Assessing bioavailability risks of heavy metals in polymetallic mining regions: a comprehensive analysis of soils with varied land uses.

To accurately assess the bioavailability risk of heavy metals (HMs) in a representative polymetallic mining region, we undertook an exhaustive analysis of Cu, Pb, Ni, Co, Cd, Zn, Mn, and Cr in soils from diverse land-use types, encompassing agricultural, forest, residential, and mining areas. We employed speciation analysis methods and a modified risk assessment approach to ascertain potential ecological threats posed by the HMs. Our findings reveal that both the total potential ecological risk and the modified bioavailability risks are most pronounced in the soil of the mining area. The modified bioavailability threats are primarily caused by Pb, Ni, Cd, and Co. Although the total potential ecological risk of Cu is high in the local soil, the predominance of its stable forms reduces its mobility, thereby mitigating its detrimental impact on the ecosystem. Additionally, medium modified bioavailability risks were identified in the peripheries of agricultural and forest areas, potentially attributable to geological processes and agricultural activities. Within the urban district, medium risks were observed in residential and mining areas, likely resulting from mining, metallurgy, industrial operations, and traffic-related activities. This study provides critical insights that can assist governmental authorities in devising targeted policies to alleviate health hazards associated with soils in polymetallic mining regions.

Machine learning based androgen receptor regulatory gene-related random forest survival model for precise treatment decision in prostate cancer.

Background: It has been demonstrated that aberrant androgen receptor (AR) signaling contributes to the pathogenesis of prostate cancer (PCa). To date, the most efficacious strategy for the treatment of PCa remains to target the AR signaling axis. However, numerous PCa patients still face the issue of overtreatment or undertreatment. The establishment of a precise risk prediction model is urgently needed to distinguish patients with high-risk and select appropriate treatment modalities. Methods: In this study, a consensus AR regulatory gene-related signature (ARS) was developed by integrating a total of 101 algorithm combinations of 10 machine learning algorithms. We evaluated the value of ARS in predicting patient prognosis and the therapeutic effects of the various treatments. Additionally, we conducted a screening of therapeutic targets and agents for high-risk patients, followed by the verification in vitro and in vivo. Results: ARS was an independent risk factor for biochemical recurrence and distant metastasis in PCa patients. The enhanced and consistent prognostic predictive capability of ARS across various platforms was confirmed when compared with 44 previously published signatures. More importantly, PCa patients in the ARShigh group benefit more from PARP inhibitors and immunotherapy, while chemotherapy, radiotherapy, and AR-targeted therapy are more effective for ARSlow patients. The results of in silico screening suggest that AURKB could potentially serve as a promising therapeutic target for ARShigh patients. Conclusions: Collectively, this prediction model based on AR regulatory genes holds great clinical translational potential to solve the dilemma of treatment choice and identify potential novel therapeutic targets in PCa.

The risk of dyslipidemia on PLHIV associated with different antiretroviral regimens in Huzhou.

BACKGROUND: Dyslipidemia is increasingly common in people living with HIV (PLHIV), thereby increasing the risk of cardiovascular events and diminishing the quality of life for these individuals. The study of blood lipid metabolism of PLHIV has great clinical significance in predicting the risk of cardiovascular disease. Therefore, this study aims to examine the blood lipid metabolism status of HIV-infected patients in Huzhou before and after receiving highly active antiretroviral therapy (HAART) and to explore the impact of different HAART regimens on dyslipidemia. METHOD: PLHIV confirmed in Huzhou from June 2010 to June 2022 was included. The baseline characteristics and clinical data during the follow-up period were collected, including some blood lipid indicators (total cholesterol and triglycerides) and HAART regimens. A multivariate logistic regression model and the generalized estimating equation model were used to analyze the independent effects of treatment regimens on the risk of dyslipidemia. RESULT: The overall prevalence of dyslipidemia among PLHIV after HAART was 70.11%. PLHIV receiving lamivudine (3TC) + efavirenz (EFV) + zidovudine (AZT) had a higher prevalence of dyslipidemia compared to those receiving 3TC+EFV+tenofovir disoproxil fumarate (TDF). In a logistic analysis adjusted for important covariates such as BMI, age, diabetes status, etc., we found that the risks of dyslipidemia were higher with 3TC+EFV+AZT (dyslipidemia: odds ratio [OR] = 2.09, 95% confidence interval [Cl]: 1.28-3.41; TG ≥1.7: OR = 2.40, 95%Cl:1.50-3.84) than with 3TC+EFV+TDF. Furthermore, on PLHIV that was matched 1:1 by the HAART regimens, the results of the generalized estimation equation again showed that 3TC+EFV+AZT (TG ≥1.7: OR = 1.84, 95%Cl: 1.10-3.07) is higher for the risk of marginal elevations of TG than 3TC+EFV+TDF. CONCLUSION: The prevalence of dyslipidemia varies according to different antiretroviral regimens. Using both horizontal and longitudinal data, we have repeatedly demonstrated that AZT has a more adverse effect on blood lipids than TDF from two perspectives. Therefore, we recommend caution in using the 3TC+EFV+AZT regimen for people at clinical risk of co-occurring cardiovascular disease.

