Herb-resistant UPEC strains have different biofilm formation abilities and different expression of certain biofilm related genes

Background: The mechanisms and patterns of drug resistances of E. coli strains that cause uncomplicated urinary tract infections (UTIs) vary considerably. The emerging herbresistance of uropathogenic Escherichia coli (UPEC) has been a serious health problem, yet with unknown underlying mechanisms.Methods: To explore the potential herb-resistance mechanisms of E. coli strains that cause uncomplicated UTIs, three clinically isolated herb-resistant UPEC strains (1351, 4996, 5028) were analyzed for their abilities to form biofilms and the expressions of the pga ABCD and luxS genes.Results: We found that the expression of pgaA and pgaB are very different between 1351 and 5028, and the loss-offunction of luxS in 4996 has impact on biofilm formation.Conclusions: 1. Herb-resistance of the strains is related to their abilities of biofilm formation. 2. Biofilm formation capabilities of herb-resistant strains show different responses to the presence of glucose. 3. luxS encoded AI-2 is not essential for biofilm formation in this strain but may help with more biofilm formation.Keywords: Herb-resistance; Biofilm formation; Uropathogenic Escherichia coli (UPEC); pga ABCD; lux

Bus Travel Time Deviation Analysis Using Automatic Vehicle Location Data and Structural Equation Modeling

To investigate the influences of causes of unreliability and bus schedule recovery phenomenon on microscopic segment-level travel time variance, this study adopts Structural Equation Modeling (SEM) to specify, estimate, and measure the theoretical proposed models. The SEM model establishes and verifies hypotheses for interrelationships among travel time deviations, departure delays, segment lengths, dwell times, and number of traffic signals and access connections. The finally accepted model demonstrates excellent fitness. Most of the hypotheses are supported by the sample dataset from bus Automatic Vehicle Location system. The SEM model confirms the bus schedule recovery phenomenon. The departure delays at bus terminals and upstream travel time deviations indeed have negative impacts on travel time fluctuation of buses en route. Meanwhile, the segment length directly and negatively impacts travel time variability and inversely positively contributes to the schedule recovery process; this exogenous variable also indirectly and positively influences travel times through the existence of signalized intersections and access connections. This study offers a rational approach to analyzing travel time deviation feature. The SEM model structure and estimation results facilitate the understanding of bus service performance characteristics and provide several implications for bus service planning, management, and operation

HERB-RESISTANT UPEC STRAINS HAVE DIFFERENT BIOFILM FORMATION ABILITIES AND DIFFERENT EXPRESSION OF CERTAIN BIOFILM RELATED GENES

Background: The mechanisms and patterns of drug resistances of E. coli strains that cause uncomplicated urinary tract infections (UTIs) vary considerably. The emerging herbresistance of uropathogenic Escherichia coli (UPEC) has been a serious health problem, yet with unknown underlying mechanisms. Methods: To explore the potential herb-resistance mechanisms of E. coli strains that cause uncomplicated UTIs, three clinically isolated herb-resistant UPEC strains (1351, 4996, 5028) were analyzed for their abilities to form biofilms and the expressions of the pga ABCD and luxS genes. Results: We found that the expression of pgaA and pgaB are very different between 1351 and 5028, and the loss-offunction of luxS in 4996 has impact on biofilm formation. Conclusions: 1. Herb-resistance of the strains is related to their abilities of biofilm formation. 2. Biofilm formation capabilities of herb-resistant strains show different responses to the presence of glucose. 3. luxS encoded AI-2 is not essential for biofilm formation in this strain but may help with more biofilm formation

MTR4 drives liver tumorigenesis by promoting cancer metabolic switch through alternative splicing.

The metabolic switch from oxidative phosphorylation to glycolysis is required for tumorigenesis in order to provide cancer cells with energy and substrates of biosynthesis. Therefore, it is important to elucidate mechanisms controlling the cancer metabolic switch. MTR4 is a RNA helicase associated with a nuclear exosome that plays key roles in RNA processing and surveillance. We demonstrate that MTR4 is frequently overexpressed in hepatocellular carcinoma (HCC) and is an independent diagnostic marker predicting the poor prognosis of HCC patients. MTR4 drives cancer metabolism by ensuring correct alternative splicing of pre-mRNAs of critical glycolytic genes such as GLUT1 and PKM2. c-Myc binds to the promoter of the MTR4 gene and is important for MTR4 expression in HCC cells, indicating that MTR4 is a mediator of the functions of c-Myc in cancer metabolism. These findings reveal important roles of MTR4 in the cancer metabolic switch and present MTR4 as a promising therapeutic target for treating HCC

IL-22+CD4+ T Cells Promote Colorectal Cancer Stemness via STAT3 Transcription Factor Activation and Induction of the Methyltransferase DOT1L

SummaryLittle is known about how the immune system impacts human colorectal cancer invasiveness and stemness. Here we detected interleukin-22 (IL-22) in patient colorectal cancer tissues that was produced predominantly by CD4+ T cells. In a mouse model, migration of these cells into the colon cancer microenvironment required the chemokine receptor CCR6 and its ligand CCL20. IL-22 acted on cancer cells to promote activation of the transcription factor STAT3 and expression of the histone 3 lysine 79 (H3K79) methytransferase DOT1L. The DOT1L complex induced the core stem cell genes NANOG, SOX2, and Pou5F1, resulting in increased cancer stemness and tumorigenic potential. Furthermore, high DOT1L expression and H3K79me2 in colorectal cancer tissues was a predictor of poor patient survival. Thus, IL-22+ cells promote colon cancer stemness via regulation of stemness genes that negatively affects patient outcome. Efforts to target this network might be a strategy in treating colorectal cancer patients

