Background Sarcomas is a group of heterogeneous malignant tumors originated from mesenchymal tissue and different types of sarcomas have disparate outcomes. The present study aims to identify the prognostic value of immune-related genes (IRGs) in sarcoma and establish a prognostic signature based on IRGs. Methods We collected the expression profile and clinical information of 255 soft tissue sarcoma samples from The Cancer Genome Atlas (TCGA) database and 2498 IRGs from the ImmPort database. The LASSO algorithm and Cox regression analysis were used to identify the best candidate genes and construct a signature. The prognostic ability of the signature was evaluated by ROC curves and Kaplan-Meier survival curves and validated in an independent cohort. Besides, a nomogram based on the IRGs and independent prognostic clinical variables was developed. Results A total of 19 IRGs were incorporated into the signature. In the training cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.938, 0.937 and 0.935, respectively. The Kaplan-Meier survival curve indicated that high-risk patients were significantly worse prognosis (P < 0.001). In the validation cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.730, 0.717 and 0.647, respectively. The Kaplan-Meier survival curve also showed significant distinct survival outcome between two risk groups. Furthermore, a nomogram based on the signature and four prognostic variables showed great accuracy in whole sarcoma patients and subgroup analyses. More importantly, the results of the TF regulatory network and immune infiltration analysis revealed the potential molecular mechanism of IRGs. Conclusions In general, we identified and validated an IRG-based signature, which can be used as an independent prognostic signature in evaluating the prognosis of sarcoma patients and provide potential novel immunotherapy targets.

ObjectiveTo establish and validate an intact rotator cuff rat model for exploring the pathophysiological effects of type 2 diabetes on the rotator cuff tendon in vivo.MethodsA total of 45 adult male rats were randomly divided into a control group (n = 9) and type 2 diabetes group (n=36). The rats were sacrificed at 2 weeks (T2DM-2w group, n=9), 4 weeks (T2DM-4w group, n=9), 8 weeks (T2DM-8w group, n=9), and 12 weeks (T2DM-12w group, n=9) after successful modeling of type 2 diabetes. Bilateral shoulder samples were collected for gross observation and measurement, protein expression(enzyme-linked immunosorbent assay,ELISA), histological evaluation, biomechanical testing, and gene expression (real-time quantitative polymerase chain reaction, qRT-PCR).ResultsProtein expression showed that the expression of IL-6 and Advanced glycation end products (AGEs)in serum increased in type 2 diabetic group compared with the non-diabetic group. Histologically, collagen fibers in rotator cuff tendons of type 2 diabetic rats were disorganized, ruptured, and with scar hyperplasia, neovascularization, and extracellular matrix disturbances, while Bonar score showed significant and continuously aggravated tendinopathy over 12 weeks. The biomechanical evaluation showed that the ultimate load of rotator cuff tendons in type 2 diabetic rats gradually decreased, and the ultimate load was negatively correlated with AGEs content. Gene expression analysis showed increased expression of genes associated with matrix remodeling (COL-1A1), tendon development (TNC), and fatty infiltration (FABP4) in tendon specimens from the type 2 diabetic group.ConclusionPersistent type 2 diabetes is associated with the rupture of collagen fiber structure, disturbance in the extracellular matrix, and biomechanical decline of the rotator cuff tendon. The establishment of this new rat model of rotator cuff tendinopathy provides a valuable research basis for studying the cellular and molecular mechanisms of diabetes-induced rotator cuff tendinopathy.

The formation and accumulation of advanced glycation end products (AGEs) have been associated with aging and the development, or worsening, of many degenerative diseases, such as atherosclerosis, chronic kidney disease, and diabetes. AGEs can accumulate in a variety of cells and tissues, and organs in the body, which in turn induces oxidative stress and inflammatory responses and adversely affects human health. In addition, under abnormal pathological conditions, AGEs create conditions that are not conducive to stem cell differentiation. Moreover, an accumulation of AGEs can affect the differentiation of stem cells. This, in turn, leads to impaired tissue repair and further aggravation of diabetic complications. Therefore, this systematic review clearly outlines the effects of AGEs on cell differentiation of various types of primary isolated stem cells and summarizes the possible regulatory mechanisms and interventions. Our study is expected to reveal the mechanism of tissue damage caused by the diabetic microenvironment from a cellular and molecular point of view and provide new ideas for treating complications caused by diabetes.

