Based on the interleukin-17(IL-17) signaling pathway, this study explores the effect and mechanism of Bufei Decoction on Klebsiella pneumoniae pneumonia in rats. SD rats were randomly divided into the control group, model group, Bufei Decoction low-dose group(6.68 g·kg~(-1)·d~(-1)), Bufei Decoction high-dose group(13.36 g·kg~(-1)·d~(-1)), and dexamethasone group(1.04 mg·kg~(-1)·d~(-1)), with 10 rats in each group. A pneumonia model was established by tracheal drip injection of K. pneumoniae. After successful model establishment, the improvement in lung tissue damage was observed following drug administration. Core targets and signaling pathways were screened using transcriptomics techniques. Real-time fluorescence quantitative polymerase chain reaction was used to detect the mRNA expression of core targets interleukin-6(IL-6), interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and chemokine CXC ligand 6(CXCL6). Western blot was used to assess key proteins in the IL-17 signaling pathway, including interleukin-17A(IL-17A), nuclear transcription factor-κB activator 1(Act1), tumor necrosis factor receptor-associated factor 6(TRAF6), and downstream phosphorylated p38 mitogen-activated protein kinase(p-p38 MAPK), and phosphorylated nuclear factor-κB p65(p-NF-κB p65). Apoptosis of lung tissue cells was detected by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling(TUNEL). The results showed that, compared with the control group, the model group exhibited significant pathological damage in lung tissue. The mRNA expression of IL-6, IL-1β, TNF-α, and CXCL6, as well as the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly increased, and the number of apoptotic cells was notably higher, indicating successful model establishment. Compared with the model group, both low-and high-dose groups of Bufei Decoction showed reduced pathological damage in lung tissue. The mRNA expression levels of IL-6, IL-1β, TNF-α, and CXCL6, and the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly decreased, with a significant reduction in apoptotic cells in the high-dose group. In conclusion, Bufei Decoction can effectively improve lung tissue damage and reduce inflammation in rats with K. pneumoniae. The mechanism may involve the regulation of the IL-17 signaling pathway and the reduction of apoptosis.
Animals ; Interleukin-17/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Rats ; Male ; Klebsiella pneumoniae/physiology* ; Klebsiella Infections/immunology* ; Humans ; Lung/drug effects*

Objective To describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification re-search.Methods The data retrieved and extracted from the Web of Science Core Collection (WoSCC),the core database of the Web of Science information service platform (hereinafter referred to as "WoS"),was used to analyze the trends and topic changes in research on forensic identification of human re-mains from 1991 to 2022.Network visualisation of publication trends,countries (regions),institutions,authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10.Results A total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained.The journal with the largest number of publications was Forensic Science International (164 articles).The country (region) with the largest number of published papers was China (90 articles).Katholieke Univ Leuven (Netherlands,21 articles) was the institution with the largest number of publications.Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation,and the most commonly studied remains were teeth.Conclusion The volume of publications in the field of forensic anthropological remains identification research has a distinct phasing.However,the scope of both international and domestic collaborations remains limited.Traditionally,human remains identifica-tion has primarily relied on key areas such as the pelvis,skull,and teeth.Looking ahead,future re-search will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques.

Objective:To determine the differential expressions of long non-coding RNA(lncRNA)and messenger RNA(mRNA)in normal and asthenospermia(AS)men and analyze their biological significance in AS.Methods:We isolated and ex-tracted total RNAs from 9 normal and 9 AS sperm samples,determined the expressions of RNAs in the sperm using the DNBSEQ se-quencing platform,and analyzed their relevant functions by gene ontology enrichment(GO)and Kyoto encyclopedia of genes and ge-nomes pathway(KEGG)analyses.Results:An average of 10.64G data was generated per group,with 282 185 RNAs detected,in-cluding 107 009 lncRNAs.Among the total number of lncRNAs,15 157 were differentially expressed,2 190 upregulated and 12 967 downregulated;and among the 19 514 mRNAs,13 736 were differentially expressed,4 995 upregulated and 8 741 downregulated.Differentially expressed genes were enriched mainly in the sperm cell membrane and the pathways related to the ion channel functions,sperm development and fertilization.Conclusion:Differentially expressed lncRNAs and mRNAs can be identified by sequencing a-nalysis of AS and normal sperm.Regulation of sperm function through membrane ion channels may contribute to the development of AS,which provides a molecular basis for further research on AS.

