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Measuring pore-water pressure (PWP) in frozen soils poses significant challenges in geotechnical testing experiments, and understanding PWP is crucial for unraveling the mechanism of frost heave generation in cold regions. This paper aims to clarify the development pattern of PWP in frozen soil through laboratory tests, specifically focusing on excess PWP generated under dynamic loading. Seven sets of triaxial tests were conducted to investigate the variations in excess PWP and deformation influenced by temperature, dynamic stress amplitude, and dry density. The results reveal that excess PWP in warm saturated frozen soil undergoes two stages: pore pressure increase and dissipation. The change of external factors mainly affects the peak value of excess PWP and the change rate of excess PWP. Unlike unfrozen soil, excess PWP has a small dissipation rate after the peak and may remain dynamically stable in the later stage of loading. In addition, two empirical models of excess PWP applicable to saturated frozen soils were proposed based on the developmental patterns of excess PWP in frozen soils, and the feasibility was validated using the results obtained from laboratory tests. The model is of great significance for predicting the development of excess PWP in frozen soil under dynamic load.

Abstract Purpose Prostate cancer (PCa) is a common malignancy in men, with an escalating mortality rate attributed to Recurrence and metastasis. Recent studies have illuminated collagen’s critical regulatory role within the tumor microenvironment, significantly influencing tumor progression. Accordingly, this investigation is dedicated to examining the relationship between genes linked to collagen and the prognosis of PCa, with the objective of uncovering any possible associations between them. Methods Gene expression data for individuals with prostate cancer were obtained from the TCGA repository. Collagen-related genes were identified, leading to the development of a risk score model associated with biochemical recurrence-free survival (BRFS). A prognostic nomogram integrating the risk score with essential clinical factors was crafted and evaluated for efficacy. The influence of key collagen-related genes on cellular behavior was confirmed through various assays, including CCK8, invasion, migration, cell cloning, and wound healing. Immunohistochemical detection was used to evaluate PLOD3 expression in prostate cancer tissue samples. Results Our study identified four key collagen-associated genes (PLOD3, COL1A1, MMP11, FMOD) as significant. Survival analysis revealed that low-risk groups, based on the risk scoring model, had significantly improved prognoses. The risk score was strongly associated with prostate cancer prognosis. Researchers then created a nomogram, which demonstrated robust predictive efficacy and substantial clinical applicability.Remarkably, the suppression of PLOD3 expression notably impeded the proliferation, invasion, migration, and colony formation capabilities of PCa cells. Conclusion The risk score, derived from four collagen-associated genes, could potentially act as a precise prognostic indicator for BRFS of patients. Simultaneously, our research has identified potential therapeutic targets related to collagen. Notably, PLOD3 was differentially expressed in cancer and para-cancer tissues in clinical specimens and it also was validated through in vitro studies and shown to suppress PCa tumorigenesis following its silencing.

Abstract Background Studies have indicated a close association between genes linked to liquid–liquid phase separation (LLPS) and the progression of prostate cancer (PCa). However, the interplay among long non-coding RNAs (lncRNAs) linked to LLPS in PCa remains elusive. Therefore, we constructed a prediction model based on LLPS-related LncRNA in PCa to explore its relationship with the prognosis and drug treatment of PCa. Methods We obtained clinical and sequencing data from TCGA and LLPS genes from the Phase Separation Protein Database. By analyzing the differential expression of LLPS-related genes and lncRNAs in prostate cancer, and using Poisson correlation, we identified LLPS-related lncRNAs. Prognostic LLPS-lncRNAs were found through prognostic correlation analysis and included in a Cox model to compute regression coefficients. Patients were scored and divided into high- and low-risk groups. Independent prognostic factors were integrated into a prognostic nomogram with risk and Gleason scores. We also conducted drug sensitivity analyses, GSEA, and validated the impact of key lncRNAs through functional experiments. Results Our study identified five LLPS-associated lncRNAs that are of prognostic importance. And found notable disparities in biochemical recurrence rates and survival outcomes between these risk groups, with the low-risk cohort exhibiting superior prognostic indicators. Moreover, our prediction nomogram demonstrated robust predictive accuracy and significant clinical utility. Furthermore, our model exhibited promising capabilities in forecasting patient sensitivity to various conventional therapeutic drugs, thereby highlighting its potential in personalized treatment strategies. GSEA showed that these lncRNAs may influence PCa prognosis and sensitivity to therapeutic agents by affecting pathways such as cell cycle. Knockdown of AC009812.4 could inhibit the ability of PCa cells to proliferate, migrate and invade, and compare to paracancerous tissue, AC009812.4 in PCa tissue has significantly higher expression. Conclusion Our research uncovers the prognostic significance of lncRNAs associated with LLPS in PCa and established a model exhibiting excellent predictive accuracy for prognosis. Those lncRNAs may influence progress of PCa as well as sensitivity to therapy drugs through pathways such as cell cycle.

Freeze-thaw cycles (FTC) cause significant changes in the physical and mechanical properties of soil, leading to structural alterations that can seriously threaten the safety and longevity of engineering structures. To investigate the consolidation characteristics of soils subjected to FTC, 18 sets of consolidation compression tests were carried out with saturated clay. Using a modified consolidation apparatus, the changes in pore-water pressure (PWP) and strain during consolidation were measured, with a focus on the effects of dry density and the number of FTC. The results show that although the overall patterns of PWP and strain during consolidation are similar before and after FTC, variations in dry density and the number of FTC lead to significant differences in the measured values. Specifically, PWP decreases while soil deformation increases with an increasing number of FTC cycles, even across different dry density conditions. The most pronounced changes in PWP and strain occur during the first 1–3 FTC cycles, with some samples showing continued significant changes up to 3–5 cycles. However, beyond five FTC, the increments in PWP and strain become considerably smaller. Meanwhile, an approximate linear relationship was observed between the peak PWP and steady-state strain values during graded loading, with this linearity decreasing as dry density increases. In addition, the Burgers model was modified based on the measured dissipation pattern of PWP to overcome the shortcomings of the traditional Burgers model. The modified Burgers model provides a more accurate representation of the soil's deformation process following FTC compared to the traditional model. This study can provide theoretical guidance for predicting the deformation of soils after freeze-thaw cycles.

