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Abstract Background Excessive intraoperative bleeding remains a challenge in limb surgeries. The exsanguination tourniquet ring has emerged as a potential solution for effective exsanguination and hemostasis. This study aims to evaluate its efficacy and safety compared to the conventional exsanguination and hemostasis approach (pneumatic tourniquet combined with Esmarch bandage). Methods This randomized controlled trial evaluates the exsanguination tourniquet ring’s effectiveness and safety versus the conventional approach in 220 participants undergoing various limb surgeries. Allocation included experimental and control groups, assesses through efficacy (including intraoperative and total blood loss, hemoglobin levels, and exsanguination and hemostasis effectiveness) and safety (adverse event occurrence) indicators. Results The experimental group (n = 110) utilizes the exsanguination tourniquet ring, while the control group (n = 110) employs the conventional approach. As for intraoperative blood loss, the experimental group is non-inferior to the control group (p-value

Abstract Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.

Introduction Osteoarthritis of the hip or knee has been reported to be linked to an increased risk of frailty. However, a definitive conclusion about whether hip or knee osteoarthritis increases susceptibility to frailty remains elusive. Material and methods The instrumental variables (IVs) used in this analysis were sourced from publicly available genome-wide association study (GWAS) datasets. We used a two-sample Mendelian randomization analysis to evaluate the plausible causal nexus between hip or knee osteoarthritis and frailty. Results We included a total of 25 single-nucleotide polymorphisms (SNPs) as instrumental variables through rigorous and comprehensive screening. The results of this analysis suggested that hip or knee osteoarthritis is associated with an elevated risk of frailty. These results remained robust and consistent across multiple calculation methods, including inverse variance weighted (OR = 1.082, 95% CI: 1.0532–1.1125, p = 1.36 × 10–8), MR‒Egger regression (OR = 1.175, 95% CI: 1.0162–1.3604, p = 0.040), weighted median estimation (OR = 1.078, 95% CI: 1.0365–1.1219, p = 1.831 × 10–4), weighted mode analysis (OR = 1.089, 95% CI: 1.0078–1.1771, p = 0.041) and simple mode analysis (OR = 1.093, 95% CI: 1.0112–1.1830, p = 0.034). Cochran’s Q test showed no evidence of heterogeneity among the IV estimates derived from individual variants, and the MR‒Egger regression analysis indicated that the presence of horizontal pleiotropy was unlikely to introduce bias into the results (intercept: –0.0044, p = 0.549). Conclusions Two-sample Mendelian randomization analysis effectively identified hip or knee osteoarthritis as a contributing risk factor for frailty.

Abstract. Fibrosis, which is a manifestation of the physiological response to injury characterized by excessive accumulation of extracellular matrix components, is a ubiquitous outcome of the repair process. However, in cases of repetitive or severe injury, fibrosis may become dysregulated, leading to a pathological state and organ failure. In recent years, a novel form of regulated cell death, referred to as ferroptosis, has been identified as a possible contributor to fibrosis; it is characterized by iron-mediated lipid peroxidation. It has garnered attention due to the growing body of evidence linking ferroptosis and fibrogenesis, which is believed to be driven by underlying inflammation and immune responses. Despite the increasing interest in the relationship between ferroptosis and fibrosis, a comprehensive understanding of the precise role that ferroptosis plays in the formation of fibrotic tissue remains limited. This review seeks to synthesize previous research related to the topic. We categorized the different direct and indirect mechanisms by which ferroptosis may contribute to fibrosis into three categories: (1) iron overload toxicity; (2) ferroptosis-evoked necroinflammation, with a focus on ferroptosis and macrophage interplay; and (3) ferroptosis-associated pro-fibrotic factors and pathways. Furthermore, the review considers the potential implications of these findings and highlights the utilization of ferroptosis-targeted therapies as a promising strategy for mitigating the progression of fibrosis. In conclusion, novel anti-fibrotic treatments targeting ferroptosis could be an effective treatment for fibrosis.