Objective:To investigate the value of systemic inflammatory response syndrome (SIRS), pediatric sequential organ failure assessment (pSOFA) and pediatric critical illness score (PCIS) in predicting mortality of pediatric sepsis in pediatric intensive care units (PICU) from Southwest China.Methods:This was a prospective multicenter observational study. A total of 447 children with sepsis admitted to 12 PICU in Southwest China from April 2022 to March 2023 were enrolled. Based on the prognosis, the patients were divided into survival group and non-survival group. The physiological parameters of SIRS, pSOFA and PCIS were recorded and scored within 24 h after PICU admission. The general clinical data and some laboratory results were recorded. The area under the curve (AUC) of the receiver operating characteristic curve was used to compare the predictive value of SIRS, pSOFA and PCIS in mortality of pediatric sepsis.Results:Amongst 447 children with sepsis, 260 patients were male and 187 patients were female, aged 2.5 (0.8, 7.0) years, 405 patients were in the survival group and 42 patients were in the non-survival group. 418 patients (93.5%) met the criteria of SIRS, and 440 patients (98.4%) met the criteria of pSOFA≥2. There was no significant difference in the number of items meeting the SIRS criteria between the survival group and the non-survival group (3(2, 4) vs. 3(3, 4) points, Z=1.30, P=0.192). The pSOFA score of the non-survival group was significantly higher than that of the survival group (9(6, 12) vs. 4(3, 7) points, Z=6.56, P<0.001), and the PCIS score was significantly lower than that of the survival group (72(68, 81) vs. 82(76, 88) points, Z=5.90, P<0.001). The predictive value of pSOFA (AUC=0.82) and PCIS (AUC=0.78) for sepsis mortality was significantly higher than that of SIRS (AUC=0.56) ( Z=6.59, 4.23, both P<0.001). There was no significant difference between pSOFA and PCIS ( Z=1.35, P=0.176). Platelet count, procalcitonin, lactic acid, albumin, creatinine, total bilirubin, activated partial thromboplastin time, prothrombin time and international normalized ratio were all able to predict mortality of sepsis to a certain degree (AUC=0.64, 0.68, 0.80, 0.64, 0.68, 0.60, 0.77, 0.75, 0.76, all P<0.05). Conclusion:Compared with SIRS, both pSOFA and PCIS had better predictive value in the mortality of pediatric sepsis in PICU.

Objective By population survey,to explore the epidemiological characteristics of gastric precancerous lesions in Lishui District of Nanjing and provide objective basis for the prevention and treatment of early gastric cancer.Methods From July 2021 to December 2022,21 977 patients who received endoscopy and/or 13C-UBT in Lishui District People's Hospital and 6 medical community units in Nanjing City were retrospectively analyzed for demography characteristics,detection rate of gastric precancerous lesions,and H.Pylori infection rate.Results(1)590 cases of gastric precancerous lesions were detected(detection rate 2.68%);(2)The total detection rate of precancerous lesions and three pathological types in males were all higher than those in females(all P<0.001);(3)The minimum age for the total detection rate of precancerous lesions in males and the mini-mum age for each pathological type were lower than in females(P<0.001,0.009,0.005,0.002);(4)The popu-lation total H.pylori infection rate was 23.10%,the H.pylori infection rate in patients with precancerous lesions was higher than that in non-precancerous lesions(P<0.001),both H.pylori infection rate of male and female in precancerous lesions were all higher than those of non-precancerous lesions of the same sex(all P<0.001),in addition,the H.pylori infection rate of male whether in precancerous or non-precancerous lesions was higher than that of female(all P<0.001);(5)The precancerous lesions detection rate in male,female,and the overall age range of 20～29 to 70～79 years is positively correlated with age growth(P<0.001),and rapidly decreases after the age of 79,the of H.pylori infection rate was also positively correlated with age growth(P<0.001),and the trend of age change(P<0.001)was parallel to the precancerous lesions detection rate.Conclusions The detec-tion rate of gastric precancerous lesions in this region is above the average level in China;the total H.pylori infec-tion rate is at a relatively low level in China;the H.pylori infection rate is parallel to the age trend of the detection rate of gastric precancerous lesions,and increases with age.

