Search

Abstract Exposure to adverse life events is linked to somatic disorders. The study aims to evaluate the association between adverse events at varying life stages and the risk of chronic kidney disease (CKD), a condition affecting about 10% population worldwide. This prospective cohort study included 140,997 participants from the UK Biobank. Using survey items related to childhood maltreatment, adulthood adversity and catastrophic trauma, we performed latent class analysis to summarize five distinct patterns of exposure to adverse life events, namely “low-level exposure”, “childhood exposure”, “adulthood exposure”, “sexual abuse” and “child-to-adulthood exposure”. We used Cox proportional hazard regression to evaluate the association of patterns of exposure to adverse life events with CKD, regression-based mediation analysis to decompose the total effect, and gene-environment-wide interaction study (GEWIS) to identify interactions between genetic loci and adverse life events. During a median follow-up of 5.98 years, 2734 cases of incident CKD were identified. Compared with the “low-level exposure” pattern, “child-to-adulthood exposure” was associated with increased risk of CKD (hazard ratio 1.37, 95% CI 1.14 to 1.65). BMI, smoking and hypertension mediated 11.45%, 9.79%, and 4.50% of this total effect, respectively. Other patterns did not show significant results. GEWIS and subsequent analyses indicated that the magnitude of the association between adverse life events and CKD differed according to genetic polymorphisms, and identified potential underlying pathways (e.g., interleukin 1 receptor activity). These findings underscore the importance of incorporating an individual’s psychological encounters and genetic profiles into the precision prevention of CKD.

Objective To examine cardiovascular and kidney benefits and harms of sodium-glucose co-transporter-2 (SGLT-2) inhibitors stratified by risk in adults with chronic kidney disease regardless of diabetes status.Design Systematic review and meta-analysis.Data sources Ovid Medline, Embase, and Cochrane Central from database inception to 15 June 2024.Eligibility criteria for selecting studies Randomised controlled trials that compared SGLT-2 inhibitors with placebo or standard care with no SGLT-2 inhibitors in adults with chronic kidney disease with a follow-up duration of ≥12 weeks were eligible. Secondary analyses based on subpopulations from randomised controlled trials and publications not in English language were excluded.Data synthesis Random effects meta-analyses were conducted, with effect estimates presented as risk ratios with 95% confidence intervals (CIs). Absolute treatment effects were estimated over a five year duration for individuals with varied risks of cardiovascular and kidney complications based on the Kidney Disease Improving Global Outcomes (KDIGO) risk stratification system. Certainty of evidence was assessed using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach.Results Evidence from 13 randomised controlled trials (29 614 patients) informed treatment effect estimates. In relative terms, SGLT-2 inhibitors reduced all cause death (risk ratio 0.85 (95% CI 0.74 to 0.98)), cardiovascular death (0.84 (0.74 to 0.96)), kidney failure (0.68 (0.60 to 0.77)), non-fatal stroke (0.73 (0.57 to 0.94)), non-fatal myocardial infarction (0.75 (0.60 to 0.93)), and admission to hospital for heart failure (0.68 (0.60 to 0.78)). No credible subgroup effects were found from diabetes status, heart failure status, estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, and follow-up duration. Absolute effect estimates across these outcomes over a five year period varied across risk groups based on baseline risks of cardiovascular and kidney events. Effects of SGLT-2 inhibitors in the group at low risk included seven fewer all- cause deaths, four fewer admissions to hospital for heart failure per 1000 individuals, and no effects on kidney failure. Effects in the higher risk group included 48 fewer all cause deaths, 58 fewer kidney failures, and 25 fewer admissions to hospital for heart failure per 1000 individuals. Although SGLT-2 inhibitor use was associated with a relative increase in the risk of harms, including genital infection (2.66 (95% CI 2.07 to 3.42)), ketoacidosis (2.27 (1.30 to 3.95)), and symptomatic hypovolaemia (1.29 (1.15 to 1.44)), absolute differences for all harm outcomes were small.Conclusions Among people who have chronic kidney disease either with type 2 diabetes or not, SGLT-2 inhibitors improved cardiovascular and kidney outcomes with varying degrees of absolute benefit depending on an individual's baseline risks of cardiovascular and kidney-related sequelae. Absolute benefits and harms stratified by risk and associated with SGLT-2 inhibitors should inform individual decision making at the patient level.Systematic review registration PROSPERO CRD42022325483.

In recent years, the incidence of cancer has been increasing year by year, and the burden of the disease and the economic burden caused by it has been worsening. Although chemotherapy, immunotherapy, targeted therapy and other therapeutic means continue to progress, they still inevitably have problems such as high toxicity and side effects, susceptibility to drug resistance, and high price. Photothermal therapy and photodynamic therapy have demonstrated considerable advantages in cancer imaging and treatment due to their minimally invasive and selective nature. However, their development has been constrained by challenges related to drug delivery. In recent times, drug delivery systems constructed based on supramolecular chemistry have been the subject of considerable interest, particularly in view of their compatibility with the high permeability and long retention effect of tumors. Furthermore, the advantage of dissociating the active ingredient under pH, light and other stimuli makes them unique in cancer therapy. This paper reviews the current status of supramolecular nanomedicines in cancer therapy, elucidating the challenges faced and providing a theoretical basis for the efficient and precise treatment of malignant tumors.

Abstract Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.

