Objective To analyze the levels of serum CTCs and ctDNA in NSCLC patients receiving first-line EGFR-TKI treatment, and to explore the clinical value of CTCs and ctDNA detection in assessing the efficacy of treatment for advanced lung cancer. Methods A total of 109 NSCLC patients receiving first-line EGFR-TKI treatment were enrolled. Serum tumor markers CEA, CTCs, and ctDNA were detected at baseline and after one month of treatment. Chest CT scans were performed, and treatment efficacy was evaluated based on RECIST1.1 criteria. CTCs were counted by enrichment-staining-computational algorithm to analyze malignant features, while ctDNA was assessed using digital PCR. Results Survival rate was low in patients with abnormal CEA and ctDNA tests at baseline and in patients with reduced serum CTCs after treatment. In the SD subgroup of patients with brain metastases and advanced stage, the PFS benefit was low. Conclusion Patients in the SD subgroup have significantly higher recurrence risks than those in the PR or CR subgroups. Therefore, CTC and ctDNA testing should be applied to patients in the SD subgroup to identify high-risk patients with poor response to EGFR-TKI treatment, intervene with additional treatment promptly, and obtain long progression-free survival.

Perceptual decision making refers to the process by which individuals make choices and judgments based on sensory information, serving as a fundamental ability for human adaptation to complex environments. While traditional research has focused on perceptual decision making in isolated contexts, growing evidence highlights the profound influence of social contexts prevalent in real-world scenarios. As a crucial factor supporting individual survival and development, social context not only provides rich information sources but also shapes perceptual decision making through top-down processing mechanisms, prompting researchers to recognize the inherently social nature of human decisions. Empirical studies have demonstrated that social information, such as others’ choices or group norms, can systematically bias individuals’ perceptual decisions, often manifesting as conformity behaviors. Social influence can also facilitate performance under certain conditions, particularly when individuals can accurately identify and adopt high-quality social information. The impact of social context on perceptual decisions is modulated by a variety of external and internal factors, including group characteristics(e.g., group size, response consistency), attributes of peers (e.g., familiarity, social status, distinctions between human and artificial agents), as well as individual differences such as confidence, personality traits, and developmental stage. The motivations driving social influence encompass three primary mechanisms: improving decision accuracy through informational influence, gaining social acceptance through normative influence, and maintaining positive self-concept. Recent computational approaches have employed diverse theoretical frameworks to provide valuable insights into the cognitive mechanisms underlying social influence in perceptual decision making. Reinforcement learning models demonstrate how social feedback shapes future choices through reward-based updating. Bayesian inference frameworks describe how individuals integrate personal beliefs with social information based on their respective reliabilities, dynamically updating beliefs to optimize decisions under uncertainty. Drift diffusion models offer powerful tools to decompose social influence into distinct cognitive components, allowing researchers to differentiate between changes in perceptual processing and shifts in decision criteria. Collectively, these models establish a comprehensive methodological foundation for disentangling the multiple pathways by which social context shapes perceptual decisions. Neuroimaging and electrophysiological studies provide converging evidence that social context influences perceptual decision making through multi-level neural mechanisms. At early perceptual processing stages, social influence modulates sensory evidence accumulation in parietal cortex and directly alters primary visual cortex activity, while guiding selective attention to stimulus features consistent with social norms through attentional alignment mechanisms. At higher cognitive levels, the reward system (ventral striatum, ventromedial prefrontal cortex) is activated during group-consistent decisions; emotion-processing networks (anterior cingulate cortex, insula, amygdala) regulate experiences of social acceptance and rejection; and mentalizing-related brain regions (dorsomedial prefrontal cortex, temporoparietal junction) support inference of others’ mental states and social information integration. These neural circuits work synergistically to achieve top-down multi-level modulation of perceptual decision making. Understanding the mechanisms by which social context shapes perceptual decision making has broad theoretical and practical implications. These insights inform the optimization of collective decision-making, the design of socially adaptive human-computer interaction systems, and interventions for cognitive disorders such as autism spectrum disorder and anorexia nervosa. Future studies should combine computational modeling and neuroimaging approaches to systematically investigate the multi-level and dynamic nature of social influences on perceptual decision making.

