Objective: To evaluate the practical effectiveness of confidential unit exclusion (CUE) in ensuring blood safety in Zhengzhou, analyze its application characteristics and existing problems, and provide a basis for optimizing blood safety management strategies. Methods: A retrospective analysis was conducted on CUE data handled by Henan Red Cross Blood Center from January 2019 to December 2024. Parameters such as the number of cases, demographic characteristics, reasons for exclusion, and time of report were statistically analyzed and compared with those of non-CUE. Results: From 2019 to 2024, the CUE reporting rate in Zhengzhou was 0.002 6% (40/1 547 666). CUE donors were predominantly male (65.00%, 26/40), aged 18-34 years (47.50%, 19/40), had college degree orabove (50.00%, 20/40), and were employees of enterprises or public institutions (32.50%, 13/40). Among the 40 CUE blood units, only one was reactive for anti-TP, while all others were qualified. The main reasons for CUE were recent vaccination (32.50%, 13/40), medical conditions unsuitable for donation (27.50%, 11/40), and high-risk sexual behavior (17.50%, 7/40). A total of 70.00% of reports occurred within 24 hours after donation, during which none of the corresponding blood units had been released; all units reported after more than 7 days had already been issued for clinical use, with no adverse transfusion reactions reported upon follow-up. Conclusion: The confidential unit exclusion program has played an active role in establishing a supplementary information feedback channel for blood donors. The procedure can be optimized by strengthening interactive communication and confirmation before donation, improving the accuracy of donors' self-assessment, and expanding convenient and rapid information-based reporting channels.

•A strategy for in situ metabolically synthesized active drug-based probes was proposed.•The potential purgative targets of SA were successfully hooked and identified.•The work provided a new insight for studying the direct targets of unstable active drugs.

Objective:To investigate the Helicobacter pylori ( H. pylori) infection of Tibetan families and individuals in the Western Sichuan Plateau region and explore the related factors which affected H. pylori infection. Methods:This was a single-center cross-sectional study. Questionnaires were collected from 50 Tibetan families including 155 individuals in Western Sichuan Plateau region during March to May 2023. The 13C-urea breath test was performed to confirm the current infection status of participants. Binary logistic regression were used to analyze the related factors associated with H. pylori infection. Results:Among the 50 Tibetan households, the individual-based H. pylori infection rate was 47.10%(73/155), with two out of nine children and 48.63%(71/146) adults infected. The age group of 18 to 40 years had the highest infection rate (55.00%, 11/20). The prevalence of infection based on family was 80.00%(40/50), of which 16.00%(8/50) had all family members infected. Of the 59 couples surveyed, 23.73%(14/59) were both infected, and 45.76%(27/59) had one person infected. Of the six families which had children and adolescents, two households had their children infected. Logistic regression analysis showed that size of the family was a factor related to H. pylori infection (odds ratio=3.038, 95% confidence interval 1.043 to 10.491, P=0.042). Conclusions:The family-based H. pylori infection rate is relatively high in Tibetan residents in the Western Sichuan Plateau, and larger family size is related with higher risk of H. pylori infection within the family.