Osteosarcoma, as the most prevalent primary malignant bone tumor, has consistently shown suboptimal clinical treatment outcomes. In this manuscript, we proposed an efficacious and novel phototherapy strategy for osteosarcoma based on a photoresponsive near-infrared (NIR) material, CaCO3-ICG-DDP-PEG-PT (CIDP-PT), which contained calcium carbonate (CaCO3) and Cisplatin (DDP) via the gas dispersion method, and indocyanine green (ICG) was encapsulated through a nanoprecipitation reaction by employing DSPE-PEG2000-COOH to enhance the stability and hydrophilicity. The targeting oligopeptide (PT) for osteosarcoma cells was inserted into the outer membrane of nanoparticles, thereby further enhancing the tumor-targeting capability through receptor-mediated binding. The prepared CIDP-PT nanoparticles exhibited high targeting efficiency and multifunctionality. In vitro and in vivo experiments demonstrated that CIDP-PT significantly enhanced the therapeutic efficacy for osteosarcoma via the NIR-II photoresponsive and tumor-targeting approach. It achieves efficient tumor cell eradication through multiple modalities while maintaining an exceptional level of biocompatibility. Hence, the CIDP-PT nanocarriers possess considerable practical value for future clinical applications in adjunct osteosarcoma phototherapy.

Abstract This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making assistance. We retrospectively analyzed the breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver operating characteristic (ROC) curve (AUC), learning curve, precision curve, calibration plot, and decision curve analysis to evaluate performance of the machine learning models. Univariable and multivariable logistic regression analyses showed that bone metastases were significantly associated with age, race, sex, grade, T stage, N stage, surgery, radiotherapy, chemotherapy, tumor size, brain metastasis, liver metastasis, lung metastasis, breast subtype, and PR. Univariate and multivariate Cox regression analyses revealed that age, race, marital status, grade, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, lung metastasis, breast subtype, ER, and PR were closely associated with the prognosis of BCBM. Among the six machine learning models, the XGBoost algorithm predicted the most accurate results (Diagnostic model AUC = 0.98; Prognostic model AUC = 0.88). According to the Shapley additive explanations (SHAP), the most critical feature of the diagnostic model was surgery, followed by N stage. Interestingly, surgery was also the most critical feature of prognostic model, followed by liver metastasis. Based on the XGBoost algorithm, we could effectively predict the diagnosis and survival of bone metastasis in breast cancer and provide targeted references for the treatment of BCBM patients.

Abstract Little is currently known about the effect of smoking on osteoarthritis (OA). This study aimed to investigate the relationship between smoking and OA in the United States (US) general population. Cross-sectional study. Level of evidence, 3. 40,201 eligible participants from the National Health and Nutrition Examination Survey 1999–2018 were included and divided into OA and non-arthritis groups. Participants demographics and characteristics were compared between the two groups. Then the participants were divided into non-smokers, former smokers, and current smokers based on their smoking status, also demographics and characteristics among the three groups were compared. Multivariable logistic regression was used to determine the relationship between smoking and OA. The current and former smoking rate in the OA group (53.0%) was significantly higher than that in the non-arthritis group (42.5%; p

Cancer cells frequently change their metabolism from aerobic glycolysis to lipid metabolism and amino acid metabolism to adapt to the malignant biological behaviours of infinite proliferation and distant metastasis. The significance of metabolic substances and patterns in tumour cell metastasis is becoming increasingly prominent. Tumour metastasis involves a series of significant steps such as the shedding of cancer cells from a primary tumour, resistance to apoptosis, and colonisation of metastatic sites. However, the role of glutamine in these processes remains unclear. This review summarises the key enzymes and transporters involved in glutamine metabolism that are related to the pathogenesis of malignant tumour metastasis. We also list the roles of glutamine in resisting oxidative stress and promoting immune escape. Finally, the significance of targeting glutamine metabolism in inhibiting tumour metastasis was proposed, research in this field improving our understanding of amino acid metabolism rewiring and simultaneously bringing about new and exciting therapeutic prospects.

