ObjectiveTo explore the mechanism of Shaoyaotang in the prevention and treatment of colitis-associated carcinogenesis （CAC） based on myeloid-derived suppressor cells （MDSCs）-related immunosuppressive microenvironment. MethodsA total of 140 six-week-old SPF FVB male mice were randomly divided into seven groups： Blank group， Shaoyaotang without model group （7.12 g·kg^-1）， model group， sulfasalazine group （0.52 g·kg^-1）， Shaoyaotang low-dose group （3.56 g·kg^-1）， Shaoyaotang medium-dose group （7.12 g·kg^-1） and Shaoyaotang high-dose group （14.24 g·kg^-1）， with 20 mice in each group. The blank control group and the Shaoyaotang without model group received a single intraperitoneal injection of physiological saline （10 mg·kg^-1）， while the other five groups were given a single intraperitoneal injection of azoxymethane （AOM） （10 mg·kg^-1）. After 1 week， the mice were given drinking water containing 2% dextran sulfate sodium （DSS） for 1 week， followed by normal drinking water for 2 weeks. This cycle was repeated three times over a total period of 14 weeks to establish the CAC mouse model. Each group was administered gavage once daily for 2 weeks starting on the 14^th day of the experiment， followed by three times a week until the end of the experiment. The body weight of the mice was recorded weekly. Mice were sacrificed on the 28^th and 98^th days of the experiment. After dissection， the colon length， colon weight， spleen weight， tumor size， and tumor number were measured. Hematoxylin and eosin （HE） staining was used to assess the pathological morphology of colon tumor tissue. Flow cytometry was used to detect MDSCs， regulatory T cells （Tregs）， CD4⁺ T cells， CD8⁺ T cells， and the CD4⁺/CD8⁺ T cell ratio in the spleen. Immunohistochemistry was used to detect the expression levels of programmed cell death protein-1 （PD-1）， programmed cell death ligand 1 （PD-L1）， phosphorylated AMP-activated protein kinase （p-AMPK）， phosphorylated nuclear factor-κB （p-NF-κB）， and hypoxia-inducible factor 1α （HIF-1α） in the colon tissue. ResultsOn day 14， compared with the blank group， the body weight of the model group was significantly reduced （P<0.01）， reaching its lowest point on day 28 （23.39 ± 0.95 ） g. On days 28 and 98， compared with the blank group， the colon length in the model group was significantly shortened （P<0.01）， the colon index significantly increased （P<0.01）， the spleen index significantly increased （P<0.01）， and the tumor load significantly increased （P<0.01）. HE staining showed that in the model group， tumor cells， a large number of inflammatory cell infiltrates， goblet cell disappearance， and crypt loss were observed. In each dose group of Shaoyaotang， the damage to the colonic mucosa， inflammatory cell infiltration， and crypt structure destruction were alleviated. Compared with the model group， the body weight of mice in each dose group of Shaoyaotang increased. On day 98， the colon length was significantly increased （P<0.01）， the colon index significantly decreased （P<0.01）， the spleen index significantly decreased （P<0.01）， and the tumor burden significantly decreased （P<0.01） in each Shaoyaotang dose group. On days 28 and 98， MDSCs and Tregs in the spleen of the medium- and high-dose Shaoyaotang groups were significantly reduced （P<0.01）， while CD4⁺ T cells and the CD4⁺/CD8⁺ T cell ratio were significantly increased （P<0.01）. The proportion of CD8⁺ T cells in the spleen and the expression levels of PD-1 and PD-L1 in the colon tissues of mice in each Shaoyaotang dose group were significantly increased to varying degrees （P<0.05， P<0.01）. On days 28 and 98， the expression of p-AMPK-positive cells in the colon tissue of the medium- and high-dose Shaoyaotang groups was significantly increased （P<0.01）， while the expression of p-NF-κB and HIF-1α was significantly reduced （P<0.01）. ConclusionShaoyaotang can regulate MDSC recruitment and modulate the immune function of T lymphocyte subsets to inhibit the occurrence and development of AOM/DSS-induced CAC in mice. The mechanism may be related to the activation of the AMPK/NF-κB/HIF-1α pathway.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

[Objective] To study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.

