Objective:This study aims to initially establish a scoring system for comprehensively reflecting the severity of intracranial atherosclerotic lesions and to explore the correlation between this score and atherosclerotic risk factors as well as stroke events.Methods:This study retrospectively analyzed patients who underwent head and neck computer tomography angiography(CTA)examinations and had head MRI examinations within one month before or after the CTA examination from January 2021 to August 2024 in Beijing Hospital.An intracranial atherosclerosis disease score(ICADS)system was constructed based on the degree and number of vascular stenosis.The relationship between ICADS and atherosclerotic risk factors was explored by grouping patients according to the quartile of ICADS.Patients were divided into acute stroke group and non-acute stroke group to compare differences in ICADS and cerebrovascular disease risk factors between the two groups, and to investigate the correlation between stroke events and ICADS.Results:There were statistically significant differences in the proportions of patients with hypertension and diabetes among different ICADS groups.Multiple linear regression analysis showed that hypertension( B=1.17, 95% CI: 0.20-2.14, P<0.05)and diabetes( B=2.75, 95% CI: 1.85-3.64, P<0.001)were risk factors for higher ICADS.The ICADS was higher in the acute stroke group than in the non-acute stroke group(9 vs.6, P<0.001), and a higher ICADS was identified as a risk factor for stroke( OR=1.10, 95% CI: 1.07-1.14, P<0.001). Conclusions:ICADS can comprehensively reflect the severity of intracranial atherosclerotic lesions and is correlated with stroke events, making it useful for clinical screening of high-risk patients for stroke.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Sepsis is a systemic inflammatory response caused by severe infection or trauma, and is one of the common causes of acute lung injury(ALI) and acute respiratory distress syndrome(ARDS). Sepsis-acute lung injury(SALI) is a critical clinical condition with high morbidity and mortality. Its pathogenesis is complex and not yet fully understood, and there is currently a lack of targeted and effective treatment options. Pyroptosis, a novel form of programmed cell death, plays a key role in the pathological process of SALI by activating inflammasomes and releasing inflammatory factors, making it a potential therapeutic target. In recent years, the role of traditional Chinese medicine(TCM) in regulating signaling pathways related to pyroptosis through multi-components and multi-targets has attracted increasing attention. TCM may intervene in pyroptosis by inhibiting the activation of NLRP3 inflammasomes and regulating the expression of Caspase family proteins, thus alleviating inflammatory damage in lung tissues. This paper systematically reviews the molecular regulatory network of pyroptosis in SALI and explores the potential mechanisms and research progress on TCM intervention in cellular pyroptosis. The aim is to provide new ideas and theoretical support for basic research and clinical treatment strategies of TCM in SALI.
Pyroptosis/drug effects* ; Humans ; Sepsis/genetics* ; Acute Lung Injury/physiopathology* ; Animals ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Inflammasomes/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics*

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective:This study aims to initially establish a scoring system for comprehensively reflecting the severity of intracranial atherosclerotic lesions and to explore the correlation between this score and atherosclerotic risk factors as well as stroke events.Methods:This study retrospectively analyzed patients who underwent head and neck computer tomography angiography(CTA)examinations and had head MRI examinations within one month before or after the CTA examination from January 2021 to August 2024 in Beijing Hospital.An intracranial atherosclerosis disease score(ICADS)system was constructed based on the degree and number of vascular stenosis.The relationship between ICADS and atherosclerotic risk factors was explored by grouping patients according to the quartile of ICADS.Patients were divided into acute stroke group and non-acute stroke group to compare differences in ICADS and cerebrovascular disease risk factors between the two groups, and to investigate the correlation between stroke events and ICADS.Results:There were statistically significant differences in the proportions of patients with hypertension and diabetes among different ICADS groups.Multiple linear regression analysis showed that hypertension( B=1.17, 95% CI: 0.20-2.14, P<0.05)and diabetes( B=2.75, 95% CI: 1.85-3.64, P<0.001)were risk factors for higher ICADS.The ICADS was higher in the acute stroke group than in the non-acute stroke group(9 vs.6, P<0.001), and a higher ICADS was identified as a risk factor for stroke( OR=1.10, 95% CI: 1.07-1.14, P<0.001). Conclusions:ICADS can comprehensively reflect the severity of intracranial atherosclerotic lesions and is correlated with stroke events, making it useful for clinical screening of high-risk patients for stroke.

