Clinical trials represent a pivotal stage in the development of pharmaceutical drugs. Nevertheless， given the unique characteristics of traditional Chinese medicine （TCM） and the diagnostic and treatment principle of syndrome differentiation and treatment in TCM， the clinical evaluation techniques and methods that can comprehensively reflect the characteristics of TCM and are tailored to its specificities are still in need of refinement and innovation. This paper systematically summarizes the key techniques and methods for designing and evaluating the clinical research on the treatment of the spleen and stomach diseases with TCM from three aspects including clinical research design， evaluation， and platform construction， compares domestic and international research landscapes， and proposes for future directions. It is suggested that a multidimensional evaluation system integrating modern medicine and TCM theory should be established， and further innovation is needed in TCM research design and methodologies， leveraging intelligent devices and technologies powered by next-generation information technology to transform clinical data into high-quality TCM evidence. Moreover， standardized and shared platforms for TCM clinical data should be accelerated， so as to provide references for the design， implementation， and evaluation of future clinical research on the treatment of the spleen and stomach diseases with TCM.

Objective To analyze the factors affecting the prognosis of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy and construct an individualized prognostic nomogram prediction model. Methods A retrospective analysis was conducted on the clinical data of 385 patients with driver gene-negative, locally advanced or metastatic NSCLC who received first-line immune checkpoint inhibitors. Univariate and multivariate Cox regression analyses were used to identify prognostic risk factors, and a prognostic nomogram model was established. The predictive performance of the model was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves and area under the curve (AUC), and calibration curves. The cutoff value of the nomogram was calculated to stratify patients by risk. Survival curves were calculated by Kaplan-Meier analysis. Results Age (HR=1.775, 95%CI: 1.265-2.490), degree of differentiation (HR=0.365, 95%CI: 0.257-0.519), low PD-L1 expression (HR=0.661, 95%CI: 0.455-0.960), high PD-L1 expression (HR=0.423, 95%CI: 0.297-0.603), SCC-Ag (HR=1.549, 95%CI: 1.109-2.163), and CONUT score (HR=2.527, 95%CI: 1.797-3.554) were independent risk factors affecting overall survival (OS) of patients with NSCLC undergoing immunotherapy. The nomogram prediction model constructed on the basis of these factors had a C-index of 0.767. Time-dependent ROC curves for survival showed that the AUCs for 1-, 2-, and 3-year OS were 0.830, 0.853, and 0.886, respectively. Calibration curves indicated that the nomogram-predicted survival rates were in good agreement with the actual outcomes. The cutoff value for the study’s nomogram prediction model was 136.60 points, and survival curves showed statistically significant differences between different risk groups (P<0.05). Conclusion The nomogram model established in this study can effectively predict the prognosis of patients with driver gene-negative locally advanced or metastatic NSCLC treated with first-line immunosuppressive therapy. It provides a new tool for assessing prognosis and aids clinicians in formulating individualized treatment plans.

Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.