Objective To explore the value of model established with radiomics features based on contrast enhanced arterial phase CT and model with radiogenomics for predicting prognosis of ovarian serous cystadenocarcinoma(OSC).Methods Enhanced arterial phase CT images of 110 OSC patients were retrospectively collected from 2 centers and The Cancer Imaging Archive(TCIA)database.The radiomics features were extracted,among those related to prognosis were selected to establish a radiomics Cox regression model.Genes data of 399 OSC patients were obtained from The Cancer Genome Atlas(TCGA)database,and genes related to the radiomics features included in the above radiomics model were identified with high Pearson correlation coefficient,and then enrichment gene analyses were performed.For 57 OSC cases with complete enhanced CT and gene data,the hub genes which had the highest connectivity with radiomics prognosis predicting model were detected using Cox regression and protein-protein interaction(PPI).Furthermore,a radiogenomics prognosis predicting model was established with the hub genes.The efficiencies of these 2 models for predicting prognosis of OSC patients were analyzed.Results Finally,the radiomics model included 5 OSC prognosis-related radiomics features,with C-index of 0.782 and 0.735 in corresponding training and test set,respectively.Meanwhile,the radiogenomics model included 30 prognostic hub genes,with C-index of 0.673 and 0.659 in corresponding training and test set,respectively.The survival rates of patients with better predicted prognosis according to radiomics model and radiogenomics model were both higher compared with the others(both P＜0.05).Totally 1 135 mRNA genes were found being associated with radiomics model,including biological behaviors such as cell adhesion,and signaling pathways such as PI3K-Akt,extracellular matrix receptor interaction pathway and type 1 diabetes pathway.Conclusion The radiomics model was effective for predicting prognosis of OSC patients.Analysis of mRNA bioinformatics in OSC patients might provide biological interpretations for the radiomics model.

Objective To construct and validate a risk prediction model for delayed healing of venous leg ulcer(VLU),so as to provide a reference basis for early identification of people at high risk of delayed healing.Methods Using a convenience sampling method,331 VLU patients attending vascular surgery departments in 2 tertiary A hospitals in Sichuan Province from January 2018 to December 2022 were selected as a modeling group and an internal validation group,and 112 patients admitted to another tertiary A hospital were selected as an external validation group.Risk factors for delayed healing in VLU patients were screened using univariate analysis,LASSO regression,and multivariate logistic regression analysis,and a risk prediction model was constructed using R software,and the predictive effects of the models were examined using the area under the receiver operating characteristic curve,the Hosmer-Lemeshow test,decision curve,and the bootstrap resampling for internal validation and spatial external validation were performed,respectively.Results The predictors that ultimately entered the prediction model were diabetes(OR=4.752),deep vein thrombosis(OR=4.104),lipodermatosclerosis(OR=5.405),ulcer recurrence(OR=3.239),and ankle mobility(OR=5.520).The model had good discrimination(AUC:0.819 for internal validation and 0.858 for external validation),calibration(Hosmer-Lemeshow test:χ2=13.517,P=0.095 for internal validation and χ2=3.375,P=0.909 for external validation)and clinical validity.Conclusion The model constructed in this study has good differentiation and calibration,and it can effectively predict people at high risk of delayed healing of VLU,which facilitates targeted clinical interventions to improve ulcer outcomes and reduce the risk of delayed ulcer healing.

