Hepatocellular carcinoma （HCC） is a common malignant tumor with a high mortality rate， an insidious onset， and complex pathological mechanisms. In the tumor microenvironment， tumor-promoting immune cells protect tumor cells from immune attacks， while dysfunction of anti-tumor immune cells causes the inhibition of immune response， thereby leading to the continuous deterioration of cancer. In recent years， traditional Chinese medicine has shown good efficacy in the treatment of HCC， and it can inhibit the proliferation and metastasis of cancer cells by regulating immune cells. By analyzing related articles in China and globally， this article summarizes how immune cells affect the progression of HCC through the immunosuppressive pathway and how traditional Chinese medicine exerts an anti-HCC effect by regulating immune cells， in order to provide theoretical basis and reference for optimizing the treatment of HCC.

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 suitability of the existing hemolysis rate standards for locally processed red blood cell components by retrospectively analyzing 5-year hemolysis rate data at the end of storage. Methods: A total of 720 blood samples of three types of red blood cell components from our blood station from January 2019 to December 2023 were collected. Parameters included hemoglobin concentration (Hb), hematocrit (Hct), and free hemoglobin concentration (fHb). Hemolysis rate were taken as the control standard of 0.8% in accordance with the national standard. The hemolysis rates were compared against the national standard threshold of 0.8% (GB18469-2012), and annual trends of the detection parameters were observed. Results: The hemolysis rates (x-+s,%) of leukocyte-depleted whole blood at the end of storage were (0.038±0.023 8) in 2019, (0.049±0.039 5) in 2020, (0.043±0.040 7) in 2021, (0.049±0.030 7) in 2022, and (0.058±0.054 8) in 2023, respectively; The hemolysis rates (x-+s" />,%) of leukocyte-depleted suspended red blood cells at the end of storage were (0.093±0.050 2) in 2019, (0.086±0.049 5) in 2020, (0.123±0.072 3) in 2021, (0.122±0.052 1) in 2022, and (0.106±0.058 6) in 2023, respectively; The hemolysis rates (x-+s,%) of washed red blood cells at the end of storage were (0.127±0.038 2) in 2019, (0.150±0.066 5) in 2020, (0.121±0.052 2) in 2021, (0.124±0.038 9) in 2022, and (0.128±0.044 3) in 2023, respectively. Conclusion: Hemolysis rates at the end of blood storage of three red blood cell components were significantly lower than the limits specified in Quality Requirements for Whole Blood and Components (GB18469-2012), as well as standards from the EU, AABB and the United States. The results demonstrate excellent product quality control. A regional internal control standard of <0.2% is proposed for hemolysis rates at the end of storage.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

Nucleotide-binding oligomerization domain (NOD)-like receptor protein 3 (NLRP3) is a cytosolic pattern recognition receptor that recognizes multiple pathogen-associated molecular patterns and damage-associated molecular patterns. It is a cytoplasmic immune factor that responds to cellular stress signals, and it is usually activated after infection or inflammation, forming an NLRP3 inflammasome to protect the body. Aberrant NLRP3 inflammasome activation is reportedly associated with some inflammatory diseases and metabolic diseases. Recently, there have been mounting indications that NLRP3 inflammasomes play an important role in liver injuries caused by a variety of diseases, specifically hepatic ischemia/reperfusion injury, hepatitis, and liver failure. Herein, we summarize new research pertaining to NLRP3 inflammasomes in hepatic injury, hepatitis, and liver failure. The review addresses the potential mechanisms of action of the NLRP3 inflammasome, and its regulation in these liver diseases.
Humans ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammasomes/physiology* ; Animals ; Liver Diseases/metabolism* ; Liver/metabolism* ; Reperfusion Injury/metabolism*

Metal ion-promoted chemodynamic therapy(CDT) combined with photodynamic therapy(PDT) offers broad application prospects for enhancing anti-tumor effects. In this study, glycyrrhizic acid(GA), copper ions(Cu~(2+)), and norcantharidin(NCTD) were co-assembled to successfully prepare a natural small-molecule, carrier-free hydrogel(NCTD Gel) with excellent material properties. Under 808 nm laser irradiation, NCTD Gel responded to the tumor microenvironment(TME) and acted as an efficient Fenton reagent and photosensitizer, catalyzing the conversion of endogenous hydrogen peroxide(H_2O_2) within the tumor into oxygen(O_2), and hydroxyl radicals(·OH, type Ⅰ reactive oxygen species) and singlet oxygen(~1O_2, type Ⅱ reactive oxygen species), while depleting glutathione(GSH) to stabilize reactive oxygen species and alleviate tumor hypoxia. In vitro and in vivo experiments demonstrated that NCTD Gel exhibited significant CDT/PDT synergistic therapeutic effects. Further safety evaluation and metabolic testing confirmed its good biocompatibility and safety. This novel hydrogel is not only simple to prepare, safe, and cost-effective but also holds great potential for clinical transformation, providing insights and references for the research and development of metal ion-mediated hydrogel-based anti-tumor therapies.
Hydrogels/chemistry* ; Animals ; Photochemotherapy ; Humans ; Mice ; Antineoplastic Agents/administration & dosage* ; Photosensitizing Agents/chemistry* ; Neoplasms/metabolism* ; Female ; Copper/chemistry* ; Reactive Oxygen Species/metabolism* ; Tumor Microenvironment/drug effects* ; Cell Line, Tumor ; Male