Determinants of carbon emission: A multiple scale decomposition of Gansu Province.

China, being the largest contributor to total carbon emissions, still has a long way to go in energy conservation and emission reduction. Employing the structural decomposition analysis (SDA) method and using input-output table data, this study examines the evolution of carbon emissions resulting from energy consumption in Gansu Province in China over the period 2007 to 2017. By exploring carbon emission driving factors and identifying key final demand and sectors for carbon emissions, Gansu province can formulate more effective emission reduction policies that can balance economic development and carbon emission control. The key findings are as follows: 1) Regarding the driving factors, both the energy intensity effect and the demand sector structure effect emerge as the main contributors to emission reduction. Conversely, the total demand effect and the input-output structure effect predominantly led to emission increase. 2) In terms of each final demand, urban residents' consumption, rural residents' consumption and outflow represent the primary categories contributing to increased emissions. 3) The sectors experiencing the most significant decline in carbon emissions and carbon intensity are Electricity, Heat Production and Supply Industry, while Metal Smelting and Rolling Processing Industry as well as Construction Industry are the primary contributors to increasing emissions. Consequently, to achieve the carbon neutrality goal, Gansu governments should consider all these factors and propose mitigation policies in light of the local realities.

Molecular Regulation of Shoot Architecture in Soybean.

Soybean (Glycine max [L.] Merr.) serves as a major source of protein and oil for humans and animals. Shoot architecture, the spatial arrangement of a plant's above-ground organs, strongly affects crop yield and is therefore a critical agronomic trait. Unlike wheat and rice crops that have greatly benefitted from the Green Revolution, soybean yield has not changed significantly in the past six decades owing to its unique shoot architecture. Soybean is a pod-bearing crop with pods adhered to the nodes, and variation in shoot architecture traits, such as plant height, node number, branch number and number of seeds per pod, directly affects the number of pods and seeds per plant, thereby determining yield. In this review, we summarize the relationship between soybean yield and these major components of shoot architecture. We also describe the latest advances in identifying the genes and molecular mechanisms underlying soybean shoot architecture and discuss possible directions and approaches for breeding new soybean varieties with ideal shoot architecture and improved yield.

Genome-wide association study of bacterial blight resistance in soybean.

Bacterial blight caused by Pseudomonas syringae pv. glycines (Psg) is a widespread foliar disease. Although four Resistance to Pseudomonas syringae pv. glycinea (Rpg) 1 ~ 4 (Rpg1~4) genes that have been observed to segregate in a Mendelian pattern have been reported to confer resistance to Psg in soybean, the genetic basis of quantitative resistance to bacterial blight in soybean remains unclear. In the present study, the Psg resistance of two soybean association panels consisting of 573 and 213 lines, respectively, were phenotyped in multiple environments in 2014 - 2016. Genome-wide association study (GWAS) were performed using 2 models FarmCPU and BLINK to identify Psg resistance loci. A total of 40 soybean varieties with high level of Psg resistance were identified, and 14 quantitative trait loci (QTLs) were detected on 12 soybean chromosomes. These QTLs were identified for the first time. The majority of the QTLs were only detected in one or the other association panels, while qRPG-18-1 was detected in both association panels for at least one growing season. A total of 46 candidate Psg resistance genes were identified from the qRpg_13_1, qRPG-15-1, and qRPG-18-1 loci based on gene function annotation. In addition, we found the genomic region covering rpg1-b and rpg1-r harbored the synteny with a genomic region on chromosome 15, and identified 16 nucleotide binding site - leucine-rich repeat (NBS-LRR) genes as the candidate Psg resistance genes from the synteny blocks. This study provides new information for dissecting the genetic control of Psg resistance in soybean.