Abstract Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary system characterized by poor prognosis and difficult treatment. It has been reported that iron metabolism dysregulation is a common phenomenon in ccRCC and is closely related to the process of ccRCC. But still now, the exact function and underlying mechanisms of iron metabolism dysregulation in ccRCC have not been fully elucidated. In this study, we comprehensively investigated the prognostic value and potential role of STEAP3 (an iron metabolism-related gene) in ccRCC. STEAP3 is significantly up-regulated in ccRCC. High STEAP3 expression is associated with gender, hemoglobin level, pathological grade, tumor stage and significantly predicts an unfavorable prognosis of ccRCC patients. Functional enrichment analysis and evaluation of the tumor microenvironment indicated that STEAP3 was involved in the remodeling of tumor extracellular matrix and the shaping of an immune-suppressive tumor microenvironment to promote tumor metastasis and evade immune killing. Besides, the expression of STEAP3 is also associated with the expression of various immune checkpoint molecules and the IC50 of targeted drugs. Finally, we verified STEAP3 by RT-qPCR and IHC staining. In conclusion, we found that STEAP3 can serve as a candidate prognostic biomarker for ccRCC, and targeting STEAP3 and its biological processes may provide new references for the individualized treatment of ccRCC.

Abstract Background Human urine-derived stem cells (USCs)-derived exosomes (USC-Exo) could improve kidney ischemia/reperfusion injury (IRI), while the underlying mechanisms of this protective effect remain unclear. Methods Human USCs and USC-Exo were isolated and verified by morphology and specific biomarkers. The effects of USC-Exo on ferroptosis and kidney injury were detected in the IRI-induced acute kidney injury (AKI) model in C57BL/6 mice. The effects of USC-Exo on ferroptosis and lncRNA taurine-upregulated gene 1 (TUG1) were detected in hypoxia/reoxygenation (H/R)-treated human proximal tubular epithelial cells (HK-2). The interaction of SRSF1 and TUG1, ACSL4 was checked via RNA pull-down/RIP and RNA stability assays. The effects of LncRNA TUG1 on SRSF1/ACSL4-mediated ferroptosis were verified in H/R-treated HK-2 cells and the IRI-induced AKI mouse models. Results USC-Exo treatment improved kidney injury and ameliorated ferroptosis in IRI-induced AKI mouse models. USC-Exo were rich in lncRNA TUG1, which suppressed ferroptosis in HK-2 cells exposed to H/R. Mechanistically, lncRNA TUG1 regulates the stability of ACSL4 mRNA by interacting with RNA-binding protein SRSF1. In addition, SRSF1 upregulation or ACSL4 downregulation partially reversed the protective effect of lncRNA TUG1 on ferroptosis in H/R-treated HK-2 cells. Further, ACSL4 upregulation partially reversed TUG1’s repression on kidney injury and ferroptosis in IRI-induced AKI mice. Conclusion Collectively, lncRNA TUG1 carried by USC-Exo regulated ASCL4-mediated ferroptosis by interacting with SRSF1 and then protected IRI-induced AKI. Potentially, USC-Exo rich in lncRNA TUG1 can serve as a promising therapeutic method for IRI-AKI.