OBJECTIVE: To explore weight-bearing stability of Pilon fracture fixed by external fixator. METHODS: Six ankle bone models (right side) and 4 pairs (8 ankle cadaver specimens) were selected. Pilon fracture model was prepared by using the preset osteotomy line based on Ruedi Allgower Pilon fracture type. Pilon fracture model was built by using a minimally invasive osteotomy. After ankle bone model and cadaver specimen model were fixed with external fixator, axial load was carried out on mechanical loading machine. After ankle bone model and cadaver specimen model were fixed with external fixator, axial load was carried out on mechanical loading machine. Axial loads of 150, 300 and 450 N were applied to ankle bone model, and displacements of fibula fracture blocks, lateral tibia fracture blocks and medial tibia fracture blocks in three-dimensional space (X, Y and Z axes) were recorded by dynamic capture instrument. Axial loads of 300, 600 and 900 N were applied to ankle cadaver model fixed by external fixator. X-ray films of Pilon fracture cadaver model fixed by external fixator under different loading conditions were taken. The anterior tibial angle, tibial malleolar point angle, talus shift value, talus tilt angle, lateral malleolar shift value, lateral malleolar shift value, medial malleolar separation shift value and articular surface step displacement value were measured under different loads by digimizer software. RESULTS: After 150, 300 and 450 N axial loads were applied to Pilon fracture models fixed by external fixator, no loosening or fracture of external fixator was observed, and no loosening, fracture or irreversible plastic deformation of Kirschner needle were observed. The displacement values of fibular fracture pieces on X-axis(around) were 0.032 (-0.022, 0.269), 0.061 (-0.002, 0.427), 0.212(-0.016, 1.223) mm, and the displacement values on Y-axis(above and below) were 0.002(-0.031, 0.103), 0.051(-1.133, 0.376), 0.128 (-1.394, 0.516) mm, and displacement values on Z-axis (front and rear) were -0.003 (-0.130, 0.171), 0.137 (-0.076, 0.433), 0.030(-0.487, 0.478) mm;the displacement values of lateral tibial fractures on X-axis were 0.000(-0.108, 0.027), 0.083(-0.364, 0.050), -0.121(-0.289, 0.165) mm, and displacement values on Y-axis were -0.009(-0.200, 0.025), -0.179(-0.710, 0.084), -0.257(-0.799, 0.027) mm, and displacement values on Z-axis were 0.112(-0.024, 0.256), 0.157(-0.068, 0.293), -0.210(-0.035, 0.430) mm;the displacement values of medial tibial fracture block on X-axis were -0.010(-0.060, 0.013), -0.165(-0.289, 0.056), -0.181(-0.395, 0.013) mm, and the displacement values on Y-axis were -0.036(-0.156, 0.007), -0.104(-0.269, 0.178), -0.245(-0.380, -0.011) mm, and displacement values on Z-axis were -0.005(-0.372, 0.189), -0.012 (-1.774, 0.380), 0.200 (-1.963, -0.540) mm. After 300, 600 and 900 N axial loads were applied to Pilon fracture cadaverous models fixed with external fixators, there were no significant difference in anterior tibial angles, angles of malleolar points of tibia, oblique angles of talus, fracture steps, shift values of talus, lateral shift values of lateral malleolus, lateral shift values of medial malleolus, lateral shift values of medial malleolus between under different loading conditions and those without loading (P>0.05). No loosening or fracture of external fixator as a whole, loosening, fracture or irreversible deformation of Kirschner needle at the local fixed fracture end occurred. CONCLUSION The early weight-bearing external fixator could maintain stability of fracture end and ankle joint, and the maximum weight is not more than 300 N. In clinical practical application, material characteristics of the implant and type of fracture should be selected.
