Enhanced nitrogen prediction and mechanistic process analysis in high-salinity wastewater treatment using interpretable machine learning approach.

This study introduces an interpretable machine learning framework to predict nitrogen removal in membrane bioreactor (MBR) treating high-salinity wastewater. By integrating Shapley additive explanations (SHAP) with Categorical Boosting (CatBoost), we address the critical gap in linking predictive accuracy to operational decision-making for saline systems. CatBoost achieved the best performance, with an coefficient of determination (R) of 0.

Promotes the Growth and Metastasis of Colorectal Cancer by Activating E-Cadherin/Krüppel-Like Factor 4/Integrin α5 Signaling in a Calcium-Dependent Manner.

Gut microbiota and integrins are known to contribute to colorectal cancer (CRC), but whether they interact has been unclear. Here, we provided evidence that upregulated integrin α5 (ITGA5) in CRC in both human patients and murine models. Knocking down in CRC cells weakened the ability of to stimulate their malignant characteristics.

PM concentration prediction using a whale optimization algorithm based hybrid deep learning model in Beijing, China.

PM is a significant global atmospheric pollutant impacting visibility, climate, and public health. Accurate prediction of PM concentrations is critical for assessing air pollution risks and providing early warnings for effective management. This study proposes a novel hybrid machine learning model that combines the whale optimization algorithm (WOA) with a convolutional neural network (CNN), long short-term memory (LSTM), and an attention mechanism (AM) to predict daily PM concentrations.

Utilizing Target Sequences with Multiple Flanking Protospacer Adjacent Motif (PAM) Sites Reduces Off-Target Effects of the Cas9 Enzyme in Pineapple.

Background/objectives: CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats)-associated protein 9 is now widely used in agriculture and medicine. Off-target effects can lead to unexpected results that may be harmful, and these effects are a common concern in both research and therapeutic applications.

Methods: In this study, using pineapple as the gene-editing material, eighteen target sequences with varying numbers of PAM (Protospacer-Adjacent Motif) sites were used to construct gRNA vectors.

Research progress on influencing factors and intervention methods of protein-energy wasting in maintenance hemodialysis patients: A literature review.

Protein-energy wasting (PEW) has high incidence in hemodialysis patients and refers to a state of decreased protein and energy substance. With the extensive development of hemodialysis in patients with end-stage kidney disease, most patients with maintenance hemodialysis have the problem of PEW, which is one of the common complications of maintenance hemodialysis patients, resulting in decreased quality of life and increased mortality. This article searches and analyzes the literature in recent years to summarize the current influencing factors and common interventions of PEW in maintenance hemodialysis patients, which will provide reference for subsequent nutritional management of maintenance hemodialysis patients.

Anti-inflammatory effect of polysaccharides from Sambucus williamsii Hance roots in lipopolysaccharide-stimulated RAW264.7 macrophages and acute lung injury in mice.

This study aimed to investigate the structural characterization of polysaccharide from Sambucus williamsii Hance roots (SWH1-1) and its effects on inflammation and acute lung injury (ALI). Results showed that SWH1-1 had a molecular weight of 10,040 Da and primarily consisted of arabinose, galactose, glucose and mannose. Its main backbone was composed of →6)-α-D-Glcp-(1→, →6)-α-D-Man-(1→, and →6)-β-D-Galp-(1→.

Spatiotemporal analysis of carbon emission efficiency across economic development stages and synergistic emission reduction in the Beijing-Tianjin-Hebei region.

Exploring regional carbon emission efficiency and its patterns is crucial for promoting a sustainable economy. This study investigated the spatiotemporal variations of carbon emissions and emission efficiency in the Beijing-Tianjin-Hebei region. Night light data was used to estimate carbon emissions, and the Super-EBM model was employed to calculate carbon emission efficiency.

Fractional Langevin equation far from equilibrium: Riemann-Liouville fractional Brownian motion, spurious nonergodicity, and aging.

We consider the fractional Langevin equation far from equilibrium (FLEFE) to describe stochastic dynamics which do not obey the fluctuation-dissipation theorem, unlike the conventional fractional Langevin equation (FLE). The solution of this equation is Riemann-Liouville fractional Brownian motion (RL-FBM), also known in the literature as FBM II. Spurious nonergodicity, stationarity, and aging properties of the solution are explored for all admissible values α>1/2 of the order α of the time-fractional Caputo derivative in the FLEFE.