Objective:To analyze the dietary patterns of Chinese adults and explore the relationship with serum uric acid (SUA) and hyperuricemia (HUA).Methods:A total of 9 358 adults were selected in the 2018 China Health and Nutrition Survey. Dietary intake data were collected by three consecutive 24-hour dietary recalls and weighing method. The social demographic information of the survey subjects was obtained through questionnaire surveys. The dietary patterns were extracted using factor analysis, and the relationship between dietary patterns and SUA was analyzed using multiple linear regression analysis. The correlation between HUA and dietary patterns was analyzed using logistic regression analysis models.Results:Four dietary patterns were identified: northern (high intakes of wheat, other cereals,and tubers); modern (high intakes of fruit, dairy, eggs, and nuts); southern (high intakes of rice and vegetables);animal food-wine (high intake of organ meats, seafood, and wine). The multiple linear regression analysis results showed that the northern pattern was negatively correlated with SUA ( β=-0.438, 95% CI: -0.500--0.376); the modern pattern was negatively correlated with SUA ( β=-0.134, 95% CI: -0.219--0.049); the southern model was significantly correlated with higher SUA ( β=0.146, 95% CI: 0.079-0.214); the animal food-wine pattern was positively correlated with SUA ( β=0.188, 95% CI: 0.123-0.252). Logistic regression analysis showed that compared with the northern model score Q1 group, the risk of developing HUA was reduced in Q3 and Q4 groups, with ORs values of 0.777 (95% CI: 0.650-0.929) and 0.509 (95% CI: 0.423-0.613), respectively; and compared with the modern model score Q1 group, the higher the scores in Q3 and Q4 groups, the HUA was lower, with ORs of 0.793 (95% CI: 0.660-0.953) and 0.768 (95% CI: 0.631-0.934), respectively. Compared with the animal food-wine pattern score Q1 group, the risk of developing HUA was increased in both Q3 and Q4 groups ( Q3 group: OR=1.224, 95% CI: 1.012-1.480; Q4 group: OR=1.312, 95% CI: 1.086-1.584). Conclusions:Dietary patterns are associated with HUA. The northern and modern patterns are related to lower SUA levels and reduced risk of HUA, while the animal food-wine pattern increases the risk of HUA.

Objective:This study analyzed the expression of CD24 antigen on bone marrow plasma cells (BMPC) of patients with multiple myeloma (MM) and the predictive value of induction therapy.Methods:This clinical observational study utilized 258 MM patients samples treated at the Hematology Department of Beijing Jishuitan Hospital who met the inclusion criteria in the Department of Hematology, Capital Medical University, from August 12th, 2022 to February 1st, 2024. According to the different stages of the disease, patients were divided into three groups: 78 cases of Newly Diagnosed Multiple Myeloma(NDMM) (42 males and 36 females, aged 62±11), 56 cases of the relapse refractory group (34 males and 22 females, aged 64±9), and 124 cases of the disease remission group (68 males and 56 females, aged 62±10). Multiparameter flow cytometry (MFC) was used to detect the expression level of CD24 antigen on BMPC and the relationship between CD24 and MM disease status. The clinical data and test results of 78 NDMM patients at initial diagnosis were retrospectively analyzed, including gender, age, MFC detection of the positive expression rate of antigens (CD19, CD20, CD24, CD27, CD56), the results of efficacy evaluation after induction therapy, ISS staging, R-ISS staging, blood hemoglobin, β2-microglobulin, human serum albumin, serum creatinine, lactate dehydrogenas, correction of calcium, BMPC ratio, and the results of FISH. The patients were divided into a deep remission group [including complete remission (CR) and very good partial remission (VGPR)] with 43 cases and a non-deep remission group (non CR and VGPR) with 17 cases according to the difference of antigen positive expression rate after induction therapy. The differences of antigen expression on BMPC between the two groups were compared. Binary logistic regression was used to analyze the relationship between the expression of each antigen and the efficacy after induction therapy in patients, and the results showed that CD24 was more correlated with the achievement of deep remission after induction therapy than other antigens. Therefore, taking the positive expression rate of CD24 in NDMM patients at the initial diagnosis and deep remission after induction therapy as the research objects, the predictive value of CD24 for NDMM patients reaching deep remission after induction therapy was analyzed by using receiver operating characteristic curve (ROC), and the optimal cutoff value was obtained. NDMM was divided into two groups according to the cut-off value, and the differences between the two groups in clinical baseline data and prognostic indicators were compared.Results:The positive rates of plasma cell CD24 expression in the NDMM group, the relapse refractory group and the disease remission group were 2.18 (95% CI 0.08-81.85)%, 3.81 (95% CI 0.10-64.56)%, 8.74 (95% CI 0.79-95.55)% respectively. Compared with the disease remission group, the NDMM and relapse refractory group was lower ( Z=-7.889, -5.282, respectively, P<0.001). Univariate analysis showed that there was a significant difference in the positive expression rate of CD24 at initial diagnosis between the deep remission group and the non-deep remission group ( Z=-3.265, P<0.001), while there was no significant difference in CD19 ( Z=-0.271, P=0.787), CD20 ( Z=-0.205, P=0.837), CD27 ( Z=-0.582, P=0.560), and CD56 ( Z=-0.328, P=0.743) between the two groups. Binary logistic regression analysis showed that compared with other antigens [CD19 ( OR=1.045, 95% CI 0.975-1.120, P=0.217), CD20 ( OR=1.000, 95% CI 0.971-1.030, P=0.976), CD27 ( OR=0.997, 95% CI 0.977-1.016, P=0.734), CD56 ( OR=1.006, 95% CI 0.990-1.006, P=0.449)], the expression of CD24 ( OR=0.423, 95% CI 0.990-1.006, P=0.449) on BMPC in NDMM patients was most closely related to the achievement of deep remission was achieved after induction therapy. The lower the proportion of CD24 at the initial diagnosis was, the lower the probability of achieving deep remission after induction therapy was. The area under the curve (AUC) of CD24 in predicting deep remission after induction therapy was 0.772 (95% CI 0.655-0.889, P=0.001), with a sensitivity of 60.50%, a specificity of 85.00%, and the optimal critical value was 2.21%. Compared with the group with plasma CD24 positive rate>2.21%, the group with plasma CD24 positive rate<2.21% had a higher proportion of male (39.47%vs 65.00%, χ2=5.092, P=0.024), ISS stagingⅢ (41.67% vs 58.33%, χ2=6.175, P=0.046), β2 microglobulin (3.19 mg/L vs 4.14 mg/L, Z=-2.257, P=0.024), and BMPC [(8.672±1.827)% vs (19.530±3.188)%, t=-2.963, P=0.004] detected by MFC, and the differences were statistically significant. Conclusions:The low positive rate of plasma cell CD24 is closely related to the higher tumor burden and the worse disease status of MM patients. In addition, the positive expression rate of CD24 is at initial diagnosis can predict the efficacy achieved after induction therapy, and the lower positive rate of CD24 is, the worse the efficacy achieved after induction therapy. At the same time, MFC detection of CD24 is convenient and efficient in the evaluation and prediction of MM.

