ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Asthma and cough variant asthma （CVA） are both chronic heterogeneous diseases characterized by airway microenvironment homeostasis disruption as their core pathological basis. In recent years， micro ribonucleic acid （miRNA）， as core post-transcriptional regulators， have been shown to finely modulate multiple critical signaling pathways， including Janus kinase/signal transducer and activator of transcription （JAK/STAT）， nuclear factor-κB （NF-κB）， transforming growth factor-β/Smad （TGF-β/Smad）， and phosphoinositide 3-kinase/protein kinase B （PI3K/Akt）， as well as various pathological processes such as airway epithelial barrier restoration， type 1 helper T cell（Th1）/Th2 immune balance， M1/M2 macrophage polarization， airway smooth muscle cell function， and airway hyperresponsiveness. miRNAs play a pivotal role in maintaining and disrupting airway microenvironment homeostasis. Based on recent Chinese and international literature， a logical framework centered on "airway microenvironment homeostasis disruption， miRNA regulation， and microenvironment restoration" was constructed. From the perspective of the airway microenvironment， the therapeutic roles of miRNA in asthma and CVA were systematically summarized， and the cascade regulatory mechanisms of miRNA throughout the entire disease course were elucidated. The hub miRNA was identified， and research progress on traditional Chinese medicine intervention strategies was explored. Furthermore， current clinical studies on RNA therapeutics and traditional Chinese medicine in achieving multi-target and multi-pathway integrated treatment by modulating miRNA were analyzed. The value of miRNA as biomarkers for diagnosis， phenotyping， and prognosis assessment， as well as the potential and application prospects of miRNA mimics and antagonists in precision therapy， were summarized， with the ultimate goal of advancing precision therapy for asthma and CVA.

ObjectiveTo construct a novel KPC mouse model of type 2 diabetes mellitus （T2DM） comorbid with spontaneous pancreatic cancer based on the gene editing-metabolic intervention dual-driven strategy， and to compare it with traditional models. MethodsA total of 14 male KPC mice were randomly divided into novel model group （T2DM-KPC group with 7 mice） and control group （KPC group with 7 mice）， and 14 male BALB/c-nu nude mice were randomly divided into traditional model group （T2DM-pancreatic cancer group with 7 mice） and control group （pancreatic cancer group with 7 mice）. The mice in the KPC group and the pancreatic cancer group were fed with normal diet， and those in the T2DM-KPC group and the T2DM-pancreatic cancer group were fed with a high-fat diet. After 4 weeks， the mice in the T2DM-KPC group and the T2DM-pancreatic cancer group were given intraperitoneal injection of streptozotocin. Subsequently， the mice in the KPC group and the T2DM-KPC group developed primary pancreatic tumor spontaneously over time， while those in the T2DM-pancreatic cancer group and the pancreatic cancer group were inoculated with tumor cells to form subcutaneous tumor xenograft at 2 weeks after stabilization of blood glucose. The 4 groups were observed in terms of tumor formation rate， tumor formation time， body weight， and the change in blood glucose； RNA sequencing was performed for tumors from the KPC group and the T2DM-KPC group， and then molecular subtyping was performed； HE staining， Masson staining， and immunohistochemical staining were used to assess the histopathological features and tumor microenvironment of pancreatic tumor from the T2DM-KPC group， which were compared with those of the T2DM-pancreatic cancer group. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups； the Fisher’s exact test was used for comparison of categorical data between multiple groups. ResultsThe T2DM-KPC group had a tumor formation rate of 85.71% and a tumor formation time of 104.40±2.87 days， while the T2DM-pancreatic cancer group had a tumor formation rate of 71.43% and a tumor formation time of 95.20±9.47 days， and there were no significant differences between the two groups in tumor formation rate， tumor formation time， body weight， and blood glucose （all P>0.05）. Molecular subtyping showed that the model in the KPC group highly resembled the pancreatic progenitor subtype of human pancreatic ductal adenocarcinoma （PDAC）， and the model in the T2DM-KPC group highly resembled the immunogenic subtype of PDAC. HE staining showed that tumor cells in the T2DM-KPC group were arranged into glandular tubular structures of varying shapes， exhibiting significant cellular atypia， and this model faithfully recapitulated the pathological features of primary pancreatic cancer and showed greater invasiveness than the KPC group. Immunohistochemical staining and Masson staining showed that compared with the T2DM-pancreatic cancer group， the T2DM-KPC group had significantly higher degrees of tumor proliferation （assessed by Ki-67 expression） and fibrosis （assessed by α-SMA and Masson） （all P<0.05）， suggesting that the mouse model in the T2DM-KPC group could better recapitulate the features of hyperproliferation and pronounced desmoplasia in human pancreatic cancer. ConclusionA novel KPC mouse model of T2DM comorbid with spontaneous pancreatic cancer is successfully constructed in this study. This model can accurately mimic the histopathological architecture and stromal microenvironment of T2DM comorbid with pancreatic cancer， realize the longitudinal simulation of the progression of pancreatic tissue from intraepithelial neoplasia to invasive carcinoma and metastasis in the presence of T2DM， and support the translational research on immunotherapy， thereby providing a novel experimental carrier for in vivo studies on spontaneous pancreatic cancer in T2DM.

ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.

ObjectiveTo establish background data for a 90-day feeding trial of SD rats to ensure the reliability of research data. MethodsBackground data from six independent 90-day feeding trials of SD rats conducted by the National Center for Safety Evaluation of Drugs from 2020 to 2023 were summarized. These studies involved a blank control group of 120 SPF-grade 4-week-old SD rats, with an equal number of males and females, which were only given standard full-nutrient pelleted rat feed. After the quarantine period, the animals were observed for an additional 90 days, followed by intraperitoneal injection of Zoletil (50 mg/mL) for anesthesia, blood sampling, euthanasia, and necropsy. By analyzing the data from the blank control group, a relevant background database for SD rats was established. ResultsBoth male and female rats exhibited steady weight gain, with a more pronounced increase in male rats. Within 90 days, the average body weight of male and female rats increased to over 500 g and 300 g, respectively. Three weeks later, the average daily food intake of male rats stabilized at approximately 25~28 g per rat, while that of female rats remained stable at approximately 16~19 g per rat. The food utilization rate of all animals gradually decreased from the first week of the experiment. In the white blood cell (WBC) differential count results, significant differences were observed in the counts of WBCs, neutrophils (Neut), lymphocytes (Lymph), and monocytes (Mono) between males and females (P<0.001). However, there were no significant differences in the percentages of neutrophil (%Neut), lymphocyte (%Lymph), and monocyte (%Mono) between the sexes (P>0.05). The average red blood cell count (RBC), hemoglobin concentration (HGB), hematocrit (HCT), platelet count (PLT), prothrombin time (PT), and activated partial thromboplastin time (APTT) were higher in male animals than in female animals (P<0.05). The average values of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), creatine phosphokinase (CK), lactate dehydrogenase (LDH), glucose (GLU), and triglyceride (TG) in male rats were higher than those in female rats (P<0.05). The urinary pH range for male animals was 5.0 to 8.5, while for female animals it was 6.5 to 9.0. The majority of male animals had a urinary specific gravity lower than 1.020, and the majority of female animals had a urinary specific gravity lower than 1.015. The weights of various organs (excluding the adrenal glands and reproductive organs) in male animals were heavier than those in female animals (P<0.001), while the organ/body weight ratios (excluding the kidneys and reproductive organs) of female animals were higher than those of male animals (P<0.001). ConclusionThis study summarizes the background reference ranges for body weight, food intake, hematology, and serum biochemistry indicators in SPF-grade SD rats in the untreated control group from six 90-day feeding trials conducted by the National Center for Safety Evaluation of Drugs. It provides important reference data for related research. By summarizing the background and spontaneous histopathological changes in rats, this study aids in the standardization and normalization of subsequent research, as well as in the evaluation and analysis of abnormal results.

The cholinergic anti-inflammatory pathway(CAP)is a neuroimmunoregulatory pathway that has attracted much attention in recent years.This pathway releases acetylcholine(ACh)by activating the vagus nerve.The binding of ACh to α7 nicotinic acetylcholine receptor receptors on the surface of macrophages can inhibit the release of proinflammatory factors,so as to effectively regulate the inflammatory response in the body.CAP plays a key role in suppressing excessive inflammatory responses and maintaining immune balance,providing a potential therapeutic pathway for a variety of inflammatory immune diseases.Research progress on the physiological function of CAP and its activation and blocking methods are reviewed in this paper,in order to provide new methods and ideas for treatment of inflammation-related diseases and exploring therapeutic drugs targeting CAP pathway.

AIM To investigate the differences between boiled powder and decoction of Ermiao Powder.METHODS GC-MS was used to identify volatile constituents,after which the content determination of linalool,4-terpineol,α-terpineol,β-eucalyptol and taxifolin in distillate was performed,evaporation rate curve was drawn.The rat model for collagen-induced arthritis was established,then HE and SO/FG staining were conducted,and body weight,footpad swelling degree,arthritis score,immune organ(spleen,thymus)indices,serum inflammatory factors(IL-10,IL-6),ankle joint structure(foot claw swelling,micro-CT)and locomotor ability were detected.RESULTS Total 43 and 26 volatile constituents were identified in boiled powder and decoction,respectively.With the extension of boiling time,the average evaporation rates of 5 volatile constituents in the boiled powder distillate demonstrated the trends of first increase and then decrease,which reached a maximum at 15-20 min;those in the decoction distillate displayed the trends of decrease,which were not detected after 15 min except for β-eucalyptol.Compared with the decoction,the boiled powder exhibited stronger effects on improving foot swelling and arthritis score,alleviating pathological changes in joint tissues,inhibiting inflammatory factors and restoring motor ability.CONCLUSION More volatile constituents are observable in the boiled powder of Ermiao Powder than those in its decoction,along with stronger anti-rheumatoid arthritis activity.The optimal decocting endpoint is determined to be within 15 min in boiling water.