OBJECTIVE To understand the development status and existing problems of traditional Chinese medicine（TCM） pharmacists in public TCM hospitals in China， aiming to provide suggestions for the competent departments to formulate management policies for TCM pharmacists and promote the healthy development of TCM. METHODS The data on the number and professional titles of TCM pharmacists in public TCM hospitals in China from 2019 to 2023 were collected. Descriptive analysis was employed to analyze the number， distribution and professional titles of TCM pharmacists in public TCM hospitals across the country， and to measure the quantity shortfalls of the number of TCM pharmacists in these hospitals. RESULTS From 2019 to 2023， the number of TCM pharmacists in public TCM hospitals in China grew slowly， with an average annual growth rate of 2.56%. However， the proportion of TCM pharmacists to the total number of pharmacists in public TCM hospitals gradually decreased， with an average annual growth rate of －0.65%. In terms of hospital grades， the number of TCM pharmacists in tertiary public TCM hospitals showed positive growth， while those in secondary and primary public TCM hospitals showed negative growth. In terms of hospital types， the average annual growth rate of TCM pharmacists in TCM hospitals was 2.22%， in integrated Chinese and Western medicine hospitals it was 7.97%， and in ethnic minority medicine hospitals it was 2.74%. The development of TCM pharmacists in different provinces was uneven. The annual growth rate of TCM pharmacists in Guizhou exceeded 10%， while the growth rate in Hunan and Heilongjiang was negative. In 2023， the number of TCM pharmacists per thousand population in public TCM hospitals was 0.03， indicating a relatively low staffing level. The professional titles of TCM pharmacists in public TCM hospitals were mainly primary and E-mail：601907549@qq.com intermediate， with a total of 67.33%. According to the calculation that the proportion of TCM pharmacists to pharmacists was not less than 60%， public TCM hospitals and hospitals of integrated TCM and Western medicine should be reconfigured with TCM pharmacists 6 212 and 1 288 people， respectively. CONCLUSIONS The number of TCM pharmacists in public TCM hospitals is growing slowly， with insufficient staffing levels， relatively low professional titles， and uneven distribution and development across provinces. It is suggested that relevant competent departments strengthen policy guidance， increase the attention given by the state level to TCM pharmacists， strengthen the construction of the talent team for TCM pharmacists， improve the quality and optimize the allocation of TCM pharmacist talents in order to promote the high-quality development of TCM services.

Objective To analyze the nonlinear relationship between hypothermic machine perfusion (HMP) parameters and delayed graft function (DGF) and optimize the construction of a predictive model for DGF. Methods The data of 923 recipients who underwent kidney transplantation from deceased donors were retrospectively analyzed. According to the occurrence of DGF, the recipients were divided into DGF group (n=823) and non-DGF group (n=100). Donor data, HMP parameters and recipient data were analyzed for both groups. The nonlinear relationship between HMP parameters and the occurrence of DGF was explored based on restricted cubic splines (RCS). Over-sampling, under-sampling and balanced sampling were used to address the imbalance in the proportion of DGF to construct logistic regression predictive models. The area under the curve (AUC) of each model was compared in the validation set, and a nomogram model was constructed. Results Donor BMI, cold ischemia time of the donor kidney, and HMP parameters (initial and final pressures, resistance, and perfusion time) were significantly different between the DGF and non-DGF groups (all P<0.05). The RCS analysis revealed a threshold-like nonlinear relationship between HMP parameters and the risk of DGF. Among the models constructed using different sampling methods, the balanced sampling model had the highest AUC. Using this model, a nomogram was constructed to stratify recipients based on risk scores. Recipients in the high-risk group had higher serum creatinine levels at 1, 6, and 12 months after kidney transplantation compared to those in the low-risk group (all P<0.05). Conclusions There is a nonlinear relationship between HMP parameters and the risk of DGF, and the threshold is helpful for organ quality assessment and monitoring of graft function after transplantation. The predictive model for DGF constructed on the base of balanced sampling algorithms helps perioperative decision-making and postoperative graft function monitoring of kidney transplantation.

It is proposed that cold qi-induced accumulation encapsulates the core pathogenesis of the inflammation-cancer transformation in inflammatory bowel disease （IBD）. Cold pathogens may serve as the initiating factor. When first invading the intestines， cold pathogens obstruct the flow of qi； over time， the lingering cold impairs the middle jiao （焦）， eventually leading to the accumulation of cold-phlegm and blood stasis. Based on the progressive nature of this transformation， the process can be divided into three stages， active stage， remission stage， and carcinogenic stage. In the active stage， the main pathogenesis involves stagnation of cold qi and accumulation of damp-heat in the intestines； in the remission stage， cold qi impairs the spleen， disrupting its transport and transformation functions； and in the carcinogenic stage， the mechanisms include cold-induced accumulation， phlegm accumulation from cold， and stagnation of cold and blood stasis. Accordingly， the treatment strategies are proposed.In the active stage， regulating qi， relieving stagnation， and harmonizing cold and heat； in the remission stage， warming yang， dispersing cold， tonifying qi， and strengthening the spleen； and in the carcinogenic stage， promoting qi circulation， dispersing cold， resolving phlegm， activating yang， and eliminating stasis to remove accumulation. These approaches aim to interrupt the transformation of IBD into colorectal cancer.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