Purpose To assess whether gray-scale ultrasound (US) based radiomic features can help distinguish HER2 expressions (ie, HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing) in breast cancer. Materials and Methods This retrospective study encompassed female breast cancer patients who underwent US examinations at two distinct centers from February 2021 to July 2023. Tumor segmentation and radiomic feature extraction were performed on grayscale US images. Decision Tree analysis was employed to simultaneously evaluate feature importance, and the Least Absolute Shrinkage and Selection Operator technique was utilized for feature selection to construct the radiomic signature. The Area Under the Curve (AUC) of the Receiver Operating Characteristic curve was employed to assess the performance of the radiomic features. Multivariate logistic regression was used to identify independent predictors for distinguishing HER2 expression in the dataset. Results The training set comprised 292 patients from Center 1 (median, 51 years; interquartile range [IQR]: 45-61), while the external validation set included 131 patients from Center 2 (median, 51 years; IQR: 45-62). In the external validation dataset, the radiomic features achieved AUC of 0.76 for distinguishing between HER2-low and positive tumors versus HER2-zero tumors. The AUC for differentiating HER2-low (1+) from HER2-zero tumors was 0.74, and for distinguishing HER2-low (2+) from HER2-zero tumors, the AUC was 0.77. In the multivariate analysis assessing HER2-low and HER2-positive versus HER2-zero tumors, internal echoes (P = .029) and margins (P

ABSTRACT Background Early detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels. Methods A mixed‐cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set. Results The BCaS3miR model, utilizing only three serum miRNAs (miR‐6087, miR‐1343‐3p, and miR‐5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984–0.991), 0.964 (95% CI: 0.936–0.984), and 0.917 (95% CI: 0.836–0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR‐1343‐3p/miR‐6087 and miR‐5100/miR‐6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages. Conclusions Using a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.

Abstract A high‐temperature superconducting (HTS) dynamo flux pump can inject DC currents into closed‐loop HTS magnets without contact. It enables the realisation of current‐lead‐free or even through‐wall charging systems for high‐field applications such as nuclear magnetic resonance/magnetic resonance imaging (MRI) magnets, fusion reactors and accelerators. Researchers have proposed many simulation models to understand the working principle of HTS dynamos, few of which are in 3D because of converging problems. Therefore, the influences of many key 3D parameters in the HTS dynamo are scarcely reported. The authors propose an efficient 3D modelling method of the HTS dynamo based on the T‐A formulation. The rotating magnets are modelled by a ring‐shaped permanent magnet with space‐time‐variant remanent flux density to avoid moving meshes. This, together with the T‐A formulation, makes the 3D model efficient and universal. The accuracy of the model is verified by the experimental instantaneous and time‐integrated dynamic voltages. Using this model, the authors present systematic case studies to thoroughly explore the influences of the key parameters of a dynamo flux pump on the dynamic voltage and losses. The proposed modelling method and results could significantly benefit the design and optimisation of HTS dynamos for high‐field magnets.

Abstract Purpose Prostate cancer (PCa) is one of the major tumor diseases that threaten men’s health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two. Methods Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted. Results The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue. Conclusions A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.

Abstract Objective The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization. Methods Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat‐sen Memorial Hospital of Sun Yat‐sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c‐index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model. Results A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c‐index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system. Conclusion Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision‐making processes.

(1) Background: This research aims to identify candidates for trimodality therapy (TMT) or radical cystectomy (RC) by using a predictive model. (2) Methods: Patients with nonmetastatic muscle-invasive bladder cancer (MIBC) in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled. The clinical data of 2174 eligible patients were extracted and separated into RC and TMT groups. To control for confounding bias, propensity score matching (PSM) was carried out. A nomogram was established via multivariable logistic regression. The area under the receiver operating characteristic curve (AUC) and calibration curves were used to assess the nomogram’s prediction capacity. Decision curve analysis (DCA) was carried out to determine the nomogram’s clinical applicability. (3) Results: After being processed with PSM, the OS of the RC group was significantly longer compared with the TMT group (p < 0.001). This remarkable capacity for discrimination was exhibited in the training (AUC: 0.717) and validation (AUC: 0.774) sets. The calibration curves suggested acceptable uniformity. Excellent clinical utility was shown in the DCA curve. The RC and RC-Beneficial group survived significantly longer than the RC and TMT-Beneficial group (p < 0.001) or the TMT group (p < 0.001). However, no significant difference was found between the RC and TMT-Beneficial group and the TMT group (p = 0.321). (4) Conclusions: A predictive model with excellent discrimination and clinical application value was established to identify the optimal patients for TMT among nonmetastatic MIBC patients.

Abstract Background SPOCK3 is a secreted extracellular matrix proteoglycan. This study aimed to investigate the effect of SPOCK3 on the malignant progression of prostate cancer and to construct a prognostic model to predict DFS of patients with prostate cancer. Methods Clinical and transcriptome sequencing data for prostate cancer were download from the TCGA and GEO databases. The survival curve showed that SPOCK3 has prognostic significance. GO, KEGG, and GSEA enrichment analysis were used to investigate how SPOCK3 affects the malignant progression of prostate cancer. Based on ESTIMATE and ssGSEA, the relationship between SPOCK3 and immune cell infiltration in prostate cancer tissue was clarified. Univariate and multivariate COX regression analysis was used to identify the independent prognostic factors of prostate cancer OS and to construct a nomogram. The calibration curve and ROC curves were drawn to assess the nomogram's predictive power. Results The survival curve revealed that patients in the low-expression group of SPOCK3 had a poor prognosis. According to enrichment analysis, SOPCK3-related genes were enriched in collagen-containing extracellular matrix, PI3K-Akt, and MAPK signaling pathway. ESTIMATE analysis revealed that SPOCK3 expression was positively correlated with the interstitial score, immune score, and ESTIMATE score. The results of ssGSEA analysis revealed that the infiltration levels of Mast cells, NK cells, and B cells were higher in the SPOCK3 high expression group. Cox regression analysis showed that SPOCK3 expression level, T and Gleason score were independent risk factors of patient prognosis, and a nomogram was constructed. The ROC curve showed the AUCs of DFS at 2, 3, and 5 years. Conclusion SPOCK3 is a protective factor for DFS in prostate cancer patients. SPOCK3 is significantly associated with immune cell infiltration. The prognostic model constructed based on SPOCK3 has excellent predictive performance.

