Objective To explore the clinical factors influencing complete response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Methods Clinical data of LARC patients treated in the Department of Radiation Oncology at Beijing Shijitan Hospital between January 2013 and December 2024 were retrospectively collected. All patients received nCRT, after which surgery or a watch-and-wait approach was adopted based on treatment response. Univariable and multivariable logistic regression analyses were performed to identify prognostic factors influencing complete response. A clinical prediction model was constructed based on the multivariable analysis results, and its predictive performance was evaluated using the receiver operating characteristic curve. Results A total of 113 eligible patients were included. After nCRT, 19 patients (16.8%) achieved complete response, including 3 with clinical complete response and 16 with pathological complete response. Univariable analysis indicated that pretreatment clinical N stage, extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen were associated with complete response after nCRT (P<0.05). Multivariable logistic regression analysis identified pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen as independent influencing factors for complete response (P<0.05). A prediction model incorporating these independent factors yielded an area under the receiver operating characteristic curve of 0.813 (95% confidence interval: 0.713-0.913), with a sensitivity of 89.5% and a specificity of 60.6%, demonstrating good predictive performance. Conclusion Pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen are independent factors influencing complete response after nCRT in LARC patients. The prediction model combining these factors may assist in evaluating treatment efficacy following nCRT in LARC patients.

Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.

ObjectiveTo investigate the epidemiological characteristics and influencing factors of depressive symptoms among middle school (junior, senior, and vocational high school) students in Yunnan Province, China, and to inform evidence-based intervention strategies for adolescent mental health. MethodsA cross-sectional survey was conducted between October and November 2023 using stratified random cluster sampling. Students from eight counties (districts) across four prefectures (cities) in Yunnan Province were included. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D). Multivariate logistic regression analysis was performed to examine factors associated with depressive symptoms, with stratified analyses conducted by gender, educational stage, and ethnicity. ResultsA total of 4 672 questionnaires were distributed, with 4 670 valid questionnaires retrieved, yielding a valid response rate of 99.96%. The surveyed participants were predominantly female students (50.81%), junior high school students (49.13%), ethnic minorities (52.78%), and urban residents (79.29%). The mean CES-D score for middle school students in Yunnan Province was (15.31±10.83). Female students had a significantly higher mean score (16.63±11.41) than male students (13.95±10.02) (P<0.001). Senior high school students had a significantly higher mean score (16.61±10.61) compared to both junior high school students (14.74±11.45) and vocational high school students (13.10±7.71) (all pairwise comparisons P<0.001). The prevalence of depressive symptoms among middle school students in Yunnan Province was 28.18%. The prevalence was significantly higher in females (34.09%) than in males (22.07%). By school type, the detection rate was highest among senior high school students (33.39%), followed by junior high school students (26.29%) and vocational high school students (17.27%) (P<0.05). Multivariate logistic regression analysis showed that female gender (OR=2.16, 95%CI: 1.86‒2.50), being in junior high school (OR=2.43, 95%CI: 1.84‒3.20) or senior high school (OR=2.27, 95%CI: 1.73‒2.98), not living with parents (OR=1.24, 95%CI: 1.07‒1.44), irregular breakfast consumption (OR=1.52, 95%CI: 1.33‒1.75), lack of moderate-to-vigorous physical activity (MVPA) (OR=1.69, 95%CI: 1.37‒2.09), sleep duration ≤5 h per night (OR=2.52, 95%CI: 2.02‒3.14) or 6‒7 h per night (OR=1.47, 95%CI: 1.25‒1.73), smoking (OR=1.86, 95%CI: 1.56‒2.23), and alcohol consumption (OR=1.81, 95%CI: 1.54‒2.13) were positively associated with depressive symptoms. In contrast, screen time ≤1 h (OR=0.71, 95%CI: 0.59‒0.86) was negatively associated with depressive symptoms. Stratified analyses showed that female students not living with parents (OR=1.29, 95%CI: 1.06‒1.58), senior high school students (OR=1.51, 95%CI: 1.21‒1.88), and Han Chinese students (OR=1.37, 95%CI: 1.11‒1.69) were more likely to experience depressive symptoms. Han Chinese students who smoked were also more likely to have depressive symptoms (OR=1.72, 95%CI: 1.34‒2.21). In contrast, male students with screen time ≤1 h (OR=0.71, 95%CI: 0.53‒0.95) and ethnic minority students (OR=0.74, 95%CI: 0.58‒0.95) were less likely to experience depressive symptoms. Regardless of gender, irregular breakfast consumption, lack of MVPA, sleep duration less than 8 h per night, smoking, and alcohol consumption were all positively associated with depressive symptoms (P<0.05). Among both junior and senior high school students, irregular breakfast consumption, lack of MVPA, smoking, and alcohol consumption were positively associated with depressive symptoms (all P<0.05), while screen time ≤1 h was negatively associated with depressive symptoms (all P<0.05). For junior high school students, engaging in 1‒2 days of MVPA per week, screen time more than 2 h per day, and sleep duration 6‒7 h per night were all positively associated with depressive symptoms (all P<0.05). Among junior high, senior high, and vocational high school students, sleep duration ≤5 h per night was positively associated with depressive symptoms (P<0.05). For both Han Chinese and ethnic minority students, irregular breakfast consumption, lack of MVPA, sleep duration less than 8 h per night, and alcohol consumption were all positively associated with depressive symptoms (all P<0.05). ConclusionThe prevalence of depressive symptoms among middle school students in Yunnan Province is comparable to that in central China and higher than that in northern regions. Prevention and control efforts should prioritize female students and those in junior and senior high school stages. Universal improvements in lifestyle behaviors among middle school students, such as regular breakfast consumption, MVPA, sufficient sleep (≥8 h), and abstinence from smoking and alcohol. Particular attention should be given to limiting excessive screen time among junior high school students and addressing the mental health needs of females not living with their parents, senior high school students, and Han Chinese students.