ObjectiveThis study aims to develop and validate machine learning models to predict proliferative lupus nephritis (PLN) occurrence, offering a reliable diagnostic alternative when renal biopsy is not feasible or safe.MethodsThis study retrospectively analyzed clinical and laboratory data from patients diagnosed with SLE and renal involvement who underwent renal biopsy at West China Hospital of Sichuan University between 2011 and 2021. We randomly assigned 70% of the patients to a training cohort and the remaining 30% to a test cohort. Various machine learning models were constructed on the training cohort, including generalized linear models (e.g., logistic regression, least absolute shrinkage and selection operator, ridge regression, and elastic net), support vector machines (linear and radial basis kernel functions), and decision tree models (e.g., classical decision tree, conditional inference tree, and random forest). Diagnostic performance was evaluated using ROC curves, calibration curves, and DCA for both cohorts. Furthermore, different machine learning models were compared to identify key and shared features, aiming to screen for potential PLN diagnostic markers.ResultsInvolving 1312 LN patients, with 780 PLN/NPLN cases analyzed. They were randomly divided into a training group (547 cases) and a testing group (233 cases). we developed nine machine learning models in the training group. Seven models demonstrated excellent discriminatory abilities in the testing cohort, random forest model showed the highest discriminatory ability (AUC: 0.880, 95% confidence interval(CI): 0.835–0.926). Logistic regression had the best calibration, while random forest exhibited the greatest clinical net benefit. By comparing features across various models, we confirmed the efficacy of traditional indicators like anti-dsDNA antibodies, complement levels, serum creatinine, and urinary red and white blood cells in predicting and distinguishing PLN. Additionally, we uncovered the potential value of previously controversial or underutilized indicators such as serum chloride, neutrophil percentage, serum cystatin C, hematocrit, urinary pH, blood routine red blood cells, and immunoglobulin M in predicting PLN.ConclusionThis study provides a comprehensive perspective on incorporating a broader range of biomarkers for diagnosing and predicting PLN. Additionally, it offers an ideal non-invasive diagnostic tool for SLE patients unable to undergo renal biopsy.

Background: In addition to damage to the lungs, coronavirus disease 2019 (COVID-19) can damage multiple organs, including the kidney. Our purpose was to analyze the research hotspots and trends in COVID-19 and kidney diseases using bibliometrics to help clarify the development direction of this field. Methods: We selected and extracted all relevant publications related to COVID-19 and the kidney from the Web of Science from December 1, 2019, to July 24, 2022. VOSviewer, RStudio, CiteSpace, and other software were used to visualize keywords, publishing trends, authors and their countries, and institutions in this field and perform the statistical analysis. Results: A total of 645 articles published in 220 journals were included in this study. The United States and China contributed the most publications and were most active in international cooperation. In addition to COVID-19 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), acute kidney injury (AKI), kidney transplant and mortality were the three keywords with the highest frequencies. In the initial stage of the COVID-19 outbreak, research focused on the clinical symptoms of COVID-19 and other macrocharacteristics, while in a later stage, the associations between SARS-CoV-2 infection and CKD and AKI, as well as the prognosis of patients with kidney disease or those who underwent kidney transplantation, gained more attention. The immune response and vaccines were also recent research hotspots. Conclusions: This bibliometric analysis provides a comprehensive overview of research on COVID-19 and kidney disease, which has received continuous, global attention. AKI, CKD, kidney transplantation, immune response and vaccines are among the hotspots in this field.

Abstract Uncontrollable massive bleeding caused by trauma will cause the patient to lose a large amount of blood and drop body temperature quickly, resulting in hemorrhagic shock. This study aims to develop a hemostatic product for hemorrhage management. In this study, waste pomelo peel as raw material is chosen. It underwent processes of carbonization, purification, and freeze‐drying. The obtained carbonized pomelo peel (CPP) is hydrophilic and exhibits a porous structure (nearly 80% porosity). The water/blood absorption ratio is significantly faster than the commercial Gelfoam and has a similar water/blood absorption capacity. In addition, the CPP showed a water‐triggered shape‐recoverable ability. Moreover, the CPP shows ideal cytocompatibility and blood compatibility in vitro and favorable tissue compatibility after long terms of subcutaneous implantation. Furthermore, CPP can absorb red blood cells and fibrin. It also can absorb platelets and activate platelets, and it is capable of achieving rapid hemostasis on the rat tail amputation and hepatectomized hemorrhage model. In addition, the CPP not only can quickly stop bleeding in the rat liver‐perforation and rabbit heart uncontrolled hemorrhage models, but also promotes rat liver and rabbit heart tissue regeneration in situ. These results suggest the CPP has shown great potential for managing uncontrolled hemorrhage.

Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a “short-term” causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.

Obesity and Type 2 Diabetes (T2D) are two highly prevalent diseases that exhibit a complex interplay between them. Obesity serves as a primary risk factor for the development of T2D, and conversely, individuals with T2D often exhibit comorbid obesity. Renal dysfunction emerges as a critical consequence of the convergence of obesity and Type 2 Diabetes, contributing significantly to the overall burden of complications associated with these conditions. Recognizing the profound implications of renal dysfunction in individuals contending with both obesity and Type 2 Diabetes, interventions targeting weight loss have gained prominence as potential therapeutic avenues. Weight loss not only addresses the primary risk factor of obesity but also holds the promise of mitigating the progression of Type 2 Diabetes and its associated renal complications. This comprehensive review aims to explore the impact of weight loss on renal function in individuals contending with the convergence of obesity and T2D.