Abstract Objective Buccal mucosa cancer (BMC) is one of the most common oral cancers and has poor prognosis. The study aimed to develop and validate nomograms for predicting the 1‐, 3‐, and 5‐year overall survival (OS) and cancer‐specific survival (CSS) of BMC patients. Methods We collected and reviewed information on BMC patients diagnosed between 2004 and 2019 from the Surveillance Epidemiology and End Results database. Two nomograms were developed and validated to predict the OS and CSS based on predictors identified by univariate and multivariate Cox regression. An extra external validation was further performed using data from Sun Yat‐sen Memorial Hospital (SYSMH). Results A total of 3154 BMC patients included in this study were randomly assigned to training and validation groups in a 2:1 ratio. Independent prognostic predictors were identified, confirmed, and fitted into nomograms for OS and CSS, respectively. The C‐indices are 0.767 (Training group OS), 0.801 (Training group CSS), 0.763 (Validation group OS), and 0.781 (Validation group OS), respectively. Moreover, the nomograms exhibited remarkable precision in forecasting and significant clinical significance, as evidenced by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA). The final validation using our data from SYSMH also showed high accuracy and substantial clinical benefits within the nomograms. The C‐indices are 0.849 (SYSMH group OS) and 0.916 (SYSMH group CSS). These indexes are better than tumor, node, and metastasis stage based on prediction results. Conclusions The nomograms developed with great performance predicted 1‐, 3‐, and 5‐year OS and CSS of BMC patients. Use of the nomograms in clinical practices shall bring significant benefits to BMC patients.

Abstract Purpose To clarify the necessity and effect of a single intraoperative instillation of chemotherapy during radical cystectomy. Methods Patients who underwent radical cystectomy for bladder cancer between January 2013 and April 2019 were retrospectively evaluated and divided into a non‐instillation group and an instillation group according to the intraoperative instillation of chemotherapy. Univariate and multivariate Cox regression was used to determine the clinical predictors of overall survival and disease‐free survival. Kaplan–Meier analysis and log‐rank tests were performed to analyze overall survival and disease‐free survival. Results Of the 320 patients who were enrolled in the study, 113 underwent radical cystectomy with intraoperative instillation of chemotherapy. Univariate Cox analysis showed that intraoperative instillation was not a risk factor for overall survival or disease‐free survival (HR: 1.04, 95% CI: 0.66–1.63, p = 0.864; HR: 1.11, 95% CI: 0.76–1.62, p = 0.602, respectively). As shown in the Kaplan–Meier analysis, no significant differences were noted in overall survival (p = 0.857) and disease‐free survival (p = 0.600) between the two groups. A subgroup analysis demonstrated that intraoperative instillation was not associated with a statistically better overall survival and disease‐free survival in the nonmuscle invasive (p = 0.852 and 0.836) and muscle‐invasive (p = 0.929 and 0.805) patients. Conclusion A single intraoperative instillation of chemotherapy during radical cystectomy was not related to better disease‐free survival or overall survival. It is unnecessary to consider single instillation of chemotherapy as a regular procedure during radical cystectomy.

Abstract Objective There is very limited of evidence linking fibrinogen and bone mineral density (BMD) in postmenopausal women. Therefore, this study intended to examine the relationship between fibrinogen and total BMD in postmenopausal women. Methods This cross-sectional analysis included 2043 postmenopausal women aged 50 years and older from the 1999 to 2002 National Health and Nutrition Examination Survey. The independent variable was fibrinogen and the outcome variable was total BMD. The association between fibrinogen and total BMD in postmenopausal women was examined using multivariate linear regression models, with subgroup analyses stratified by race. Smoothing curve fitting and generalized additive models further analyzed the sample data. Results In multiple regression models adjusted for potential confounders, fibrinogen was negatively associated with total BMD (model 1: − 0.0002 [− 0.0002, − 0.0001], model 2: − 0.0000 [− 0.0001, − 0.0000], model 3: − 0.0001 [− 0.0001, − 0.0001]). In subgroup analysis stratified by race, fibrinogen levels were negatively associated with total BMD in postmenopausal women, Non-Hispanic Whites, and Mexican Americans. However, in Non-Hispanic Blacks, the correlation between fibrinogen levels and total BMD was not significant. For individuals that identify as Other Races, fibrinogen levels were positively correlated with total BMD. Conclusion Our findings show a negative association between fibrinogen levels and total BMD in most postmenopausal women aged 50 years and older, however, is variable by race. In postmenopausal women, Non-Hispanic Whites and Mexican Americans, relatively high fibrinogen levels may be adverse to bone health.

Abstract Background The pathogenesis of interstitial cystitis/bladder pain syndrome (IC/BPS) has not been elucidated, but urinary microorganisms and metabolites have been shown to be closely associated with the inflammatory response of IC/BPS. Nevertheless, the exact mechanisms related to this response have not been clarified. Methods 16S rRNA sequencing and untargeted metabolomics techniques were used to analyse the urinary microbial and metabolite profiles of 30 IC/BPS patients and 30 healthy controls, and correlation analyses were performed to explore the mechanisms by which they might be involved in the inflammatory response of IC/BPS. Results Twenty-eight differential genera, such as Lactobacillus and Sphingomonas, were identified. A total of 44 differential metabolites such as 1,3,7-trimethyluric acid and theophylline were screened. The abundance of Lactobacillus and Escherichia-Shigella was significantly higher in the urine of female IC/BPS patients and healthy controls compared to males, while Bacteroides and Acinetobacter were lower than in males. The results of the Pearson correlation analysis suggested that differential microorganisms may influence the composition of metabolites. The Lactobacillus genus may be a protective bacterium against IC/BPS, whereas Sphingomonas may be a pathogenic factor. The differential metabolite theophylline, as an anti-inflammatory substance, may downregulate the inflammatory response of IC/BPS. Conclusions This study revealed microbial and metabolite profiles in the urine of IC/BPS patients versus healthy controls in both males and females. We also found some microorganisms and metabolites closely related to the inflammatory response of IC/BPS, which provided directions for future aetiological and therapeutic research.