PurposeComplications were significantly increased 30 days after Simultaneous bilateral total knee arthroplasty (SBTKA). In this study, an individualized nomogram was established and validated to predict the complications within 30 days after SBTKA.MethodsThe general data of 861 patients (training set) who received SBTKA in The Affiliated Hospital of Qingdao University between January 1, 2012 and March 31, 2017 were retrospectively analyzed. All patients were divided into complication group (n = 96) and non-complication group (n = 765) according to the incidence of complications within 30 years after SBTKA. Independent risk factors for postoperative SBTKA complications were identified and screened by binary logistic regression analyses, and then a nomogram prediction model was constructed using R software. The area under curve (AUC), calibration curve, and decision curve analysis (DCA) were selected to evaluate the line-chart. Meanwhile, 396 patients receiving SBTKA in the Third Hospital of Hebei Medical University who met the inclusion and exclusion criteria (test set) were selected to verify the nomogram.ResultsFive independent predictors were identified by binary logistic regression analyses and a nomogram was established. The AUC of this nomogram curve is 0.851 (95% CI: 0.819–0.883) and 0.818 (95% CI: 0.735–0.900) in the training and testing sets, respectively. In the training set and test set, calibration curves show that nomogram prediction results are in good agreement with actual observation results, and DCA shows that nomogram prediction results have good clinical application value.ConclusionOlder age, lower preoperative hemoglobin level, higher preoperative blood urea nitrogen (BUN) level, longer operation time, ASA grade ≥ III are independent predictors of SBTKA complications within 30 days after surgery. A nomogram containing these five predictors can accurately predict the risk of complications within 30 days after SBTKA.

Background Sarcomas is a group of heterogeneous malignant tumors originated from mesenchymal tissue and different types of sarcomas have disparate outcomes. The present study aims to identify the prognostic value of immune-related genes (IRGs) in sarcoma and establish a prognostic signature based on IRGs. Methods We collected the expression profile and clinical information of 255 soft tissue sarcoma samples from The Cancer Genome Atlas (TCGA) database and 2498 IRGs from the ImmPort database. The LASSO algorithm and Cox regression analysis were used to identify the best candidate genes and construct a signature. The prognostic ability of the signature was evaluated by ROC curves and Kaplan-Meier survival curves and validated in an independent cohort. Besides, a nomogram based on the IRGs and independent prognostic clinical variables was developed. Results A total of 19 IRGs were incorporated into the signature. In the training cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.938, 0.937 and 0.935, respectively. The Kaplan-Meier survival curve indicated that high-risk patients were significantly worse prognosis(P < 0.001). In the validation cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.730, 0.717 and 0.647, respectively. The Kaplan-Meier survival curve also showed significant distinct survival outcome between two risk groups. Furthermore, a nomogram based on the signature and four prognostic variables showed great accuracy in whole sarcoma patients and subgroup analyses. More importantly, the results of the TF regulatory network and immune infiltration analysis revealed the potential molecular mechanism of IRGs. Conclusions In general, we identified and validated an IRG-based signature, which can be used as an independent prognostic signature in evaluating the prognosis of sarcoma patients and provide potential novel immunotherapy targets.

Purpose: The risk factors of chronic kidney disease were analyzed by using the region of interest quantitative technology of color doppler combined with QLab software, and a Nomogram was established to conduct an individualized assessment of patients with chronic kidney disease.Methods: A total of 500 patients with chronic kidney disease diagnosed in our hospital from June 2019 to March 2021 were selected as the chronic kidney disease group, and 300 healthy patients during the same period were selected as the control group. Univariate analysis was performed on the test indexes(Fasting blood glucose, total cholesterol, triglyceride, urea nitrogen , creatinine, uric acid, albumin, red blood cell count, glomerular ltration rate, urinary protein) and the vascularity index, ow index, and vascularization ow index measured by the color doppler region of interest quantitative technique. The above meaningful indicators were included in the Logistics regression analysis to obtain the independent risk factors of early chronic kidney disease. The independent risk factors were imported into R software to draw a nomogram model for predicting early chronic kidney disease and evaluate the model.Results: Single factor analysis results suggest age, hypertension, diabetes, hyperlipidemia, disease of heart head blood-vessel, body mass index, vascularity index, ow index, and vascularization ow index, fasting blood sugar, triglyceride, total cholesterol, urea nitrogen, creatinine, uric acid, glomerular ltration rate differences statistically signi cant (P < 0.05), while gender, renal length to diameter, the thickness of the cortex, Resistance index and peak systolic velocity and albumin difference has no statistical signi cance (P > 0.05). Logistics regression analysis showed that hypertension, diabetes, ow index, and vascularization ow index, urea nitrogen and albumin were independent risk factors for the early occurrence of chronic kidney disease. The C index of this nomogram using independent risk factors is 0.896 (95%CI: 0.862-0.930), which indicates that the nomogram has good discriminant power. The receiver operating curve of the histograph was AUC(area under the curve) 0.884 (95%CI: 0.860-0.908), with the optimal threshold of 0.663, speci city of 88.7%, sensitivity of 78.0%, accuracy of 82.0%, and positive predictive value of 91.9%. The ROC(receiver operator characteristic curve) of urea nitrogen, albumin , ow index, and vascularization ow index were evaluated. The results indicated that the best cutoff value of urea nitrogen was 5.9mmol/L, ow index was 14.67, vascularization ow index was 4.6, and albumin was 40.26g/L. Conclusion: In the prediction of chronic kidney disease I-II stage, the quantitative technique of color Doppler region of interest has certain diagnostic value. The model established in this study has good discriminative power and can be applied to clinical practice, giving certain indicative signi cance.