Objective To establish the HPLC fingerprints for the different extracts from Coptidis Rhizoma，and investigate the spectrum-effect relationship between HPLC fingerprints and anti-Staphylococcus aureus activity in vitro to analyze the pharmacodynamic material basis. Methods Nine kinds of Coptidis Rhizoma extracts were prepared, and establish the HPLC fingerprints for them. The antibacterial rate of each extract was determined by the broth microdilution method with Staphylococcus aureus as the test bacteria. The grey relational analysis （GRA） method was used to analyze the correlation between the fingerprint data and the in vitro antibacterial test data. Results The HPLC fingerprints of nine kinds of Coptidis Rhizoma extracts were established, nine common characteristic fingerprint peaks were calibrated, and 5 peaks were identified by the reference substance comparison method. GRA analysis experiments showed that the correlation between nine peaks and antibacterial effect was 0.559 1~0.803 3; and the peak 3, peak 8 （palmatine hydrochloride）, peak 9 （berberine hydrochloride） were positively correlated with the inhibition of Staphylococcus aureus,while the peak 9 （berberine hydrochloride） had the strongest effect, and its correlation degree was 0.803 3. Conclusion The effective substance of antibacterial was preliminarily determined through the study of spectrum-effect relationship for Coptidis Rhizoma extracts,which may be the alkaloids, mostly containing hydrochloride, which provided a reference for further research on the pharmacodynamic material basis of Coptidis Rhizoma.

Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

Cold ischemia-reperfusion injury (CIRI) is a major contributor to delayed graft function and long-term graft failure after kidney transplantation.Its pathogenesis involves multiple mechanisms, including energy metabolism disorders, oxidative stress and sterile inflammatory responses.Increasing evidence indicates that immune cells play a central regulatory role in the initiation and progression of CIRI.Damage-associated molecular patterns released during cold ischemia and reperfusion activate innate immunity, leading to the rapid recruitment of neutrophils, macrophages, dendritic cells and amplification of inflammatory cascades.Subsequently, adaptive immune cells, including T cells and B cells, are activated and further contribute to sustained inflammation, disruption of immune tolerance and graft injury.Through cytokine signaling, chemokine-mediated recruitment and antigen presentation, different immune cell subsets form a complex interactive network that ultimately determines the severity and outcome of CIRI.This review summarizes the roles and mechanisms of innate and adaptive immune cells in renal allograft CIRI, highlights their interconnections, and discusses emerging immune cell-targeted therapeutic strategies, aiming to provide a theoretical basis for improving clinical outcomes in kidney transplantation.

Transfusion technicians constitute a core workforce in safeguarding blood safety, and the quality of their standardized training directly affects the operational efficiency of the blood services. At present, training programs for transfusion technicians across China have been developed in a diversified manner. Positive progress has been achieved in integrated theoretical and practical training, on-the-job faculty development, and regional collaborative training models. However, persistent challenges remain, including fragmented training providers, inconsistent training standards, limited coverage, and a disconnect between training and workforce utilization. Based on a review of current standardized training practice, this article systematically analyzes the structural challenges confronting current standardized training, and further proposes a framework for building a comprehensive training system, covering the definition and core components of standardized training, targeted improvement strategies and key assessment indicators. The study aims to facilitate the transformation of training for blood transfusion technicians in blood services from a project-based approach to an institutionalized model, and from fragmented implementation to a systematic framework.