Objective To investigate the association between creatinine to cystatin C ratio (CCR) and bone mineral density (BMD) in middle-aged and older adults. Methods This cross-sectional study investigated participants aged 50–85, using National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2002. The correlation between CCR and total BMD was assessed by multivariate linear regression models, using stratified analysis by age, sex and race (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other race) to distinguish various special populations. Results Among 2992 patients, multiple regression models revealed a significant positive correlation between CCR and total BMD: model 1, 0.030 (95% confidence interval [CI] 0.029, 0.031); model 2, 0.009 (95% CI 0.008, 0.010); model 3, 0.010 (95% CI 0.009, 0.013). After controlling for all covariates, a positive correlation was observed between CCR and total BMD in both men and women, and was further strengthened in older age groups. When stratifying by race, the positive correlation was most significant among ‘other Hispanic’ participants; there was no significant correlation among those of ‘other race’. Conclusions A positive correlation was demonstrated between CCR and total BMD in middle-aged and older adults aged 50–85 years, with the most significant positive correlation in the older ‘other Hispanic’ population. No significant correlation was observed among participants of ‘other race’.

Abstract Objective The prognostic factors for patients with epithelial sarcoma remain unclear. The study aims to develop a practical clinical nomogram that predicts prognosis in patients with ES using the Surveillance, Epidemiology, and End Results (SEER) database. Methods We extracted clinical data from 2004 to 2015 from the SEER database about patients with ES. All patients were randomly divided into training cohort and validation cohort. Kaplan–Meier analyses were used to compare outcomes between different subgroups. In order to estimate the chance of survival for patients with ES, we developed a nomogram. Nomogram performance was evaluated by discrimination and calibration. Additionally, an analysis of decision curves was conducted to evaluate the clinical usefulness of this newly developed model. Results In the primary cohort,320 met the inclusion criteria to be entered into this study. The median OS was 66.000 months (range 34.704 to 94.296 months), and the 1‐, 3‐, and 5‐year OS rates were 70.7%, 56.1%, and 50.4%, respectively. For the validation cohort, we studied 136 consecutive patients. Age, primary site, grade, AJCC (American Joint Committee on Cancer) T, AJCC M, and surgery were included in the nomogram. The C‐index values for the training set and validation set were 0.817 and 0.832, respectively. The calibration plots showed good agreement between the prediction and the observation. Based on the clinical decision curve, the model has a good clinical net benefit for ES patients. Conclusions It is the first study that developed an effective survival prediction model for patients with ES. Using this nomogram can assist in clinical decision‐making as it has satisfactory accuracy. Even so, additional external validation is needed.

(1) Purpose: The purpose of this study was to evaluate the prognostic capacity of the pathological N status (pN), lymph node ratio (LNR), and the log odds of positive lymph nodes (LODDS), and to build a prognostic nomogram to predict overall survival (OS) for bladder cancer patients treated by radical cystectomy. (2) Methods: The clinical and pathological characteristics of 10,938 patients with bladder cancer were identified from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017. The predictive capacity was assessed by univariate and multivariate Cox regression analyses, the area under the receiver operating characteristic curve (AUC), and C-index. Calibration curves, decision curve analysis (DCA), and risk-grouping were utilized to evaluate the predictive accuracy and discriminative ability of the nomogram. (3) Results: LODDS was an independent risk factor for bladder cancer (all p < 0.001) and demonstrated the highest values of C-index and AUC. The values of AUCs in the training cohort were 0.747, 0.743, and 0.735 for predicting 1-, 3-, and 5-year OS, respectively. Calibration curves and DCA curves suggested the excellent clinical application value of our nomogram. (4) Conclusions: LODDS is a better predictive indicator for bladder cancer patients compared to pN and LNR. The LODDS-incorporated nomogram has excellent accuracy and promising clinical application value for non-metastatic bladder cancer after radical cystectomy.

Abstract Background With the development of digital pathology and the renewal of deep learning algorithm, artificial intelligence (AI) is widely applied in tumor pathology. Previous researches have demonstrated that AI-based tumor pathology may help to solve the challenges faced by traditional pathology. This technology has attracted the attention of scholars in many fields and a large amount of articles have been published. This study mainly summarizes the knowledge structure of AI-based tumor pathology through bibliometric analysis, and discusses the potential research trends and foci. Methods Publications related to AI-based tumor pathology from 1999 to 2021 were selected from Web of Science Core Collection. VOSviewer and Citespace were mainly used to perform and visualize co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references and keywords in this field. Results A total of 2753 papers were included. The papers on AI-based tumor pathology research had been continuously increased since 1999. The United States made the largest contribution in this field, in terms of publications (1138, 41.34%), H-index (85) and total citations (35,539 times). We identified the most productive institution and author were Harvard Medical School and Madabhushi Anant, while Jemal Ahmedin was the most co-cited author. Scientific Reports was the most prominent journal and after analysis, Lecture Notes in Computer Science was the journal with highest total link strength. According to the result of references and keywords analysis, “breast cancer histopathology” “convolutional neural network” and “histopathological image” were identified as the major future research foci. Conclusions AI-based tumor pathology is in the stage of vigorous development and has a bright prospect. International transboundary cooperation among countries and institutions should be strengthened in the future. It is foreseeable that more research foci will be lied in the interpretability of deep learning-based model and the development of multi-modal fusion model.

