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

Aim To express and purify recombinant hCGH-CTP fusion protein in high-density suspension culture of Chinese hamster ovary cells (CHO-S), and to verify the lipid accumulation effect of rhCGH-CTP on 3T3-L1 mature adipocytes. Methods The recombinant protein expression vector (pcDNA3. 1-rhCGH-CTP) was constructed, achieved by fusing the human glycoprotein hormone beta 5/alpha 2 cDNA with CTP Linker. The expression plasmid was transiently transfected into the suspended CHO-S to express rhCGH-CTP protein and then purified, and the protein biological activity was verified. Intervention with 3T3-L1 mature adipocyte cells for 24 h was performed to detect the changes of intracellular triglyceride (TG) level. Results Western blot results showed that rhCGH-CTP protein was successfully expressed in CHO-S cells, and the yield was up to 715. 4 mg • L~ . The secreted protein was purified by AKTA pure system with higher purity that was up to 90% as identified by SDS-PAGE. In addition, the intracellular cAMP content of mature adipocytes with high expression of TSHR gene significantly increased after intervention with different concentrations of rhCGH-CTP protein by ELISA kit, indicating that rhCGH-CTP protein had biological activity. Oil red 0 staining showed that compared with the control group, the lipid content of mature adipocytes in the intervention groups with different concentrations of rhCGH-CTP protein significantly decreased (P < 0. 05) . Conclusions The rhCGH-CTP protein has been successfully expressed and purified with biological activity, and effectively reduce TG. This research provides an important theoretical basis for further revealing the physiological role of CGH protein and its potential application in clinical practice.

Umbilical cord mesenchymal stem cells (UC-MSCs) have been widely used in regenerative medicine, but there is limited research on the stability of UC-MSCs formulation during production. This study aims to assess the stability of the cell stock solution and intermediate product throughout the production process, as well as the final product following reconstitution, in order to offer guidance for the manufacturing process and serve as a reference for formulation reconstitution methods. Three batches of cell formulation were produced and stored under low temperature (2-8 ℃) and room temperature (20-26 ℃) during cell stock solution and intermediate product stages. The storage time intervals for cell stock solution were 0, 2, 4, and 6 h, while for intermediate products, the intervals were 0, 1, 2, and 3 h. The evaluation items included visual inspection, viable cell concentration, cell viability, cell surface markers, lymphocyte proliferation inhibition rate, and sterility. Additionally, dilution and culture stability studies were performed after reconstitution of the cell product. The reconstitution diluents included 0.9% sodium chloride injection, 0.9% sodium chloride injection + 1% human serum albumin, and 0.9% sodium chloride injection + 2% human serum albumin, with dilution ratios of 10-fold and 40-fold. The storage time intervals after dilution were 0, 1, 2, 3, and 4 h. The reconstitution culture media included DMEM medium, DMEM + 2% platelet lysate, 0.9% sodium chloride injection, and 0.9% sodium chloride injection + 1% human serum albumin, and the culture duration was 24 h. The evaluation items were viable cell concentration and cell viability. The results showed that the cell stock solution remained stable for up to 6 h under both low temperature (2-8 ℃) and room temperature (20-26 ℃) conditions, while the intermediate product remained stable for up to 3 h under the same conditions. After formulation reconstitution, using sodium chloride injection diluted with 1% or 2% human serum albumin maintained a viability of over 80% within 4 h. It was observed that different dilution factors had an impact on cell viability. After formulation reconstitution, cultivation in medium with 2% platelet lysate resulted in a cell viability of over 80% after 24 h. In conclusion, the stability of cell stock solution within 6 h and intermediate product within 3 h meets the requirements. The addition of 1% or 2% human serum albumin in the reconstitution diluent can better protect the post-reconstitution cell viability.

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.

Decoction is the most commonly used dosage form in the clinical treatment of traditional Chinese medicine (TCM). During boiling, the violent movement of various active ingredients in TCM creates molecular forces such as hydrogen bonding, π-π stacking, hydrophobic interactions and electrostatic interactions, which results in the formation of self-assembled aggregates in decoction (SADs), including particles, gels, fibers, etc. It was found that SADs widely existed in decoction with biological activities superior to both effective monomers and their physical mixtures, providing a new idea to reveal the pharmacodynamic material basis of Chinese herbal medicine from the perspective of component interactions-phase structure. Recently, SADs have become a novel focus of research in TCM. This paper reviewed their relevant studies in recent years and found some issues to be concerned in the research, such as the polydispersity of decoction system, instability of active ingredient interactions during boiling, uncertainty of the aggregates self-assembly rules, and stability, purity, yield of the products. In this regard, some solutions and new ideas were presented for the integrated development and clinical application of SADs.

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.

【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.