Humans ; Weight-Bearing ; Biomechanical Phenomena ; External Fixators ; Tibial Fractures/physiopathology* ; Fracture Fixation/instrumentation* ; Male

Objective To explore the value of constructing a model to predict the number of positive cores in systematic biopsy in prostate cancer(PCa)using a combination of radiomics features based on magnetic resonance imaging and clinical indicators.Methods Retrospectively collected magnetic resonance imaging and clinical data from two medical institutions(Gansu Provincial Hospital from January 2018 to February 2023,Zhangye People's Hospital Affiliated to Hexi College from April 2020 to February 2023).The 155 patients from Gansu Provincial Hospital were randomly divided into a training set(n=109;80 cases with positive needle count≥6 and 29 cases with positive needle count<6)and an internal validation set(n=46;34 cases with positive needle count≥6 and 12 cases with positive needle count<6)in a 7:3 ratio.The 43 patients from Zhangye People's Hospital Affiliated to Hexi College were used as external validation set.Small field of view high-resolution T2-weighted imaging(sFOV HR-T2WI)and contrast-enhanced delayed-phase images were selected to extract radiomic features from the three-dimensional region of interest of the entire prostate,and radiomics model was constructed and Radscores calculated after dimensionality reduction and feature selection.Univariate and multivariate logistic regressions were used to screen for independent risk factors for positive cores in systematic biopsy.Nomogram was constructed using Radscore and clinical independent risk factors to predict the number of positive cores in systematic biopsy in PCa patients,which was then externally validated.Results Age,alkaline phosphatase(ALP),free prostate specific antigen(FPSA),total prostate specific antigen(TPSA),FPSA/TPSA ratio,and prostate specific antigen density(PSAD)were not statistically significantly different between the training,internal validation,and external validation sets(P>0.05).FPSA,TPSA,FPSA/TPSA ratio,and PSAD were significantly different between the positive cores<6 and positive cores≥6 groups(P<0.001).Univariate logistic regression analysis showed that FPSA(P<0.001),TPSA(P<0.001),FPSA/TPSA ratio(P=0.001),PSAD(P<0.001),and Radscore(P<0.001)were risk factors for positive cores in systematic biopsy in PCa.Multivariate logistic regression analysis showed that PSAD(OR=0.251,95%CI 0.063-0.996,P=0.049)and Radscore(OR=1.990,95%CI 1.409-2.812,P<0.001)were independent risk factors for positive cores in systematic biopsy in PCa.The clinical models achieved AUCs of 0.849(95%CI 0.774-0.924),0.817(95%CI 0.693-0.941),and 0.631(95%CI 0.439-0.822);the 12 features for radiomics models are derived solely from sFOV HR-T2WI,the radiomics models achieved AUCs of 0.868(95%CI 0.791-0.945),0.846(95%CI 0.695-0.996),and 0.815(95%CI 0.660-0.970);the nomogram achieved AUCs of 0.921(95%CI 0.869-0.973),0.868(95%CI 0.743-0.992),and 0.840(95%CI 0.702-0.978)in the training set,internal validation set,and external validation set,respectively.Conclusions The combination of radiomic features extracted from sFOV HR-T2WI and PSAD can preoperatively be used as a noninvasive manner to predict the number of positive cores of the PCa patients.This approach has a certain value in risk stratification of PCa patients and guiding personalized clinical management.