Abstract Objective Conventional survival analysis plays a limited role in patients who have survived a period after initial treatment. The present study analyzed how conditional survival (CS) predicted survival rate over time for nonmetastatic muscle‐invasive bladder cancer (MIBC) patients after trimodal treatment. Method This retrospective study from the SEER database included consecutive patients with nonmetastatic MIBC who received trimodal therapy (TMT) between January 2010 and December 2017. Kaplan‐Meier analysis was used to estimate overall survival (OS) and cancer‐specific survival (CSS). CS was defined as the rate of surviving y years after already surviving for x years. Multivariate Cox regression analysis was used to identify prognostic factors. Result A total of 1110 nonmetastatic MIBC patients treated with TMT were included. Given a 1‐, 2‐, 3‐, and 4‐year after TMT, the rate of surviving to 5‐year, respectively, improved by +5.0 (20.0%), +17.0 (32.0%), +30.0 (45.0%), and +52.8 (67.8%) from those calculated at baseline (15.0%). The 2‐year CS rate of patients who had survived 1‐, 2‐, or 3‐year after TMT improved, respectively, compared to 3‐, 4‐, or 5‐year actual survival. Multivariate Cox regression analysis demonstrated that adverse variables (T stage, age) of OS and CSS lost their prognostic significance over time. Discussion and Conclusion Conditional survival rate of surviving to 5‐year after TMT kept a relatively stable level over time. In addition, those adverse variables were not always the prognostic factors over time. Only age was always the significant prognostic factor for conditional OS from baseline to 5‐year survival. Our results provided real‐time survival information and prognosis estimates to adjust follow‐up plans for nonmetastatic MIBC patients after TMT.

BackgroundHuman papillomavirus (HPV) infection is the leading cause of cervical cancer. More and more studies discovered that cervical microbiota (CM) composition correlated with HPV infection and the development of cervical cancer. However, more studies need to be implemented to clarify the complex interaction between microbiota and the mechanism of disease development, especially in a specific area of China.Materials and methodsIn this study, 16S rDNA sequencing was applied on 276 Thin-prep Cytologic Test (TCT) samples of patients from the Sanmenxia area. Systematical analysis of the microbiota structure, diversity, group, and functional differences between different HPV infection groups and age groups, and co-occurrence relationships of the microbiota was carried out.ResultsThe major microbiota compositions of all patients include Lactobacillus iners, Escherichia coli, Enterococcus faecalis, and Atopobium vaginae at species level, and Staphylococcus, Lactobacillus, Gardnerella, Bosea, Streptococcus, and Sneathia in genus level. Microbiota diversity was found significantly different between HPV-positive (Chao1 index: 98.8869, p < 0.01), unique-268 infected (infections with one of the HPV genotype 52, 56, or 58, 107.3885, p < 0.01), multi-268 infected (infections with two or more of HPV genotype 52, 56, and 58, 97.5337, p = 0.1012), other1 (94.9619, p < 0.05) groups and HPV-negative group (83.5299). Women older than 60 years old have higher microbiota diversity (108.8851, p < 0.01, n = 255) than younger women (87.0171, n = 21). The abundance of Gardnerella and Atopobium vaginae was significantly higher in the HPV-positive group than in the HPV-negative group, while Burkholderiaceae and Mycoplasma were more abundant in the unique-268 group compared to the negative group. Gamma-proteobacteria and Pseudomonas were found more abundant in older than 60 patients than younger groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Clusters of Orthologous Groups (COG) analysis revealed the effects on metabolism by microbiota that the metabolism of cells, proteins, and genetic information-related pathways significantly differed between HPV-negative and positive groups. In contrast, lipid metabolism, signal transduction, and cell cycle metabolism pathway significantly differed between multi-268 and negative groups.ConclusionThe HPV infection status and age of women were related to CM’s diversity and function pathways. The complex CM co-occurrent relationships and their mechanism in disease development need to be further investigated.

ObjectiveGeneral hospitals admit lower gestational age neonates than maternal and child health care centers, therefore associated with a higher morbidity and mortality. This study aimed to assess the etiology and clinical characteristics of neonatal sepsis in different medical setting models.MethodsNeonates admitted to 5 tertiary medical centers, including one national general hospital, two maternal and child health care hospitals and two regional general hospitals, in central-south China with culture-proven sepsis between January 2010 and December 2019 were included in the study. We compared maternal and neonatal characteristics, pathogen distribution, treatment and neonatal outcomes among 3 different medical setting models in this retrospective cohort.ResultsWe identified 757 episodes of culture-proven sepsis in 757 neonates. The predominant pathogens were coagulase-negative staphylococci, Klebsiella pneumoniae, Escherichia coli and Group B streptococci. A total of 683 neonates with detailed information were involved in further comparison; 54.6% were from the national general hospital, 35.9% were from the maternal and child health care hospital, and 9.5% were from the regional general hospital. Neonates in national and regional general hospitals had significantly lower gestational age and birthweight (P

Abstract Background Balloon dilation is a commonly used minimally invasive endourological treatment of ureteral stricture, but the postoperative recurrence rate is relatively high. And factors contributing to recurrence after treatment are poorly understood. Herein, we sought to develop a novel clinical nomogram to predict ureteral stricture-free survival in patients suffering from ureter stricture and performed balloon dilation. Methods The nomogram was established based on a retrospective analysis of 321 patients who received endoscopic balloon dilation alone for ureter strictures from January 2016 to January 2020 in Sun Yat-sen Memorial Hospital using the Cox regression model. Perioperative clinical data and disease outcomes were analyzed. The primary endpoint was the onset of ureteral re-stricture after ureter balloon dilation. Discrimination of the nomogram was assessed by the concordance index (C-index) and the calibration curve. The results were internally validated using bootstrap resampling. Results Overall, 321 patients with a median follow-up of 590 days were enrolled in the study, among which 97 patients (30.2%) developed recurrence of ureteral stricture during follow-up. Five variables remained significant predictors of ureteral re-stricture after multivariable analyses: stricture nature (P

The pandemic of coronavirus disease 2019 (COVID-19) has already evoked massive influence. The global pandemic has been ravaging the whole world for a year, with the number of confirmed human infection cases over 150 million and a death toll exceeding 3 million. Although the genomic sequence of the cognate pathogen SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has been quickly determined, there are still many unknown aspects, including the virus origin and evolution trend, and the effectiveness of current vaccines and drugs against the mutating virus. This review summarizes current knowledge and advances about COVID-19, including virus origin, transmission and infection, with the aim to improve the understanding of COVID-19 and provide a new perspective for future studies.