Objective:To investigate the changes of thyroid hormones and the flow velocity of superior thyroid artery in patients with Graves' disease and Hashimoto's thyrotoxicosis before and after treatment with methimazole.Methods:A case-control study was conducted to select 45 cases of Graves' disease and 45 cases of Hashimoto's thyroiditis from October 2021 to December 2022 in the Department of Endocrinology, North China University of Science and Technology Affiliated Hospital. The changes of thyroid hormone and blood flow velocity of superior thyroid artery in patients with Graves' disease and Hashimoto's thyroiditis before and after treatment with methimazole were analyzed. Measurement data satisfying normal distribution were expressed by xˉ±s, and the mean between two groups was compared by t test. Measurement data not satisfying normal distribution were expressed by M( Q1, Q3), and the median between two groups was compared by Wilcoxon rank sum test. χ 2 test was used to compare the constituent ratio of enumeration data among groups. Results:There was no significant difference in thyroid stimulating hormone (TSH) between the two groups before treatment, and there was no significant difference in TSH between the two groups after 1 month and 3 months of treatment (all P>0.05). The levels of free triiodothyronine (FT3) were (24.09±9.29) pmol/L and (17.41±9.36) pmol/L in Graves' disease group and Hashimoto's thyroiditis group respectively before treatment. FT4 were (60.23±20.82) and (43.47±21.71) pmol/L, respectively, and the peak stolie vloiy (PSV) were (69.53±5.70) and (52.65±4.64) cm/s, respectively in Graves' disease group and Hashimoto's thyroiditis group respectively before treatment. There were significant differences between the two groups ( t values wrere 3.39 and 3.74, Z=13.83, all P<0.001). The difference of FT3 between one month after treatment and before treatment was (-6.36±5.32) and (-12.64±9.08) pmol/L ( t=4.02, P<0.001) and the difference in FT3 between 3 months of treatment and before treatment was (-10.14±9.50) and (-17.80±11.17) pmol/L, respectively ( t=3.51, P<0.001) between the Graves disease group and the Hashimoto's thyroiditis group. The difference in FT4 between the Graves disease group and the Hashimoto's thyroiditis group after 1 month of treatment and before treatment was (-28.47±10.09) and (-20.57±14.48) pmol/L ( t=7.01, P<0.001), and the difference of FT4 was (-47.06±20.57) and (-30.17±20.54) pmol/L ( t=3.91, P<0.001) between the Graves disease group and the Hashimoto toxin group. The difference between one month after treatment and before treatment was (-13.10(-34.10,-2.60)) and (-10.50(-27.5,-0.20)) cm/s ( Z=2.63, P=0.009), respectively. The difference between 3 months and before treatment was (-31.40(-53.20,-12.70)) and (-19.90(-46.00,-4.70)cm/s ( Z=4.40, P<0.001)) between the Graves disease group and the Hashimoto's thyroiditis group, and the difference was statistically significant. Conclusion:Thyroid hormone levels were decreased after treatment with methimazole in patients with diffuse toxic goiter and Hashimoto toxemia, but the difference was not statistically significant. The PSV level of superior thyroid artery in patients with diffuse toxic goiter was significantly lower than that in patients with Hashimoto's thyrotoxicosis.