Background To assess the safety and efficacy of preoperative simulation and three-dimensional (3D) models in the treatment of ulnoradial diaphyses fracture. It was hypothesized that preoperative simulation and 3D printing might significantly shorten the mean operative time, intraoperative bleeding, and intraoperative fluoroscopy. Material and Methods Forty patients with forearm double fracture were divided into 3D printing group and conventional surgery group. Preoperative simulation and 3D printing were performed on patients in the 3D printing group to examine implant reduction and placement as well as preoperative plate/screw size. The operation time, intraoperative bleeding, and frequency of fluoroscopies were recorded. Results In the conventional surgery group, the operative time, intraoperative bleeding, and the frequency of fluoroscopy were 106.2 ± 15.92 min, 61.45 ± 11.33 ml and 5.65 ± 1.23 times, whereas in the 3D printing group, values of all the three parameters were better than those of the conventional surgery group (91.3 ± 14.85 min, 48.6 ± 10.39 ml and 3.85 ± 1.04 times, respectively). The forearm pronation and supination of the 3D printing group improved to 79.55 ± 5.12° and 76.80 ± 3.96°, respectively. In the conventional surgery group, patients also had significant improvement in these indicators, which improved to 78.60 ± 5.18° and 75.4 ± 5.30°. Conclusions The results showed that preoperative simulation and 3D printing can enhance the safety as well as personalization of the surgical process during the treatment of forearm double fracture and therefore holds potential for future application in clinical practice. Trial registry Name of the registry: This study was registered in the Chinese Clinical Trial Registry; Trial registration number: ChiCTR2100045790.

IntroductionLateral epicondylitis is a significant clinical problem in orthopaedics. There have been numerous articles written about this. Bibliometric analysis is critical for determining a field's most influential study. We attempt to identify and analyze the top 100 citations in lateral epicondylitis research.Materials and methodsOn December 31, 2021, an electronic search was conducted in the Web of Science Core Collection and the Scopus search engine with no restrictions on publication years, language, or study design. We reviewed each article's title and abstract until the top 100 were documented and evaluated in various ways.ResultsBetween 1979 and 2015, the 100 most cited articles were published in 49 journals. The total number of citations ranged from 75 to 508 (mean ± SD, 145.5 ± 90.9), with citation densities ranging from 2.2 to 37.6 citations per year (mean ± SD, 8.7 ± 6.5). The United States is the most productive country, and the 2000s witnessed a surge in lateral epicondylitis research. The year of publication had a moderately positive correlation with citation density.ConclusionOur findings offer readers a fresh perspective on historical development hotspot areas of lateral epicondylitis research. Disease progression, diagnosis, and management have always been topics of discussion in articles. PRP-based biological therapy has emerged as a promising area for future research.

BackgroundBone metastasis is a common adverse event in kidney cancer, often resulting in poor survival. However, tools for predicting KCBM and assessing survival after KCBM have not performed well.MethodsThe study uses machine learning to build models for assessing kidney cancer bone metastasis risk, prognosis, and performance evaluation. We selected 71,414 kidney cancer patients from SEER database between 2010 and 2016. Additionally, 963 patients with kidney cancer from an independent medical center were chosen to validate the performance. In the next step, eight different machine learning methods were applied to develop KCBM diagnosis and prognosis models while the risk factors were identified from univariate and multivariate logistic regression and the prognosis factors were analyzed through Kaplan-Meier survival curve and Cox proportional hazards regression. The performance of the models was compared with current models, including the logistic regression model and the AJCC TNM staging model, applying receiver operating characteristics, decision curve analysis, and the calculation of accuracy and sensitivity in both internal and independent external cohorts.ResultsOur prognosis model achieved an AUC of 0.8269 (95%CI: 0.8083–0.8425) in the internal validation cohort and 0.9123 (95%CI: 0.8979–0.9261) in the external validation cohort. In addition, we tested the performance of the extreme gradient boosting model through decision curve analysis curve, Precision-Recall curve, and Brier score and two models exhibited excellent performance.ConclusionOur developed models can accurately predict the risk and prognosis of KCBM and contribute to helping improve decision-making.

The rapid development of tissue engineering makes it an effective strategy for repairing cartilage defects. The significant advantages of injectable hydrogels for cartilage injury include the properties of natural extracellular matrix (ECM), good biocompatibility, and strong plasticity to adapt to irregular cartilage defect surfaces. These inherent properties make injectable hydrogels a promising tool for cartilage tissue engineering. This paper reviews the research progress on advanced injectable hydrogels. The cross-linking method and structure of injectable hydrogels are thoroughly discussed. Furthermore, polymers, cells, and stimulators commonly used in the preparation of injectable hydrogels are thoroughly reviewed. Finally, we summarize the research progress of the latest advanced hydrogels for cartilage repair and the future challenges for injectable hydrogels.