OBJECTIVE: To investigate whether electroacupuncture (EA) at sensitized acupoints could reduce sympathetic-sensory coupling (SSC) and neurogenic inflammatory response by interfering with 5-hydroxytryptamine (5-HT)ergic neural pathways to relieve colitis and somatic referred pain, and explore the underlying mechanisms. METHODS: Rats were treated with 5% dextran sodium sulfate (DSS) solution for 7 days to establish a colitis model. Twelve rats were randomly divided into the control and model groups according to a random number table (n=6). According to the "Research on Rat Acupoint Atlas", sensitized acupoints and non-sensitized acupoints were determined. Rats were randomly divided into the control, model, Zusanli-EA (ST 36), Dachangshu-EA (BL 25), and Xinshu (BL 15) groups (n=6), as well as the control, model, EA, and EA + GR113808 (a 5-HT inhibitor) groups (n=6). The rats in the control group received no treatment. Acupuncture was administered on 2 days after modeling using the stimulation pavameters: 1 mA, 2 Hz, for 30 min, with sparse and dense waves, for 14 consecutive days. GR113808 was injected into the tail vein at 5 mg/kg before EA for 10 min for 7 consecutive days. Mechanical sensitivity was assessed with von Frey filaments. Body weight and disease activity index (DAI) scores of rats were determined. Hematoxylin and eosin staining was performed to observe colon histopathology. SSC was analyzed by immunofluorescence staining. Immunohistochemical staining was performed to detect 5-HT and substance P (SP) expressions. The calcitonin gene-related peptide (CGRP) in skin tissue and tyrosine hydroxylase (TH) protein levels in DRG were detected by Western blot. The levels of hyaluronic acid (HA), bradykinin (BK), prostaglandin I2 (PGI2) in skin tissue, 5-HT, tryptophan hydroxylase 1 (TPH1), serotonin transporters (SERT), 5-HT 3 receptor (5-HT3R), and 5-HT 4 receptor (5-HT4R) in colon tissue were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: BL 25 and ST 36 acupoints were determined as sensitized acupoints, and BL 15 acupoint was used as a non-sensitized acupoint. EA at sensitized acupoints improved the DAI score, increased mechanical withdrawal thresholds, and alleviated colonic pathological damage of rats. EA at sensitized acupoints reduced SSC structures and decreased TH and CGRP expression levels (P<0.05). Furthermore, EA at sensitized acupoints reduced BK, PGI2, 5-HT, 5-HT3R and TPH1 levels, and increased HA, 5-HT4R and SERT levels in colitis rats (P<0.05). GR113808 treatment diminished the protective effect of EA at sensitized acupoints in colitis rats (P<0.05). CONCLUSION EA at sensitized acupoints alleviated DSS-induced somatic referred pain in colitis rats by interfering with 5-HTergic neural pathway, and reducing SSC inflammatory response.
Rats ; Animals ; Electroacupuncture ; Rats, Sprague-Dawley ; Serotonin ; Acupuncture Points ; Pain, Referred ; Calcitonin Gene-Related Peptide ; Signal Transduction ; Colitis/therapy* ; Indoles ; Sulfonamides

Biosensor analysis technology is a kind of technology with high specificity that can convert biological reactions into optical and electrical signals. In the development of drugs for Alzheimer's disease (AD), according to different disease hypotheses and targets, this technology plays an important role in confirming targets and screening active compounds. This paper briefly describes the pathogenesis of AD and the current situation of therapeutic drugs, introduces three biosensor analysis techniques commonly used in the discovery of AD drugs, such as surface plasmon resonance (SPR), biolayer interferometry (BLI) and fluorescence analysis technology, explains its basic principle and application progress, and summarizes their advantages and limitations respectively.

Based on the interaction between supramolecule of traditional Chinese medicine and enterobacteria, the material basis of Rhei Radix et Rhizoma and Coptidis Rhizoma was explored. Scanning electron microscopy (SEM) and dynamic light scattering (DLS) were used to characterize the morphological differences of Rhubarb single decoction, Coptis single decoction and Rhubarb and Coptis co-decoction. An in vitro antibacterial model (E. coli, E. faecium and B. subtilis) was established to evaluate the damage effect of the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma on enterobacteria. Ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to analyze the changes of chemical components of single decoctions and co-decoctions. The co-decoction of Rhei Radix et Rhizoma and Coptidis Rhizoma was turbid after decocting. The spherical particles of 300-400 nm were observed under SEM, and the co-decoction was more uniform and stable than that of single decoction. The interaction between supramolecules formed after the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma and enterobacteria was significantly different from that of single decoction. In the process of interaction between supramolecules and enterobacteria, the spherical state was maintained, and the medicinal ingredients in Coptidis Rhizoma or Rhei Radix et Rhizoma were blocked, which could effectively alleviate the damage to enterobacteria. This study provided a reference for subsequent studies on the regulation of intestinal flora homeostasis by the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma.