Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Astrocytes are a crucial type of glial cells in the central nervous system, not only maintaining brain homeostasis, but also actively participating in the transmission of information within the brain. Astrocytes have a complex structure that includes the soma, various levels of processes, and end-feet. With the advancement of genetically encoded calcium indicators and imaging technologies, researchers have discovered numerous localized and small calcium activities in the fine processes and end-feet. These calcium activities were termed as microdomain calcium activities, which significantly differ from the calcium activities in the soma and can influence the activity of local neurons, synapses, and blood vessels. This article elaborates the detection and analysis, characteristics, sources, and functions of microdomain calcium activities, and discusses the impact of aging and neurodegenerative diseases on these activities, aiming to enhance the understanding of the role of astrocytes in the brain and to provide new insights for the treatment of brain disorders.
Astrocytes/cytology* ; Humans ; Animals ; Calcium/metabolism* ; Calcium Signaling/physiology* ; Brain/physiology* ; Aging/physiology* ; Membrane Microdomains/physiology* ; Neurodegenerative Diseases/physiopathology*

OBJECTIVES: We propose a multimodal model integrating social media text and image data for automated assessment of psychological stress in college students to support the development of intelligent mental health services in higher education institutions. METHODS: Based on deep learning technology, we designed an evaluation framework comprising a text sentiment modeling module, an image sentiment modeling module, and a multimodal fusion prediction module. Text sentiment features were extracted using Bi-LSTM, and image semantic cues were extracted via U-Net. A feature concatenation strategy was used to enable cross-modal semantic collaboration to achieve automatic identification of 3 psychological stress levels: mild, moderate, and severe. We constructed a multimodal annotated dataset using social platform data from 1577 students across multiple universities in Guangdong Province. After data cleaning, 252 samples were randomly selected for model training and testing. RESULTS: In the 3-classification task, the model demonstrated outstanding performance on the test set, and achieved an accuracy of 92.86% and an F1 score of 0.9276, exhibiting excellent stability and consistency. Confusion matrix analysis further revealed the model's ability to effectively distinguish between different pressure levels. CONCLUSIONS The multimodal psychological stress assessment model developed in this study effectively integrates unstructured social behavior data to enhance the scientific rigor and practical applicability of psychological state recognition, and thus provides support for developing intelligent psychological service systems.
Humans ; Stress, Psychological/diagnosis* ; Students/psychology* ; Universities ; Social Media ; Deep Learning

The complement system comprises intrinsic complement components,complement regulatory pro-teins,and complement receptors.Complement activation plays a role in promoting the sensitization of peripheral pain re-ceptors,enhancing immune cell activity,and participating in the regulation of axon regeneration after nerve injury.The in-teraction of the complement system contributes to the development and maintenance of pathological pain,affecting the dor-sal root ganglion neurons,spinal dorsal horn,and brain.Consequently,targeting the complement system holds promise as a therapeutic approach for neuropathic pain treatment.This paper reviews the progress in understanding the functions of the complement system and its implications in pathological pain,offering valuable insights for the future development of targeted drug therapies.

【Objective】 To investigate the expression of optineurin (OPTN) in multiple myeloma (MM) and explore the mechanism and clinical value of OPTN gene in the occurrence and development of MM. 【Methods】 In this study, three gene expression omnibus (GEO) data sets were used to analyze the expression level of OPTN in MM. Clinical bone marrow samples of MM patients were collected. qRT-PCR was used to further verify the expression of OPTN in MM patients. The Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to analyze the value of OPTN in the prognosis and diagnosis of MM. At the same time, MM transcriptome data were downloaded from the Cancer Genome Atlas (TCGA) database. According to the median boundary of OPTN mRNA expression level, the MM patients were divided into OPTN high- and low-expression groups. In order to investigate the possible molecular mechanisms of OPTN in MM, gene set enrichment analysis (GSEA) was made after the differentially expressed genes were filtered using the limma package of the R language. 【Results】 The expression level of OPTN was significantly lower in MM tissues than in normal tissues (P<0.05). OPTN expression level was significantly correlated with International Staging System (ISS) in MM patients (P<0.05). ROC results showed that the expression level of OPTN could distinguish between normal and MM patients. Survival analysis showed that the overall survival (OS) of patients with low OPTN expression was significantly lower than that of patients with high OPTN expression (P<0.05). GO, KEGG and GSEA enrichment analyses indicated that OPTN might affect apoptosis and autophagy, and regulate cellular immune response by regulating Nod-like receptors, NF-κB, TNF and RAS/MAPK pathways. 【Conclusion】 Low expression of OPTN in MM is associated with poor prognosis of patients, and thus may be an important potential biomarker for the diagnosis and treatment of MM.