The risk of osteoporosis in breast cancer patients is higher than that in healthy populations. The fracture and death rates increase after patients are diagnosed with osteoporosis. We aimed to develop machine learning-based models to predict the risk of osteoporosis as well as the relative fracture occurrence and prognosis. We selected 749 breast cancer patients from two independent Chinese centers and applied six different methods of machine learning to develop osteoporosis, fracture and survival risk assessment models. The performance of the models was compared with that of current models, such as FRAX, OSTA and TNM, by applying ROC, DCA curve analysis, and the calculation of accuracy and sensitivity in both internal and independent external cohorts. Three models were developed. The XGB model demonstrated the best discriminatory performance among the models. Internal and external validation revealed that the AUCs of the osteoporosis model were 0.86 and 0.87, compared with the FRAX model (0.84 and 0.72)/OSTA model (0.77 and 0.66), respectively. The fracture model had high AUCs in the internal and external cohorts of 0.93 and 0.92, which were higher than those of the FRAX model (0.89 and 0.86). The survival model was also assessed and showed high reliability via internal and external validation (AUC of 0.96 and 0.95), which was better than that of the TNM model (AUCs of 0.87 and 0.87). Our models offer a solid approach to help improve decision making.

The Achilles tendon (AT) is responsible for running, jumping, and standing. The AT injuries are very common in the population. In the adult population (21–60 years), the incidence of AT injuries is approximately 2.35 per 1,000 people. It negatively impacts people’s quality of life and increases the medical burden. Due to its low cellularity and vascular deficiency, AT has a poor healing ability. Therefore, AT injury healing has attracted a lot of attention from researchers. Current AT injury treatment options cannot effectively restore the mechanical structure and function of AT, which promotes the development of AT regenerative tissue engineering. Various nanofiber-based scaffolds are currently being explored due to their structural similarity to natural tendon and their ability to promote tissue regeneration. This review discusses current methods of AT regeneration, recent advances in the fabrication and enhancement of nanofiber-based scaffolds, and the development and use of multiscale nanofiber-based scaffolds for AT regeneration.

Abstract Background Osteosarcoma is an aggressive malignant tumor which has attracted worldwide attention. MEX3A may be associated with tumors while has not yet seen its coverage on osteosarcoma. Herein, this study was to investigate the correlation between MEX3A and the progression of osteosarcoma. Methods Firstly, we determined that expression of MEX3A was significantly higher in osteosarcoma tissues than that in marginal bone by immunohistochemical staining. Additionally, MEX3A expression was downregulated by the RNAi‐mediated knockdown. The functions of MEX3A knockdown on proliferation, apoptosis, cell cycle, migration was assessed by MTT assay, flow cytometry, wound-healing assay and Transwell assay, respectively. Knockdown of MEX3A resulted in suppressing cell proliferation, increasing cell apoptosis, inducing the G2 phase cell cycle arrest, and attenuating cellular migration. Furthermore, mouse xenograft model confirmed inhibitory effects of MEX3A knockdown on osteosarcoma formation. Results The preliminary exploration on the molecular mechanism of MEX3A in osteosarcoma cells showed that the induction of apoptosis needs the participation of a series of apoptosis- associated factors, such as upregulation of Caspase 3, Caspase 8 and HSP60, downregulation of HSP27 and XIAP. Conclusions In summary, these findings predicated that therapy directed at decreasing MEX3A expression is a potential osteosarcoma treatment.

