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.

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 explore the relationship between levels of vascular endothelial growth factor(VEGF),insulin-like growth factor 1(IGF-1),and transforming growth factor-β1(TGF-β1)in the synovial fluid of children with avascular necrosis of the femoral head(also known as Perthes disease)and the efficacy of postoperative revascularization,aiming to provide a basis for subsequent diagnosis and treatment.Methods A retrospective study was conducted on 262 children with Perthes disease admitted to the Affiliated Hospital of Gansu University of Chinese Medicine from January 2023 to June 2024.Based on postoperative revascularization efficacy,patients were divided into good revascularization group(n=228)and poor revascularization group(n=34).For poor revascularization group,a 1:2 matched case-control design was used to select 68 age-matched children with hip synovitis who underwent hip joint fluid puncture as control group.Additionally,82 children with Perthes disease treated at the hospital from June 2024 to January 2025 were enrolled as a validation cohort for nomogram model verification.The expression levels of VEGF,IGF-1 and TGF-β1 in the synovial fluid of three groups were compared.Confounding biases were controlled through univariate and stratified analyses.Binary logistic regression analysis was used to identify independent factors affecting the revascularization effect.R software was utilized to draw and verify the nomogram model for predicting the postoperative revascularization effect.Results The levels of VEGF,IGF-1 and TGF-β1 in the synovial fluid of children in poor revascularization group were all higher than those in control group and good revascularization group(P<0.05).After three types of reconstructive surgeries,the levels of VEGF,IGF-1 and TGF-β1 in the synovial fluid of children with poor revascularization were all higher than those in children with good revascularization(P<0.05);however,there was no statistically significant difference in the above indicators among different surgical types(P>0.05).Binary logistic regression analysis showed that the levels of VEGF,IGF-1,and TGF-β1 in the synovial fluid were independent risk factors for poor postoperative revascularization in children with Perthes disease.The area under the ROC curve of the nomogram model established accordingly for predicting poor postoperative revascularization in children with Perthes disease was 0.875(95%CI 0.805-0.945),with a sensitivity of 0.874 and a specificity of 0.851.Moreover,the calibration curve and decision curve analysis(DCA)indicated that the model had good clinical applicability.Conclusions The increased levels of VEGF,IGF-1 and TGF-β1 in synovial fluid are associated with poor postoperative revascularization in children with Perthes disease.These three factors are expected to become prognostic indicators for children with Perthes disease.

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 ?

This review aims to sum up how Non-coding RNAs (ncRNAs) regulate the development of periodontitis and provides a new perspective for understanding the pathogenesis of periodontitis. We explored the ncRNA's dual role in the development of periodontitis by summarizing evidence from previous in vivo and in vitro studies as well as clinical samples. In our review, the downregulation of 18 miRNAs, 22 lncRNAs and 10 circRNAs demonstrates protective roles in periodontitis. In contrast, the expression of other 11 miRNAs, 7 lncRNAs and 6 circRNAs are upregulated in periodontitis, which promote the progression of periodontitis. These dysregulated ncRNAs exert their protective or destructive roles by mainly influencing cell proliferation, differentiation and apoptosis via cross-talking with various molecules or signaling pathways. Our findings suggested which and how ncRNAs promote or delay the progression of periodontitis, which may greatly contribute to diagnose and therapy development of periodontitis based on ncRNAs in the future.
Humans ; RNA, Long Noncoding/genetics* ; RNA, Circular ; MicroRNAs ; Periodontitis/genetics* ; Apoptosis