BackgroundObstructive sleep apnea （OSA） represents a prevalent sleep disordered breathing condition characterized by complex pathophysiology. The arousal threshold （ArTH）， a core non-anatomical contributor to OSA pathogenesis， is intimately tied to the disease severity and clinical phenotypes. To date， research regarding factors associated with ArTH has yielded inconsistent findings， and ArTH profiles and disparities across populations with different genetic backgrounds are not fully elucidated. ObjectiveTo explore the differences of ArTH in OSA patients with different genetic backgrounds and analyze the key factors affecting ArTH， thereby providing evidence for understanding OSA pathophysiology and formulating targeted treatment regimens. MethodsA total of 285 patients who met the diagnostic criteria for OSA， as defined by the Multidisciplinary Diagnosis and Treatment Guidelines for Adult Obstructive Sleep Apnea， were retrospectively enrolled in this study. All participants underwent overnight polysomnography （PSG） at the Sleep Medicine Center of Inner Mongolia Mental Health Center from December 2022 to May 2024. Based on the study design， the cohort was stratified into two distinct genetic background subgroups （group A and group B）. Demographic and clinical characteristics， the Epworth Sleepiness Scale （ESS） score， and overnight PSG data were collected. The apnea hypopnea index （AHI）， the lowest pulse oxygen saturation （LSpO₂）， and fraction of hypopneas （F_Hypopneas） were utilized as surrogate indicators to estimate ArTH in OSA patients. The influencing factors of low ArTH were tested by binary Logistic regression analysis. ResultsAmong the 285 OSA patients， there were 227 cases （79.65%） in group A and 58 cases （20.35%） in group B. Comparisons between the two genetic background subgroups revealed no statistically significant differences in the proportion of low ArTH， ESS score， PSG parameters， and the three markers for low ArTH （AHI<30 events/h， LSpO₂>82.5%， F_Hypopneas>58.3%） （P>0.05）. Binary Logistic regression analysis identified sex （OR=2.421， 95% CI： 1.070–5.478）， BMI （OR=0.847， 95% CI： 0.770–0.932）， N1 sleep duration （OR=0.974， 95% CI： 0.963–0.985）， and hypertension （OR=0.348， 95% CI： 0.143–0.848） as independent factors associated with low ArTH in the total cohort. Stratified analysis by genetic backgrounds revealed that sex（OR=3.799， 95% CI： 1.389–10.392）， BMI（OR=0.819， 95% CI：0.723–0.929）， and N1 sleep duration（OR=0.973， 95% CI： 0.961–0.986） were independent factors of low ArTH in group A. In contrast， only N1 sleep duration （OR=0.951， 95% CI： 0.911–0.993） remained a significant factor in group B. ConclusionArthur may have conservative characteristics in patients with OSA with different genetic backgrounds， but the pathophysiological mechanism of OSA may have population heterogeneity. ［Funded by Inner Mongolia Autonomous Region Natural Science Fundation Project （number， 2024QN08050）； Intra-institutional Scientific Research Project of Inner Mongolia Mental Health Center （number， 2022QNWN0010）］

Blood transfusion is an important life-support measure in modern medicine. As clinical demand for transfusion continues to rise, blood supply remains under persistent strain, making the efficient utilization of this precious medical resource a critical component of blood management. Accurate prediction of transfusion needs is of great significance for optimizing blood resource allocation and conserving blood products. Traditional transfusion decision-making relies on clinical experience and simplified scoring systems, which are insufficient to meet the demands of precision medicine. Machine learning (ML) technology can integrate multidimensional data—including demographic characteristics, laboratory indicators, surgical information, and dynamic physiological waveforms—to construct high-performance predictive models, offering a new approach to transfusion prediction. This article systematically reviews the application progress of ML in transfusion prediction across clinical scenarios such as trauma, the perioperative period, and obstetrics. In trauma, ML has been applied to early massive transfusion prediction, prehospital transfusion decision-making, and precise prediction in pediatric trauma. In the perioperative field, applications span specialties including traumatic brain injury, orthopedic surgery, cardiovascular and major vascular surgery, and hepatic surgery. In obstetrics, models can effectively predict postpartum hemorrhage and transfusion requirements associated with cesarean section. Studies have shown that algorithms such as random forest, gradient boosting machines, and deep neural networks achieve area under the receiver operating characteristic curve (AUC) values of 0.83-0.98 in massive transfusion prediction, 0.75-0.97 in perioperative scenarios, and 0.80-0.89 in obstetric transfusion prediction—significantly outperforming traditional scoring tools. However, current studies are generally limited by single-center retrospective designs, insufficient external validation, and inadequate reporting standards; limited model interpretability and challenges in clinical integration further constrain practical translation. Future research should focus on constructing multicenter data cohorts, integrating multimodal data, conducting prospective implementation studies, and deeply embedding models within electronic health record systems, thereby advancing the application of ML to optimize clinical transfusion decision-making.