ObjectiveTo evaluate the causal relationship between childhood body-mass index (BMI) at different ages and adult cardiometabolic traits.MethodsWe retrieved genetic instrument variables (IVs) for exposures (standardized BMI at newborn, infant, toddler and late childhood), cardiometabolic traits and potential confounders or mediators (adult BMI, SHBG, testosterone and age at menarche) from the corresponding genome-wide association analysis. We performed univariate and multivariable Mendelian randomization (MR) to dissect associations between age-specific childhood BMI and adult cardiometabolic outcomes. Odds ratio was used to present the direction of the causal association.ResultsIn univariate MR, higher newborn BMI was causally associated with reduced risk for type 2 diabetes in women. Late childhood BMI was associated with increased risk for female diabetes and coronary artery disease (CAD), myocardial infarction (MI), and chronic kidney disease (CKD) in general population. Among these associations, only association between late childhood BMI with MI remained significant after adjusting for adult male BMI and sex hormones, (OR = 1.120, 95% CI 1.023-1.226, p = 0.014). Besides, in multivariable MR, we found evidence for causal association between newborn BMI with reduced risk for CAD (OR = 0.862, 95% CI 0.751-0.989, p = 0.034) and MI (OR = 0.864, 95% CI 0.752-0.991, p = 0.037) in men. No obvious impact of infant or toddler BMI was identified on the above-mentioned diseases. For continuous cardiometabolic traits, in all age epochs except infant, higher BMI was associated with increased level of fasting glucose in women.ConclusionBMI at birth and late childhood exerts different impact on adult cardiometabolic diseases, while BMI at infant and toddler ages is not causally associated with these outcomes. The effect of childhood BMI may be influenced by sex disparities.

Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most challenging problems in computational biology and chemistry, and has puzzled scientists for 50 years. The advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much attention. Subsequent release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community, especially in the fields of biology and medicine. AF2 is thought to have a significant impact on structural biology and research areas that need protein structure information, such as drug discovery, protein design, prediction of protein function, et al. Though the time is not long since AF2 was developed, there are already quite a few application studies of AF2 in the fields of biology and medicine, with many of them having preliminarily proved the potential of AF2. To better understand AF2 and promote its applications, we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success, and particularly focus on reviewing its applications in the fields of biology and medicine. Limitations of current AF2 prediction will also be discussed.

Sorting unreelable inferior cocoons during the reeling process is essential for obtaining high-quality silk products. At present, silk reeling enterprises mainly rely on manual sorting, which is inefficient and labor-intensive. Automated sorting based on machine vision and sorting robots is a promising alternative. However, the accuracy and computational complexity of object detection are challenges for the practical application of automatic sorting, especially for small stains of inferior cocoons in images of densely distributed cocoons. To deal with this problem, an efficient fine-grained object detection network based on attention mechanism and multi-scale feature fusion, called AMMF-Net, is proposed for inferior silkworm cocoon recognition. In this model, fine-grained object features are key considerations to improve the detection accuracy. To efficiently extract fine-grained features of silkworm cocoon images, we designed an efficient hybrid feature extraction network (HFE-Net) that combines depth-wise separable convolution and Transformer as the backbone. It captures local and global information to extract fine-grained features of inferior silkworm cocoon images, improving the representation ability of the network. An efficient multi-scale feature fusion module (EMFF) is proposed as the neck of the object detection structure. It improves the typical down-sampling method of multi-scale feature fusion to avoid the loss of key information and achieve better performance. Our method is trained and evaluated on a dataset collected from multiple inferior cocoons. Extensive experiments validated the effectiveness and generalization performance of the HFE-Net network and the EMFF module, and the proposed AMMF-Net achieved the best detection results compared to other popular deep neural networks.

Abstract The loss of skeletal muscle mass and function is defined as sarcopenia, which might develop in elderly patients with cancers. It has been indicated as a potential negative factor in the survival of patients with malignant tumours. The aim of this systematic review and meta‐analysis was to evaluate the associations between sarcopenia and survival outcomes or postoperative complications in patients with oesophageal cancer (EC). Web of Science, Embase, Medline, and Cochrane Library databases were searched until 10 May 2022, using keywords: sarcopenia, oesophageal cancer, and prognosis. Studies investigating the prognostic value of sarcopenia on EC survival were included. Forest plots and summary effect models were used to show the result of this meta‐analysis. The quality of included studies was evaluated with the Newcastle‐Ottawa Scale (NOS). A total of 1436 studies were identified from the initial search of four databases, and 41 studies were included for the final quantitative analysis. This meta‐analysis revealed a significant association between sarcopenia and overall survival (OS) [hazard ratios (HR):1.68, 95% confidence interval (CI):1.54–1.83, P = 0.004, I2 = 41.7%] or disease‐free survival (DFS) 1.97 (HR: 1.97, 95% CI: 1.44–2.69, P = 0.007, I2 = 61.9%) of EC patients. Subgroup analysis showed that sarcopenia remained a consistent negative predictor of survival when stratified by different treatment methods, populations, or sarcopenia measurements. Sarcopenia was also a risk factor for postoperative complications with a pooled odds ratio of 1.47 (95% CI: 1.21–1.77, P = 0.094, I2 = 32.7%). The NOS scores of all included studies were ≥6, and the quality of the evidence was relatively high. The results from the study suggested that sarcopenia was significantly associated with both survival outcomes and postoperative complications in EC patients. Sarcopenia should be appropriately diagnosed and treated for improving short‐term and long‐term outcomes of patients with EC.