Objective: Many cancer cells cannot survive without exogenous glutamine (Gln); however, cancer cells expressing glutamine synthetase (GS) do not have this restriction. Previous metabolomics studies have indicated that glutamine metabolism is altered during pituitary tumorigenesis. However, the main role of Gln in pituitary adenoma (PA) pathophysiology remains unknown. The aim of this study was to evaluate the expression of GS and the main role of Gln in human PAs. Methods: We used cell proliferation assay and flow cytometry to assess t he effect of Gln depletion on three different pituitary cell lines and human prim ary PA cells. We then investigated the expression level of Gln synthetase (GS) in 24 human PA samples. At last, we used LC-MS/MS to identify the differences in metabolite s of PA cells after the blockage of both endogenous and exogenous Gln. Results: PA cell lines showed different sensitivities to Gln starvation, and the sensitivity is correlated with GS expression level. GS expressed in 21 out of the 24 human PA samples. Furthermore, a positive p53 and ki-67 index was correlated with a higher GS expression level (P < 0.05). Removal of both endogenous and exogenous Gln from GS- expressing PA cells resulted in blockage of nucleotide metabolism and cell cycle arrest. Conclusions: Our data indicate that GS is needed for PA cells to undergo proliferation during Gln deprivation, and most human PA cells express GS and might have a negative response to exogenous Gln depletion. Moreover, Gln is mainly responsible for nucleotide metabolism in the proliferation of GS-expressing pituitary tumor cells.

BackgroundWith the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate cancer.ObjectiveThis study mainly summarizes the research on the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores possible future research hotspots.MethodsThe articles and reviews regarding application of AI in prostate cancer between 1999 and 2020 were selected from Web of Science Core Collection on August 23, 2021. Microsoft Excel 2019 and GraphPad Prism 8 were applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 5.8.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field.ResultsA total of 2,749 articles were selected in this study. AI-related research on prostate cancer increased exponentially in recent years, of which the USA was the most productive country with 1,342 publications, and had close cooperation with many countries. The most productive institution and researcher were the Henry Ford Health System and Tewari. However, the cooperation among most institutions or researchers was not close even if the high research outputs. The result of keyword analysis could divide all studies into three clusters: “Diagnosis and Prediction AI-related study”, “Non-surgery AI-related study”, and “Surgery AI-related study”. Meanwhile, the current research hotspots were “deep learning” and “multiparametric MRI”.ConclusionsArtificial intelligence has broad application prospects in prostate cancer, and a growing number of scholars are devoted to AI-related research on prostate cancer. Meanwhile, the cooperation among various countries and institutions needs to be strengthened in the future. It can be projected that noninvasive diagnosis and accurate minimally invasive treatment through deep learning technology will still be the research focus in the next few years.

BackgroundSome studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer.MethodsGene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer.ResultsBy analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links.ConclusionsA predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.

The crustal structure in Myanmar can provide valuable information for the eastern margin of the ongoing Indo-Eurasian collision system. We successively performed H–k stacking of the receiver function and joint inversion of the receiver function and surface wave dispersion to invert the crustal thickness (H), shear wave velocity (VS), and the VP/VS ratio (k) beneath nine permanent seismic stations in Myanmar. H was found to increase from 26 ​km in the south and east of the study area to 51 ​km in the north and west, and the VP/VS ratio was complex and high. Striking differences in the crust were observed for different tectonic areas. In the Indo-Burma Range, the thick crust (H ​∼ ​51 ​km) and lower velocities may be related to the accretionary wedge from the Indian Plate. In the Central Myanmar Basin, the thin crust (H ​= ​26.9–35.5 ​km) and complex VP/VS ratio and VS suggest extensional tectonics. In the Eastern Shan Plateau, the relatively thick crust and normal VP/VS ratio are consistent with its location along the western edge of the rigid Sunda Block.

BackgroundA survival benefit was observed in metastatic bladder cancer patients who underwent primary tumor resection, but it was still confusing which patients are suitable for the surgery. For this purpose, we developed a model to screen stage M1 patients who would benefit from primary tumor resection.MethodsPatients with metastatic bladder cancer were screened from the Surveillance, Epidemiology, and End Results database (2004–2016) and then were divided into surgery (partial or complete cystectomy) group and non-surgery group. To balance the characteristics between them, a 1:1 propensity score matching analysis was applied. A hypothesis was proposed that the received primary tumor resection group has a more optimistic prognosis than the other group. The multivariable Cox model was used to explore the independent factors of survival time in two groups (beneficial and non-beneficial groups). Logistic regression was used to build a nomogram based on the significant predictive factors. Finally, a variety of methods are used to evaluate our model.ResultsA total of 7,965 patients with metastatic bladder cancer were included. And 3,314 patients met filtering standards, of which 545 (16.4%) received partial or complete cystectomy. Plots of the Kaplan–Meier and subgroup analyses confirmed our hypothesis. After propensity score matching analysis, a survival benefit was still observed that the surgery group has a longer median overall survival time (11.0 vs. 6.0 months, p < 0.001). Among the surgery cohort, 303 (65.8%) patients lived longer than 6 months (beneficial group). Differentiated characteristics included age, gender, TNM stage, histologic type, differentiation grade, and therapy, which were integrated as predictors to build a nomogram. The nomogram showed good discrimination in both training and validation cohorts (area under the receiver operating characteristic curve (AUC): 0.806 and 0.742, respectively), and the calibration curves demonstrated good consistency. Decision curve analysis showed that the nomogram was clinically useful. Compared with TNM staging, our model shows a better predictive value in identifying optimal patients for primary tumor resection.ConclusionsA practical predictive model was created and verified, which might be used to identify the optimal candidates for the partial or complete cystectomy group of the primary tumor among metastatic bladder cancer.