Effects of sophorolipids and coconut wax incorporation on the physical, structural, and antibacterial properties of cellulose nanofibers-based Pickering emulsion for cherry tomato preservation.

A novel acidic sophorolipid-enhanced cellulose nanofiber-based coconut wax Pickering emulsion (ASL-CCPE) using cellulose nanofibers (CNF) as a stabilizer, lactonic sophorolipids (LSL) as an antimicrobial agent, and acidic sophorolipids (ASL) as a co-stabilizer were developed. Through optimization of the oil phase type, oil-to-water ratio, and ASL content, the emulsion exhibited shear-thinning behavior and elastic gel characteristics, making it suitable for coating applications. After 182 days of storage at room temperature, the emulsion's droplet size remained uniform, with no significant flocculation observed.

Latent profile analysis and influence factors study of nurses' job performance.

Objective: To investigate the current status of nurses' job performance, to analyze the latent profile analysis of nurses' job performance and their relationship with occupational coping self-efficacy, perceived social support and to explore the factors influencing the different profiles.

Methods: From April to June 2024, 390 nurses from five general hospitals were facilitated to be selected as survey respondents using a general information questionnaire, job performance scale, occupational coping self-efficacy scale, and perceived social support scale. Latent profile analysis of nurses' job performance were analyzed, and logistic regression was used to analyze the factors influencing different categories of nurses' job performance.

Integrated transcriptomic hypothalamic-pituitary-ovarian axis network analysis reveals the role of energy availability on egg production in layers.

Energy is a crucial component for maintaining egg production in layers. The hypothalamic-pituitary-ovarian (HPO) axis is an energy-sensitive functional axis for follicle development, synthesis, and secretion of reproductive hormones, and plays a key role in modulating sustained ovulation in layers. To investigate the mechanism of integrated network regulation of the HPO axis under energy fluctuation, ninety Hy-line brown layers (265-day-old, 1.

Impacts of changes in PM concentrations and their major components on blood pressure during pregnancy.

Sulfate, nitrate, ammonium, organic matter, and black carbon account for more than two-thirds of the total mass of PM and have stronger cardiovascular toxicity than other components. However, evidence regarding the gestational cardiovascular toxicity of these PM components is lacking. A prospective cohort study was conducted among 1913 pregnant women in Guangzhou, Pearl River Delta, China, from 2017 to 2020.

Transcriptome and chromatin accessibility landscape of ovarian development at different egg-laying stages in taihe black-bone silky fowls.

Taihe Black-Bone Silky Fowl (SF) is a famous local breed in China, known for its high nutritional and medicinal value. However, its low egg-laying rate significantly limits its economic benefits. This study aims to explore the ovarian development status, as well as the changes in the transcriptome and chromatin accessibility landscape at different egg-laying stages of SF, in order to reveal the epigenetic regulatory mechanisms underlying ovarian development in laying hens.

Seedling size affects the strategy of dune seedlings responding to rainfall variation.

Background And Aims: Climate change poses a growing threat to population maintenance in harsh desert habitats with high precipitation variability. Desert seeds may germinate at different times as a bet-hedging strategy to cope with increased rainfall fluctuation. As a result, a population may consist of seedlings of various sizes.

Knowledge, attitudes, and practices of vocational college teachers towards occupational burnout.

Objective: This study aimed to investigate the knowledge, attitudes, and practices (KAP) of vocational college teachers regarding occupational burnout.

Methods: A cross-sectional study was conducted among teachers from 15 vocational colleges between 20 April 2024 and 20 June 2024. Basic demographic information and KAP scores were collected through a self-developed questionnaire.

Simulation and prediction of PM2.5 concentrations and analysis of driving factors using interpretable tree-based models in Shanghai, China.

PM2.5 is a critical air pollutant, and understanding its drivers is essential for regional air quality control. This study employed meteorological and pollutant variables to predict PM2.

Chromoanagenesis Is Frequently Associated With Highly Complex Karyotypes, Extensive Clonal Heterogeneity, and Treatment Refractoriness in Acute Myeloid Leukemia.

Chromoanagenesis (CAG) encompasses a spectrum of catastrophic genomic events, including chromothripsis, chromoanasynthesis, and chromoplexy. We studied CAG in 410 patients with a diagnosis of acute myeloid leukemia (AML), 292 newly diagnosed (ND), and 118 refractory/relapsed, using optical genome mapping. CAG was identified by the presence of clusters (with 10 or more breakpoints) of structural abnormalities and/or segmental copy number alterations within one or more chromosomal regions.

Crystal-level timing calibration using cascaded photons ofCo point source for long axial animal PET system.

Timing calibration is essential for positron emission tomography (PET) system as it enhances timing resolution to improve image quality. Traditionally, positron sources are employed for timing calibration. However, the photons emitted by these sources travel in opposite directions, necessitating that positrons annihilate at multiple locations to collect coincidence data across a greater number of lines of response.

Dynamic classification and attention mechanism-based bidirectional long short-term memory network for daily runoff prediction in Aksu River basin, Northwest China.

Inland river runoff variability is pivotal for maintaining regional ecological stability. Daily flow forecasting in arid regions is crucial in understanding water body ecological processes and promoting healthy river ecology. Precise daily runoff forecasting serves as a cornerstone for ecological evaluation, management, and decision-making.

Can ACR TI-RADS predict the malignant risk of medullary thyroid cancer?

Objectives: This study aimed to evaluate the diagnostic performance for medullary thyroid cancer (MTC) based on the 2017 Thyroid Imaging Reporting and Data System by the American College of Radiology (ACR TI-RADS) guideline, and the ability to recommend fine needle aspiration (FNA) for MTC.

Methods: Fifty-six MTCs were included, and 168 benign thyroid nodules (BTNs) and 168 papillary thyroid nodules (PTCs) were matched according to age. Ultrasound (US) features were reviewed according to ACR TI-RADS.

Detection of Partial Tandem Duplication by Optical Genome Mapping in Myeloid Neoplasms: Associated Cytogenetics, Gene Mutations, Treatment Responses, and Patient Outcomes.

partial tandem duplication (PTD) involves intragenic duplications and has been associated with poorer prognosis. In this study, we evaluated PTD in 1277 patients with hematological malignancies using optical genome mapping (OGM). PTD was detected in 35 patients with acute myeloid leukemia (AML) (7%), 5 patients with myelodysplastic syndrome (MDS) (2.

Ureaplasma parvum serovar 6 may be a novel element in the progression of HPV infection to CIN: A cross-sectional study of 7058 women.

Background: Ureaplasma parvum (U. parvum) is generally regarded as innocuous, and studies focusing on variations in pathogenicity among U. parvum serovars are inadequate.

Advancements in research and clinical management of interstitial lung injury associated with ADC drugs administration in breast cancer.

Antibody-drug conjugates (ADCs) represent a novel class of targeted anti-tumor medications that utilize the covalent linkage between monoclonal antibodies and cytotoxic agents. This unique mechanism combines the cytotoxic potency of drugs with the targeting specificity conferred by antigen recognition. However, it is essential to recognize that many ADCs still face challenges related to off-target toxicity akin to cytotoxic payloads, as well as targeted toxicity and other potential life-threatening adverse effects, such as treatment-induced interstitial lung injury.

A probabilistic deep learning approach to enhance the prediction of wastewater treatment plant effluent quality under shocking load events.

Sudden shocking load events featuring significant increases in inflow quantities or concentrations of wastewater treatment plants (WWTPs), are a major threat to the attainment of treated effluents to discharge quality standards. To aid in real-time decision-making for stable WWTP operations, this study developed a probabilistic deep learning model that comprises encoder-decoder long short-term memory (LSTM) networks with added capacity of producing probability predictions, to enhance the robustness of real-time WWTP effluent quality prediction under such events. The developed probabilistic encoder-decoder LSTM (P-ED-LSTM) model was tested in an actual WWTP, where bihourly effluent quality prediction of total nitrogen was performed and compared with classical deep learning models, including LSTM, gated recurrent unit (GRU) and Transformer.