Abstract. Background:. The risk for chronic kidney disease (CKD) is influenced by genetic predisposition, sex, and lifestyle. Previous research indicates that coffee is a potentially protective factor in CKD. The current study aims to investigate whether sex disparity exists in the coffee–CKD association, and whether genetic risk of CKD or genetic polymorphisms of caffeine metabolism affect this association. Methods:. A total of 359,906 participants from the UK Biobank who were enrolled between 2006 and 2010 were included in this prospective cohort study, which aimed to estimate the hazard ratios for coffee intake and incident CKD using a Cox proportional hazard model. Allele scores of CKD and caffeine metabolism were additionally adjusted for in a subsample with qualified genetic data (n = 255,343). Analyses stratified by genetic predisposition, comorbidities, and sex hormones were performed. Tests based on Bayesian model averaging were conducted to ascertain the robustness of the results. Results:. Coffee was inversely associated with CKD in a dose-dependent manner. The effects of coffee did not differ across different strata of genetic risk for CKD, but were more evident among slower genetically predicted caffeine metabolizers. Significant sex disparity was observed (P value for interaction = 0.013), in that coffee drinking was only associated with the risk reduction of CKD in females. Subgroup analysis revealed that testosterone and sex hormone-binding globulin (SHBG), but not estradiol, modified the coffee–CKD association. Conclusions:. In addition to the overall inverse coffee–CKD association that was observed in the general population, we could also establish that a sex disparity existed, in that females were more likely to experience the benefit of the association. Testosterone and SHBG may partly account for the sex disparity.

Background: Chronic kidney disease (CKD) is an incurable disease requiring lifelong management. China has a high prevalence of CKD, which disproportionately affects older adults and those with chronic risk factors for CKD development. The rising prevalence of CKD in China places a substantial burden on the general population and the healthcare system. Summary: In China, there are currently many unmet needs for patients with CKD and high-risk individuals, resulting from a lack of education and support to reduce risk factors, delayed diagnoses, limited knowledge of CKD among primary care physicians and poor access to treatments among some patient populations. An integrated, nationwide approach is required to improve the current situation of CKD management in China. There are currently several national healthcare frameworks in place that focus on new major health policies to prevent disease and encourage people to adopt healthier lifestyles, and while they do not directly target CKD, they may have a positive indirect impact. We explore the unmet needs for patients with CKD in China and discuss the potential strategies that may be required to overcome them. Such strategies include improving physician and patient education, establishing a targeted screening programme, supporting patients to improve self-management behaviours, accelerating the creation of medical consortia and medical satellite centres, and migrating from hospital- to community-based management. In additional to policy-driven strategies, development of novel therapies will be key to providing new solutions for the long-term management of CKD.

Abstract Background Chronic kidney disease (CKD) affects 8 to 16% of the world’s population and is one of the top ten important drivers of increasing disease burden. Apart from genetic predisposition, lifestyle factors greatly contribute to the incidence and progression of CKD. The current bibliometric analysis aims to characterize the current focus and emerging trends of the research about the impact of modifiable lifestyle factors on CKD. Methods We searched articles addressing the impact of modifiable lifestyle factors on the incidence and/or progression of CKD, published between 2011 and 2020, from the Science Citation Index Expanded (SCIE) database. An adjusted citation index, which considered both the original citation count and publication year, was derived for the selection of most-cited publications. Publishing trends, co-authorship network, keywords, and research hotspots were analyzed and visualized. Results Among the top 100 most influential articles, 32 were narrative reviews, 16 systematic reviews and/or meta-analysis, 44 clinical research, and 8 basic research. The United States occupied a dominant position in the perspective of article numbers and international partnerships, followed by European countries. The modifiable factors that drew the most and constant attention over the decade were diet or nutrition management reported in 63 papers, followed by obesity or body mass index (n = 27), and physical activity or exercises (n = 8). Alcohol consumption, fish oil, chain fatty-acids, and water-soluble vitamins were emerging hotspots identified in the recent most cited publications. Conclusions Based on the bibliometric analysis of the most influential articles, our study provides a comprehensive description of publishing trends and research focus over a decade in the field of lifestyle factors’ impact on CKD. Diet, obesity, and physical activity were factors receiving the most attention in this topic.

The survival prognosis of human papillomavirus (HPV)-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) is largely different, and little is known about the anti-tumor mechanism of tumor-infiltrated exhausted CD8+ T cells (Tex) in HNSCC. We performed cell-level multi-omics sequencing on human HNSCC samples to decipher the multi-dimensional characteristics of Tex cells. A proliferative exhausted CD8+ T cell cluster (P-Tex) which was beneficial to survival outcomes of patients with HPV-positive HNSCC was identified. Interestingly, P-Tex cells expressed CDK4 genes as high as cancer cells, which could be simultaneously inhibited by CDK4 inhibitors and might be a potential reason for the ineffectiveness of CDK4 inhibitors in treating HPV-positive HNSCC. P-Tex cells could aggregate in the antigen-presenting cell niches and activate certain signaling pathways. Together, our findings suggest a promising role for P-Tex cells in the prognosis of patients with HPV-positive HNSCC by providing modest but persistent anti-tumor effects.