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale

OBJECTIVES: To investigate the chain mediating role of family care and emotional management in the relationship between social support and anxiety among rural primary school students. METHODS: A questionnaire survey was conducted among students in grades 4 to 6 from four counties in Hunan Province. Data were collected using the Social Support Rating Scale, Family Care Index Scale, Emotional Intelligence Scale, and Generalized Anxiety Disorder -7. Logistic regression analysis was used to explore the influencing factors of anxiety symptoms. Mediation analysis was conducted to assess the chain mediating effects of family care and emotional management between social support and anxiety. RESULTS: A total of 4 141 questionnaires were distributed, with 3 874 valid responses (effective response rate: 93.55%). The prevalence rate of anxiety symptoms among these students was 9.32% (95%CI: 8.40%-10.23%). Significant differences were observed in the prevalence rates of anxiety symptoms among groups with different levels of social support, family functioning, and emotional management ability (P<0.05). The total indirect effect of social support on anxiety symptoms via family care and emotional management was significant (β=-0.137, 95%CI: -0.167 to -0.109), and the direct effect of social support on anxiety symptoms remained significant (P<0.05). Family care and emotional management served as significant chain mediators in the relationship between social support and anxiety symptoms (β=-0.025,95%CI:-0.032 to -0.018), accounting for 14.5% of the total effect. CONCLUSIONS Social support can directly affect anxiety symptoms among rural primary school students and can also indirectly influence anxiety symptoms through the chain mediating effects of family care and emotional management. These findings provide scientific evidence for the prevention of anxiety in primary school students from multiple perspectives.
Humans ; Female ; Male ; Social Support ; Anxiety/etiology* ; Child ; Students/psychology* ; Emotions ; Logistic Models

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Influenza virus causes serious threat to human life and health. Due to the inherent high variability of influenza virus, clinically resistant mutant strains of currently approved anti-influenza virus drugs have emerged. Therefore, it is urgent to develop antiviral drugs with new targets or mechanisms of action. RNA-dependent RNA polymerase is directly responsible for viral RNA transcription and replication, and plays key roles in the viral life cycle, which is considered an important target of anti-influenza drug design. From the point of view of medicinal chemistry, this review summarizes current advances in diverse small-molecule inhibitors targeting influenza virus RNA-dependent RNA polymerase, hoping to provide valuable reference for development of novel antiviral drugs.

Interpreting genes of interest is essential for identifying molecular mechanisms, but acquiring such information typically involves tedious manual retrieval. To streamline this process, the fanyi package offers tools to retrieve gene information from sources like National Center for Biotechnology Information (NCBI), significantly enhancing accessibility. Additionally, understanding the latest research advancements and sharing achievements are crucial for junior researchers. However, language barriers often restrict knowledge absorption and career development. To address these challenges, we developed the fanyi package, which leverages artificial intelligence (AI)-driven online translation services to accurately translate among multiple languages. This dual functionality allows researchers to quickly capture and comprehend information, promotes a multilingual environment, and fosters innovation in academic community. Meanwhile, the translation functions are versatile and applicable beyond biomedicine research to other domains as well. The fanyi package is freely available at https://github.com/YuLab-SMU/fanyi.

The post-translational modification of proteins is a key mechanism that imparts physiological functions to proteins,among which reversible phosphorylation modifications play a pivotal role in many biological processes.Aberrant changes in phosphorylation are often closely associated with various major disease processes.In recent years,with the aid of proteomic technologies and methods,high-throughput,high-precision qualitative and quantitative approaches for phosphorylated proteins have rapidly advanced.This article reviews the research progress of phosphorylated protein quantification and chemical proteomics analysis methods based on the"bottom-up"strategy,including phosphopeptide enrichment methods,mass spectrometry fragmentation methods,quantification analysis methods and phosphorylation site stoichiometry,and discusses the development trend of quantification and stoichiometric analysis methods for phosphorylated proteins.