ATP synthase subunit ATP5B interacts with TGEV Nsp2 and acts as a negative regulator of TGEV replication.

Coronavirus nonstructural protein 2 (Nsp2) is regarded as a virulence determinant and plays a critical role in virus replication, and innate immunity. Screening and identifying host cell proteins that interact with viral proteins is an effective way to reveal the functions of viral proteins. In this study, the host proteins that interacted with transmissible gastroenteritis virus (TGEV) Nsp2 were identified using immunoprecipitation combined with LC-MS/MS. 77 host cell proteins were identified as putative Nsp2 interaction host cell proteins and a protein-protein interaction (PPI) was constructed. The identified proteins were found to be associated with various subcellular locations and functional categories through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. It is hypothesized that the host cell proteins interacting with TGEV Nsp2 are mainly involved in the formation of the cytoplasmic translation initiation complex, mRNA binding, ribosomes, and proteasomes. Among these, the ATP5B, a core subunit of the mitochondrial ATP synthase was further studied. The Coimmunoprecipitation (Co-IP) and indirect immunofluorescence (IFA) results confirmed that TGEV Nsp2 interacted with ATP5B. Furthermore, the downregulation of ATP5B expression was found to promote TGEV replication, suggesting that ATP5B might function as a negative regulator of TGEV replication. Collectively, our results offer additional insights into the functions of Nsp2 and provide a novel antiviral target against TGEV.

PDIA3 defines a novel subset of adipose macrophages to exacerbate the development of obesity and metabolic disorders.

Adipose tissue macrophages (ATMs) play important roles in maintaining adipose tissue homeostasis and orchestrating metabolic inflammation. Given the extensive functional heterogeneity and phenotypic plasticity of ATMs, identification of the authentically pathogenic ATM subpopulation under obese setting is thus necessitated. Herein, we performed single-nucleus RNA sequencing (snRNA-seq) and unraveled a unique maladaptive ATM subpopulation defined as ATF4hiPDIA3hiACSL4hiCCL2hi inflammatory and metabolically activated macrophages (iMAMs), in which PDIA3 is required for the maintenance of their migratory and pro-inflammatory properties. Mechanistically, ATF4 serves as a metabolic stress sensor to transcribe PDIA3, which then imposes a redox control on RhoA activity and strengthens the pro-inflammatory and migratory properties of iMAMs through RhoA-YAP signaling. Administration of Pdia3 small interfering RNA (siRNA)-loaded liposomes effectively repressed adipose inflammation and high-fat diet (HFD)-induced obesity. Together, our data support that strategies aimed at targeting iMAMs by suppressing PDIA3 expression or activity could be a viable approach against obesity and metabolic disorders in clinical settings.

Construction and clinical significance of prognostic risk markers based on cancer driver genes in lung adenocarcinoma.

BACKGROUND: Cancer driver genes (CDGs) have been reported as key factors influencing the progression of lung adenocarcinoma (LUAD). However, the role of CDGs in LUAD prognosis has not been fully elucidated. METHODS: LUAD transcriptome data and CDG-related data were obtained from public databases and literature. Differentially expressed CDGs (DE-CDGs) greatly associated with LUAD survival (P < 0.05) were identified to establish a prognostic model. In addition, immune analysis of high-risk (HR) and low-risk (LR) groups was conducted by utilizing the CIBERSORT and single sample gene set enrichment analysis (ssGSEA) algorithms to assess immune differences. Subsequently, mutation analysis was conducted using maftools. Finally, candidate drugs were identified using the CellMiner database. RESULTS: 40 DE-CDGs significantly associated with LUAD survival and 11 DE-CDGs associated with prognosis were identified through screening. Regression analysis revealed that risk score can independently predict LUAD prognosis (P < 0.05). Immune landscape analysis revealed that compared to the HR group, the LR group had higher immune scores and high infiltration of various immune cells such as follicular helper B cells and T cells. Mutation landscape analysis demonstrated that missense mutation was the most common mutation type in both risk groups. Drug prediction analysis revealed strong correlations of fulvestrant, S-63845, sapacitabine, lomustine, BLU-667, SR16157, motesanib, AZD-9496, XK-469, dimethylfasudil, P-529, and imatinib with the model genes, suggesting their potential as candidate drugs targeting the model genes. CONCLUSION: This study identified 11 effective biomarkers, DE-CDGs, which can predict LUAD prognosis and explored the biological significance of CDGs in LUAD prognosis, immunotherapy, and treatment.