Objective:To construct a combined radiomics model based on preoperative enhanced computed tomography (CT) examination for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and provide biological explanations for the radiomics model.Methods:The retrospective cohort study was conducted. The messenger RNA (mRNA) of 424 HCC patients, the clinicopathological data of 39 HCC patients entered into the Cancer Genome Atlas database from its establishment until January 2023, and the clinicopathological data of 53 HCC patients who were admitted to the Gansu Provincial People′s Hospital from January 2020 to January 2023 were collected. The 92 HCC patients were randomly divided into a training dataset of 64 cases and a test dataset of 28 cases with a ratio of 7∶3 based on a random number table method. The CT images of patients in the arterial phase and portal venous phase as well as the corresponding clinical data were analyzed. The 3Dslicer software (version 5.0.3) was used to register the CT images in the arterial phase and portal venous phase and delineate the three-dimensional regions of interest. The original images were preprocessed and the corresponding features were extracted by the open-source software FAE (version 0.5.5). After selecting features using the Least Absolute Shrinkage and Selection Operator, the radiomics model was constructed and the radiomics score (R-score) was calculated. The nomogram was constructed by integrating clinical parameters, imaging features and R-score based on Logistic regression. The gene modules related to radiomics model were obtained and subjected to enrichment analysis by conducting weighted gene co-expression network analysis and correlation analysis. Observation indicators: (1) comparison of clinical characteristics of patients with different MVI properties; (2) establishment of MVI risk model; (3) evaluation of MVI risk model; (4) clustering of gene modules; (5) functional enrichment of feature-correlated gene modules. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Comparison of count data was conducted using the chi-square test. The intra-/inter-class correlation coefficient (ICC) was used to assess the inter-observer consistency of radiomics feature extracted by different observers. ICC >0.75 indicated a good consistency in feature extraction. The Logistic regression model was used for univariate and multivariate analyses. The receiver operating characteristic curve was drawn, and the area under curve (AUC), the decision curve and the calibration curve were used to evaluate the diagnostic efficacy and clinical practicality of the model. Results:(1) Comparison of clinical characteristics of patients with different MVI properties. Of 92 HCC patients, there were 47 cases with MVI-positive and 45 cases with MVI-negative, and there were significant differences in hepatitis, tumor diameter, peritumoral enhancement, intratumoral arteries, pseudocapsule and smoothness of tumor margin between them ( χ2=5.308, 9.977, 47.370, 32.368, 21.105, 31.711, P<0.05). (2) Establishment of MVI risk model. A total of 1 781 features were extrac-ted from arterial and portal venous phases of the intratumoral and peritumoral regions. After feature dimension reduction, 8 radiomics features were selected from arterial and portal venous phases to construct the combined model. Results of multivariate analysis showed that peritumoral enhancement, intratumoral arteries, pseudocapsule, smoothness of tumor margins, and R-score were independent risk factors for MVI in patients with HCC [ hazard ratio=0.049, 0.017, 0.017, 0.021, 2.539, 95% confidence interval ( CI) as 0.005-0.446, 0.001-0.435, 0.001-0.518, 0.001-0.473, 1.220-5.283, P<0.05]. A nomogram model was constructed incorporating peritumoral enhancement, intratumoral arteries, pseudocapsule, smoothness of tumor margins, and R-score. (3) Evaluation of the MVI risk model. The AUC of radiomics model was 0.923 (95% CI as 0.887-0.944) and 0.918 (95% CI as 0.894-0.945) in the training dataset and test dataset, respectively. The AUC of nomogram model, incorpora-ting both the R-score and radiomics features, was 0.973 (95% CI as 0.954-0.988) and 0.962 (95% CI as 0.942-0.987) in the training dataset and test dataset, respectively. Results of decision curve showed that the nomogram had better clinical utility compared to the R-score. Results of calibration curve showed good consistency between the actual observed outcomes and the nomogram or the R-score. (4) Clustering of gene module. Results of weighted gene co-expression network analysis showed that 8 gene modules were obtained. (5) Functional enrichment of feature-related gene modules. Results of correlation analysis showed 4 gene modules were significantly associated with radiomics features. The radiomics features predicting of MVI may be related to pathways such as the cell cycle, neutrophil extracellular trap formation, and PPAR signaling pathway. Conclusions:The combined radiomics model based on preoperative enhanced CT imaging can predict the MVI status of HCC. By obtaining mRNA gene expression profiles associated with radiomics features, a biological interpretation of the radiomics model is provided.