Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Norovirus is the global leading cause of epidemic and endemic acute gastroenteritis in people of all ages.To inves-tigate the genetic diversity of GⅡ genogroup noroviruses linked to clustered infections in northeast Chongqing,we collected anal swabs or environmental smears from 11 norovirus outbreaks during 2021-2022.Norovirus RNA was detected by quantitative real-time PCR(qRT-PCR),and partial viral RdRp/capsid genes were amplified by reverse transcription PCR(RT-PCR)and sequenced.Among samples from 11 outbreaks in 4 districts and counties,55 strains of GⅡ genogroup norovirus were detected.Six genotypes were identified with an online norovirus genotyping tool(http://www.rivm.nl/mpf/norovirus/typingtool).Genotype GⅡ.17[P17]was associated with four outbreaks;the co-circulating GⅡ.17[P17]and GⅡ.1[P16]caused another out-break;GⅡ.6[P7]and GⅡ.8[P8]respectively were linked to two outbreaks;and GⅡ.3[P12]and GⅡ.2[P16]respectively ac-counted for one outbreak.Phylogenetic analysis also indicated that 55 GⅡ genogroup strains formed five clusters,with norovir-uses of identical genotypes from diverse events belonging to the same cluster,and that genetically distinct genotypes from di-verse events belonged to different clusters.Therefore,our results revealed that multiple genotypes associated with norovirus outbreaks were circulating in northeast Chongqing,and GⅡ.17[P17]was the predominant genotype linked to these out-breaks during 2021-2022.Most norovirus outbreak events were caused by single sources,and genetic relationships were demonstrated among noroviruses of identical genotypes from diverse events.

Objective:To evaluate the long-term efficacy of percutaneous microwave ablation (MWA) therapy for hepatocellular carcinoma.Methods:2054 cases with Barcelona Clinic Liver Cancer (BCLC) stage 0~B at the Fifth Medical Center of the Chinese People's Liberation Army General Hospital from January 2006 to September 2020 were retrospectively collected. All patients were followed up for at least 2 years. The primary endpoint of overall survival and secondary endpoints (tumor-related survival, disease-free survival, and postoperative complications) of patients treated with ultrasound-guided percutaneous MWA were analyzed. Kaplan-Meier method was used for stratified survival rate analysis. Fine-and-Gray competing risk model was used to analyze overall survival.Results:A total of 5 503 HCC nodules [mean tumor diameter (2.6±1.6) cm] underwent 3 908 MWAs between January 2006 and September 2020, with a median follow-up time of 45.6 (24.0 -79.2) months.The technical effectiveness rate of 5 375 tumor nodules was 97.5%. The overall survival rates at 5, 10, and 15-years were 61.6%, 38.8%, and 27.0%, respectively. The tumor-specific survival rates were 67.1%, 47.2%, and 37.7%, respectively. The free tumor survival rates were 25.8%, 15.7%, and 9.9%, respectively. The incidence rate of severe complications was 2.8% (108/3 908). Further analysis showed that the technical effectiveness and survival rate over the passing three time periods from January 2006-2010, 2011-2015, and 2016-September 2020 were significantly increased, with P ?

OBJECTIVE: To observe the levels of soluble programmed cell death protein 1 (sPD-1) and soluble programmed cell death ligand 1 (sPD-L1) in peripheral blood of lymphoma patients, and reveal their clinical significances. METHODS: The peripheral blood specimens and clinical data of 64 newly diagnosed lymphoma patients and 30 healthy volunteers were collected. The levels of sPD-1 and sPD-L1 were detected by enzyme-linked immunosorbent assay (ELISA), and their correlations with clinical characteristics of the patients including pathological type, stage, lactate dehydrogenase (LDH) level, T cell subsets were analyzed. RESULTS: The levels of both sPD-1 and sPD-L1 in peripheral blood of lymphoma patients were higher than those of normal controls (P <0.05). There were no significant differences in sPD-1 and sPD-L1 levels in peripheral blood between Hodgkin lymphoma and non-Hodgkin lymphoma patients. Different pathological subtypes of lymphoma had different levels of sPD-1. The level of sPD-1 in patients with T-cell lymphoma was higher than that in patients with B-cell lymphoma (P =0.001). The levels of both sPD-1 and sPD-L1 in patients with Ann Arbor stage III and IV were higher than those in patients with stage I and II (P <0.05). The level of sPD-L1 in patients with abnormally increased LDH was higher than that in patients with normal LDH (P =0.001), but there was no significant difference in sPD-1 level. T cell subset analysis showed that the level of sPD-L1 was negatively correlated to CD4⁺ T cell content (r =-0.265). CONCLUSION The levels of sPD-1 and sPD-L1 in peripheral blood of lymphoma patients are related to the pathological type, Ann Arbor stage, LDH content and T cell subsets, and will be potential biomarkers in predicting the prognosis of lymphoma.
Humans ; Clinical Relevance ; Prognosis ; T-Lymphocyte Subsets/metabolism* ; Lymphoma, T-Cell, Peripheral ; Enzyme-Linked Immunosorbent Assay ; B7-H1 Antigen/metabolism*

Aim To predict the targets of Modified Danggui Shaoyao San ( MDSS) in the treatment of chronic atrophic gastritis ( CAG) based on network pharmacology and vertify the results based on experim-ention. Methods TCMSP, SWISS TARGETS, GENE CARDS and OMIM databases were used to screen the therapeutic targets of MDSS for CAG. STRING database and Cytoscape software were used to construct the protein interaction network and screen the core targets. Metascape database was used for GO analysis and KEGG enrichment pathways. And molecular docking was used for target validation. CAG rat model was pre¬pared by N-methyl-N'-nitroso-N-nitroguanidine free drink combined with sodium salicylate gastric lavage. The pathology of rat gastric mucosa was observed by hematoxylin-eosin staining,and the ultrastructure of ep¬ithelial cells was observed by transmission electron mi-croscopy. The serum IL-6 and IL-10 content was detected by enzyme-linked immunosorbent assay, and the expression of JAK2, STAT3 , p-STAT3 , c-MYC mRNA and protein in rats was detected by qPCR and Western blot. Results MDSS acted on 189 targets, mainly involved in response to oxidative stress and apoptotic signaling pathway. KEGG analysis related to pathways in cancer and JAK-STAT signaling pathway. The experimental results showed that the MDSS could improve the degree of atrophy of gastric mucosa in CAG rats and improve the status of epithelial cells, down-regulate the serum IL-6 content of CAG rats, up-regulate the IL-10 content, and reduce the expression of JAK2, STAT3 , p-STAT3 , c-MYC mRNA and protein in gastric mucosa with statistical significance. Conclusions MDSS treats CAG through multiple active ingredients, targets, and pathways, the mechanism of which may be related to the inhibition of the JAK2/STAT3 signaling pathway.