Objective:To investigate the value of CT quantitative parameters of tumor and spleen in predicting the clinical stage of gastric cancer (Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage).Methods:This study was a case-control study. The data of 145 patients with gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from February 2019 to June 2021 were retrospectively collected, including 70 cases of Ⅰ/Ⅱ stage and 75 cases of Ⅲ/Ⅳ stage. On the baseline CT images, the tumor related parameters, including tumor thickness, length of tumor, CT attenuation of tumor unenhanced phase, CT attenuation of tumor arterial phase, CT attenuation of tumor venous phase were measured. The spleen related parameters, including splenic thickness, CT attenuation of splenic unenhanced phase, CT attenuation of splenic arterial phase, CT attenuation of splenic venous phase, and standard deviation of CT attenuation (CTsd) in splenic unenhanced phase were also measured. The independent sample t test or Mann-Whitney U test was used to compare the parameters between the Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage patients. The multi-factor logistic regression analysis was used to find the independent predictors of gastric cancer clinical stage, and establish the combined parameters. The efficiency to the diagnosis of gastric cancer stage of single and combined parameters was evaluated using the operating characteristic curve, and the DeLong test was used to compare the differences of area under the curve (AUC). Results:There were significant differences in tumor thickness, length of tumor, CT attenuation of tumor venous phase, CT attenuation of splenic unenhanced phase, CT attenuation of splenic venous phase, CTsd in splenic unenhanced phase between the Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage of gastric cancer ( P<0.05). Multivariate analysis showed that tumor thickness ( OR=1.073, 95% CI 1.026-1.123, P=0.002), CT attenuation of splenic venous phase ( OR=1.040, 95% CI 1.011-1.070, P=0.006) and CTsd in splenic unenhanced phase ( OR=1.625, 95% CI 1.330-1.987, P<0.001) were independent risk factors for the clinical stage of gastric cancer and the combined parameters were established. The AUC values of tumor thickness, CT attenuation of splenic venous phase, CTsd in splenic unenhanced phase and combined parameters were 0.655, 0.614, 0.749 and 0.806, respectively. The AUC of combined parameters was higher than those of tumor thickness and CT attenuation of splenic venous phase, and the differences were statistically significant ( Z=3.37, 3.82, both P<0.001). Conclusion:Tumor thickness, CT attenuation of splenic venous phase and CTsd in splenic unenhanced phase are independent risk factors for the clinical stage of gastric cancer, and combined parameters can improve the diagnostic efficiency.

