Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

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.

Macrophages are innate immune cells connected with the development of inflammation. Retinoic acid has previously been proved to have anti-inflammatory and anti-arthritic properties. However, the exact mechanism through which retinoic acid modulates arthritis remains unclear. This study aimed to investigate whether retinoic acid ameliorates rheumatoid arthritis by modulating macrophage polarization. This study used retinoic acid to treat mice with adjuvant arthritis and evaluated anti-inflammatory effects by arthritis score, thermal nociceptive sensitization test, histopathologic examination and immunofluorescence assays. In addition, its specific anti-arthritic mechanism was investigated by flow cytometry, cell transfection and inflammatory signaling pathway assays in RAW264.7 macrophages in vitro. Retinoic acid significantly relieved joint pain and attenuated inflammatory cell infiltration in mice. Furthermore, this treatment modulated peritoneal macrophage polarization, increased levels of arginase 1, as well as decreased inducible nitric oxide synthase expression. In vitro, we verified that retinoic acid promotes macrophage transition from the M1 to M2 type by upregulating mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) expression and inhibiting P38, JNK and ERK phosphorylation in lipopolysaccharide-stimulated RAW264.7 cells. Notably, the therapeutic effects of retinoic acid were inhibited by MKP-1 knockdown. Retinoic acid exerts a significant therapeutic effect on adjuvant arthritis in mice by regulating macrophage polarization through the MKP-1/MAPK pathway, and play an important role in the treatment of rheumatic diseases.

Macrophages are innate immune cells connected with the development of inflammation. Retinoic acid has previously been proved to have anti-inflammatory and anti-arthritic properties. However, the exact mechanism through which retinoic acid modulates arthritis remains unclear. This study aimed to investigate whether retinoic acid ameliorates rheumatoid arthritis by modulating macrophage polarization. This study used retinoic acid to treat mice with adjuvant arthritis and evaluated anti-inflammatory effects by arthritis score, thermal nociceptive sensitization test, histopathologic examination and immunofluorescence assays. In addition, its specific anti-arthritic mechanism was investigated by flow cytometry, cell transfection and inflammatory signaling pathway assays in RAW264.7 macrophages in vitro. Retinoic acid significantly relieved joint pain and attenuated inflammatory cell infiltration in mice. Furthermore, this treatment modulated peritoneal macrophage polarization, increased levels of arginase 1, as well as decreased inducible nitric oxide synthase expression. In vitro, we verified that retinoic acid promotes macrophage transition from the M1 to M2 type by upregulating mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) expression and inhibiting P38, JNK and ERK phosphorylation in lipopolysaccharide-stimulated RAW264.7 cells. Notably, the therapeutic effects of retinoic acid were inhibited by MKP-1 knockdown. Retinoic acid exerts a significant therapeutic effect on adjuvant arthritis in mice by regulating macrophage polarization through the MKP-1/MAPK pathway, and play an important role in the treatment of rheumatic diseases.

Macrophages are innate immune cells connected with the development of inflammation. Retinoic acid has previously been proved to have anti-inflammatory and anti-arthritic properties. However, the exact mechanism through which retinoic acid modulates arthritis remains unclear. This study aimed to investigate whether retinoic acid ameliorates rheumatoid arthritis by modulating macrophage polarization. This study used retinoic acid to treat mice with adjuvant arthritis and evaluated anti-inflammatory effects by arthritis score, thermal nociceptive sensitization test, histopathologic examination and immunofluorescence assays. In addition, its specific anti-arthritic mechanism was investigated by flow cytometry, cell transfection and inflammatory signaling pathway assays in RAW264.7 macrophages in vitro. Retinoic acid significantly relieved joint pain and attenuated inflammatory cell infiltration in mice. Furthermore, this treatment modulated peritoneal macrophage polarization, increased levels of arginase 1, as well as decreased inducible nitric oxide synthase expression. In vitro, we verified that retinoic acid promotes macrophage transition from the M1 to M2 type by upregulating mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) expression and inhibiting P38, JNK and ERK phosphorylation in lipopolysaccharide-stimulated RAW264.7 cells. Notably, the therapeutic effects of retinoic acid were inhibited by MKP-1 knockdown. Retinoic acid exerts a significant therapeutic effect on adjuvant arthritis in mice by regulating macrophage polarization through the MKP-1/MAPK pathway, and play an important role in the treatment of rheumatic diseases.

