Identifying potential bacterial pathogens in wastewater by expert reliability analysis of full-length 16S rRNA and untargeted RNA sequencing data processed with four bioinformatic workflows.

Municipal wastewater may serve as a critical community-composite sample for monitoring bacteria excreted by the contributing population, providing insights into public health risks and microbial diversity. The present study emphasizes the integration of DNA (full-length 16S rRNA) methods, untargeted RNA methods, and different bioinformatic protocols to identify potential human bacterial pathogens in wastewater. Results revealed that, DNA surveillance identified roughly 50 % of the sequencing reads were associated with potentially pathogenic bacteria, as compared to RNA surveillance, which identified roughly 33 % of the reads as associated with potential bacterial pathogens.

Mitigating gaseous nitrogen emissions in cotton fields through green manure and reduced nitrogen fertilization.

Integrating green manure with reduced nitrogen (N) fertilization is a promising strategy to mitigate N emissions in intensive cotton cultivation, however, the underlying mechanisms remain poorly understood. This study investigated the effects of three green manure incorporation patterns-no green manure (NG), (OVG), and (VVG)-combined with four N reduction levels (100, 50, 25%, and conventional) on gaseous N emissions (NH and NO), soil physicochemical properties, and bacterial community characteristics using a cotton field experiment in the Yellow River Basin. Results showed that OVG incorporation with 25% N reduction (N2 treatment) significantly reduced total gaseous N emissions by 36.

Heatmap clustering and performance analysis of cotton genotypes in response to environmental conditions.

Cotton (Gossypium hirsutum) is a crucial cash crop in China, with yield performance influenced by genotype, environmental conditions, and management practices. The aim of this study was to assess the yield performance, biomass accumulation, and growth of nine cotton genotypes in Henan Province during three growing seasons (2017-2019) with different climates. Field experiments were conducted using a randomized complete block design (RCBD) at the Institute of Cotton Research, Chinese Academy of Agricultural Sciences (CAAS), Anyang, China.

In-depth comparison of untargeted and targeted sequencing for detecting virus diversity in wastewater.

Sequencing approaches may enable monitoring of a broad range of viruses in wastewater, including potential emerging and non-reportable human viruses. Considering the fact that metagenomic sequencing may be non-specific for low-abundance human viruses, integration of viral amplification and enrichment strategies are proposed to enhance the accurate detection of a broad range of human viruses in municipal wastewater. In this study, we focused on the in-depth comparison analysis of three untargeted amplification methods (Multiple Displace Amplification [MDA], Reverse Transcription - MDA [RT-MDA], and a PCR-based random amplification [PCR-based]) and one targeted method (Twist Comprehensive Viral Research Panel [TWIST]) for detecting virus diversity in wastewater.

Community case study: an academia-industry-government partnership that monitors and predicts outbreaks in Tri-County Detroit area since 2017.

The Tri-County Detroit Area (TCDA) is the 12th most populous metropolitan area in the United States with over three million people. Multiple communicable diseases are endemic in the TCDA. In 2017, to explore innovative methods that may provide early warnings of outbreaks affecting populations in the TCDA, an exploratory partnership that was funded by a U.

Effect of channel roughness on the particle diffusion and permeability of carbon nanotubes in reverse electrodialysis process applying molecular dynamics simulation.

Innovative technology and methods are crucial for making pure and refreshing water. Two main methods are present to delete soluble salts from water: membrane processes and thermal processes. A beneficial membrane technique is reverse electrodialysis.

A hybrid deep learning network for automatic diagnosis of cardiac arrhythmia based on 12-lead ECG.

Cardiac arrhythmias are the leading cause of death and pose a huge health and economic burden globally. Electrocardiography (ECG) is an effective technique for the diagnosis of cardiovascular diseases because of its noninvasive and cost-effective advantages. However, traditional ECG analysis relies heavily on the clinical experience of physicians, which can be challenging and time-consuming to produce valid diagnostic results.

Association between blood pressure levels and premature atrial contractions in patients with hypertension.

Background: High blood pressure (BP) induces left atrial structural and functional remodeling that increases susceptibility to atrial arrhythmia. We hypothesized that lower systolic BP (SBP) levels are associated with a lower prevalence of premature atrial contractions (PACs) in patients with hypertension.

Methods: This analysis included 4,697 participants (mean age 62±13.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan.

Background: Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing.

Results: During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated.

Racial differences in prevalence and impact of electrocardiographic subclinical myocardial injury risk factors.

Background: We explored whether the reported racial differences in subclinical myocardial injury (SCMI) are due to variations in the prevalence or differential impact of the SCMI risk factors.

Methods: This analysis included 3074 Whites, 1337 Blacks, and 1441 Mexican Americans from the Third National Health and Nutrition Examination Survey who were free of cardiovascular disease. SCMI was defined from standard electrocardiograms as a cardiac infarction/injury score ≥ 10 points.

Fractional derivative method for anomalous aquitard flow in a leaky aquifer system with depth-decaying aquitard hydraulic conductivity.

Aquitards significantly affect groundwater flow in multi-aquifer systems through adjacent aquifer leakage. Despite this, studies focusing on their heterogeneity and the non-conventional diffusion patterns of their flow are still limited. In this study, a factional derivative approach was first extended to explore the time-dependent behavior of flow transport in the aquitard.

Electrocardiographic left atrial abnormality and risk of heart failure.

Introduction: The association and the racial differences of the electrocardiographic markers of left atrial abnormality (ECG-LAA) with heart failure (HF) are unclear.

Methods: We examined the cross-sectional association of ECG-LAA, defined as deep terminal negativity of P wave in V1 (DTNPV1) with HF in 8460 participants (51.5% women, 60.

Effect of wastewater collection and concentration methods on assessment of viral diversity.

Monitoring of potentially pathogenic human viruses in wastewater is of crucial importance to understand disease trends in communities, predict potential outbreaks, and boost preparedness and response by public health departments. High throughput metagenomic sequencing opens an opportunity to expand the capabilities of wastewater surveillance. However, there are major bottlenecks in the metagenomic enabled wastewater surveillance, including the complexities in selecting appropriate sampling and concentration/virus enrichment methods as well as in bioinformatic analysis of complex samples with low human virus concentrations.

Toward High-Performance Mg/S Batteries with M4-Assisted Mg(AlCl ) /PYR14TFSI/DME Electrolyte and MoS @CMK/S Cathode.

Rechargeable magnesium batteries (RMBs) are considered as one of the most promising candidates for next-generation batteries. However, the popularization of RMBs is seriously plagued due to the lack of suitable non-nucleophilic electrolytes and the passivation of Mg anode. Herein, a novel non-nucleophilic electrolyte is developed by introducing (s)-1-methoxy-2-propylamine (M4) into themagnesium aluminum chloride complex (MACC)-like electrolyte.

A study on feature selection using multi-domain feature extraction for automated k-complex detection.

Background: K-complex detection plays a significant role in the field of sleep research. However, manual annotation for electroencephalography (EEG) recordings by visual inspection from experts is time-consuming and subjective. Therefore, there is a necessity to implement automatic detection methods based on classical machine learning algorithms.

To explore the change of motor cognitive function in pituitary tumor rats after operation.

To study the changes of motor and cognitive function of pituitary tumor rats after the operation. Methods: The experiment was divided into three groups: control group, model group and operation group (30 animals for each group). Female Fischer344 rats were selected.

A RUSBoosted tree method for k-complex detection using tunable Q-factor wavelet transform and multi-domain feature extraction.

Background: K-complex detection traditionally relied on expert clinicians, which is time-consuming and onerous. Various automatic k-complex detection-based machine learning methods are presented. However, these methods always suffered from imbalanced datasets, which impede the subsequent processing steps.

Competition for Light Interception in Different Plant Canopy Characteristics of Diverse Cotton Cultivars.

Identifying the ideal plant nature and canopy structure is of great importance for improving photosynthetic production and the potential action of plants. To address this challenge, an investigation was accomplished in 2018 and 2019 at the Institute of Cotton Research (ICR) of the Chinese Academy of Agricultural Science (CAAS), Henan Province, China. Six cotton varieties with diverse maturities and plant canopy structures were used to evaluate the light interception (LI) in cotton, the leaf area index (LAI), the biomass, and the yield throughout the two years of study.

Effects of plastic film mulching on the spatiotemporal distribution of soil water, temperature, and photosynthetic active radiation in a cotton field.

Plastic film mulching (PFM) affects the spatiotemporal distribution of soil moisture and temperature, which in turn affects cotton growth and the spatiotemporal distribution of canopy photosynthetically active radiation (PAR). Due to the spatial heterogeneity of soil moisture, temperature and limited monitoring methods, the issues such as relatively few sampling points and long sampling intervals in most existing studies prevent the accurate quantification of spatiotemporal changes in moisture and temperature along soil profile. To investigate the effects of PFM on spatiotemporal changes in soil moisture, temperature, and canopy PAR in cotton fields, two field trials of plastic film-mulched (M) and nonmulched (NM) cultivations were performed in 2018 and 2019.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence.

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area.

Scaling up ultrathin boat-graphane with the non-classical stiffness relation to macroscopic metamaterials.

Scaling up ultrathin nanosheets with unusual mechanical properties to macroscopic metamaterials is an intriguing topic considering the significant gap of their characteristic scales. In this regard, we investigate the relation between the in- and out-of-plane stiffness of monolayer boat-graphane in two principal axis directions by quantum mechanical calculations. A non-classical relation between the two types of stiffness is found, in opposition to the classical one for orthotropic thin plates.

Digital versus conventional full-arch impressions in linear and 3D accuracy: a systematic review and meta-analysis of in vivo studies.

Objectives: The purpose of this systematic review was to compare the accuracy of digital and conventional full-arch impressions in vivo.

Materials And Methods: This systematic review was conducted according to the PRISMA and registered at the PROSPERO (CRD42021232736). Electronic and hand searches were performed to identify in vivo studies comparing the linear or 3D accuracy of digital and conventional impressions.

Radiomics Model Based on Enhanced Gradient Level Set Segmentation Algorithm to Predict the Prognosis of Endoscopic Treatment of Sinusitis.

Methods: Computed tomography (CT) images of sinusitis in 91 patients were collected. By introducing boundary gradient information into the edge detection function, the sensitivity of the level set model to the boundary of different intensities of lesions was adjusted to obtain accurate segmentation results. After that, the segmented CT image was imported into Mazda texture analysis software for feature extraction.