BackgroundBoth modified Suanzaoren Decoction and estazolam serve as effective treatments for chronic insomnia disorder （CID）. Default mode network （DMN） dysfunction is recognized as the primary pathophysiological mechanism underlying CID. However， it remains unclear whether the two treatments exert their therapeutic effects via convergent modulation of DMN functional connectivity. ObjectiveTo investigate the convergent remodeling characteristics of bidirectional effective connectivity （EC） of core DMN nodes with both the intra-network and the remaining whole-brain regions in CID patients with Yin-deficiency and fire-hyperactivity syndrome following the treatment with modified Suanzaoren Decoction or estazolam， so as to provide neuroimaging evidence for the convergent neural mechanisms underlying the therapeutic effects of both therapies in treating CID. MethodsEighty-two patients diagnosed with CID according to the International Classification of Sleep Disorder， third edition （ICSD-3） were consecutively recruited from the outpatient clinic of the Inner Mongolia Autonomous Region Mental Health Center from October 2020 to September 2023. Based on treatment preference， patients were assigned to receive a 6-week intervention in either the modified Suanzaoren Decoction group （n=52） or the estazolam group （n=30）. Ultimately， 66 patients completed follow-up assessments （modified Suanzaoren Decoction group， n=41； estazolam group， n=25）. All CID patients underwent resting-state functional magnetic resonance imaging scanning before and after treatment. Core DMN nodes including medial prefrontal cortex （mPFC）， bilateral inferior parietal lobule （IPL）， and precuneus （PCUN） were selected as seed regions. Granger causality analysis （GCA） was employed to assess bidirectional EC between the seed regions and both the other intra-DMN nodes and the remaining whole-brain regions. Hepatic and renal function indices were detected pre- and post-treatment to evaluate the safety profiles of both treatments. ResultsAt baseline， significant between-group differences were identified in EC from the left IPL to the left middle fronto-orbital gyrus/gyrus rectus （t=5.24， Z=4.84， voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）， with the modified Suanzaoren Decoction group exhibiting stronger EC than the estazolam group. No significant between-group differences were observed in EC between other core DMN nodes and remaining whole-brain regions （P>0.05）. Within-group pre- to post-treatment comparisons demonstrated consistent connectivity alterations in both groups. Specifically， EC from the left IPL to the supplementary motor area （SMA） decreased after treatment （modified Suanzaoren Decoction group： t=-6.28， Z=5.208； estazolam group： t=-5.58， Z=4.425）. Conversely， EC from the SMA to the left IPL increased （modified Suanzaoren Decoction group： t=5.89， Z=4.968； estazolam group： t=6.15， Z=4.720）. Furthermore， both groups demonstrated reduced EC from the PCUN to the left IPL （modified Suanzaoren Decoction group： t=-5.85， Z=4.94； estazolam group： t=-5.75， Z=4.515）， and elevated EC from the left IPL to the PCUN （modified Suanzaoren Decoction group： t=5.29， Z=4.579； estazolam group： t=4.55， Z=3.826） （voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）. No significant pre- to post-treatment differences were observed in hepatic or renal function indices in either group （P>0.05）. ConclusionIn CID patients with Yin-deficiency and fire-hyperactivity syndrome， both modified Suanzaoren Decoction and estazolam induce convergent bidirectional remodeling of EC between the left IPL and the SMA and the PCUN. ［Funded by Natural Science Fund Project of Inner Mongolia Autonomous Region （number， 2019MS08099）； ClinicalTrials.gov number， NCT06452953］