ObjectiveAccording to previous studies, the incidence of post-contrast acute kidney injury(PC-AKI) in diabetic is far higher than that in the general population. Therefore, we explored the relationship between the incidence of PC-AKI and different baseline serum creatinine (SCr) levels, and determined the relationship between PC-AKI and different types of contrast media (CMs), different doses of CM, and different examination methods in this specific population.Materials and methodsPatients with diabetes in whom CM was used between 2010 and 2020 at our institution were included. Participants were identified according to the following three schemes: Scheme 1 (n=5911), SCr was detected before and within 72 h after using CM; Scheme 2 (n=2385), SCr was detected within 24 h before and within 24–72 h after using CM; and Scheme 3 (n=81), SCr was detected within 24 h before and within 0–24, 24–48, and 48–72 h after using CM. The incidence of PC-AKI with different types of CM, incidence of PC-AKI on digital subtraction angiography (DSA) and enhanced computed tomography (CT), proportion of PC-AKI with different doses of CM, and baseline SCr at different stages of PC-AKI were compared. Multivariate logistic regression analysis was used to explore risk factors for PC-AKI.ResultsA total of 29,081 patients were included in this study. The incidence of PC-AKI in Scheme 3 (22.22%) was higher than those in Schemes 1 (6.19%) and 2 (7.71%). The incidence of PC-AKI on DSA was higher than that on enhanced CT (8.30% vs. 5.80%; P

BackgroundThe Geriatric Nutritional Index (GNRI) has been indicated as a nutritional index which is highly associated with complications and mortality in older hospitalized patients. Moreover, early studies had suggested that GNRI is a potential prognostic indicator for some malignances. However, the prognostic value of GNRI in esophageal squamous cell carcinoma (ESCC) patients underwent neoadjuvant therapy followed by esophagectomy remains elusive.Materials and methodsThis retrospective study incorporated 373 patients with ESCC who had underwent neoadjuvant therapy followed by radical esophagectomy at West China Hospital of Sichuan University between April 2011 and September 2021. The GNRI formula was: 1.489 × albumin (g/dl) + 41.7 × current weight/ideal weight. Patients were classified as GNRI-low (GNRI < 98.7) or GNRI high (GNRI ≥ 98.7). The association between GNRI and clinical survival status were assessed utilizing Kaplan-Meier methods and Cox regression analysis.ResultsThree hundred and seventy three patients were retrospectively included in this study. 80 (21.5%) and 293 (78.5%) patients had been divided into the GNRI-low and GNRI-high groups respectively. Pathological T stage and the rate of nodal metastasis were significantly higher in the GNRI low group than in the GNRI high group (P = 0.003 and P = 0.001, respectively) among the examined demographic parameters. Furthermore, GNRI was significantly correlated with postoperative complications, patients with lower GNRI had a higher postoperative complication rate as compared with GNRI high group [Odds ratio: 2.023; 95% confidence interval (CI): 1.208–3.389; P = 0.007]. Univariate analysis of 5-year overall survival (OS) and disease-free survival (DFS) found that the rate of survival was considerably lower in the GNRI-low group than in the GNRI-high group (P < 0.001). However, multivariate analysis demonstrated that GNRI was not an independent risk factor.ConclusionIn patients with ESCC, low GNRI exhibited a poor nutritional indicator and related to postoperative complications after neoadjuvant therapy. Intensive follow-up after surgery should be performed for ESCC patients with low GNRI.

This study aimed to find out the blood data characteristics of patients and explore the correlation between severe preeclampsia and blood index value. Provide assistance for the early attention direction of severe preeclampsia diagnosis and treatment. 19,653 pregnant women presenting to the West China Second University Hospital, Sichuan University from January 2017 to April 2019. After screening, a total of 248 patients, 124 severe preeclampsia cases, and 124 controls were selected for this study. Forty-three blood examination variables were obtained from routine blood work, hepatic, renal and coagulation function examination. Light gradient boosting machine (light GBM), decision tree and random forest were used for date diving. We randomly divided 35% of the original data as a testing set to conduct internal validation of the performance of the prediction model. The area under receiver operating characteristic curve (AUC) was used as the main score to compare the three methods. Finally, a binary classification light GBM model based on aspartate aminotransferase, direct bilirubin and activated partial thromboplastin time ratio can predict severe preeclampsia with sensitivity of 88.37%, specificity of 77.27%, AUC of 89.74% and positive predictive value of 65.96%. We believe relevant quantifiable indicators can establish an effective prediction model, which can provide guidance for early detection and prevention of severe preeclampsia.

Many studies have confirmed that micro-RNA (mir) is related to the prognosis of esophageal carcinoma (EC), suggesting the mir could be used to guide the therapeutic strategy of EC. Some of mir molecules are considered as favorable prognostic factors for EC. The purpose of our study is to evaluate the prognostic potential of mir-375, 133, 143, 145 in primary EC, we summarized all the results from available studies, aiming delineating the prognostic role of mir in EC. Relevant studies were identified by searching databases including Medline, Embase, Web of science, Cochrane Library. The studies which explored the prognostic value of mir-375, 133, 143, 145 expressions on survival outcomes in patients with EC were included in this study. The hazard ratios (HR) and their responding 95% confidence interval (CI) were also extracted. A total of 25 studies were collected, including 1260 patients, and the prognostic values of four mirs in EC were analyzed. Survival outcomes including overall survival (OS), progression-free survival (PFS) and disease-free survival (DFS) were used as the primary endpoint to evaluate the prognostic value of mir. The pooled analysis results showed that up-regulation of mir-375 indicated favorable OS (HR=0.50; 95%CI: 0.37-0.69; P