Objective:To explore the acupoint selection law in acupuncture and moxibustion in treating postpartum incontinence by using data mining technology.Methods:The clinical research literature on acupuncture and moxibustion treatment for postpartum incontinence was retrieved from CNKI, Wanfang Data, VIP, CBM, China Medical Journal Full-text Database, PubMed, Embase, Web of Science from the establishment of the databases to February 1, 2023. The acupoint prescription database was established using Excel 2016 and conducting frequency statistics of acupoints, meridians and specific acupoints. Clustering analysis was performed using SPSS Statistics 25.0, and association rule analysis was performed using SPSS Modeler 18.0.Results:A total of 70 articles were included, involving 70 acupuncture prescriptions and including 31 acupoints with a total frequency of 384 times. The top five acupoints were Sanyinjiao (SP6, 46 times), Guanyuan (CV4, 45 times), Zusanli (ST36, 43 times), Zhongji (RN3, 41 times), and Qihai (CV6, 38 times). The commonly used meridians were Conception Vessel, bladder meridian and spleen meridian. The involved acupoints were mostly located in the lower limbs and belly, and most of them were Jiaohui, Mu and Wushu acupoints. Five effective clustering groups were obtained by clustering analysis of high frequency acupoints. The core acupoint combination of association rules was Sanyinjiao (SP6)-Zusanli (ST36)-Guanyuan (CV4)-Qihai (CV6)-Zhongji (RN3).Conclusions:The pathogenesis of postpartum urinary incontinence is mainly characterized by qi deficiency. Acupuncture and moxibustion treatment of postpartum urinary incontinence follows the principles of invigorating qi and tonifying spleen, nourishing lung and tonifying kidney, paying attention to the use of acupoints in abdomen and lower limbs, and using the methods of upper and lower acupoints, anterior and posterior acupoints.

Objective:To investigate the effects of intra-articular injection of exosomes derived from dental pulp stem cells from hu-man exfoliated deciduous teeth(SHED-EXO)on subchondral bone homeostasis in rat temporomandibular joint osteoarthritis(TMJ OA)process.Methods:36 male SD rats were randomly divided into 3 groups(n=12):control(CON),sodium iodoacetate(MIA)-induced TMJ OA(MIA),and SHED-EXO injection into TMJ OA(SHED-EXO)groups.At 2 and 6 weeks post-treatment,Micro-CT,Double labeling,TRAP staining,and immunohistochemical staining were employed to detect osteoclasts and osteoblasts in the subchondral bone.Additionally,the mRNA expression levels of ADAMTs5,IL-1β,OCN and OPG/RANKL were analyzed by qRT-PCR.Results:The MIA group exhibited significant bone loss and an enlarged bone marrow cavity.In comparison with the CON group,BV/TV and Tb.Th were lower(P＜0.001),while BS/BV,Tb.Sp,and Tb.N were higher(P＜0.01).Additionally,the bone formation rate within 5 days was low-er than that of the control group(P＜0.001).When compared to the MIA group,the SHED-EXO group showed a significant increase in bone morphology and bone mass.BV/TV and Tb.Th were increased(P＜0.01),while BS/BV,Tb.Sp and Tb.N were decreased(P＜0.05).The bone formation rate was higher(P＜0.01).Compared with both the control and treatment groups,the MIA group exhibited a significant increase in the number of osteoclasts in the subchondral bone(P＜0.01),along with a notable decrease in H-type blood vessels and OCN-positive areas(P＜0.01).Conclusion:Intra-articular injection of SHED-EXO can reg-ulate condylar subchondral bone homeostasis in TMJ OA of rats by promoting osteogenesis and inhibiting osteoclasts.