BackgroundThe functional changes of the default mode network （DMN） are closely related to the onset of major depressive disorders. However， the relationship between the DMN subsystem （core subsystem， dorsomedial prefrontal cortex subsystem， medial temporal lobe subsystem） and symptoms of first-episode major depressive disorder remains unclear. ObjectiveTo investigate abnormal functional connectivity between DMN subsystems and the whole brain in first-episode major depressive disorder patients during the resting-state， and to analyse the correlations between these functional connectivity patterns and clinical symptoms， so as to reveal the potential neural mechanisms from the perspective of DMN subsystem. MethodsFrom September 2020 to September 2023， a total of 64 first-episode outpatients and inpatients meeting the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were enrolled at the Inner Mongolia Autonomous Region Mental Health Center as the study group. During the same period， 54 healthy volunteers matched for age， gender， and years of education were recruited from the community as the control group. Both groups were assessed using the Hamilton Depression Scale-24 item （HAMD-24）. Resting-state functional magnetic resonance images （rs-fMRI） of the two groups were acquired using a Siemens 3.0 T scanner， and differences in functional connectivity between DMN subsystems （core subsystem， dorsomedial prefrontal cortex subsystem， medial temporal lobe subsystem） and the whole brain were compared. The functional connectivity values of brain regions with statistically significant differences between the two groups were extracted. Spearman's rank correlation coefficient analysis was used to investigate the correlation between these functional connectivity values and HAMD-24 scores of the study group. ResultsUltimately， 46 patients and 43 controls completed the study. Compared with the control group， the study group exhibited significantly stronger functional connectivity in the following pathways： between the right superior parietal lobule （core subsystem） and right cerebellar lobule VIII （t=3.954， P<0.05， GRF-corrected）， between the right lateral temporal cortex （dorsomedial prefrontal cortex subsystem） and right cerebellar lobule VIII， right and left hippocampi， right medial， and paracingulate gyrus （t=4.595， 4.208， 5.200， 4.038， P<0.05， GRF-corrected）， and between the temporoparietal junction （dorsomedial prefrontal cortex subsystem） and left lingual gyrus and right cerebellar lobule VIII （t=3.557， 4.274， P<0.05， GRF-corrected）. Conversely， weaker functional connectivity was observed between the right inferior frontal gyrus and left gyrus rectus （t=-3.824， P<0.05， GRF-corrected）. Furthermore， within the study group， the functional connectivity values between the right lateral temporal cortex and right hippocampus， as well as between the temporoparietal junction and right cerebellar lobule VIII， were both negatively correlated with the HAMD-24 cognitive impairment factor score （r=-0.306， -0.318， P<0.05）. ConclusionIncreased functional connectivity between the DMN （specifically its core and dorsomedial prefrontal cortex subsystems） and cerebellum， partial limbic system， and lingual gyrus may be associated with the neuropathology of first-episode major depressive disorder. Furthermore， alterations in functional connectivity between the dorsomedial prefrontal cortex subsystem and both the cerebellum and hippocampus in these patients may be related to cognitive function. ［Funded by 2019 Annual Inner Mongolia Autonomous Region Natural Science Foundation Project （number， 2019MS03038）； 2023 Annual Inner Mongolia Autonomous Region Natural Science Foundation Project （number， 2023MS08028）］

Objective:To explore the characteristics of emotional contagion in the elderly and analyze its rela-tionship with cognitive level.Methods:Totally 33 elderly people and 29 young people were recruited in experiment 1.By watching emotional videos,data on facial muscle activity and subjective emotion scores were collected to ex-plore the characteristics of emotional contagion in the elderly.Experiment 2 recruited 16 elderly people with mild cognitive impairment and 18 healthy elderly people to further explore the impact of cognitive ability on emotional contagion in the elderly.Results:There were no significant differences in muscle activity data between the elderly and young people(experiment 1)and between the elderly with mild cognitive impairment and elderly with normal cognitive level(experiment 2)(Ps＞0.05).The elderly group scored higher on internal emotional experience of happy emotions than the young people(P＜0.05).The elderly with mild cognitive impairment scored higher on in-ternal emotional experience of sad emotions than the elderly with normal cognitive level(P＜0.05).Conclusion:The emotional contagion characteristics of the elderly are characterized by a stronger ability to contaminate happy e-motions.Differences in cognitive levels may affect the process of emotional contagion in the elderly,elderly people with mild cognitive impairment are more susceptible to sad emotions.