BackgroundPancreatic cancer (PC) is one of the most common malignant types of cancer, with the lung being the frequent distant metastatic site. Currently, no population-based studies have been done on the risk and prognosis of pancreatic cancer with lung metastases (PCLM). As a result, we intend to create two novel nomograms to predict the risk and prognosis of PCLM.MethodsPC patients were selected from the Surveillance, Epidemiology, and End Results Program (SEER) database from 2010 to 2016. A multivariable logistic regression analysis was used to identify risk factors for PCLM at the time of diagnosis. The multivariate Cox regression analysis was carried out to assess PCLM patient's prognostic factors for overall survival (OS). Following that, we used area under curve (AUC), time-dependent receiver operating characteristics (ROC) curves, calibration plots, consistency index (C-index), time-dependent C-index, and decision curve analysis (DCA) to evaluate the effectiveness and accuracy of the two nomograms. Finally, we compared differences in survival outcomes using Kaplan-Meier curves.ResultsA total of 803 (4.22%) out of 19,067 pathologically diagnosed PC patients with complete baseline information screened from SEER database had pulmonary metastasis at diagnosis. A multivariable logistic regression analysis revealed that age, histological subtype, primary site, N staging, surgery, radiotherapy, tumor size, bone metastasis, brain metastasis, and liver metastasis were risk factors for the occurrence of PCLM. According to multivariate Cox regression analysis, age, grade, tumor size, histological subtype, surgery, chemotherapy, liver metastasis, and bone metastasis were independent prognostic factors for PCLM patients' OS. Nomograms were constructed based on these factors to predict 6-, 12-, and 18-months OS of patients with PCLM. AUC, C-index, calibration curves, and DCA revealed that the two novel nomograms had good predictive power.ConclusionWe developed two reliable predictive models for clinical practice to assist clinicians in developing individualized treatment plans for patients.

BackgroundThe overall survival (OS) of pancreatic cancer (PC) patients with bone metastasis (BM) is extremely low, and it is pretty hard to treat bone metastasis. However, there are currently no effective nomograms to predict the diagnosis and prognosis of pancreatic cancer with bone metastasis (PCBM). Therefore, it is of great significance to establish effective predictive models to guide clinical practice.MethodsWe screened patients from Surveillance Epidemiology and End Results (SEER) database between 2010 and 2016. The independent risk factors of PCBM were identified from univariable and multivariable logistic regression analyses, and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors affecting the prognosis of PCBM. In addition, two nomograms were constructed to predict the risk and prognosis of PCBM. We used the area under the curve (AUC), C-index and calibration curve to determine the predictive accuracy and discriminability of nomograms. The decision curve analysis (DCA) and Kaplan-Meier(K-M) survival curves were employed to further confirm the clinical effectiveness of the nomogram.ResultsMultivariable logistic regression analyses revealed that risk factors of PCBM included age, primary site, histological subtype, N stage, radiotherapy, surgery, brain metastasis, lung metastasis, and liver metastasis. Using Cox regression analyses, we found that independent prognostic factors of PCBM were age, race, grade, histological subtype, surgery, chemotherapy, and lung metastasis. We utilized nomograms to visually express data analysis results. The C-index of training cohort was 0.795 (95%CI: 0.758-0.832), whereas that of internal validation cohort was 0.800 (95%CI: 0.739-0.862), and the external validation cohort was 0.787 (95%CI: 0.746-0.828). Based on AUC of receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA), we concluded that the risk and prognosis model of PCBM exhibits excellent performance.ConclusionNomogram is sufficiently accurate to predict the risk and prognostic factors of PCBM, allowing for individualized clinical decisions for future clinical work.

Ferroptosis is a newly proposed programmed cell death that has great potential in limiting tumor progression and malignancies that are resistant to conventional therapies. However, recent reports have shown that ferroptosis in the tumor microenvironment can provide a favorable environment to promote tumor survival and progression, which is induced by the infiltration and polarization of pro-tumor immune cells and the dysfunction of anti-tumor immunity. In this mini-review, we introduce the mechanisms of ferroptosis, describe the crosstalk between ferroptosis and cancer, demonstrate the potential ways in which ferroptosis shapes the pro-tumor immune microenvironment, and present our thoughts on ferroptosis-based cancer therapies.