Esophageal cancer (EC) is a common malignant gastrointestinal (GI) cancer in adults. Although surgical technology combined with neoadjuvant chemoradiotherapy has advanced rapidly, patients with EC are often diagnosed at an advanced stage and the five-year survival rate remains unsatisfactory. The poor prognosis and high mortality in patients with EC indicate that effective and validated therapy is of great necessity. Recently, immunotherapy has been successfully used in the clinic as a novel therapy for treating solid tumors, bringing new hope to cancer patients. Several immunotherapies, such as immune checkpoint inhibitors (ICIs), chimeric antigen receptor T-cell therapy, and tumor vaccines, have achieved significant breakthroughs in EC treatment. However, the overall response rate (ORR) of immunotherapy in patients with EC is lower than 30%, and most patients initially treated with immunotherapy are likely to develop acquired resistance (AR) over time. Immunosuppression greatly weakens the durability and efficiency of immunotherapy. Because of the heterogeneity within the immune microenvironment and the highly disparate oncological characteristics in different EC individuals, the exact mechanism of immunotherapy resistance in EC remains elusive. In this review, we provide an overview of immunotherapy resistance in EC, mainly focusing on current immunotherapies and potential molecular mechanisms underlying immunosuppression and drug resistance in immunotherapy. Additionally, we discuss prospective biomarkers and novel methods for enhancing the effect of immunotherapy to provide a clear insight into EC immunotherapy.

Autophagy is a critical cellular homeostatic mechanism, and its dysfunction is linked to invasive breast carcinoma (BRCA). Recently, several omics methods have been applied to explore autophagic regulators in BRCA; however, more reliable and robust approaches for identifying crucial regulators and druggable targets remain to be discovered. Thus, we report here the results of multi-omics approaches to identify potential autophagic regulators in BRCA, including gene expression (EXP), DNA methylation (MET) and copy number alterations (CNAs) from The Cancer Genome Atlas (TCGA). Newly identified candidate genes, such as SF3B3, TRAPPC10, SIRT3, MTERFD1, and FBXO5, were confirmed to be involved in the positive or negative regulation of autophagy in BRCA. SF3B3 was identified firstly as a negative autophagic regulator, and siRNA/shRNA-SF3B3 were shown to induce autophagy-associated cell death in in vitro and in vivo breast cancer models. Moreover, a novel small-molecule activator of SIRT3, 1-methylbenzylamino amiodarone, was discovered to induce autophagy in vitro and in vivo. Together, these results provide multi-omics approaches to identify some key candidate autophagic regulators, such as the negative regulator SF3B3 and positive regulator SIRT3 in BRCA, and highlight SF3B3 and SIRT3 as new druggable targets that could be used to fill the gap between autophagy and cancer drug development.

Abstract Few histological prognostic indicators for end-stage renal disease (ESRD) have been validated in diabetic patients. This biopsy-based study aimed to identify nephropathological risk factors for ESRD in Chinese patients with type 2 diabetes. Histological features of 322 Chinese type 2 diabetic patients with biopsy-confirmed diabetic nephropathy (DN) were retrospectively analysed. Cox proportional hazards analysis was used to estimate the hazard ratio (HR) for ESRD. Single glomerular proteomics and immunohistochemistry were used to identify differentially expressed proteins and enriched pathways in glomeruli. During the median follow-up period of 24 months, 144 (45%) patients progressed to ESRD. In multivariable models, the Renal Pathology Society classification failed to predict ESRD, although the solidified glomerulosclerosis (score 1: HR 1.65, 95% confidence interval [CI] 1.04–2.60; score 2: HR 2.48, 95% CI 1.40–4.37) and extracapillary hypercellularity (HR 2.68, 95% CI 1.55–4.62) were identified as independent risk factors. Additionally, single glomerular proteomics, combined with immunohistochemistry, revealed that complement C9 and apolipoprotein E were highly expressed in solidified glomerulosclerosis. Therefore, solidified glomerulosclerosis and extracapillary hypercellularity predict diabetic ESRD in Chinese patients. Single glomerular proteomics identified solidified glomerulosclerosis as a unique pathological change that may be associated with complement overactivation and abnormal lipid metabolism.

Esophageal cancer (EC) is one of the most common cancers worldwide. Malnutrition often leads to poor prognosis of patients with EC. Geriatric nutritional risk index (GNRI) was reported as an objective nutrition-related risk index. We intend to comprehensively review evidence of GNRI in predicting EC prognosis. To explore the influence of GNRI on the long-term survival outcome of patients with EC, a meta-analysis was needed. We searched the Web of Science, Medline, Embase, and the Cochrane Library databases. The association between prognosis of patients with EC and GNRI was evaluated by pooling hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs). The fixed model or random model method was chosen according to the heterogeneity among the studies. Totally, 11 studies with 1785 patients who met the inclusion criteria were eventually included in our meta-analysis. Comparing the lower level GNRI group and the higher level GNRI group, the pooled results showed that lower GNRI had a negative impact on overall survival (OS) (HR: 1.75, 95% CI: 1.45–2.10, P < 0.01) and cancer-specific survival (CSS) (HR: 1.77, 95% CI: 1.19–2.62, P < 0.01), indicating that lower GNRI significantly predicted poor OS. In conclusion, lower GNRI could predict the poor prognosis of patients with EC. Meanwhile, more well-designed randomized controlled trials (RCTs) are needed to confirm the findings.

Esophageal cancer (EC) is a common malignant tumor of the upper digestive tract. The microbiota in the digestive tract epithelium comprises a large number of microorganisms that adapt to the immune defense and interact with the host to form symbiotic networks, which affect many physiological processes such as metabolism, tissue development, and immune response. Reports indicate that there are microbial compositional changes in patients with EC, which provides an important opportunity to advance clinical applications based on findings on the gut microbiota. For example, microbiota detection can be used as a biomarker for screening and prognosis, and microorganism levels can be adjusted to treat cancer and decrease the adverse effects of treatment. This review aims to provide an outline of the gut microbiota in esophageal neoplasia, including the mechanisms involved in microbiota-related carcinogenesis and the prospect of utilizing the microbiota as EC biomarkers and treatment targets. These findings have important implications for translating the use of gut microbiota in clinical applications.