At present, implant surgery robots have basically achieved "surgical intelligence", but "brain-inspired intelligence" of robots is still in the stage of theory and exploration. The formulation of a clinical implantation plan depends on the timing of implantation, implantation area, bone condition, surgical procedure, patient factors, etc., which need to evaluate the corresponding clinical decision indicators and clinical pathways. Inspired by evidence-based medicine and the potential of big data and deep learning, combined with the data characteristics of clinical decision indicators and clinical pathways that can be quantitatively or qualitatively analyzed, this review simulates the cognitive behavior and neural mechanisms of the human brain and proposes a feasible brain-inspired intelligence scheme by predicting the decision indices and executing clinical pathways intelligently, that is, "select clinical indicators and clarify clinical pathways -- construct database -- use deep learning to intelligently predict decision indicators -- intelligent execution of clinical pathways -- brain-inspired intelligence of implant decision-making". Combined with the previous research results of our team, this review also describes the process of realization of brain-inspired intelligence for immediate implant timing decisions, providing an example of the comprehensive realization of brain-inspired intelligence of implant surgery robots in the future. In the future, how to excavate and summarize other clinical decision factors and select the best way to realize the automatic prediction of evidence-based clinical indicators and pathways and finally realize the complete intellectualization of clinical diagnosis and treatment processes will be one of the directions that dental clinicians need to strive for.

Nerve regeneration in adult mammalian spinal cord is poor because of the lack of intrinsic regeneration of neurons and extrinsic factors - the glial scar is triggered by injury and inhibits or promotes regeneration. Recent technological advances in spatial transcriptomics (ST) provide a unique opportunity to decipher most genes systematically throughout scar formation, which remains poorly understood. Here, we first constructed the tissue-wide gene expression patterns of mouse spinal cords over the course of scar formation using ST after spinal cord injury from 32 samples. Locally, we profiled gene expression gradients from the leading edge to the core of the scar areas to further understand the scar microenvironment, such as neurotransmitter disorders, activation of the pro-inflammatory response, neurotoxic saturated lipids, angiogenesis, obstructed axon extension, and extracellular structure re-organization. In addition, we described 21 cell transcriptional states during scar formation and delineated the origins, functional diversity, and possible trajectories of subpopulations of fibroblasts, glia, and immune cells. Specifically, we found some regulators in special cell types, such as Thbs1 and Col1a2 in macrophages, CD36 and Postn in fibroblasts, Plxnb2 and Nxpe3 in microglia, Clu in astrocytes, and CD74 in oligodendrocytes. Furthermore, salvianolic acid B, a blood-brain barrier permeation and CD36 inhibitor, was administered after surgery and found to remedy fibrosis. Subsequently, we described the extent of the scar boundary and profiled the bidirectional ligand-receptor interactions at the neighboring cluster boundary, contributing to maintain scar architecture during gliosis and fibrosis, and found that GPR37L1_PSAP, and GPR37_PSAP were the most significant gene-pairs among microglia, fibroblasts, and astrocytes. Last, we quantified the fraction of scar-resident cells and proposed four possible phases of scar formation: macrophage infiltration, proliferation and differentiation of scar-resident cells, scar emergence, and scar stationary. Together, these profiles delineated the spatial heterogeneity of the scar, confirmed the previous concepts about scar architecture, provided some new clues for scar formation, and served as a valuable resource for the treatment of central nervous system injury.
Mice ; Animals ; Gliosis/pathology* ; Cicatrix/pathology* ; Spinal Cord Injuries ; Astrocytes/metabolism* ; Spinal Cord/pathology* ; Fibrosis ; Mammals ; Receptors, G-Protein-Coupled