BACKGROUND:High-methionine diet can cause liver injury in Cbs+/-mice,and hyperhomocystinemia is related to the occurrence and progression of various liver-related diseases,such as hepatic steatosis,autoimmune hepatitis,and alcoholic fatty liver disease.MicroRNAs(miRNAs)are involved in various cellular processes including cell survival,differentiation and autophagy,which are of great significance. OBJECTIVE:To investigate the critical role of miR-144-3p on Cbs+/-mouse hepatocyte autophagy induced by high methionine die. METHODS:(1)Ten male cystathione-β-synthase normal(Cbs+/+)mice and another 10 male mice with single gene knockout(Cbs+/-)of similar body mass,4 weeks of age,were fed a high-methionine diet and executed after 12 weeks to take liver tissue.(2)Human hepatocytes(HL-7702)were cultured in vitro and divided into control[0 μmol/L homocysteine(Hcy)],Hcy(100 μmol/L Hcy),mimic-NC(transfected with mimic-NC),mimic-NC + Hcy(mimic-NC transfecton+100 μmol/L Hcy),miR-144-3p mimic(transfected with miR-144-3p mimic),and miR-144-3p mimic + Hcy(miR-144-3p mimic transfection+100 μ mol/L Hcy),inhibitor-NC(transfected with inhibitor-NC),inhibitor-NC + Hcy(inhibitor-NC transfection + 100 μmol/L Hcy),miR-144-3p inhibitor(transfected with miR-144-3p inhibitor),and miR-144-3p inhibitor + Hcy(miR-144-3p inhibitor transfection + 100 μmol/L Hcy).Quantitative real-time PCR was used to detect the expression of miR-144-3p in liver tissue and hepatocytes.After transfection of miR-144-3p mimic or inhibitor,quantitative real-time PCR and western blot were used to detect the transfection efficiency of miR-144-3p and its effect on the expression of autophagy-related proteins LC3B and p62.The levels of alanine transferase and aspartate aminotransferase in hepatocyte supernatants were determined by enzyme linked immunosorbent assay.The correlation between the expression of miR-144-3 in hepatocyte and the levels of alanine transferase and aspartate aminotransferase in hepatocyte supernatants were analyzed by Pearson correlation analysis. RESULTS AND CONCLUSION:Compared with the Cbs+/+ group and control group,the expression of miR-144-3p in the liver tissue of the Cbs+/-group and in hepatocytes of the Hcy group was decreased(P<0.01).The expression of LC3B-Ⅱ/Ⅰ was decreased in hepatocyte after transfection of miR-144-3p mimic,while the protein expression of p62 was increased(P<0.01).The opposite results were obtained after transfection of miR-144-3p inhibitor(P<0.01).Compared with the mimic-NC group,the levels of alanine transferase and aspartate aminotransferase were decreased in the miR-144-3p mimic group(P<0.01),while the opposite results were obtained in the inhibitor-NC group(P<0.01).The expression of miR-144-3p in hepatocytes was negatively correlated with the levels of alanine transferase(P<0.01,r=-0.887 6)and aspartate aminotransferase(P<0.01,r=-0.829 9)in the supernatant of hepatocytes.To conclude,Hcy promotes hepatocyte autophagy by inhibiting the expression of miR-144-3p,which subsequently aggravates liver injury.

Cordycepin (Cpn), a natural active compound derived from the traditional Chinese medicine Cordyceps sinensis, has antifibrotic, antioxidant, and anti-inflammatory effects, but the impact of Cpn on pulmonary fibrosis and the downstream molecular mechanism remain unclear. In this study, A549 cells were induced by transforming growth factor β1 (TGFβ1) in vitro, the viability of A549 cells was evaluated by CCK-8 assay; and migration of A549 cells were detected by wound healing assay, invasion of A549 cells were detected by transwell assay. Molecular docking and molecular dynamics simulations were used to predict the interaction of histone deacetylase 7 (HDAC7) with vimentin and the association of Cpn with HDAC7. The pulmonary fibrosis model of mice was established by bleomycin in vivo to investigate the effect of Cpn on pathological changes of lung tissue. The impact of Cpn and molecular mechanism on pulmonary fibrosis were studied by Western blot assay, cell transfection assay, immunoprecipitation assay, immunofluorescence assay, immunohistochemistry and real-time quantitative PCR (RT-qPCR). All animal experiments were approved by the Shanghai Children's Medical Center Experimental Animal Ethics Committee (grant No. SCMC-LAWEC-2022-017). Results showed that Cpn had no toxic effect on A549 cells even at the concentration of 100 μmol·L^-1. Cpn inhibited migration and invasion of A549 cells and reduced deposition of collagen, the degree of lung inflammation and fibrosis in mice; in vivo and in vitro models, Cpn significantly reversed mRNA and protein expressions of epithelial-mesenchymal transition (EMT) and lung fibrosis markers collagen I, α-smooth muscle actin (α-SMA), N-cadherin, vimentin and E-cadherin and HDAC7. Deficiency of HDAC7 suppressed TGFβ1-induced EMT and expression of collagen I; vimentin interacted with HDAC7; and molecular docking experiment revealed that Cpn was interrelated with HDAC7. In conclusion, Cpn can target HDAC7 to mediate EMT and exert its anti-fibrotic effect, the inhibition of EMT and the improvement of pulmonary fibrosis provide a new idea and choice for the development of anti-pulmonary fibrosis drug.