The heavy metals contamination in soil has attracted increasing attention. In this study, the main objective was to determine three heavy metals (Cd, Pb, and Cr) of soils contaminated by smelting waste, and to evaluate pollution risk. The Pb (15.48 mg/kg) and Cd (311.39 mg/kg) mean concentrations exceeded the national standard, while Cr (48.60 mg/kg) concentration did not exceed. The Heavy metal fractions analysis showed that three heavy metals were dominated by FeMn oxides fraction (Fe-Mn). The correlation and cluster analysis indicated that there was significant correlation between Cd and Pb (0.55< r < 0.96), while Cr was not correlation to Cd and Pb. The environmental pollution of heavy metals was assessed by the ratio of secondary phase and primary phase (RSP). The result showed that RSP values of Cd, Pb, and Cr range from 13.05–54.28, 16.11–4.97 and 1.61–52.33, which indicated soil was serious contaminated by them. These results showed that smelting waste discharge led to this smelter soil being seriously contaminated by multiple heavy metals which have a tendency to transport and accumulate into deep soil due to their high fractional transformation.

Background Gastric cancer is one of the most lethal tumors and is characterized by poor prognosis and lack of effective diagnostic or therapeutic biomarkers. The aim of this study was to find hub genes serving as biomarkers in gastric cancer diagnosis and therapy. Methods GSE66229 from Gene Expression Omnibus (GEO) was used as training set. Genes bearing the top 25% standard deviations among all the samples in training set were performed to systematic weighted gene co-expression network analysis (WGCNA) to find candidate genes. Then, hub genes were further screened by using the “least absolute shrinkage and selection operator” (LASSO) logistic regression. Finally, hub genes were validated in the GSE54129 dataset from GEO by supervised learning method artificial neural network (ANN) algorithm. Results Twelve modules with strong preservation were identified by using WGCNA methods in training set. Of which, five modules significantly related to gastric cancer were selected as clinically significant modules, and 713 candidate genes were identified from these five modules. Then, ADIPOQ, ARHGAP39, ATAD3A, C1orf95, CWH43, GRIK3, INHBA, RDH12, SCNN1G, SIGLEC11 and LYVE1 were screened as the hub genes. These hub genes successfully differentiated the tumor samples from the healthy tissues in an independent testing set through artificial neural network algorithm with the area under the receiver operating characteristic curve at 0.946. Conclusions These hub genes bearing diagnostic and therapeutic values, and our results may provide a novel prospect for the diagnosis and treatment of gastric cancer in the future.

Drug resistance represents the major obstacle to get the maximum therapeutic benefit for patients with esophageal cancer since numerous patients are inherently or adaptively resistant to therapeutic agents. Notably, increasing evidence has demonstrated that drug resistance is closely related to the crosstalk between tumor cells and the tumor microenvironment (TME). TME is a dynamic and ever-changing complex biological network whose diverse cellular and non-cellular components influence hallmarks and fates of tumor cells from the outside, and this is responsible for the development of resistance to conventional therapeutic agents to some extent. Indeed, the formation of drug resistance in esophageal cancer should be considered as a multifactorial process involving not only cancer cells themselves but cancer stem cells, tumor-associated stromal cells, hypoxia, soluble factors, extracellular vesicles, etc. Accordingly, combination therapy targeting tumor cells and tumor-favorable microenvironment represents a promising strategy to address drug resistance and get better therapeutic responses for patients with esophageal cancer. In this review, we mainly focus our discussion on molecular mechanisms that underlie the role of TME in drug resistance in esophageal cancer. We also discuss the opportunities and challenges for therapeutically targeting tumor-favorable microenvironment, such as membrane proteins, pivotal signaling pathways, and cytokines, to attenuate drug resistance in esophageal cancer.

Pharmaceutical therapies are essential for esophageal cancer (EC). For the advanced EC, the neoadjuvant therapy regimen, including chemotherapy plus radiotherapy and/or immunotherapy, is effective to achieve clinical benefit, even pathological complete response. For the unresectable, recurrent, and metastatic EC, the pharmaceutical therapy is the limited effective regimen to alleviate the disease and prolong the progression-free survival and overall survival. In this review, we focus on the pharmaceutical applications in EC treatment including cytotoxic agents, molecular targeted antibodies, and immune checkpoint inhibitors (ICIs). The chemotherapy regimen is based on cytotoxic agents such as platinum-based complexes, fluorinated pyrimidines and taxenes. Although the cytotoxic agents have been developed in past decades, the standard chemotherapy regimen is still the cisplatin and 5-FU or paclitaxel because the derived drugs have no significant advantages of overcoming the shortcomings of side effects and drug resistance. The targeted molecular therapy is an essential supplement for chemotherapy; however, there are only a few targeted therapies available in clinical practice. Trastuzumab and ramucirumab are the only two molecular therapy drugs which are approved by the US Food and Drug Administration to treat advanced and/or metastatic EC. Although the targeted therapy usually achieves effective benefits in the early stage therapy of EC, the patients will always develop drug resistance during treatment. ICIs have had a significant impact on routine clinical practice in cancer treatment. The anti-programmed cell death-1 monoclonal antibodies pembrolizumab and nivolumab, as the ICIs, are recommended for advanced EC by several clinical trials. However, the significant issues of pharmaceutical treatment are still the dose-limiting side effects and primary or secondary drug resistance. These defects of pharmaceutical therapy restrain the clinical application and diminish the effectiveness of treatment.

