platycodin-type saponins between Henan Platycodon grandiflorus and Jilin Platycodon grandiflorus, while Anhui P. grandiflorum exhibited significant differences from both. PLS-DA further screened 15 major differential compounds. Among them, the contents of 6 components including 3''-O-acetylpolygalacin D2 and platycodin H in Anhui Platycodon grandiflorus were higher than those in Henan and Jilin Platycodon grandiflorus; platycodigenic acid A had the highest content in Jilin Platycodon grandiflorus; the contents of platycodin D3, polygalacin J, and polygalacin D were relatively higher in Henan Platycodon grandiflorus. Conclusion This study clarified the characteristic differences in core components of Platycodon grandiflorus from the three major producing areas, which provided an important theoretical basis for the screening of high-quality Platycodon grandiflorus resources, elucidation of the mechanism underlying its authenticity, and construction of a standardized quality control system.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

BackgroundIn recent years， the prevalence of obstructive sleep apnea （OSA） is escalating in China， leading to a serious disease burden. However， previous studies on the influencing factors of OSA， such as obesity and sleep position， were mostly cross-sectional studies. This approach inherently hinders the identification of dynamic interaction mechanism among multiple variables， consequently obstructing the formulation of individualized intervention strategies. ObjectiveTo investigate the differences in body mass index （BMI）-oxygen saturation-sleep position-heart rate variability （HRV） network models between OSA and non-OSA populations， thereby offering a reference for the early detection and management of OSA. MethodsA total of 384 adult participants undergoing sleep monitoring at the Affiliated Hospital of Southwest Medical University from July 12， 2022 to October 11， 2023 were included. Subjects were categorized into OSA group （n=203） and control group （n=181） based on an apnea-hypopnea index （AHI） threshold of 5 events per hour. Subsequently， BMI-oxygen saturation-sleep position-HRV networks were constructed and compared between two groups. ResultsThere was no significant difference in the overall edge weight （P=0.55） and overall strength （P=0.28） of the network model between control group and OSA group. Notable differences emerged in both the node connection strength （e.g.， minimum oxygen saturation with BMI， sleep in prone position， and mean RR interval） and node centrality indices （mean oxygen saturation， minimum oxygen saturation， AHI in upright position， AHI in right lateral position and mean heart rate） within the two network models （P<0.05）. ConclusionSignificant differences are observed between the non-OSA and OSA populations in specific factors， including sleep position， heart rate and oxygen saturation.

The development of antiviral drugs targeting SARS-CoV-2 remains a major strategy for the prevention and treatment of COVID-19 infection. Current anti-SARS-CoV-2 agents mainly act on key viral protein targets involved in the viral life cycle, such as the main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp). However, these drugs are insufficient to address the challenges posed by the rapid mutation rate and drug resistance of SARS-CoV-2. In recent years, viral RNA has demonstrated to be a highly promising therapeutic target. Small-molecule drugs that target viral RNA possess distinct advantages, featuring novel mechanisms of action and the potential for broad-spectrum antiviral activity as well as the ability to overcome drug resistance. Such agents provide a new avenue for combating coronavirus threats. This review systematically summarizes recent advances in the development of small-molecule inhibitors targeting conserved SARS-CoV-2 RNA structures, including the frameshift stimulation element (FSE), stem-loops (SL), G-quadruplexes (G-4), and RNA-targeting chimeras (RNATAC), aiming to provide some insight to guide future.

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.

ObjectiveTo analyze the distribution characteristics of traditional Chinese medicine （TCM） syndrome elements in different risk populations of heart failure complicated with type 2 diabetes. MethodsClinical data of 675 type 2 diabetes patients were retrospectively collected. Lasso-multivariate Logistic regression was used to construct a clinical prediction nomogram model. Based on this， 441 non-heart failure patients were divided into a low-risk group （325 cases） and a high-risk group （116 cases） according to the median risk score of heart failure complicated with type 2 diabetes. TCM diagnostic information （four diagnostic methods） was collected for both groups， and factor analysis was applied to summarize the distribution of TCM syndrome elements in different risk populations. ResultsLasso-multivariate Logistic regression analysis identified age， disease duration， coronary heart disease， old myocardial infarction， arrhythmia， absolute neutrophil count， activated partial thromboplastin time， and α-hydroxybutyrate dehydrogenase as independent risk factors for heart failure complicated with type 2 diabetes. These were used as final predictive factors to construct the nomogram model. Model validation results showed that the area under the curve （AUC） of the receiver operating characteristic （ROC） curve for the modeling group and validation group were 0.934 and 0.935， respectively. The Hosmer-Lemeshow test （modeling group P = 0.996， validation group P = 0.121） indicated good model discrimination. Decision curve analysis showed that the curves for All and None crossed in the upper right corner， indicating high clinical utility. The low-risk and high-risk groups each obtained 14 common factors. Preliminary analysis revealed that the main disease elements in the low-risk group were qi deficiency （175 cases， 53.85%）， dampness （118 cases， 36.31%）， and heat （118 cases， 36.31%）， with the primary locations in the spleen （125 cases， 38.46%） and lungs （99 cases， 30.46%）. In the high-risk group， the main disease elements were yang deficiency （73 cases， 62.93%）， blood stasis （68 cases， 58.62%）， and heat （49 cases， 42.24%）， with the primary locations in the kidney （84 cases， 72.41%） and heart （70 cases， 60.34%）. ConclusionThe overall disease characteristics in different risk populations of type 2 diabetes patients with heart failure are a combination of deficiency and excess， with deficiency being predominant. Deficiency and heat are present throughout. The low-risk population mainly shows qi deficiency with dampness and heat， related to the spleen and lungs. The high-risk population shows yang deficiency with blood stasis and heat， related to the kidneys and heart.

Objective:To explore the differences in sociodemographic and clinical characteristics between pa-tients with unipolar depression bipolar depression and to establish a nomogram for identifying bipolar depression.Methods:Using data from the China Mental Disorders Cohort Study,the sociodemographic and clinical characteristics of 2 643 patients with unipolar depression and 250 patients with bipolar depression diagnosed accord-ing to the criteria of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5)were includ-ed to compare their sociodemographic and clinical characteristics.These characteristics included general demograph-ic information,disease-related information,clinical examination results,and the severity of the disease assessed with the Global Assessment of Functioning(GAF)and Hamilton Depression Rating Scale.Logistic regression analysis was employed to identify factors influencing bipolar depression,and a nomogram was constructed for its identifica-tion.Results:The risk factors for bipolar depression included being male(OR=1.48),being employed(OR=1.38),having non-melancholic features during episodes(OR=2.33),a Body Mass Index ranging from normal to obese(OR=2.48,2.49,4.65),psychotic features(OR=2.14),mixed episode(OR=9.36),comorbid physical diseases(OR=2.47),four or more depressive episodes(OR=1.67),earlier age of onset(OR=0.95),longer ill-ness duration(OR=1.03),and higher GAF scores(OR=1.02).The nomogram model achieved an AUC of 0.81(95％CI:0.78-0.84).The Hosmer-Lemeshow test result was x2=6.96(P＞0.05),indicating good model fit.The calibration curve showed good performance.The decision curve analysis revealed that the nomogram pro-vides significant clinical benefit when the risk of bipolar depression was within the range of 0 to 0.9.Conclusion:The nomogram established based on the identified sociodemographic and clinical factors can accurately assess the risk of bipolar depression,providing a useful tool for early identification and intervention.