Macrophages are innate immune cells connected with the development of inflammation. Retinoic acid has previously been proved to have anti-inflammatory and anti-arthritic properties. However, the exact mechanism through which retinoic acid modulates arthritis remains unclear. This study aimed to investigate whether retinoic acid ameliorates rheumatoid arthritis by modulating macrophage polarization. This study used retinoic acid to treat mice with adjuvant arthritis and evaluated anti-inflammatory effects by arthritis score, thermal nociceptive sensitization test, histopathologic examination and immunofluorescence assays. In addition, its specific anti-arthritic mechanism was investigated by flow cytometry, cell transfection and inflammatory signaling pathway assays in RAW264.7 macrophages in vitro. Retinoic acid significantly relieved joint pain and attenuated inflammatory cell infiltration in mice. Furthermore, this treatment modulated peritoneal macrophage polarization, increased levels of arginase 1, as well as decreased inducible nitric oxide synthase expression. In vitro, we verified that retinoic acid promotes macrophage transition from the M1 to M2 type by upregulating mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) expression and inhibiting P38, JNK and ERK phosphorylation in lipopolysaccharide-stimulated RAW264.7 cells. Notably, the therapeutic effects of retinoic acid were inhibited by MKP-1 knockdown. Retinoic acid exerts a significant therapeutic effect on adjuvant arthritis in mice by regulating macrophage polarization through the MKP-1/MAPK pathway, and play an important role in the treatment of rheumatic diseases.

Macrophages are innate immune cells connected with the development of inflammation. Retinoic acid has previously been proved to have anti-inflammatory and anti-arthritic properties. However, the exact mechanism through which retinoic acid modulates arthritis remains unclear. This study aimed to investigate whether retinoic acid ameliorates rheumatoid arthritis by modulating macrophage polarization. This study used retinoic acid to treat mice with adjuvant arthritis and evaluated anti-inflammatory effects by arthritis score, thermal nociceptive sensitization test, histopathologic examination and immunofluorescence assays. In addition, its specific anti-arthritic mechanism was investigated by flow cytometry, cell transfection and inflammatory signaling pathway assays in RAW264.7 macrophages in vitro. Retinoic acid significantly relieved joint pain and attenuated inflammatory cell infiltration in mice. Furthermore, this treatment modulated peritoneal macrophage polarization, increased levels of arginase 1, as well as decreased inducible nitric oxide synthase expression. In vitro, we verified that retinoic acid promotes macrophage transition from the M1 to M2 type by upregulating mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) expression and inhibiting P38, JNK and ERK phosphorylation in lipopolysaccharide-stimulated RAW264.7 cells. Notably, the therapeutic effects of retinoic acid were inhibited by MKP-1 knockdown. Retinoic acid exerts a significant therapeutic effect on adjuvant arthritis in mice by regulating macrophage polarization through the MKP-1/MAPK pathway, and play an important role in the treatment of rheumatic diseases.

Objective: To explore the correlation between traditional Chinese medicine (TCM) constitution and depressive symptom among school aged children and adolescents, so as to provide evidences for informing constitution based regulation and prevention of depressive symptom. Methods: From June to December 2024, a total of 4 729 students aged 6-14 were recruited by cluster random sampling from 10 primary schools in Baoding (Hebei Province), Heze and Liaocheng (Shandong Province). General information, TCM constitution and depressive symptom were collected. Restricted cubic spline (RCS) models were used to analyze related factors and threshold effects of depressive symptom. Binary Logistic regression was applied to examine the association between depressive symptom and TCM constitution, with subgroup analyses conducted. Results: The detection rate of depressive symptom among the included children and adolescents was 25.82%. RCS analyses indicated non linear associations between depressive symptom and age (inflection point at 10 years old), bedtime (inflection point at 22:00), and wake up time (inflection point at 6:30 ) (all P non linearity <0.01). Linear associations were observed with body mass index (BMI) and sleep duration (all P non linearity > 0.05 ). After adjusting for covariates such as age, BMI and sleep status, binary Logistic regression analyses showed that Yin deficient constitution ( OR =1.26, 95% CI =1.09-1.45) and Phlegm-dampness constitution ( OR =1.42, 95% CI =1.11-1.82) were significantly associated with depressive symptom among children and adolescents (all P <0.05). Conclusions Depressive symptom among school aged children and adolescents is primarily associated with Yin deficiency and Phlegm dampness constitutions in TCM constitution. Active attention should be paid to susceptible TCM constitution among children and adolescents. Targeted health guidance and interventions should be implemented to improve TCM constitution health status for preventing the occurrence of depressive symptom.