Developing Patient-Derived 3D-Bioprinting models of pancreatic cancer.

INTRODUCTION: Pancreatic cancer (PC) remains a challenging malignancy, and adjuvant chemotherapy is critical in improving patient survival post-surgery. However, the intrinsic heterogeneity of PC necessitates personalized treatment strategies, highlighting the need for reliable preclinical models. OBJECTIVES: This study aimed to develop novel patient-derived preclinical PC models using three-dimensional bioprinting (3DP) technology. METHODS: Patient-derived PC models were established using 3DP technology. Genomic and histological analyses were performed to characterize these models and compare them with corresponding patient tissues. Chemotherapeutic drug sensitivity tests were conducted on the PC 3DP models, and correlations with clinical outcomes were analyzed. RESULTS: The study successfully established PC 3DP models with a modeling success rate of 86.96%. These models preserved genomic and histological features consistent with patient tissues. Drug sensitivity testing revealed significant heterogeneity among PC 3DP models, mirroring clinical variability, and potential correlations with clinical outcomes. CONCLUSION: The PC 3DP models demonstrated their utility as reliable preclinical tools, retaining key genomic and histological characteristics. Importantly, drug sensitivity profiles in these models showed potential correlations with clinical outcomes, indicating their promise in customizing treatment strategies and predicting patient prognoses. Further validation with larger patient cohorts is warranted to confirm their potential clinical utility.

Allergo-immunopathology mechanism of thymol-inhibiting airway remodeling in asthmatic mice by regulating TGF-ß/Smad3 pathway.

Allergic asthma is an important public health problem and is a complicated respiratory sickness that is characterized by bronchial inflammation, bronchoconstriction, and breathlessness. Asthma is orchestrated by type 2 immune response and remodeling is one of the important outputted problem in chronic asthma. Thymol is a naturally occurring monocyclic phenolic, it has a series of biological properties, and its immunomodulatory and anti-remodeling effects on allergic asthma were evaluated. The OVA-LPS-induced asthmatic mice were treated with thymol. Methacholine challenge test, eosinophil count, and levels of IL-4, IL-5, IL-13, and IL-33 in bronchoalveolar lavage fluid, total and OVA-specific IgE levels in serum, remodeling factors, gene expression of TGF-ß, Smad2, Smad3, and lung histopathology were done. Treatment with thymol could control AHR, eosinophil percentage levels of Th2 cytokines and Igs, remodeling factors, expression of TGF-ß, Smad2 and Smad3 genes, inflammation, goblet cell hyperplasia, and mucus production in asthmatic mice. Thymol can control asthma pathogens and related remodeling and fibrosis bio-factors and can be a potential treatment of asthma.

Magnetic solid-phase extraction coupled with LC-MS/MS methods for the simple extraction and rapid determination of sugammadex in human plasma.

Sugammadex (SUG) is a novel antagonist of neuromuscular blocking agents (NMBAs). The NMBA rocuronium is usually employed to obtain better surgical conditions in kidney transplant. Nevertheless, rocuronium has several disadvantages, such as an increased risk of pulmonary complications. Thus, SUG is vital to kidney-transplant surgery. However, because SUG is excreted by the kidneys in prototypes, the pharmacokinetics (PK) may be affected in patients with renal impairment. We developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to monitor SUG in plasma samples to investigate the PK of SUG in kidney-transplant patients. Due to the complexity and limitation of other methods of sample preparation, magnetic solid-phase extraction (MSPE) was adopted to purify samples. Chromatographic separation was obtained using a reversed-phase Polaris® C18 column and gradient elution with 0.1% formic acid (FA) in water as phase A and in methanol (MeOH) as phase B as mobile phases. The transitions 999.7 → 963.9 (m/z) and 1055.7 → 1012.2 (m/z) were used to quantify SUG and ORG26265, respectively, under negative electrospray ionization. A linear calibration curve was achieved in concentrations varying from 100 to 10 000 ng mL-1. The acceptable accuracy varied from 95.7% to 106.4%, and intra- and inter-precision did not exceed 15% (20% at the lower limit of quantitation (LLOQ)). The matrix effect, stability, dilution integrity, and carry-over were validated. This method was applied successfully for the PK study of 13 recipients and 12 donors of kidney transplant after intravenous injection of SUG (2 mL per kg bodyweight).