Bavachin is a dihydroflavonoid compound isolated from Psoralea corylifolia, and exhibits anti-bacterial, anti-inflammatory, anti-tumor and lipid-lowering activities. Recent attention has gradually drawn on bavachin-induced apoptosis in many human cancer cell lines. However, the anti-cancer effects and related mechanisms in colorectal cancer remain unknown. Here, we investigated the effects of bavachin on colorectal cancer in vivo and in vitro. The results showed that bavachin inhibited the proliferation of human colorectal cancer cells and induce apoptosis. These changes were mediated by activating the MAPK signaling pathway, which significantly up-regulated the expression of Gadd45a. Furthermore, Gadd45a silencing obviously attenuated bavachin-mediated cell apoptosis. Inhibition of the MAPK signaling pathway by JNK/ERK/p38 inhibitors also weakened the up-regulation of Gadd45a by bavachin. The anticancer effect of bavachin was also validated using a mouse xenograft model of human colorectal cancer. In conclusion, these findings suggest that bavachin induces the apoptosis of colorectal cancer cells through activating the MAPK signaling pathway.
Humans ; Signal Transduction ; Flavonoids/pharmacology* ; Proteins/pharmacology* ; MAP Kinase Signaling System ; Colorectal Neoplasms/metabolism* ; Apoptosis ; Cell Line, Tumor ; Cell Proliferation ; Cell Cycle Proteins/pharmacology*

Objective:To evaluate the value of preoperative prediction of vessel invasion (VI) of locally advanced gastric cancer by machine learning model based on the venous phase enhanced CT radiomics features.Methods:A retrospective analysis of 296 patients with locally advanced gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from July 2011 to December 2020 was performed. The patients were divided into VI positive group ( n=213) and VI negative group ( n=83) based on pathological results. The data were divided into training set ( n=207) and test set ( n=89) according to the ratio of 7∶3 with stratification sampling. The clinical characteristics of patients were recorded, and the independent risk factors of gastric cancer VI were screened by multivariate logistic regression. Pyradiomics software was used to extract radiomic features from the venous phase enhanced CT images, and the minimum absolute shrinkage and selection algorithm (LASSO) was used to screen the features, obtain the optimal feature subset, and establish the radiomics signature. Four machine learning algorithms, including extreme gradient boosting (XGBoost), logistic, naive Bayes (GNB), and support vector machine (SVM) models, were used to build prediction models for the radiomics signature and the screened clinical independent risk factors. The efficacy of the model in predicting gastric cancer VI was evaluated by the receiver operating characteristic curve. Results:The degree of differentiation (OR=13.651, 95%CI 7.265-25.650, P=0.003), Lauren′s classification (OR=1.349, 95%CI 1.011-1.799, P=0.042) and CA199 (OR=1.796, 95%CI 1.406-2.186, P=0.044) were independent risk factors for predicting the VI of locally advanced gastric cancer. Based on the venous phase enhanced CT images, 864 quantitative features were extracted, and 18 best constructed radiomics signature were selected by LASSO. In the training set, the area under the curve (AUC) of XGBoost, logistic, GNB and SVM models for predicting gastric cancer VI were 0.914 (95%CI 0.875-0.953), 0.897 (95%CI 0.853-0.940), 0.880 (95%CI 0.832-0.928) and 0.814 (95%CI 0.755-0.873), respectively, and in the test set were 0.870 (95%CI 0.769-0.971), 0.877 (95%CI 0.788-0.964), 0.859 (95%CI 0.755-0.961) and 0.773 (95%CI 0.647-0.898). The logistic model had the largest AUC in the test set. Conclusions:The machine learning model based on the venous phase enhanced CT radiomics features has high efficacy in predicting the VI of locally advanced gastric cancer before the operation, and the logistic model demonstrates the best diagnostic efficacy.