Tumorigenesis is a multistage progressive oncogenic process caused by alterations in the structure and expression level of multiple genes. Normal cells are continuously endowed with new capabilities in this evolution, leading to subsequent tumor formation. Immune cells are the most important components of inflammation, which is closely associated with tumorigenesis. There is a broad consensus in cancer research that inflammation and immune response facilitate tumor progression, infiltration, and metastasis via different mechanisms; however, their protumor effects are equally important in tumorigenesis at earlier stages. Previous studies have demonstrated that during the early stages of tumorigenesis, certain immune cells can promote the formation and proliferation of premalignant cells by inducing DNA damage and repair inhibition, releasing trophic/supporting signals, promoting immune escape, and activating inflammasomes, as well as enhance the characteristics of cancer stem cells. In this review, we focus on the potential mechanisms by which immune cells can promote tumor initiation and promotion in the early stages of tumorigenesis; furthermore, we discuss the interaction of the inflammatory environment and protumor immune cells with premalignant cells and cancer stem cells, as well as the possibility of early intervention in tumor formation by targeting these cellular mechanisms.

IntroductionClear cell renal cell carcinoma (ccRCC) is a malignant tumor characterized by poor prognosis and difficult treatment. Ferroptosis is a relatively new form of programmed cell death that involved in cancer development and therapy resistance. Studies have shown that targeted ferroptosis may be a novel option for the treatment of ccRCC, but key genes and their roles between ferroptosis and ccRCC are limited so far. This study aims to develop a ccRCC stratified model based on ferroptosis-related genes to provide a reference for the prognosis prediction and the individualized treatment of ccRCC.Materials and MethodsThe mRNAs expression data of ccRCC and FRGs were obtained from TCGA and FerrDb database, respectively. Through multiple analysis, a 4-FRG based prognostic stratified model was constructed and its predictive performance was validated through various methods. Then, a nomogram based on the model was constructed and ccRCC patients stratified by the model were analyzed for tumor microenvironment, immune infiltration, sensitivity for immune checkpoint inhibitors (ICIs)/traditional anti-tumor therapy and tumor mutation burden (TMB). Functional enrichment analysis was performed to explore potential biological pathways. Finally, we verified our model by RT-qPCR, siRNA transfection, scratch assay and CCK-8 assay.ResultsIn this study, the stratified model and a model-based nomogram can accurately predict the prognosis of ccRCC patients in TCGA database. The patients stratified by the model showed different tumor microenvironments, immune infiltration, TMB, resistance to traditional and ICIs therapy, and sensitivity to ferroptosis. Functional enrichment analysis suggested several biological pathways related to the process and prognosis of ccRCC. RT-qPCR confirmed the differential expression of ferroptosis-related genes. Scratch assay and CCK-8 assay indicated the promotion effects of CD44 on the proliferation and migration of ccRCC.ConclusionIn this study, we established a novel ccRCC stratified model based on FRGs, which can accurately predict the prognosis of ccRCC patients and provide a reference for clinical individualized treatment.

Abstract Purpose To compare the time return to work and long-term results of tendoscopic versus open technique for de Quervain’s disease. Methods From 2005 to 2013, either tendoscopic or open decompression was performed on 56 consecutive patients (56 wrists) with symptomatic de Quervain’s disease despite a minimum of 3 months non-operative treatment. Of the 50 patients who met the inclusion criteria, 41 patients were followed-up for a mean of 7.21 years postoperatively. Among these 41 wrists, 20 underwent tendoscopic release (group A), and 21 underwent open release (group B). The clinical evaluations were performed preoperatively, 1 month postoperatively and at last follow-up visit, using visual analog scale (VAS); the Disabilities of the Arm, Shoulder and Hand (DASH) Outcome score; and the Finkelstein’s test. The Patient and Observer Scar Assessment Scale (POSAS) was used as an esthetic evaluation tool of the scar at last follow-up. Results No significant baseline differences were found between two groups. The average time return to work in group A was less than in group B (P