BackgroundCurrently, the progress of targeted drugs in the treatment of metastatic clear cell renal cell carcinoma (mccRCC) is limited. Cytoreductive nephrectomy (CN), as an alternative treatment, can improve the prognosis of patients with metastatic renal cell carcinoma to some extent. However, it is unclear which patients would benefit from this tumor reduction operation. As a consequence, we developed a predictive model to identify patients who may well benefit from CN in terms of survival.MethodsWe identified patients with metastatic clear cell renal cell carcinoma retrospectively from the Surveillance, Epidemiology, and End Results (SEER) database (2010–2015) and classified them into surgery and non-surgery groups. Propensity score matching (PSM) was performed to balance the baseline characteristics. Patients who survived longer than the median overall survival (OS) of no-surgery group were defined as surgical-benefit patients. Then, we developed a predictive model based on preoperative characteristics using multivariable Logistic regression. Calibration curves and the area under the receiver operating characteristic (AUC) were used to evaluate the efficiency of the predictive model. The clinical value of the nomogram was assessed utilizing decision curve analysis (DCA).ResultsOur study collected 5544 patients from the SEER database, with 2352(42.4%) receiving cytoreductive surgery. Overall survival (OS) was longer in the CN group than in the non-surgery group after 1:1 propensity scoring matching (median OS: 19 months vs 7 months; hazard ratio (HR) =0.4106, P< 0.001). In the matched surgery group, 65.7% (367) patients survived more than 7 months after the operation and they were considered to benefit from CN. The predictive model performed well on both the training group (AUC=73.4%) and the validation group (AUC=71.9%) and the calibration curves indicated a high degree of consistency. The decision curve analysis curve demonstrated the clinical utility. We classified surgical patients into the beneficial group and non-beneficial group by using the predictive model, then discovered a substantial difference in OS between the two groups.ConclusionsWe developed a nomogram to select ideal mccRCC patients who might benefit from cytoreductive nephrectomy. Clinicians could make a more precise treatment strategy for mccRCC patients.

Abstract Background Metabolic reprogramming is an important characteristic of tumors. In the progression of pituitary adenomas (PA), abnormal glucose metabolism has been confirmed by us before. However, whether cholesterol metabolism is involved in the process of PA remains unclear. This study aimed to investigate whether abnormal cholesterol metabolism could affect the progression of PA. Methods We analyzed the expression of sterol carrier protein 2 (SCP2) in 40 surgical PA samples. In vitro experiments and xenograft models were used to assess the effects of SCP2 and cholesterol on proliferation of PA. The incidence of hypercholesterolemia between 140 PA patients and 100 heathy controls were compared. Results We found an upregulation of SCP2 in PA samples, especially in tumors with high proliferation index. Forced expression of SCP2 promoted PA cell lines proliferation in vitro. Furthermore, SCP2 regulated cholesterol trafficking from cytoplasm to membrane in GH3 cells, and extracellularly treating GH3 cells and primary PA cells with methyl-β-cyclodextrin/cholesterol complex to mimic membrane cholesterol concentration enhanced cell proliferation, which suggested a proliferative effect of cholesterol. Mechanistically, cholesterol induced activation of PKA/SUFU/GLI1 signaling via smoothened receptor, which was well-known as Hedgehog signaling, resulting in inhibiting apoptosis and promoting cell cycle. Accordingly, activation of Hedgehog signaling was also confirmed in primary PA cells and surgical PA samples. In vivo, SCP2 overexpression and high cholesterol diet could promote tumor growth. Intriguingly, the incidence of hypercholesterolemia was significantly higher in PA patients than healthy controls. Conclusions Our data indicated that dysregulated cholesterol metabolism could promote PA growth by activating Hedgehog signaling, supporting a potential tumorigenic role of cholesterol metabolism in PA progression.

Abstract Background Induced pluripotent stem cells (iPSCs) can generate epithelial stem cells (EpSCs) as seed cells for skin substitutes to repair skin defects. Here, we investigated the effects of a human acellular amniotic membrane (hAAM) combined with iPSC-derived CD200+/ITGA6+ EpSCs as a skin substitute on repairing skin defects in nude mice. Methods Human urinary cells isolated from a healthy donor were reprogrammed into iPSCs and then induced into CD200+/ITGA6+ epithelial stem cells. Immunocytochemistry and RT-PCR were used to examine the characteristics of the induced epithelial stem cells. iPSC-derived EpSCs were cultured on a hAAM, and cytocompatibility of the composite was analyzed by CCK8 assays and scanning electron microscopy. Then, hAAMs combined with iPSC-derived EpSCs were transplanted onto skin defects of mice. The effects of this composite on skin repair were evaluated by immunohistochemistry. Results The results showed that CD200+/ITGA6+ epithelial stem cells induced from iPSCs displayed the phenotypes of hair follicle stem cells. After seeding on the hAAM, iPSC-derived epithelial stem cells had the ability to proliferate. After transplantation, CD200+/ITGA6+ epithelial stem cells on the hAAM promoted the construction of hair follicles and interfollicular epidermis. Conclusions These results indicated that transplantation of a hAAM combined with iPS-derived EpSCs is feasible to reconstruct skin and skin appendages, and may be a substantial reference for iPSC-based therapy for skin defects.

Aramid fiber-reinforced plastic (AFRP) composites are widely used in aerospace, rail transit, marine and military industries, due to their high specific strength, high impact resistance, fatigue resistance and excellent designable properties. In order to meet different application requirements, cutting processes need to be carried out, such as window opening, edge cutting and slit cutting. However, the characteristics of high tensile strength and toughness, low interlaminar strength, non-uniformity and anisotropy make AFRP composites a difficult-to-machine material. They are prone to produce rough cutting surfaces and cutting damages including burr, wire drawing, delamination, resin burn, material flanging, etc. To solve this problem, the ultra-thin diamond dicing blade was used for high-speed cutting of AFRP composites in sub-fiber scale in this research. The influence of process parameters on cutting force, cutting temperature, maximum spindle current, tool wear and cutting surface quality were investigated by establishing the cutting force model, L16(45) orthogonal experiment, single factor experiment, range analysis and variance analysis. The theoretical and experimental results show that cutting AFRP composites with ultra-thin diamond dicing blade can obtain smooth surfaces without common cutting damages. When the cutting speed is 91.11 m/s (spindle speed n = 30,000 r/min), the cutting depth is 0.2 mm and the feed speed is 5 mm/s, the surface roughness Ra can be as low as 32 nm, which realize the precision cutting of AFRP composites.

Ankylosing spondylitis (AS) is a highly heritable, inflammatory rheumatic disease, characterized by inflammation of the spine and the sacroiliac joints. Although some genes are reportedly associated with this disease, the pathogenesis of AS remains largely unknown. In this study, the peripheral blood mononuclear cells of a patient with AS were reprogrammed to induced pluripotent stem cells (iPSCs) using transgene-free, episomal plasmid vectors. The established iPSC line was validated by multiple methods and demonstrated typical characteristics of embryonic stem cells. This cell line (SHFDi001-A) may be beneficial in disease modeling and related research.