OBJECTIVE: To explore the molecular mechanism of Shenmai Injection (SMI) against doxorubicin (DOX) induced cardiomyocyte apoptosis. METHODS: A total of 40 specific pathogen-free (SPF) male Sprague Dawley (SD) male rats were divided into 5 groups based on the random number table, including the control group, the model group, miR-30a agomir group, SMI low-dose (SMI-L) group, and SMI high-dose (SMI-H) group, with 8 rats in each group. Except for the control group, the rats were injected weekly with DOX (2 mg/kg) in the tail vein for 4 weeks to induce myocardial injury, and were given different regimens of continuous intervention for 2 weeks. Cardiac function was detected by echocardiography and myocardial pathological changes were observed by Van Gieson (VG) staining. Myocardial injury serum markers, including creatine kinase (CK), lactate dehydrogenase (LDH), troponin T (cTnT), N-terminal pro-brain natriuretic peptide (NT-proBNP), soluble ST2 (sST2), and growth differentiation factor-15 (GDF-15) were detected by enzyme linked immunosorbent assay (ELISA). Cardiomyocyte apoptosis was observed by terminal deoxynucleotidyl transferase-mediated biotinylated dUTP triphosphate nick end labeling (TUNEL) and transmission electron microscopy, and the expressions of target proteins and mRNA were detected by Western blot and quantitative real time polymerase chain reaction (qRT-RCR), respectively. RESULTS: The treatment with different doses of SMI reduced rat heart mass index and left ventricular mass index (P<0.05), significantly improved the left ventricular ejection fraction (P<0.05), decreased the levels of serum CK, LDH, cTnT, and NT-proBNP (P<0.05 or P<0.01), reduced the levels of serum sST2 and GDF-15 (P<0.05 or P<0.01), decreased the collagen volume fraction, reduced the expressions of rat myocardial type I and type III collagen (P<0.05 or P<0.01), and effectively alleviated myocardial fibrosis. And the study found that SMI promoted the expression levels of miR-30a and Bcl-2 in myocardium, and down-regulated the expression of Bax, which inhibited the activation of Caspase-3 and Caspase-9 (P<0.05 or P<0.01), and improved myocardial cell apoptosis. CONCLUSIONS SMI can alleviate myocardial injury and apoptosis caused by DOX, and its mechanism possibly by promoting the targeted expression of myocardial Bcl-2 protein through miR-30a.
Animals ; Myocytes, Cardiac/metabolism* ; Apoptosis/drug effects* ; MicroRNAs/genetics* ; Rats, Sprague-Dawley ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Doxorubicin/pharmacology* ; Proto-Oncogene Proteins c-bcl-2/genetics* ; Drug Combinations ; Injections ; Rats

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVE: To investigate the value of difference between hematocrit (HCT) and albumin (Alb) in predicting the prognosis of patients with sepsis. METHODS: A retrospective study was conducted on the septic patients hospitalized at the First Affiliated Hospital of Guangxi Medical University from January to October in 2024. Clinical data including gender, age, body mass index (BMI), history of hypertension or diabetes, vital signs on admission, and sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation II (APACHE II) score, blood lactic acid (Lac), oxygenation index (PaO₂/FiO₂), hemoglobin (Hb), white blood cell count (WBC), platelet count (PLT), lymphocyte count (LYM), HCT, Alb, difference between HCT and Alb, bilirubin, scrum creatinine (SCr), and fibrinogen (Fib) within 48 hours of admission were collected. The 28-day prognosis of patients was also recorded. Binary multivariate Logistic regression analysis was used to identify risk factors for 28-day death in patients with sepsis. The predictive efficacy of the difference between HCT and Alb on 28-day death was evaluated using the receiver operator characteristic curve (ROC curve). RESULTS: Among 180 enrolled septic patients, 140 survived and 40 died on 28 days. Compared with the survival group, the patients in the death group was significantly older (years old: 64±16 vs. 55±15, P < 0.05), and had higher SOFA score, APACHE II score, and SCr [SOFA score: 6 (4, 9) vs. 3 (2, 5), APACHE II score: 13 (10, 18) vs. 8 (6, 11), SCr (μmol/L): 136 (70, 416) vs. 77 (58, 126), all P < 0.05] as well as lower Hb, PLT, HCT, difference between HCT and Alb, and Fib within 48 hours of admission [Hb (g/L): 90±30 vs. 106±79, PLT (×10⁹/L): 158 (57, 240) vs. 215 (110, 315), HCT: 0.258±0.081 vs. 0.333±0.077, difference between HCT and Alb: -6.52±7.40 vs. 1.07±7.63, Fib (g/L): 3.72±1.57 vs. 4.59±1.55, all P < 0.05]. No significant difference in gender, BMI, history of hypertension or diabetes, vital signs on admission, or other laboratory indicators was found between the two groups. Binary multivariate Logistic regression analysis revealed that age [odds ratio (OR) = 1.040, 95% confidence interval (95%CI) was 1.004-1.078, P = 0.030], APACHE II score (OR = 1.218, 95%CI was 1.038-1.430, P = 0.016), Hb (OR = 1.040, 95%CI was 1.014-1.068, P = 0.003), and difference between HCT and Alb (OR = 0.804, 95%CI was 0.727-0.889, P < 0.001) were independent risk factors for 28-day death of septic patients. ROC curve analysis showed that the area under the ROC curve (AUC) of difference between HCT and Alb for predicting 28-day death of septic patients was 0.764 (95%CI was 0.679-0.849, P < 0.001). A cut-off value of difference between HCT and Alb ≤ -5.35 yielded a sensitivity of 80.7% and specificity of 65.0%. CONCLUSIONS The difference between HCT and Alb at early admission is a valuable predictor of prognosis in septic patients. A difference ≤ -5.35 indicates an increased death risk of septic patients.
Humans ; Prognosis ; Sepsis/blood* ; Retrospective Studies ; Hematocrit ; Serum Albumin/analysis* ; Male ; Female ; Middle Aged ; Aged ; APACHE