ObjectiveThe number of primary hip arthroplasty (PHA) has increased sharply in recent years. Whether the epidemiological characteristics and trends of PHA have changed are unknown. This study aims to analyze the epidemiological characteristics and trends of those patients are urgent for public health institutions.MethodsThe data of patients who underwent PHA in five tertiary hospitals from January 2011 to December 2020 were retrospectively reviewed. A total of 21,898 patients were included, most of whom were aged 60–69 years (25.1% males and 31.5% females). According to the hospitalization date, the patients were divided into two groups (Group A and Group B). The patients admitted between January 2011 and December 2015 were designated as Group A (7862), and those admitted between January 2016 and December 2020 were designated as Group B (14036). The patient data of the two groups, including sex, age, disease causes, body mass index (BMI), comorbidities, surgical procedures, hospital stay duration, and hospitalization costs, were analyzed by Pearson chi‐Square test, Student t test or Mann–Whitney U test.ResultsMore women were included in Group B than in Group A (58.5% vs 52.5%, P < 0.001). The mean age of Group B was less than that of Group A (62.27 ± 14.77 vs 60.69 ± 14.44 years, P < 0.001). Femoral head necrosis was the primary pathogenic factor in both groups, with a higher proportion in Group B than in Group A (55.5% vs 45.5%, P < 0.001). Significant differences were found between the two groups in BMI, comorbidities, surgical procedures, hospital stay duration, and hospitalization costs. Total hip arthroplasty (THA) was the most common surgical procedure in both groups, with a higher proportion in Group B than in Group A (89.8% vs 79.3%, P < 0.001). The proportion of patients with one or more comorbidities was significantly higher in Group B than in Group A (69.2% vs 59.9%, P < 0.001). In addition, Group B had a shorter hospital stay duration and higher hospitalization costs than Group A.ConclusionFemoral head necrosis was the primary etiology for PHA in this study, followed by femoral neck fracture and hip osteoarthritis. Patients who underwent PHA exhibited a higher percentage of femoral head necrosis; underwent THA more often; and had larger BMIs, more comorbidities, higher medical costs, and younger age in the past decade.

Purpose By comparing the occurrence of complications at 30 days after Simultaneous bilateral total knee arthroplasty (SBTKA) for each age group, the optimal age range of patients receiving SBTKA was determined.An individualized histogram model was established to predict complications within 30 days after SBTKA. Methods The general data of 861 patients who received SBTKA in our hospital on January 1, 2012 and March 31, 2017 were retrospectively analyzed. According to the age of the patients, they were divided into four ages: less than 60 years old, 60 to 64 years old, 65 to 69 years old and over 70 years old. The incidence of complications in different ages was studied.According to the occurrence of complications, 96 cases were included in the complication group and 765 cases in the non-complication group. Univariate and multivariate Logistic regression analysis was conducted to determine and screen out the independent risk factors for complications after SBTKA, and then R software was used to construct the prediction model of the nomogram.The area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were selected to evaluate the nomogram. Results Patients aged 60 to 64 years had the lowest overall postoperative complication rate (7.17%).Five independent predictors were identified by multivariate analysis and were used to establish the nomogram.The AUC of the nomogram was 0.851(95%CI:0.819–0.883).The calibration curve showed that the prediction of nomogram was highly consistent with the actual observation, and DCA showed that nomogram had good clinical usefulness. Conclusion The optimal age group for SBTKA is between 60 and 64 years of age, where the incidence of complications is lowest.Older age, lower preoperative hemoglobin levels, higher preoperative blood urea nitrogen(BUN) levels, longer operation time, and ASA grade ≥ III were identified as independent predictors of complications within 30 days after SBTKA.A nomogram containing the above five predictors could accurately predict the risk of complications within 30 days after SBTKA.