Background The air quality index (AQI), which is based on the concentration of a dominant pollutant, and the air quality health index (AQHI), which is constructed using excess risk estimates for individual pollutants, may not fully capture the health risks associated with combined exposure to air pollutants. These approaches also provide limited information on the relative contributions of different pollutants. Given the geographical heterogeneity in the composition and health effects of air pollutant mixtures, it is necessary to develop region- and disease-specific AQHIs for different population groups. Objective To develop and evaluate a health risk-based AQHI for respiratory disease mortality associated with air pollutant mixtures using the weighted quantile sum (WQS) regression model and to quantify the relative weight contributions of selected pollutants. Methods Daily data on six air pollutants, the AQI, meteorological factors, and deaths from respiratory diseases in the central urban districts of Tianjin from 2014 to 2019 were collected and integrated into a time-series database. First, generalized additive models (GAMs) were applied to identify indicator pollutants associated with respiratory disease mortality. Second, the WQS regression model was then applied to estimate the relative weight contributions of selected pollutants and to establish the exposure-response relationship between air pollutant mixtures and respiratory disease mortality for AQHI development. Finally, the exposure-response relationships of the AQHI and AQI with respiratory disease mortality were evaluated and compared across population subgroups and seasons. Results Fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), and ozone (O₃) were identified as indicator pollutants for combined air pollution exposure. Particulate matter, including PM_2.5 and PM₁₀, and O₃ contributed the most to the mixture index, followed by SO₂. Each interquartile range (IQR) increase in the WQS-based AQHI was significantly associated with respiratory disease mortality in the total population, males, elderly individuals, non-elderly individuals, and during the warm season. The corresponding excess risks (ER) were 3.79% (95%CI: 1.24%, 6.27%), 4.37% (95%CI: 0.96%, 7.67%), 3.16% (95%CI: 0.47%, 5.77%), 9.36% (95%CI: 2.01%, 16.15%), and 7.13% (95%CI: 1.31%, 13.30%), respectively. Compared with the AQI, the AQHI showed stronger associations with respiratory disease mortality across different population subgroups and seasons. Conclusion PM_2.5, PM₁₀, and O₃ contribute substantially to the association between air pollutant mixtures and respiratory disease mortality in Tianjin. Compared with the AQI, the WQS-based AQHI better characterizes the association between air quality and respiratory disease mortality across population subgroups.

ObjectiveTo investigate the current status of ethical sensitivity among clinical nursing interns in the context of artificial intelligence （AI） and analyze its influencing factors. MethodsAdopting mixed research methods and convenience sampling， a total of 237 nursing interns from a tertiary A hospital in Xi’an were selected as research subjects. Data were collected using a general information questionnaire and the Nursing Students’ Ethical Sensitivity Scale， and semi-structured interviews were conducted with 8 nursing interns. ResultsThe total score of ethical sensitivity among nursing interns was （33.98±6.32）， which was at a moderate level. Multiple linear regression analysis revealed that academic degree （undergraduate： β=0.147， P<0.05； postgraduate： β=0.139， P<0.05）， affinity for the nursing profession （β=0.118， P<0.05）， whether they had taken nursing ethics courses （β=-0.124， P<0.05）， and familiarity with artificial intelligence （β=-0.159，P<0.05） were influencing factors of ethical sensitivity among nursing interns. Four themes were extracted from semi-structured interviews， namely， the incomplete mastery of nursing ethics-related knowledge among nursing interns， weakened ethical sensitivity in the AI teaching scenario of nursing interns， insufficient professional identity affecting the development of nursing interns’ ethical sensitivity， and technological dependence leading to the lack of humanistic care among nursing interns. ConclusionEthical sensitivity of nursing interns represents a moderate level， primarily influenced by educational background， degree of fondness for the nursing profession， learning experience of nursing ethics courses， and familiarity with AI. Nursing educators and clinical administrators urgently need to establish a sustainable school-hospital collaborative model of nursing ethics education， attach importance to the cultivation of ethical awareness and value guidance for nursing interns， and strengthen the intensity and depth of nursing ethics education among nursing interns， thereby improving their level of ethical sensitivity in the context of AI.