Abstract Background Pancreatic cancer is one of the most lethal tumors with poor prognosis, and lacks of effective biomarkers in diagnosis and treatment. The aim of this investigation was to identify hub genes in pancreatic cancer, which would serve as potential biomarkers for cancer diagnosis and therapy in the future. Methods Combination of two expression profiles of GSE16515 and GSE22780 from Gene Expression Omnibus (GEO) database was served as training set. Differentially expressed genes (DEGs) with top 25% variance followed by protein-protein interaction (PPI) network were performed to find candidate genes. Then, hub genes were further screened by survival and cox analyses in The Cancer Genome Atlas (TCGA) database. Finally, hub genes were validated in GSE15471 dataset from GEO by supervised learning methods k-nearest neighbor (kNN) and random forest algorithms. Results After quality control and batch effect elimination of training set, 181 DEGs bearing top 25% variance were identified as candidate genes. Then, two hub genes, MMP7 and ITGA2, correlating with diagnosis and prognosis of pancreatic cancer were screened as hub genes according to above-mentioned bioinformatics methods. Finally, hub genes were demonstrated to successfully differ tumor samples from normal tissues with predictive accuracies reached to 93.59 and 81.31% by using kNN and random forest algorithms, respectively. Conclusions All the hub genes were associated with the regulation of tumor microenvironment, which implicated in tumor proliferation, progression, migration, and metastasis. Our results provide a novel prospect for diagnosis and treatment of pancreatic cancer, which may have a further application in clinical.

Nano Ag has excellent antibacterial properties and is widely used in various antibacterial materials, such as antibacterial medicine and medical devices, food packaging materials and antibacterial textiles. Despite the many benefits of nano-Ag, more and more research indicates that it may have potential biotoxic effects. Studies have shown that people who ingest nanoparticles by mouth have the highest uptake in the intestinal tract, and that the colon area is the most vulnerable to damage and causes the disease. In this study, we examined the toxic effects of different concentrations of Ag-NPs on normal human colon cells (NCM460) and human colon cancer cells (HCT116). As the concentration of nanoparticles increased, the activity of the two colon cells decreased and intracellular reactive oxygen species (ROS) increased. RT-qPCR and Western-blot analyses showed that Ag NPs can promote the increase in P38 protein phosphorylation levels in two colon cells and promote the expression of P53 and Bax. The analysis also showed that Ag NPs can promote the down-regulation of Bcl-2, leading to an increased Bax/Bcl-2 ratio and activation of P21, further accelerating cell death. This study showed that a low concentration of nano Ag has no obvious toxic effect on colon cells, while nano Ag with concentrations higher than 15 μg/mL will cause oxidative damage to colon cells.

BACKGROUND:Previous studies have revealed that increased body mass index (BMI) is associated with decreased mortality among hemodialysis patients. However, few studies have dealt with the association between BMI and mortality among patients undergoing peritoneal dialysis (PD) and even fewer studies have focused on the Asian PD patients. The reported studies were often non-conclusive and some even yielded contradictory results. This paper, to our best knowledge, registers the first attempt to systematically review the current literature and summarize new results on the association between BMI and mortality among the Asian PD population. METHOD:A systematic literature review was performed in Medline and EMBASE to identify relevant cohort studies on all-cause and cardiovascular disease (CVD) mortality stratified by BMI categories tailored to Asians among the Asian PD population. We meta-analyzed individual results based on a random effect model, strictly complying with Preferred Reporting Items for Systematic Reviews and Meta-analysis. RESULTS:The paper reviews seven cohort studies with a total of 3,610 Asian PD patients. Obese group (BMI = 25-29.9 kg/m2) was associated with higher risk of all-cause mortality (HR = 1.46, 95%CI [1.07-1.98]; p = 0.02) and CVD mortality (HR = 2.01, 95%CI [1.14-3.54]; p = 0.02), compared to the normal group (BMI = 18.5-22.9 kg/m2). The underweight group (BMI

Treatment of septic acute kidney injury (AKI) has still been beyond satisfaction, although anti-inflammatory therapy is beneficial for sepsis-induced AKI. Compound 5b was derived from natural pyranochalcones and exhibited potent anti-inflammatory activity in adjuvant-induced arthritis. In this study, we aimed to investigate the renoprotective effects and potential mechanism of 5b against lipopolysaccharide (LPS)-induced AKI. C57BL/6 mice and human renal proximal tubule cell line (HK-2 cell) were treated with LPS, respectively. Compound 5b was orally administrated at a dose of 25 mg/kg/day for 5 days before LPS (10 mg/kg) intraperitoneal injection. Cells were pretreated with 25 μg/mL 5b for 30 min before LPS (1 μg/mL) treatment. Pretreatment with 5b markedly alleviated tubular injury and renal dysfunction in LPS-induced AKI. The expression of IL-1β, IL-6, and TNF-α both in renal tissue of AKI mice and in the LPS-stimulated HK-2 cell culture medium were reduced by 5b treatment (p < 0.05). The results of immunohistochemistry staining showed that 5b reduced the expression of NF-κB p65 in kidneys. Similarly, 5b decreased the LPS-induced levels of NF-κB p65 and TLR4 proteins in kidneys and HK-2 cells. These data demonstrated that a potent pyranochalcone derivative, 5b, exhibited renoprotective effect against LPS-induced AKI, which was associated with anti-inflammatory activity by inhibiting the TLR4/NF-κB pathway.