Local TSH/TSHR signaling promotes CD8+ T cell exhaustion and immune evasion in colorectal carcinoma.

BACKGROUND: Dysfunction of CD8+ T cells in the tumor microenvironment (TME) contributes to tumor immune escape and immunotherapy tolerance. The effects of hormones such as leptin, steroid hormones, and glucocorticoids on T cell function have been reported previously. However, the mechanism underlying thyroid-stimulating hormone (TSH)/thyroid-stimulating hormone receptor (TSHR) signaling in CD8+ T cell exhaustion and tumor immune evasion remain poorly understood. This study was aimed at investigating the effects of TSH/TSHR signaling on the function of CD8+ T cells and immune evasion in colorectal cancer (CRC). METHODS: TSHR expression levels in CD8+ T cells were assessed with immunofluorescence and flow cytometry. Functional investigations involved manipulation of TSHR expression in cellular and mouse models to study its role in CD8+ T cells. Mechanistic insights were mainly gained through RNA-sequencing, Western blotting, chromatin immunoprecipitation and luciferase activity assay. Immunofluorescence, flow cytometry and Western blotting were used to investigate the source of TSH and TSHR in CRC tissues. RESULTS: TSHR was highly expressed in cancer cells and CD8+ T cells in CRC tissues. TSH/TSHR signaling was identified as the intrinsic pathway promoting CD8+ T cell exhaustion. Conditional deletion of TSHR in CD8+ tumor-infiltrating lymphocytes (TILs) improved effector differentiation and suppressed the expression of immune checkpoint receptors such as programmed cell death 1 (PD-1) and hepatitis A virus cellular receptor 2 (HAVCR2 or TIM3) through the protein kinase A (PKA)/cAMP-response element binding protein (CREB) signaling pathway. CRC cells secreted TSHR via exosomes to increase the TSHR level in CD8+ T cells, resulting in immunosuppression in the TME. Myeloid-derived suppressor cells (MDSCs) was the main source of TSH within the TME. Low expression of TSHR in CRC was a predictor of immunotherapy response. CONCLUSIONS: The present findings highlighted the role of endogenous TSH/TSHR signaling in CD8+ T cell exhaustion and immune evasion in CRC. TSHR may be suitable as a predictive and therapeutic biomarker in CRC immunotherapy.

Corrigendum to 'CRISPR/Cas9 system and its applications in nervous system diseases' [Genes & Diseases 11 (2024) 675-686].

[This corrects the article DOI: 10.1016/j.gendis.2023.03.017.].

Glucose metabolite methylglyoxal induces vascular endothelial cell pyroptosis via NLRP3 inflammasome activation and oxidative stress in vitro and in vivo.

Methylglyoxal (MGO), a reactive dicarbonyl metabolite of glucose, plays a prominent role in the pathogenesis of diabetes and vascular complications. Our previous studies have shown that MGO is associated with increased oxidative stress, inflammatory responses and apoptotic cell death in endothelial cells (ECs). Pyroptosis is a novel form of inflammatory caspase-1-dependent programmed cell death that is closely associated with the activation of the NOD-like receptor 3 (NLRP3) inflammasome. Recent studies have shown that sulforaphane (SFN) can inhibit pyroptosis, but the effects and underlying mechanisms by which SFN affects MGO-induced pyroptosis in endothelial cells have not been determined. Here, we found that SFN prevented MGO-induced pyroptosis by suppressing oxidative stress and inflammation in vitro and in vivo. Our results revealed that SFN dose-dependently prevented MGO-induced HUVEC pyroptosis, inhibited pyroptosis-associated biochemical changes, and attenuated MGO-induced morphological alterations in mitochondria. SFN pretreatment significantly suppressed MGO-induced ROS production and the inflammatory response by inhibiting the NLRP3 inflammasome (NLRP3, ASC, and caspase-1) signaling pathway by activating Nrf2/HO-1 signaling. Similar results were obtained in vivo, and we demonstrated that SFN prevented MGO-induced oxidative damage, inflammation and pyroptosis by reversing the MGO-induced downregulation of the NLRP3 signaling pathway through the upregulation of Nrf2. Additionally, an Nrf2 inhibitor (ML385) noticeably attenuated the protective effects of SFN on MGO-induced pyroptosis and ROS generation by inhibiting the Nrf2/HO-1 signaling pathway, and a ROS scavenger (NAC) and a permeability transition pore inhibitor (CsA) completely reversed these effects. Moreover, NLRP3 inhibitor (MCC950) and caspase-1 inhibitor (VX765) further reduced pyroptosis in endothelial cells that were pretreated with SFN. Collectively, these findings broaden our understanding of the mechanism by which SFN inhibits pyroptosis induced by MGO and suggests important implications for the potential use of SFN in the treatment of vascular diseases.