ABSTRACT: Heredity is the major factor contributing to the susceptibility to ankylosing spondylitis(AS). Janus kinase 2 (JAK2) has been associated with AS. Urine-derived cells from an AS patient with JAK2 mutation were used to generate induced pluripotent stem cells (iPSCs) with five episomal iPSC reprogramming vectors (pCXLE-hOCT3/4-shp53-F, pCXLE-hSK, pCXLE-hUL, pCXLE-EGFP and pCXWB-EBNA1). The iPSCs were pluripotent and will be valuable for research on the role and mechanism of JAK2 in the pathogenesis of AS.

CHARGE syndrome is a rare disease caused by a genetic disorder. The clinical features of this syndrome include coloboma of the eye, heart anomaly, choanal atresia, retardation of mental and somatic development, microphallus, ear abnormalities and/or deafness. CHD7 is the main causative gene for CHARGE syndrome. In this study, we generated an induced pluripotent stem cell (iPSC) line from the dermal fibroblasts of a 1.5-year-old girl, carrying a de novo mutation (CHD7;NM_017780;c.3449_3450delTC;p.L1151Gfs*17). This iPSC line will be a useful tool for investigating the pathogenesis and for developing treatment for this complicated syndrome.

Objective: The surgical technique, safety, efficacy, and clinical application value of the intra-neuroendoscopic technique (INET) for the treatment of subacute-chronic and chronic septal subdural hematoma was investigated based on the structure and pathological features of the hematoma wall, and the critical factors of hematoma growth and recurrence were determined, in order to provide reference for clinical drug treatment.Methods: This was non-randomized concurrent control study. A total of 94 patients who met the inclusion criteria were recruited between May 2015 and February 2019 and were divided into the INET treatment group (INET group, 45 cases) and the burr hole drainage (BHD) treatment group (control group, 49 cases). The hematoma fluid components and the morphological structure and pathological characteristics of the hematoma wall were analyzed, and the surgical duration, subdural drainage tube (SDT) placement duration, intracranial infection rate, Bender grade at the 1 month post-operative follow-up and hematoma recurrence rate within the 6 months of post-operative follow-up were compared between the two groups. A multiple logistic regression model was established to analyze the risk factors associated with recurrence within 6 months.Results: Intraoperative endoscopy showed that the adhesion bands that formed early in the hematoma cavity were strip-like and that those that formed late were lock-column-like. The hematoma cavity was divided into different-sized chambers with by these strips/columns. Pathological sections of cyst wall reveled angiogenesis inside the cyst and mucus-like changes, rupture and hemorrhage in the vascular wall. Obvious inflammatory cell infiltration and fibrous connective tissue hyperplasia were observed in the cyst wall. The osmotic pressure of the hematoma fluid was not significantly different from that of the peripheral venous blood [(296.7 ± 10.3) mOsm/kg vs. (291.5 ± 12.4) mOsm/kg, p = 0.68]. However, the D-dimer contents which reflect the severity of fibrinolysis in the hematoma and the proinflammatory cytokine interleukin 6 (IL-6) were significantly higher in the hematoma fluid than in the peripheral venous blood. The surgery duration for the INET group was significantly longer than that for the control group [(60.4 ± 10.6) min vs. (44.1 ± 9.8) min, p = 0.00], but both the hematoma recurrence rate within 6 months of post-operative follow-up (4.4 vs. 24.5%, p = 0.00) and the SDT placement duration [(2.1 ± 0.6) d vs. (3.9 ± 0.7) d, p = 0.00] for the INET group were both lower than those for the control group. The intracranial infection rate did not differ significantly between the two groups (4.4 vs. 10.2%, p = 0.50). The overall effective rate of the Bender grade at 1 month of follow-up did not differ significantly between the two groups (95.6 vs. 87.8%, p = 0.32), but the proportion of patients who recovered to Bender grade 0 with no symptoms was significantly higher in the INET group than in the control group (86.7 vs. 67.3%, p = 0.03). Multiple logistic regression analysis showed that INET surgery [odds ratio (OR) 3.71, 95% confidence interval (CI) 1.31–9.62, p = 0.02], age of 65 years or younger (OR 1.51, 95% CI 1.05–2.87, p = 0.03) and unilateral subdural hematoma (OR 1.76, 95% CI 1.05–3.41, p = 0.02) were independent factors that reduced the post-operative recurrence rate.Conclusion: The INET surgical plan based on the structure and pathological features of the subacute-chronic and chronic subdural hematoma wall can reduce the recurrence rate and improve the clinical prognosis.Trial registration:ClinicalTrials.gov, NCT02515903. Registered 5 August, 2015.

BACKGROUND: Cartilage degradation is a typical characteristic of arthritis. This study examined whether there was a subset of phagocytic chondrocytes that expressed the specific macrophage marker, CD163, and investigated their role in cartilage degradation. METHODS: Cartilage from the knee and temporomandibular joints of Sprague-Dawley rats was harvested. Cartilage degradation was experimentally-induced in rat temporomandibular joints, using published biomechanical dental methods. The expression levels of CD163 and inflammatory factors within cartilage, and the ability of CD163(+) chondrocytes to conduct phagocytosis were investigated. Cartilage from the knees of patients with osteoarthritis and normal cartilage from knee amputations was also investigated. RESULTS: In the experimentally-induced degrading cartilage from temporomandibular joints, phagocytes were capable of engulfing neighboring apoptotic and necrotic cells, and the levels of CD163, TNF-α and MMPs were all increased (P0.05). CD163(+) chondrocytes were found in the cartilage mid-zone of temporomandibular joints and knee from healthy, three-week old rats. Furthermore, an increased number of CD163(+) chondrocytes with enhanced phagocytic activity were present in Col-II(+) chondrocytes isolated from the degraded cartilage of temporomandibular joints in the eight-week experimental group compared with their age-matched controls. Increased number with enhanced phagocytic activity of CD163(+) chondrocytes were also found in isolated Col-II(+) chondrocytes stimulated with TNF-α (P