Construction and validation of a musculoskeletal disease risk prediction model for underground coal miners

ObjectiveTo understand the prevalence among underground coal miners of musculoskeletal disorders (MSDs), analyze the risk factors affecting MSDs, and develop and validate a risk prediction model for the development of MSDs.Materials and methodsMSD questionnaires were used to investigate the prevalence of work-related musculoskeletal disorders among 860 underground coal miners in Xinjiang. The Chinese versions of the Effort-Reward Imbalance Questionnaire (ERI), the Burnout Scale (MBI), and the Self-Rating Depression Inventory (SDS) were used to investigate the occupational mental health status of underground coal miners. The R4.1.3 software cart installation package was applied to randomly divide the study subjects into a 1:1 training set and validation set, screen independent predictors using single- and multi-factor regression analysis, and draw personalized nomogram graph prediction models based on regression coefficients. Subject work characteristic (ROC) curves, calibration (Calibrate) curves, and decision curves (DCA) were used to analyze the predictive value of each variable on MSDs and the net benefit.Results(1) The prevalence of MSDs was 55.3%, 51.2%, and 41.9% since joining the workforce, in the past year, and in the past week, respectively; the highest prevalence was in the lower back (45.8% vs. 38.8% vs. 33.7%) and the lowest prevalence was in the hips and buttocks (13.3% vs. 11.4% vs. 9.1%) under different periods. (2) Underground coal miners: the mean total scores of occupational stress, burnout, and depression were 1.55 ± 0.64, 51.52 ± 11.53, and 13.83 ± 14.27, respectively. (3) Univariate regression revealed a higher prevalence of MSDs in those older than 45 years (49.5%), length of service > 15 years (56.4%), annual income <$60,000 (79.1$60,000 (OR = 1.742, 95% CI: 1.100–2.759), and severe burnout (OR = 0.284, 95% CI: 0.109–0.739), and that these were independent predictors of the occurrence of MSDs among workers in underground coal mine operations (p <  0.05). (5) The areas under the ROC curve for the training and validation sets were 0.665 (95% CI: 0.615–0.716) and 0.630 (95% CI: 0.578–0.682), respectively, indicating that the model has good predictive ability; the calibration plots showed good agreement between the predicted and actual prevalence of the model; and the DCA curves suggested that the predictive value of this nomogram model for MSDs was good.ConclusionThe prevalence of MSDs among workers working underground in coal mines was high, and the constructed nomogram showed good discriminatory ability and optimal accuracy

Cumulative Genetic Score and C9orf72 Repeat Status Independently Contribute to Amyotrophic Lateral Sclerosis Risk in 2 Case-Control Studies

[Background and Objectives] Most patients with amyotrophic lateral sclerosis (ALS) lack a monogenic mutation. This study evaluates ALS cumulative genetic risk in an independent Michigan and Spanish replication cohort using polygenic scores.[Methods] Participant samples from University of Michigan were genotyped and assayed for the chromosome 9 open reading frame 72 hexanucleotide expansion. Final cohort size was 219 ALS and 223 healthy controls after genotyping and participant filtering. Polygenic scores excluding the C9 region were generated using an independent ALS genome-wide association study (20,806 cases, 59,804 controls). Adjusted logistic regression and receiver operating characteristic curves evaluated the association and classification between polygenic scores and ALS status, respectively. Population attributable fractions and pathway analyses were conducted. An independent Spanish study sample (548 cases, 2,756 controls) was used for replication.[Results] Polygenic scores constructed from 275 single-nucleotide variation (SNV) had the best model fit in the Michigan cohort. An SD increase in ALS polygenic score associated with 1.28 (95% CI 1.04–1.57) times higher odds of ALS with area under the curve of 0.663 vs a model without the ALS polygenic score (p value = 1 × 10−6). The population attributable fraction of the highest 20th percentile of ALS polygenic scores, relative to the lowest 80th percentile, was 4.1% of ALS cases. Genes annotated to this polygenic score enriched for important ALS pathomechanisms. Meta-analysis with the Spanish study, using a harmonized 132 single nucleotide variation polygenic score, yielded similar logistic regression findings (odds ratio: 1.13, 95% CI 1.04–1.23).[Discussion] ALS polygenic scores can account for cumulative genetic risk in populations and reflect disease-relevant pathways. If further validated, this polygenic score will inform future ALS risk models.National ALS Registry/CDC/ATSDR (1R01TS000289); National ALS Registry/CDC/ATSDR CDCP-DHHS-US (CDC/ATSDR 200-2013-56856); NIEHS K23ES027221; NIEHS R01ES030049; NINDS R01NS127188, ALS Association (20-IIA-532), the Dr. Randall W. Whitcomb Fund for ALS Genetics, the Peter R. Clark Fund for ALS Research, the Scott L. Pranger ALS Clinic Fund, and the NeuroNetwork for Emerging Therapies at the University of Michigan. This work was supported in part by the Intramural Research Program of the NIH, National Institute on Aging (Z01-AG000949-02). Project “ALS Genetic study in Madrid Autonomous Community” funded by “ESTRATEGIAS FRENTE A ENFERMEDADES NEURODEGENERATIVAS” from Spanish Ministry of Health.Peer reviewe

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk