Two cadmium-resistant bacteria Burkholderia contaminans HA09 and Arthrobacter humicola improve phytoremediation efficiency of cadmium in Ageratum conyzoides L.

To investigate the impact and mechanism of Cd-tolerant bacteria in soil on promoting Cd accumulation in Ageratum conyzoides L., we verified the impact of inoculating two strains, B-1 (Burkholderia contaminans HA09) and B-7 (Arthrobacter humicola), on Cd accumulation in A. conyzoides through a pot experiment. Additionally, we investigated the dissolution of CdCO3 and nutrient elements, as well as the release of indoleacetic acid (IAA) by the two strains. The results showed that both strains can significantly improve the dissolution of CdCO3. Strains B-1 and B-7 had obvious effect of dissolving phosphorus, which was 5.63 and 2.76 times higher than that of the control group, respectively. Strain B-7 had significant effect of dissolution potassium, which was 1.79 times higher than that of the control group. Strains B-1 and B-7 had significant nitrogen fixation effect, which was 29.53 and 44.39 times higher than that of the control group, respectively. In addition, inoculating with strain B-1 and B-7 significantly increased the Cd extraction efficiency of A. conyzoides (by 114% and 45% respectively) through enhancing Cd accumulation and the biomass of A. conyzoides. Furthermore, the inoculation of strain B-1 and B-7 led to a significant increase in the activities of CAT and SOD, as well as the content of chlorophyll a and total chlorophyll in the leaves of A. conyzoides. To sum up, strain B-1 and B-7 can promote the phytoremediation efficiency of A. conyzoides on Cd by promoting the biomass and Cd accumulation of A. conyzoides.

Using Targeted Next-Generation Sequencing to Diagnose Severe Pneumonia Due to Tropheryma Whipplei and Human Metapneumovirus: A Case Report and Literature Review.

Background: In addition to the well-known Whipple's disease (WD), Tropheryma Whipplei (TW) can also lead to acute pneumonia. There is no unified consensus on the susceptible population, pathogenesis, clinical manifestations, diagnostic criteria, and treatment options for TW pneumonia. Clinical Presentation and Intervention: This is an elderly patient with multiple injuries caused by falling from a building, and was transferred to intensive care unit (ICU) for mechanical ventilation and empirical anti-infection treatment due to severe pneumonia, and then the results of targeted next-generation sequencing (tNGS) in patient's bronchoalveolar lavage fluid (BALF) suggested TW and human metapneumovirus (HMPV) infection, and after switching to anti-infective therapy for TW, the patient was successfully extubated and transferred out of the ICU. Conclusion: This is the first case of using tNGS to diagnose severe pneumonia caused by TW and HMPV. We hope that our study can serve as a reference for the diagnosis and treatment of related cases in the future.

Unveiling the Etiology of Urological Tumors: A Systematic Review of Mendelian Randomization Applications in Renal Cell Carcinoma, Bladder Cancer, and Prostate Cancer.

BACKGROUND: Our study aims to address two pivotal questions: "What are the recent advancements in understanding the etiology of urological tumors through Mendelian Randomization?" and "How can Mendelian Randomization be more effectively applied in clinical settings to enhance patient health outcomes in the future?" METHODS: In our systematic review conducted in April 2023, we utilized databases like PubMed and Web of Science to explore the influence of Mendelian Randomization in urological oncological diseases. We focused on studies published from January 2018, employing keywords related to urological tumors and Mendelian Randomization, supplemented with MeSH terms and manual reference checks. Our inclusion criteria targeted original research studies, while we excluded reports and non-relevant articles.  Data extraction followed a PICO-based approach, and bias risk was independently evaluated, with discrepancies resolved through discussion. This systematic approach adhered to PRISMA guidelines for accuracy and thoroughness in reporting. RESULTS: From the initial 457 publications, we narrowed down to 43 full-text articles after screening and quality assessments.A deeper understanding of Mendelian Randomization can help us explore risk factors with a clear causal relationship to urological tumors.This insight may pave the way for future research in early diagnosis, treatment, and management of associated diseases. CONCLUSION: Our review underscores the value of MR in urogenital tumor research, highlighting its efficacy in establishing causality and its potential to clarify disease mechanisms. Despite challenges like large sample sizes and variant identification, MR offers new perspectives for understanding and managing these tumors, suggesting a trend towards more inclusive and diverse research approaches.

Basal metabolic rate and the risk of urolithiasis: a two-sample Mendelian randomization study.

OBJECTIVE: Few studies have investigated the impact of basal metabolic rate (BMR) on the development of urolithiasis, and the causal relationship is yet to be established. In this study, a two-sample Mendelian randomization (MR) analysis was utilized to identify the causal relationship between BMR and risk of urolithiasis. METHOD: Genetic instruments for BMR were drawn from a public genome-wide association study (GWAS). Summary dates on BMR and urolithiasis were obtained from a GWAS meta-analysis with sample sizes of 454,874 and 212,453, respectively. The inverse-variance weighted (IVW) method was provided as the main approach to estimate the causal relationship. The weighted-median method and the MR-Egger method were used as supplements to the IVW method. In addition, we conducted sensitivity analyses, including heterogeneity tests, pleiotropy tests and leave-one-out analysis, to assess the robustness of the outcomes. Furthermore, the funnel plot asymmetry was visually inspected to evaluate possible bias. RESULTS: The inverse-variance weighted data revealed that genetically predicted BMR significantly decreased the risk of urolithiasis [beta coefficient (beta): - 0.2366, odds ratio (OR): 0.7893, 95% confidence interval (CI) 0.6504-0.9579, p = 0.0166]. CONCLUSIONS: BMR has causal effects on urolithiasis in an MR study, and the risk of urolithiasis in patients with lower levels of BMR is higher.

The association between wet overactive bladder and consumption of tea, coffee, and caffeine: Results from 2005-2018 National Health and Nutrition Examination Survey.

BACKGROUND & AIMS: Previous studies have reported an inconsistent relationship between overactive bladder (OAB) and the consumption of tea, coffee, and caffeine. Our study aims to determine these associations in a large and nationally representative adult sample. METHODS: This cross-sectional study included 15,379 participants from the 2005-2018 US National Health and Nutrition Examination Survey (NHANES) database. The outcome was the risk of wet OAB that was diagnosed when the OAB symptom score was ≥3 with urgent urinary incontinence and excluded other diseases affecting diagnosis. The exposures were the consumption of tea, coffee, and caffeine. Weighted logistic regression models were established to explore these associations by calculating odds ratios (OR) and 95% confidence intervals (CI), as did restricted cubic splines (RCS) used to analyze the nonlinear associations. RESULT: Of all the participants (n = 15,379), 2207 had wet OAB. Mean [SE] consumption of tea, total coffee, caffeinated coffee, decaffeinated coffee, and caffeine was 233.6 [15.7] g/day, 364.3 [15.5] g/day, 301.6 [14.9] g/day, 62.7 [7.9] g/day, 175.5 [6.6] mg/day in participants with wet OAB, respectively. In the fully adjusted model, compared to those without tea consumption, the high consumption of tea (>481 g/day) was associated with an increased risk of wet OAB (OR: 1.29; 95%CI: 1.01-1.64). Low decaffeinated coffee (0.001-177.6 g/day) had a negative association with the risk (OR: 0.66; 95%CI: 0.49-0.90). In the RCS analysis, tea consumption showed a positive linear association with the risk of wet OAB, and decaffeinated coffee showed a nonlinear relationship with the risk and had a turning point of 78 g/day in the U-shaped curve between 0 and 285 g/day. Besides, total coffee, caffeinated coffee, and caffeine consumption had no significant association with the risk. Interestingly, in the high tea consumption, participants with high total coffee consumption [>527.35 g/day, OR and 95%CI: 2.14(1.16-3.94)] and low caffeine consumption [0.1-74.0 mg/day, OR and 95%CI: 1.50(1.03-2.17)] were positively associated with the risk of wet OAB. CONCLUSION: High tea consumption was associated with the increased risk of wet OAB, especially intake together with high total coffee and low caffeine consumption, but no significant association with the single consumption of total coffee and caffeine. Low decaffeinated coffee was associated with a decreased risk of wet OAB. It is necessary to control tea intake when managing the liquid intake of wet OAB patients.

Construction and validation of a perioperative concomitant lower extremity deep vein thrombosis line graph model in patients with aneurysmal subarachnoid hemorrhage.

Background: To develop and validate a nomogram for predicting the probability of deep venous thrombosis (DVT) in patients with aneurysmal subarachnoid hemorrhage (aSAH) during the perioperative period, using clinical features and readily available biochemical parameters. Methods: The least absolute shrinkage and selection operator (LASSO) regression technique was employed for data dimensionality reduction and selection of predictive factors. A multivariable logistic regression analysis was conducted to establish a predictive model and nomogram for post-aSAH DVT. The discriminative ability of the model was determined by calculating the area under the curve (AUC). Results: A total of 358 aSAH patients were included in the study, with an overall incidence of DVT of 20.9%. LASSO regression identified four variables, including age, modified Fisher grade, total length of hospital stay, and anticoagulation therapy, as highly predictive factors for post-aSAH DVT. The patients were randomly divided into a modeling group and a validation group in a 6:4 ratio to construct the nomogram. The AUCs of the modeling and validation groups were 0.8511 (95% CI, 0.7922-0.9099) and 0.8633 (95% CI, 0.7968-0.9298), respectively. Conclusions: The developed nomogram exhibits good accuracy, discriminative ability, and clinical utility in predicting DVT, aiding clinicians in identifying high-risk individuals and implementing appropriate preventive and treatment measures.

New discovery of extremely high adsorption of environmental DNA on cuttlefish bone pyrolysis derivative via large pore structure and carbon film.

Environmental DNA (eDNA) carrying antibiotic resistance gene (ARG) has attracted a great deal of attention because of its threat to the ecology and human health. Traditional porous adsorbents, such as microporous biochar and natural mineral, are low-effective in removing eDNA from sewage. This study used cuttlefish-bone (CB), a fishery waste, as an anticipated material to adsorb a model compound of eDNA from herring sperm (hsDNA). An interesting result was firstly observed that extremely high DNA adsorption on cuttlefish-bone pyrolysis derivative (CCB) was up to 88.7 mg/g, 3-10 folds higher than that of most other adsorbents in the existing literatures, which was attributed to the carbon film and large pores. To achieve an adsorption rate of 75 %, hsDNA adsorption took 96 h on CB but only 24 h on CCB, which was attributed to the fluent channel of CCB. The ligand exchange, Ca2+ bridge and π-π interaction were identified as dominated adsorption mechanisms, based on FTIR and phosphate competition experiments. This study exploited a high-efficient, environmentally friendly, and low-cost adsorbent for treating ARG-contaminated soil and water.

Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis.

The plant genome produces an extremely large collection of long noncoding RNAs (lncRNAs) that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes. Here, we mapped the transcriptional heterogeneity of lncRNAs and their associated gene regulatory networks at single-cell resolution. We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing (scRNA-seq) datasets from juvenile Arabidopsis seedlings. We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers. We further demonstrated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity. In addition, we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs, and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs. The analysis results are available at the single-cell-based plant lncRNA atlas database (scPLAD; https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstrates the power of integrative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.

Safety and Efficacy of Hybrid Surgery in Chronic Internal Carotid Artery Occlusion: A Systematic Review and Meta-Analysis.

INTRODUCTION: Chronic internal carotid artery occlusion (CICAO) is a common cause of stroke and ischemia recurrence. An increasing number of reports have highlighted the potential of hybrid surgery for treating CICAO. There are few studies, specifically nonrandomized controlled trials, on the safety and effectiveness of hybrid surgery for the treatment of CICAO, so in this study, we hypothesized that hybrid surgery would be safe, have an acceptable complication rate and a high success rate. METHODS: MEDLINE, Embase, Cochrane Library, and Web of Science databases were searched for relevant studies published up to January 30, 2023. The primary endpoint was recanalization rates of occluded vessels, and the secondary endpoint was perioperative death and procedure-related complications. Subgroup analysis focused on the recanalization rates of endovascular intervention (EI) and hybrid surgery, as well as the rates of recanalization below the clinoid segment and at the clinoid segment and beyond. The follow-up visit was conducted at least 3 months after surgery, and stenosis or occlusion recurrence was confirmed by review of CTA or DSA scan. RESULTS: The databases were searched and 1,709 records were identified, of which 16 articles were used in the meta-analysis, and 464 CICAO patients with complete data who underwent hybrid surgery were enrolled. Hybrid surgery was associated with higher success rates (RD = 0.87, 95% CI [0.84-0.91], p < 0.00001) than EI (OR = 4.71, 95% CI [2.32-9.56], p < 0.0001). The procedural success rate in the below-clinoid segment group was significantly higher than that in the clinoid segment and beyond group (OR = 13.76, 95% CI [5.31-35.66], p < 0.00001). The total periprocedural complication rate was low (RD = 0.11, 95% CI [0.07-0.15], p < 0.00001 and RD = 0.04, 95% CI [0.00-0.07], p = 0.03). Target vessel restenosis or reocclusion occurred in 35 patients (8%) during the follow-up period (RD = 0.08, 95% CI [0.04-0.12], p < 0.0001). CONCLUSION: Hybrid surgery is the combination of the advantages of open surgery and EI, has a high success rate and a low risk of recurrence of stenosis and occlusion in the long term. Randomized controlled trials on hybrid surgery for internal carotid artery occlusion are necessary.

Rasd1 is involved in white matter injury through neuron-oligodendrocyte communication after subarachnoid hemorrhage.

AIMS: Rasd1 has been reported to be correlated with neurotoxicity, metabolism, and rhythm, but its effect in case of subarachnoid hemorrhage (SAH) remained unclear. White matter injury (WMI) and ferroptosis participate in the early brain injury (EBI) after SAH. In this work, we have investigated whether Rasd1 can cause ferroptosis and contribute to SAH-induced WMI. METHODS: Lentivirus for Rasd1 knockdown/overexpression was administrated by intracerebroventricular (i.c.v) injection at 7 days before SAH induction. SAH grade, brain water content, short- and long-term neurobehavior, Western blot, real-time PCR, ELISA, biochemical estimation, immunofluorescence, diffusion tensor imaging (DTI), and transmission electron microscopy (TEM) were systematically performed. Additionally, genipin, a selective uncoupling protein 2(UCP2) inhibitor, was used in primary neuron and oligodendrocyte co-cultures for further in vitro mechanistic studies. RESULTS: Rasd1 knockdown has improved the neurobehavior, glia polarization, oxidative stress, neuroinflammation, ferroptosis, and demyelination. Conversely, Rasd1 overexpression aggravated these changes by elevating the levels of reactive oxygen species (ROS), inflammatory cytokines, MDA, free iron, and NCOA4, as well as contributing to the decrease of the levels of UCP2, GPX4, ferritin, and GSH mechanistically. According to the in vitro study, Rasd1 can induce oligodendrocyte ferroptosis through inhibiting UCP2, increasing reactive oxygen species (ROS), and activating NCOA4-mediated ferritinophagy. CONCLUSIONS: It can be concluded that Rasd1 exerts a modulated role in oligodendrocytes ferroptosis in WMI following SAH.

Establishment and multicenter external validation of a risk prediction model for de novo intracranial aneurysms based on a systematic review and meta-analysis of 19 cohorts.

OBJECTIVE: A de novo intracranial aneurysm (IA) is a second, new IA that develops in patients with IAs distant from where the initial IA was detected. This study aimed to identify risk factors for de novo IA formation and establish and externally validate a multicenter risk prediction model for de novo IAs. METHODS: A systematic review and meta-analysis of existing de novo IA cohorts was conducted to form the derivation cohort. The risk ratios and 95% CIs of each risk factor were calculated. In addition, risk scores included in the model were calculated based on the statistically significant risk factors with their weightings. Then the model was validated in a multicenter external cohort of Chinese patients, and receiver operating characteristic and calibration curves, decision curve analysis, and Kaplan-Meier curves were used to evaluate the model. RESULTS: Nineteen studies with 9351 patients, of whom 304 patients (3.25%) developed de novo IAs, were included in the derivation cohort. These patients developed de novo IAs at 2.5-18.5 years during a total follow-up of 3.3-18.8 years. The statistically significant risk factors were age < 60 years, female sex, smoking history, family history of IAs, multiple IAs at initial diagnosis, and initial IAs in the middle cerebral artery, with risk scores of 4, 5, 2, 6, 3, and 3, respectively. Then, a multicenter external cohort comprising 776 patients, of whom 45 patients (5.80%) developed de novo IAs, was included in the validation cohort. De novo IAs formed in these patients at a mean of 5.25 years during a mean follow-up of 6.19 years. The area under the curve of the model was 0.804, with a sensitivity of 0.667 and specificity of 0.900, at a cutoff value of 13. The calibration curve, decision curve analysis, and Kaplan-Meier curves also indicated good performance of the model. CONCLUSIONS: This prediction model is a convenient and intuitive tool for identifying high-risk patients with de novo IAs. Reasonable use of the model can not only aid in clinical decision-making but also play a positive role in the prevention of aneurysmal subarachnoid hemorrhage to a certain extent.

The Landscape of Biomimetic Nanovesicles in Brain Diseases.

Brain diseases, such as brain tumors, neurodegenerative diseases, cerebrovascular diseases, and brain injuries, are caused by various pathophysiological changes, which pose a serious health threat. Brain disorders are often difficult to treat due to the presence of the blood-brain barrier (BBB). Biomimetic nanovesicles (BNVs), including endogenous extracellular vesicles (EVs) derived from various cells and artificial nanovesicles, possess the ability to penetrate the BBB and thus can be utilized for drug delivery to the brain. BNVs, especially endogenous EVs, are widely distributed in body fluids and usually carry various disease-related signal molecules such as proteins, RNA, and DNA, and may also be analyzed to understand the etiology and pathogenesis of brain diseases. This review covers the exhaustive classification and characterization of BNVs and pathophysiological roles involved in various brain diseases, and emphatically focuses on nanotechnology-integrated BNVs for brain disease theranostics, including various diagnosis strategies and precise therapeutic regulations (e.g., immunity regulation, disordered protein clearance, anti-neuroinflammation, neuroregeneration, angiogenesis, and the gut-brain axis regulation). The remaining challenges and future perspectives regarding the nanotechnology-integrated BNVs for the diagnosis and treatment of brain diseases are also discussed and outlined.

scPlantDB: a comprehensive database for exploring cell types and markers of plant cell atlases.

Recent advancements in single-cell RNA sequencing (scRNA-seq) technology have enabled the comprehensive profiling of gene expression patterns at the single-cell level, offering unprecedented insights into cellular diversity and heterogeneity within plant tissues. In this study, we present a systematic approach to construct a plant single-cell database, scPlantDB, which is publicly available at https://biobigdata.nju.edu.cn/scplantdb. We integrated single-cell transcriptomic profiles from 67 high-quality datasets across 17 plant species, comprising approximately 2.5 million cells. The data underwent rigorous collection, manual curation, strict quality control and standardized processing from public databases. scPlantDB offers interactive visualization of gene expression at the single-cell level, facilitating the exploration of both single-dataset and multiple-dataset analyses. It enables systematic comparison and functional annotation of markers across diverse cell types and species while providing tools to identify and compare cell types based on these markers. In summary, scPlantDB serves as a comprehensive database for investigating cell types and markers within plant cell atlases. It is a valuable resource for the plant research community.

Willis covered stent treatment for internal carotid artery pseudoaneurysm: A meta-analysis of efficacy and safety.

Background: Pseudoaneurysm (PSA) of internal carotid artery is a rare but severe cerebrovascular disease and difficult to repair surgically. A novel medical device called Willis covered stent (WCS) has been created especially for the treatment of complex cerebrovascular diseases. However, the efficacy and safety of WCS therapy for PSA are still debatable. Additional substantial proof is needed. Methods: To find research pertaining to WCS treatment for PSA, a systematic review of literature was conducted in the Medline, Embase, Web of Science, CNKI, Wanfang, and CBM databases. The results comprising the data of intraoperative situation, postoperative situation, and follow-up were then included in a meta-analysis. Results: The criteria were met by 11 noncomparative studies with 152 patients and 157 PSAs. Technical success rate was nearly 100 % (>0.999 (95 % confidence interval (CI), 0.958, 1.000)), complete occlusion rate was 97.8 % (95 % CI, 0.932, 1.000), and side branch occlusion rate was 0.5 % (95 % CI, 0.001, 0.045). The rates of acute in-stent thrombosis (<0.001 (95 % CI, 0.000, 0.013)) and hemorrhage (<0.001 (95 % CI, 0.000, 0.005)) were both less than 0.1 %. In postoperative situation, surgery-related mortality rate was less than 0.1 % (<0.001 (95 % CI, 0.000, 0.005)). The rates of recurrence (<0.001 (95 % CI, 0.000, 0.002)) and parent artery stenosis (<0.001 (95 % CI, 0.000, 0.008)) were both less than 0.1 %, while late in-stent stenosis occurred in 1.3 % (95 % CI, 0.000, 0.053) of patients. In the end, 98.5 % (95 % CI, 0.943, 1.000) of patients had a good outcome. Conclusion: The application of WCS could be effective and safe for PSAs. The findings of this study could serve as a reference for upcoming clinical trials.

Identification of signature genes for renal ischemia‒reperfusion injury based on machine learning and WGCNA.

Background: As an inevitable event after kidney transplantation, ischemia‒reperfusion injury (IRI) can lead to a decrease in kidney transplant success. The search for signature genes of renal ischemia‒reperfusion injury (RIRI) is helpful in improving the diagnosis and guiding clinical treatment. Methods: We first downloaded 3 datasets from the GEO database. Then, differentially expressed genes (DEGs) were identified and applied for functional enrichment analysis. After that, we performed three machine learning methods, including random forest (RF), Lasso regression analysis, and support vector machine recursive feature elimination (SVM-RFE), to further predict candidate genes. WGCNA was also executed to screen candidate genes from DEGs. Then, we took the intersection of candidate genes to obtain the signature genes of RIRI. Receiver operating characteristic (ROC) analysis was conducted to measure the predictive ability of the signature genes. Kaplan‒Meier analysis was used for association analysis between signature genes and graft survival. Verifying the expression of signature genes in the ischemia cell model. Results: A total of 117 DEGs were screened out. Subsequently, RF, Lasso regression analysis, SVM-RFE and WGCNA identified 17, 25, 18 and 74 candidate genes, respectively. Finally, 3 signature genes (DUSP1, FOS, JUN) were screened out through the intersection of candidate genes. ROC analysis suggested that the 3 signature genes could well diagnose and predict RIRI. Kaplan‒Meier analysis indicated that patients with low FOS or JUN expression had a longer OS than those with high FOS or JUN expression. Finally, we validated using the ischemia cell model that compared to the control group, the expression level of JUN increased under hypoxic conditions. Conclusions: Three signature genes (DUSP1, FOS, JUN) offer a good prediction for RIRI outcome and may serve as potential therapeutic targets for RIRI intervention, especially JUN. The prediction of graft survival by FOS and JUN may improve graft survival in patients with RIRI.

Associations between overactive bladder and sleep patterns: a cross-sectional study based on 2007-2014 NHANES.

OBJECTIVES: To determine whether relationship exists between overactive bladder (OAB) and sleep patterns through the cross-sectional study. PATIENTS AND METHODS: Patients from the National Health and Nutrition Examination Survey (NHANES) 2007-2014 were included in this study. Data were extracted through questionnaires, including demographics, dietary and health-related behaviors, body measurements and disease information. Three sleep factors were included to aggregate overall sleep scores, ranging from 0 to 3. A sleep score of 0 to 1, 2 or 3 was expressed as a bad, intermediate or healthy sleep pattern, respectively. The Overactive Bladder Symptom Score (OABSS) scale was applied to quantify the severity of OAB for each participant. Weighted logistic regression models were used to investigate the associations between sleep and OAB. RESULTS: A total of 16,978 participants were enrolled in this study. The relationship between OAB and sleep patterns was statistically significant. After fully adjusting for confounding factors, the OAB risk of patients with intermediate and poor sleep patterns obviously increased by 26% and 38%, respectively, and mild (OR = 1.21, 95% CI [1.03,1.42]), moderate (OR = 1.45, 95% CI [1.27,1.66]) and severe (OR = 1.57, 95% CI [1.18,2.09]) OAB were significantly associated with sleep pattern grouping. The prevalence of OAB is significantly higher in patients with bad sleep patterns, and vice versa. CONCLUSION: This study indicated that there is a positive relationship between OAB and worse sleep-related issues.

Quality control prediction of electrolytic copper using novel hybrid nonlinear analysis algorithm.

Traditional linear regression and neural network models demonstrate suboptimal fit and lower predictive accuracy while the quality of electrolytic copper is estimated. A more dependable and accurate model is essential for these challenges. Notably, the maximum information coefficient was employed initially to discern the non-linear correlation between the nineteen factors influencing electrolytic copper quality and the five quality control indicators. Additionally, the random forest algorithm elucidated the primary factors governing electrolytic copper quality. A hybrid model, integrating particle swarm optimization with least square support vector machine, was devised to predict electrolytic copper quality based on the nineteen factors. Concurrently, a hybrid model combining random forest and relevance vector machine was developed, focusing on primary control factors. The outcomes indicate that the random forest algorithm identified five principal factors governing electrolytic copper quality, corroborated by the non-linear correlation analysis via the maximum information coefficient. The predictive accuracy of the relevance vector machine model, when accounting for all nineteen factors, was comparable to the particle swarm optimization-least square support vector machine model, and surpassed both the conventional linear regression and neural network models. The predictive error for the random forest-relevance vector machine hybrid model was notably less than the sole relevance vector machine model, with the error index being under 5%. The intricate non-linear variation pattern of electrolytic copper quality, influenced by numerous factors, was unveiled. The advanced random forest-relevance vector machine hybrid model circumvents the deficiencies seen in conventional models. The findings furnish valuable insights for electrolytic copper quality management.

The Association between Dietary Sugar Intake and Nephrolithiasis: Results from National Health and Nutrition Examination Survey 2007-2018.

BACKGROUND: Dietary sugar intake is gradually considered a risk factor for many diseases. A sugary diet was positively associated with risk of nephrolithiasis, but the specific relationships remain undefined. OBJECTIVES: To determine associations between risk of nephrolithiasis and dietary sugar intake. METHODS: This cross-sectional study involved 21,590 participants based on the National Health and Nutrition Examination Survey from 2007 to 2018. Amounts of dietary sugar intake (g/d) were the main exposure, including total sugar intake, added sugar intake, and food sources. Associations were analyzed by logistic regression models and restricted cubic splines using complex weighted designs. RESULTS: Weighted mean intake [standard error] of total sugar and added sugar were 111.2 [2.0] g/d and 73.7 [1.9] g/d in participants with nephrolithiasis, respectively. In the fully adjusted regression model, compared to those in quartile 1, the population in quartile 4 of total sugar intake showed a significant risk of nephrolithiasis [odds ratio (OR): 1.23; 95% confidence interval (CI): 1.00-1.51]; OR for added sugar intake was 1.56 (95% CI: 1.25-1.94). The risks of nephrolithiasis increased steadily when total sugar and added sugar intake exceeded ∼150 g/d and 63 g/d in restricted cubic spline analyses, respectively. The highest sugar intake from beverages was associated with an increased risk of nephrolithiasis (OR for total sugar: 1.36; 95% CI: 1.07-1.72; OR for added sugar: 1.37; 95% CI: 1.09-1.73). Added sugar intake from meat, egg, and oil was significantly associated with risk of nephrolithiasis (quartile 4, OR: 1.22; 95% CI: 1.02-1.47), whereas total sugar intake from dairy products was in reverse (quartile 4, OR: 0.67; 95% CI: 0.54-0.82). CONCLUSIONS: Total and added sugar intake, sugar intake from beverages, and added sugar intake from meat, egg, and oil were associated with an increased risk of nephrolithiasis, whereas total sugar intake from dairy products was negatively associated.