Application of machine learning techniques in the diagnosis of endometriosis.

OBJECTIVE: The aim of this study is to assess the use of machine learning methodologies in the diagnosis of endometriosis (EM). METHODS: This study included a total of 106 patients with EM and 203 patients with non-EM conditions (like simple cysts and simple uterine fibroids), all admitted to the Shunyi Women's and Children's Hospital of Beijing Children's Hospital between January 2017 and September 2022. All participants were free of comorbidities and their diagnoses were confirmed via postoperative pathology. Comparative analysis was conducted between the EM and non-EM groups. Baseline data were assessed, including white blood cell count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, mean platelet volume, hemoglobin, carbohydrate antigen 125 (CA125), carbohydrate antigen 199, coagulation parameters, and other serologic indicators. An optimal predictive model was developed using an artificial intelligence algorithm to determine the presence of EM. The objective is to provide new insights for the clinical diagnosis and treatment of EM. RESULTS: The random forest algorithm demonstrated superior performance when compared to decision trees, LogitBoost, artificial neural networks, naïve Bayes, support vector machines, and linear regression in machine learning methods. Combining CA125 with the NLR yielded a better prediction of EM than using CA125 alone when applying the random forest algorithm. The accuracy of predicting EM with CA125 combined with NLR was 78.16%, with a sensitivity of 86.21% and an area under the curve (AUC) of 0.85 (P < 0.05). In contrast, using CA125 alone resulted in an EM prediction accuracy of 75.8%, with a sensitivity of 79.3% and an AUC of 0.82 (P < 0.05). CONCLUSION: The diagnostic value of serum CA125 combined with the NLR for EM is higher than that of serum CA125 alone. This finding indicates that NLR could serve as a new supplementary biomarker along with serum CA125 in the diagnosis of EM.

Characteristics of a Novel Zearalenone Lactone Hydrolase ZHRnZ and Its Thermostability Modification.

Zearalenone (ZEN) is a toxic secondary metabolite produced by the Fusarium fungi, which widely contaminates grains, food, and feed, causing health hazards for humans and animals. Therefore, it is essential to find effective ZEN detoxification methods. Enzymatic degradation of ZEN is believed to be an eco-friendly detoxification strategy, specifically thermostable ZEN degradation enzymes are needed in the food and feed industry. In this study, a novel ZEN lactone hydrolase ZHRnZ from Rosellinia necatrix was discovered using bioinformatic and molecular docking technology. The recombinant ZHRnZ showed the best activity at pH 9.0 and 45 °C with more than 90% degradation for ZEN, α-zearalenol (α-ZOL), ß-zearalenol (ß-ZOL) and α-zearalanol (α-ZAL) after incubation for 15 min. We obtained 10 mutants with improved thermostability by single point mutation technology. Among them, mutants E122Q and E122R showed the best performance, which retained more than 30% of their initial activity at 50 °C for 2 min, and approximately 10% of their initial activity at 60 °C for 1 min. The enzymatic kinetic study showed that the catalytic efficiency of E122R was 1.3 times higher than that of the wild-type (WT). Comprehensive consideration suggests that mutant E122R is a promising hydrolase to detoxify ZEN in food and feed.

Katanin regulatory subunit B1 (KATNB1) regulates BTB dynamics through changes in cytoskeletal organization.