Background Due to the prominent particularity of medical work,nurses are prone to developing depression,which not only poses a considerable threat to the physical and mental health of nurses,but also affects the quality of nursing to some extent.Occupational stress is a known contributor to depression in nurses,whereas relatively little research has been done to investigate the underlying mediation path.Objective To explore the mediation effect of perceived organizational support and psychological capital on the relationship between occupational stress and depression among nurses,and to provide theoretical references for the prevention and treatment of occupational stress-induced depression in nurses.Methods From March to August 2019,a stratified random sampling method was utilized to select a sample size of 720 nurses in each department of a grade A tertiary hospital in Shandong Province.All subjects were assessed using Effort-Reward Imbalance Questionnaire(ERI),Perceived Organization Support Questionnaire(POS),Psychological Capital Questionnaire(PCQ)and Center for Epidemiologic Studies Depression Scale(CES-D).Pearson correlation was adopted to examine the correlation among above scales,and multilevel mediation analyses were conducted with model 6 in Process macro(version 3.3)for SPSS 26.0 using Bootstrap re-sampling method.Results A total of 658 nurses(91.39%)completed the effective questionnaire survey.ERI score was positively correlated with CES-D score(r=0.499,P<0.01),and negatively correlated with POS and PCQ scores(r=-0.318,-0.275,P<0.01).POS score was positively correlated with PCQ score(r=0.455,P<0.01),and negatively correlated with CES-D score(r=-0.401,P<0.01).PCQ score was negatively correlated with CES-D score(r=-0.567,P<0.01).The total effect value of occupational stress on depression was 0.466(95%CI:0.399～0.534).Perceived organizational support(indirect effect value of 0.027,95%CI:0.006～0.057)and psychological capital(indirect effect value of 0.059,95%CI:0.013～0.120),separately from each other,mediated the relationship between occupational stress and depression,and a chained mediation effect of perceived organizational support and psychological capital was also demonstrated(indirect effect value of 0.051,95%CI:0.031～0.082),accounting for 10.94%of the total effect.Conclusion Occupational stress is a influencing factor of nurses' depression,which can affect the occurrence of depression both directly and indirectly through either separate or chained mediation of perceived organizational support and psychological capital.

Background::With an increasing proportion of multiparas, proper interpregnancy intervals (IPIs) are urgently needed. However, the association between IPIs and adverse perinatal outcomes has always been debated. This study aimed to explore the association between IPIs and adverse outcomes in different fertility policy periods and for different previous gestational ages.Methods::We used individual data from China’s National Maternal Near Miss Surveillance System between 2014 and 2019. Multivariable Poisson models with restricted cubic splines were used. Each adverse outcome was analyzed separately in the overall model and stratified models. The stratified models included different categories of fertility policy periods (2014–2015, 2016–2017, and 2018–2019) and infant gestational age in previous pregnancy (<28 weeks, 28–36 weeks, and ≥37 weeks).Results::There were 781,731 pregnancies enrolled in this study. A short IPI (≤6 months) was associated with an increased risk of preterm birth (OR [95% CI]: 1.63 [1.55, 1.71] for vaginal delivery [VD] and 1.10 [1.03, 1.19] for cesarean section [CS]), low Apgar scores and small for gestational age (SGA), and a decreased risk of diabetes mellitus in pregnancy, preeclampsia or eclampsia, and gestational hypertension. A long IPI (≥60 months) was associated with an increased risk of preterm birth (OR [95% CI]: 1.18 [1.11, 1.26] for VD and 1.39 [1.32, 1.47] for CS), placenta previa, postpartum hemorrhage, diabetes mellitus in pregnancy, preeclampsia or eclampsia, and gestational hypertension. Fertility policy changes had little effect on the association of IPIs and adverse maternal and neonatal outcomes. The estimated risk of preterm birth, low Apgar scores, SGA, diabetes mellitus in pregnancy, and gestational hypertension was more profound among women with previous term births than among those with preterm births or pregnancy loss.Conclusion::For pregnant women with shorter or longer IPIs, more targeted health care measures during pregnancy should be formulated according to infant gestational age in previous pregnancy.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

Objective The items of quality of life scale for premature ovarian insufficiency were screened using the Delphi method,thus to provide a basis for the development of the scale.Methods The core researcher group of scale development was formed firstly,and then the theoretical framework of the scale was constructed and the original item pool was established on the basis of previous literature analysis,medical record review and patient interview,Secondly,the expert consultation questionnaire was formulated,the experts were screened,and two rounds of expert investigation were conducted by the Delphi method.Finally,the survey results were statistically analyzed,the expert opinions were sorted out,and the items were screened.Results A total of 15 experts were selected,and they were from 9 provinces or municipalities directly under the central government,exerting certain discipline representativeness and authority.The two rounds of expert investigation by Delphi method were conducted by issuing 15 questionnaires in each round of expert investigation,the positive coefficient of the experts was all 100%,the authority coefficient of the experts was 0.970 and 0.963 respectively,and the Kendall's W coefficient was 0.236 and 0.381 respectively(P＜0.05).Finally,31 items(18 related with the physiological domain,8 related with the psychological domain and 5 related with the social domain)and 2 overall-evaluation items were determined.Conclusion The experts participating in the Delphi method have high authority and enthusiasm.The Kendall's W coefficient of the second-round expert investigation is higher than that of the first-round expert investigation,the experts'opinions reach unanimity,and the results are more reliable.The results of item screening of TCM quality of life scale for premature ovarian insufficiency can provide reference for the subsequent evaluation and research of the scale.