A Machine Learning Analysis of Prognostic Genes Associated With Allograft Tolerance After Renal Transplantation.

In this study, we aimed to identify transplantation tolerance (TOL)-related gene signature and use it to predict the different types of renal allograft rejection performances in kidney transplantation. Gene expression data were obtained from the Gene Expression Omnibus (GEO) database, differently expressed genes (DEGs) were performed, and the gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also conducted. The machine learning methods were combined to analyze the feature TOL-related genes and verify their predictive performance. Afterward, the gene expression levels and predictive performances of TOL-related genes were conducted in the context of acute rejection (AR), chronic rejection (CR), and graft loss through heatmap plots and the receiver operating characteristic (ROC) curves, and their respective immune infiltration results were also performed. Furthermore, the TOL-related gene signature for graft survival was conducted to discover gene immune cell enrichment. A total of 25 TOL-related DEGs were founded, and the GO and KEGG results indicated that DEGs mainly enriched in B cell-related functions and pathways. 7 TOL-related gene signature was constructed and performed delightedly in TOL groups and different types of allograft rejection. The immune infiltration analysis suggested that gene signature was correlated with different types of immune cells. The Kaplan-Meier (KM) survival analysis demonstrated that BLNK and MZB1 were the prognostic TOL-related genes. Our study proposed a novel gene signature that may influence TOL in kidney transplantation, providing possible guidance for immunosuppressive therapy in kidney transplant patients.

METTL3-dependent m6A modification mediates bladder remodeling after partial bladder outlet obstruction through CCN2 activation.

AIMS: N6-methyladenosine (m6A) modification is a critical posttranscriptional event in gene regulation. Thus, identifying methyltransferase, demethylase, or m6A binding protein-mediated m6A modifications in cancer or noncancer transcriptomes has become a promising novel strategy for disease therapy development. However, novel insights into m6A modification in partial bladder outlet obstruction (pBOO) and detailed information about the drivers of bladder remodeling remain to be elucidated. Here, we first characterized the m6A modification landscape in pBOO and investigated potential actionable pharmaceutical targets for future therapies. METHODS: We generated an improved animal model of pBOO in SD rats with urethral meatus stricture induced by suturing. Urodynamic investigations and cystometry were carried out to evaluate the physiologic changes elicited by pBOO. Whole-transcriptome sequencing (RNA-seq) and m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq) were subsequently performed to analyze the expression pattern associated with bladder remodeling in pBOO. RESULTS: The cystometric evaluation of bladder function demonstrated obvious increases in pressure-related parameters in the pBOO group. Hematoxylin and eosin staining and Masson's trichrome staining validated the occurrence of bladder remodeling. A global elevation in m6A RNA methylation levels was observed in parallel to a increased expression of METTL3 in the pBOO group. High-throughput sequencing revealed the differences in expression patterns between the pBOO and sham-operated groups. Furthermore, potential m6A-modified genes, including CCN2, may serve as new pharmaceutical targets to reverse bladder remodeling. CONCLUSIONS: Exploring the roles of m6A-modified genes identified as associated with bladder remodeling by integrating RNA-seq and MeRIP-seq data can offer new insights for developing promising treatments for pBOO patients.