Objective The role of tumor-infiltrating lymphocytes (TILs) has not yet been characterized in sarcomas. The aim of this bioinformatics study was to explore the effect of TILs on sarcoma survival and genome alterations. Methods Whole-exome sequencing, transcriptome sequencing, and survival data of sarcoma were obtained from The Cancer Genome Atlas. Immune infiltration scores were calculated using the Tumor Immune Estimation Resource. Potential associations between abundance of infiltrating TILs and survival or genome alterations were examined. Results Levels of CD4 + T cell infiltration were associated with overall survival of patients with pan-sarcomas, and higher CD4 + T cell infiltration levels were associated with better survival. Somatic copy number alterations, rather than mutations, were found to correlate with CD4 + T cell infiltration levels. Conclusions This data mining study indicated that CD4 + T cell infiltration levels predicted from RNA sequencing could predict sarcoma prognosis, and higher levels of CD4 + T cells infiltration indicated a better chance of survival.

The Sfp-type 4′-phosphopantetheinyl transferase Ppt1 is required for activation of nonribosomal peptide synthetases, including α-aminoadipate reductase (AAR) for lysine biosynthesis and polyketide synthases, enzymes that biosynthesize peptide and polyketide secondary metabolites, respectively. Deletion of the PPT1 gene, from the maize pathogen Cochliobolus heterostrophus and the rice pathogen Cochliobolus miyabeanus, yielded strains that were significantly reduced in virulence to their hosts. In addition, ppt1 mutants of C. heterostrophus race T and Cochliobolus victoriae were unable to biosynthesize the host-selective toxins (HST) T-toxin and victorin, respectively, as judged by bioassays. Interestingly, ppt1 mutants of C. miyabeanus were shown to produce tenfold higher levels of the sesterterpene-type non-HST ophiobolin A, as compared with the wild-type strain. The ppt1 strains of all species were also reduced in tolerance to oxidative stress and iron depletion; both phenotypes are associated with inability to produce extracellular siderophores biosynthesized by the nonribosomal peptide synthetase Nps6. Colony surfaces were hydrophilic, a trait previously associated with absence of C. heterostrophus Nps4. Mutants were decreased in asexual sporulation and C. heterostrophus strains were female-sterile in sexual crosses; the latter phenotype was observed previously with mutants lacking Nps2, which produces an intracellular siderophore. As expected, mutants were albino, since they cannot produce the polyketide melanin and were auxotrophic for lysine because they lack an AAR.

Purpose: To: 1) assess the correlation between CT vascularity and a candidate molecular marker of RCC metastasis (insulin-like mRNA binding protein-3 (IMP3)); and 2) demonstrate the differential expression of IMP3 in high vs. low vascular tumors. Experimental design: Retrospectively obtained contrast CT from 72 patients with primary RCC were used to establish threshold values for Low, Intermediate and High tumor vascularity. Paired histopathology specimens from 33 of these patients were used for immunohistochemistry (IHC) to correlate CT with IMP-3 expression. IMP-3 gene expression studies were performed on RCC and poorly vascular prostate cancer (PC) human bone metastases samples to confirm presence of IMP3 in metastatic samples from RCC. Gene expression studies were performed on RCC 786-O and PC3 cell lines to confirm the presence of high expression of IMP3 in the RCC cell line. Results: IMP-3 expression positively correlated with CT vascular enhancement (p

Neurofibromatosis type I is a common genetic disease that can lead to disfigurement, neurological and functional disorders. However, it is rare to meet the case which a huge mass is formed rapidly after neurofibroma ruptures. This case report describes a rare case of a 52-year-old female with a rapidly expanding mass on her back and mild anemia as the main symptoms. Physical examination showed a huge mass on the back and a surface ulceration with the diameter of 6 cm. Imaging examination revealed the abundant blood supply to the lesion. We performed preoperative arterial embolization, and surgical resection on the fifth day after embolization. After operation, proper blood transfusion and vacuum sealing drainage (VSD) were given. Through 9-months follow-up study, the incision of the patient recovered well and there was no sign of tumor recurrence. Therefore, this case report provides clinicians with valuable experience in the treatment for rapidly expanding neurofibroma. [ABSTRACT FROM AUTHOR]