In this study, we have explored the role of the KATNB1 gene, a microtubule-severing protein, in the seminiferous epithelium of the rat testis. Our data have shown that KATNB1 expressed in rat brain, testes, and Sertoli cells. KATNB1 was found to co-localize with α-tubulin showing a unique stage-specific distribution across the seminiferous epithelium. Knockdown of KATNB1 by RNAi led to significant disruption of the tight junction (TJ) permeability barrier function in primary Sertoli cells cultured in vitro with an established functional TJ-barrier, as well as perturbations in the microtubule and actin cytoskeleton organization. The disruption in these cytoskeletal structures, in turn, led to improper distribution of TJ and basal ES proteins essential for maintaining the Sertoli TJ function. More importantly, overexpression of KATNB1 in the testis in vivo was found to block cadmium-induced blood-testis barrier (BTB) disruption and testis injury. KATNB1 exerted its promoting effects on BTB and spermatogenesis through corrective spatiotemporal expression of actin- and microtubule-based regulatory proteins by maintaining the proper organization of cytoskeletons in the testis, illustrating its plausible therapeutic implication. In summary, Katanin regulatory subunit B1 (KATNB1) plays a crucial role in BTB and spermatogenesis through its effects on the actin- and microtubule-based cytoskeletons in Sertoli cells and testis, providing important insights into male reproductive biology.

Twenty-Four-Hour Post-Thrombolysis NIHSS Score As the Strongest Prognostic Predictor After Acute Ischemic Stroke: ENCHANTED Study.

BACKGROUND: This study was conducted to determine optimal predictive ability of National Institutes of Health Stroke Scale (NIHSS) measurements at baseline, 24 hours, and change from baseline to 24 hours after thrombolysis on functional recovery in patients with acute ischemic stroke who participated in the ENCHANTED (Enhanced Control of Hypertension and Thrombolysis Stroke Study). METHODS AND RESULTS: ENCHANTED was an international, multicenter, 2×2 quasifactorial, prospective, randomized open trial of low-dose versus standard-dose intravenous alteplase and intensive versus guideline-recommended blood pressure lowering in thrombolysis-eligible patients with acute ischemic stroke. Absolute (baseline minus 24 hours) and percentage (absolute change/baseline × 100) changes in NIHSS scores were calculated. Receiver operating characteristic curve analyses assessed performance of different NIHSS measurements on 90-day favorable functional recovery (modified Rankin Scale [mRS] score 0-2) and excellent functional recovery (mRS score 0-1). Youden index was used to identify optimal predictor cutoff points. A total of 4410 patients in the ENCHANTED trial were enrolled. The 24-hour NIHSS score had the highest discriminative ability for predicting favorable 90-day functional recovery (mRS score 0-2; area under the curve 0.866 versus 0.755, 0.689, 0.764; P<0.001) than baseline, absolute, and percentage change of NIHSS score, respectively. The optimal cutoff point of 24-hour NIHSS score for predicting favorable functional recovery was ≤4 (sensitivity 66.5%, specificity 87.1%, adjusted odds ratio, 9.44 [95% CI, 7.77-11.48]). The 24-hour NIHSS score (≤3) was the best predictor of 90-day excellent functional recovery (mRS score 0-1). Findings were consistent across subgroups, including sex, race, baseline NIHSS score, stroke subtype, and age. CONCLUSIONS: In thrombolysis-eligible patients with acute ischemic stroke, 24-hour NIHSS score (optimal cutpoint of 4) is the strongest predictor of 90-day functional recovery over baseline and early change of NIHSS score. REGISTRATION: URL: https://clinicaltrials.gov. Unique Identifier: NCT01422616.

Bifunctional ArsI Dioxygenase from Acidovorax sp. ST3 with Both Methylarsenite [MAs(III)] Demethylation and MAs(III) Oxidation Activities.

Methylated arsenicals, including highly toxic species, such as methylarsenite [MAs(III)], are pervasive in the environment. Certain microorganisms possess the ability to detoxify MAs(III) by ArsI-catalyzed demethylation. Here, we characterize a bifunctional enzyme encoded by the arsI gene from Acidovorax sp. ST3, which can detoxify MAs(III) through both the demethylation and oxidation pathways. Deletion of the 22 C-terminal amino acids of ArsI increased its demethylation activity while reducing the oxidation activity. Further deletion of 44 C-terminal residues enhanced the MAs(III) demethylation activity. ArsI has four vicinal cysteine pairs, with the first pair being necessary for MAs(III) demethylation, while at least one of the other three pairs contributes to MAs(III) oxidation. Molecular modeling and site-directed mutagenesis indicated that one of the C-terminal vicinal cysteine pairs is involved in modulating the switch between oxidase and demethylase activity. These findings underscore the critical role of the C-terminal region in modulating the enzymatic activities of ArsI, particularly in MAs(III) demethylation. This research reveals the structure-function relationship of the ArsI enzyme and advances our understanding of the MAs(III) metabolism in bacteria.