Cervi Cornu Pantotrichum is a precious animal-derived Chinese medicinal material, while there are often adulterants derived from animals not specified in the Chinese Pharmacopeia in the market, which disturbs the safety of medication. This study was conducted with the aim of strengthening the quality control of Cervi Cornu Pantotrichum and standardizing the medication. To achieve digital identification of Cervi Cornu Pantotrichum from different sources, a digital identification model was constructed based on ultra-high performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry(UHPLC-QTOF-MS~E) combined with an adaptive boosting algorithm(Adaboost). The young furred antlers of sika deer, red deer, elk, and reindeer were processed and then subjected to polypeptide analysis by UHPLC-QTOF-MS~E. Then, the mass spectral data reflecting the polypeptide information were obtained by digital quantification. Next, the key data were obtained by feature screening based on Gini index, and the digital identification model was constructed by Adaboost. The model was evaluated based on the recall rate, F_1 composite score, and accuracy. Finally, the results of identification based on the constructed digital identification model were validated. The results showed that when the Gini index was used to screen the data of top 100 characteristic polypeptides, the digital identification model based on Adaboost had the best performance, with the recall rate, F_1 composite score, and accuracy not less than 0.953. The validation analysis showed that the accuracy of the identification of the 10 batches of samples was as high as 100.0%. Therefore, based on UHPLC-QTOF-MS~E and Adaboost algorithm, the digital identification of Cervi Cornu Pantotrichum can be realized efficiently and accurately, which can provide reference for the quality control and original animal identification of Cervi Cornu Pantotrichum.
Animals ; Algorithms ; Antlers/chemistry* ; Boosting Machine Learning Algorithms ; Chromatography, High Pressure Liquid/methods* ; Deer ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Quality Control ; Reindeer ; Tandem Mass Spectrometry/methods* ; Tissue Extracts/analysis*

In recent years, there have been frequent adverse reactions/events associated with traditional Chinese medicine(TCM), especially liver injury related to traditional non-toxic TCM, which requires adequate attention. Liver injury related to traditional non-toxic TCM is characterized by its sporadic and insidious nature and is influenced by various factors, making its detection and identification challenging. There is an urgent need to develop a strategy and method for early detection and recognition of traditional non-toxic TCM-related liver injury. This study was based on national adverse drug reaction monitoring center big data, integrating methodologies such as reporting odds ratio(ROR), network toxicology, and computational chemistry, so as to systematically research the risk signal identification and evaluation methods for TCM-related liver injury. The optimized ROR method was used to discover potential TCM with a risk of liver injury, and network toxicology and computational chemistry were used to identify potentially high-risk TCM. Additionally, typical clinical cases were analyzed for confirmation. An integrated strategy of "discovery via big data, identification via dry/wet method, confirmation via typical cases, and precise risk prevention and control" was developed to identify the risk of TCM-related liver injury. Corydalis Rhizoma was identified as a TCM with high risk, and its toxicity-related substances and potential toxicity mechanisms were analyzed. The results revealed that liver injury is associated with components such as tetrahydropalmatine and tetrahydroberberine, with potential mechanisms related to immune-inflammatory pathways such as the tumor necrosis factor signaling pathway, interleukin-17 signaling pathway, and Th17 cell differentiation. This paper innovatively integrated real-world evidence and computational toxicology methods, offering insights and technical support for establishing a risk discovery and identification strategy for TCM-related liver injury based on real-world big data, providing innovative ideas and strategies for guiding the safe and rational use of medication in clinical practices.
Corydalis/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Chemical and Drug Induced Liver Injury/etiology* ; Medicine, Chinese Traditional/adverse effects* ; Rhizome/adverse effects* ; Male ; Female