Objective:To predict the occurrence of chronic radiation enteritis (CRE) in cervical cancer patients by developing a prediction model based on the combination of radiomic features derived from magnetic resonance imaging (MRI) scans and clinical parameters, in order to provide a reference for clinicians to determine the prognosis of these patients and offer them individualized diagnosis and treatment.Methods:A retrospective analysis was conducted on 111 cervical cancer patients who received radical radiotherapy at the First Affiliated Hospital of Anhui Medical University. Radiological features were extracted from the T1-weighted MRI images of local lesions of cervical cancer obtained before the radiotherapy. Features were selected using the least absolute shrinkage and selection operator (LASSO) to obtain the radiomics score. The radiomics scores and clinical parameters were assessed using univariate and multivariate logistic regression analyses, followed by the establishment of nomograms. The ability of radiomics to achieve CRE prediction was assessed using the area under the curve (AUC) and the calibration and decision curves.Results:Multivariate logistic regression analysis result revealed that the independent risk factors for identifying CRE in patients included radiomics score ( HR: 17.457, 95% CI: 5.540-55.009, P<0.001), tumor volume ( HR: 3.617, 95% CI: 1.293-10.115, P=0.014), and pelvic lymph node metastasis ( HR: 3.559, 95% CI: 1.013-12.501, P=0.048). The model combining radiomics and clinical data demonstrated high performance, with its AUCs of the training and validation groups (0.888 and 0.870, respectively) higher than those of the radiomics model (0.842 and 0.804, respectively) and the clinical data model (0.721 and 0.704, respectively). The analyses of calibration and decision curves confirmed the application value of clinical radiomic nomograms. Conclusions:The model combining radiomics and clinical data allows for accurate CRE prediction. Therefore, radiomic features have the potential to serve as a promising imaging biomarker for CRE.

Objective:To explore the feasibility of the new auxiliary analysis software in chromosomal aberration analysis of radiation workers during occupational health examinations.Methods:Health examination data of 2 469 radiation workers in Henan province were collected. Manual analysis of chromosomal aberrations in peripheral blood lymphocytes was conducted using the new auxiliary software and the Ikaros software. Then, the chromosomal aberrations detected using both software tools were compared.Results:The new auxiliary software yielded a lower chromosomal aberration rate among radiation workers compared with the Ikaros software [(0.314 ± 0.014)% vs. (0.391 ± 0.022)%, χ2 = 9.24, P = 0.002]. Notably, the new auxiliary software yielded a significantly lower rate of acentric fragments (ace) [(0.136 ± 0.009)% vs. (0.209 ± 0.020)%, χ2= 17.76, P < 0.001]. However, no statistically significant differences were observed between the result of the two software tools in the rates of dicentrics plus rings (dic + r) and translocations ( P > 0.05). According to the GBZ/T 248-2014 standard, the differences in abnormality rates of chromosomal aberrations between the two groups had no statistically significance ( P > 0.05), with both groups showing an abnormality rate of 0 for ace. Furthermore, the new auxiliary software could double the detection efficiency. Among pre-service radiation workers of various occupations, the differences in the chromosomal aberrations detected using the two software tools exhibited statistical significance ( χ2 = 10.26, P = 0.001). In contrast, the differences in the chromosomal aberrations among in-service and post-service radiation workers had no statistically different significance ( P>0.05). The Poisson regression analysis result demonstrated that the rate of chromosomal aberrations excluding ace was affected by age ( z = 2.73, P = 0.006), while gender, analysis method, service status, and occupation had no impact. Conclusions:The two software tools yielded largely consistent result in detecting chromosomal aberrations induced by exposure to ionizing radiation. Notably, the new auxiliary software can significantly improve detection efficiency, indicating the feasibility of applying it to chromosomal aberration analysis among radiation workers.