Identifying candidate RNA-seq biomarkers for severity discrimination in chemical injuries: A machine learning and molecular dynamics approach.

Introduction: Biomarkers play a crucial role across various fields by providing insights into biological responses to interventions. High-throughput gene expression profiling technologies facilitate the discovery of data-driven biomarkers through extensive datasets. This study focuses on identifying biomarkers in gene expression data related to chemical injuries by mustard gas, covering a spectrum from healthy individuals to severe injuries.

Mogroside V ameliorates astrocyte inflammation induced by cerebral ischemia through suppressing TLR4/TRADD pathway.

Inflammation and oxidative stress are pivotal factors in the onset and progression of secondary injury following cerebral ischemia-reperfusion (I/R). Mogroside V (MV), a primary active compound of Siraitia grosvenorii, exhibits significant anti-inflammatory and antioxidant properties. However, its specific effects in cerebral ischemia remain unclear.

Spatiotemporal estimates of anthropogenic NO emissions across China during 2015-2022 using a deep learning model.

As one of the significant air pollutants, nitrogen oxides (NO = NO + NO) not only pose a great threat to human health, but also contribute to the formation of secondary pollutants such as ozone and nitrate particles. Due to substantial uncertainties in bottom-up emission inventories, simulated concentrations of air pollutants using GEOS-Chem model often largely biased from those of ground-level observations. To address this issue, we developed a new deep learning model to simulate the inverse process of the GEOS-Chem model.

Detection of heavy metals in soil using Au@SiO nanoparticles and surface microstructure combined with laser-induced breakdown spectroscopy.

The detection of heavy metals in soil is of great scientific significance for food security and human health. However, traditional detection methods are complicated, time-consuming, and labor-intensive. Herein, we developed a novel method using Au@SiO nanoparticles (NPs) and surface microstructure combined with laser-induced breakdown spectroscopy (Au@SiO NPs-SMS-LIBS) for the rapid detection of lead (Pb), chromium (Cr), and copper (Cu) in soil samples.

Hyperplex PCR enables highly multiplexed analysis of point mutations in wastewater: Long-term SARS-CoV-2 variant surveillance in Sweden as a case study.

Wastewater-based surveillance (WBS) allows the analysis of pathogens, chemicals or other biomarkers in wastewater to derive unbiased epidemiological information at population scale. After re-gaining attention during the SARS-CoV-2 pandemic, the field holds promise as a surveillance and early warning system by tracking emerging pathogens with pandemic potential. Expanding the current toolbox of analytical techniques for wastewater analysis, we explored the use of Hyperplex PCR (hpPCR) to analyse SARS-CoV-2 mutations in wastewater samples collected weekly in up to 22 sites across Sweden between October 2022 and December 2023.

Quantitative Evaluation of 99mTc-Galactosyl Human Serum Albumin SPECT/CT for the Prediction of Posthepatectomy Liver Failure.

Purpose: To evaluate the predictive ability of 99mTc-galactosyl human serum albumin SPECT/CT quantitative parameters for posthepatectomy liver failure (PHLF).

Methods: Sixty-eight patients who underwent 99mTc-galactosyl human serum albumin scintigraphy as a preoperative examination for hepatectomy between July 2021 and December 2023 were prospectively evaluated. The patients were divided into PHLF and non-PHLF groups.

The role of chronic fatigue in the relationship between maternal self-efficacy, social support, and depressive symptoms in mothers of crying infants.

Background: Social support and maternal self-efficacy are important protective factors against depression. However, the contribution of these variables to postpartum depression in the context of persistent maternal fatigue and prolonged unrestrained infant crying is unclear.

Objectives: This study aimed to explore possible mediating roles of maternal chronic fatigue, infant crying intensity, and frustration as a maternal emotional response to infant crying on the relationship between social support, maternal self-efficacy and maternal depression.

Development of micro-nanostructured film with antibacterial, anticorrosive and thermal conductivity properties on copper surface.

A micro-nano sharkskin like film (Cu-MNS-FA) was synthesized on copper surface through chemical etching followed by formate passivation, and its anticorrosive, antibacterial and thermal conductivity properties were investigated. Results show that after 7 d of exposure to nature, Pseudomonas aeruginosa and Desulfovibrio vulgaris seawater, the charge transfer resistance of Cu-MNS-FA is more than three times higher than that of unmodified copper. In particular, in D.

Mn-Mn Dimers Induced Multimode Emitters in Mn-Activated AZn(PO) (A = K, Rb, and Cs) with Unique [ZnPO] Chains and [ZnO] Groups.

Mn-doped luminescent materials play a significant role in a variety of fields, including modern lighting, displays, and imaging. Mn exhibits a broad and adjustable emission, hinging on the local environment of the crystal field and the interaction of the 3d electrons. However, it is still a challenge to realize the precise control of the emission of Mn ions due to site-prior occupation in a specific lattice.

Exploring P-(Fe,V)-Codoped Metastable-Phase β-NiMoO for Improving the Performance of Overall Water Splitting.

It is especially essential to develop high-performance and low-cost nonprecious metal catalysts for large-scale hydrogen production. A large number of electrochemical catalysts composited by transition metal centers has been reported; however, it is still a great challenge to design and manipulate target electrocatalysts to realize high overall water-splitting activity at the atomic level. Herein, we develop totally new P-(Fe,V)-codoped metastable-phase β-NiMoO.

Unraveling the Role of Functional Groups of Terephthalate in Enhancing the Electrochemical Oxygen Evolution Reaction of Nickel-Organic Framework Nanoarrays.

The platelike nickel-terephthalate-type metal-organic framework nanoarrays (Ni-BDC NAs) on carbon cloth are obtained by employing agaric-like Ni(OH) NAs as sacrificial templates. The microenvironment of Ni-BDC NAs is modulated by various neighboring functional groups (-NH, -NO, and -Br) on the carboxylate ligand, exerting minimal destructive effects on the structure and morphology of Ni-BDC NAs. The electrochemical oxygen evolution reaction (OER) of Ni-BDC-NH NAs, Ni-BDC-NO NAs, and Ni-BDC-Br NAs exhibited a significant enhancement compared to that of Ni-BDC NAs alone, as evidenced by both experimental and theoretical assessments.

Research Funded by National Institutes of Health Concerning Sexual and Gender Minoritized Populations: A Tracking Update for 2012 to 2022.

To investigate trends in awards funded by the National Institutes of Health (NIH) focusing on sexual and gender minoritized (SGM) populations from 2012 to 2022 in the United States. Replicating the method of Coulter et al., we identified NIH-funded awards for SGM research from 2012 to 2022 using the NIH RePORTER (Research Portfolio Online Reporting Tools Expenditures and Results) system.

Precision Oncology: A Global Perspective on Implementation and Policy Development.

Despite the acknowledged merits of precision oncology (PO) and its increasing global implementation, its full potential for advancing care and prevention remains unrealized. The benefits are currently accessible to only limited patient segments because of multifaceted barriers. Successful implementation hinges on various factors-scientific complexities not limited to technical, clinical, regulatory, economic, administrative, and health care policy-related challenges.

Comparison of Temporal Artery and Rectal Temperature Measurement During Cooling and Rewarming in Neonates Treated for Hypoxic Ischemic Encephalopathy.

Background: Finding an accurate and simple method of thermometry in the neonatal intensive care unit is important. The temporal artery thermometer (TAT) has been recommended for all ages by the manufacturer; however, there is insufficient evidence for the use of TAT in infants, especially to detect hypothermia.

Purpose: To assess the accuracy of the TAT in hypothermic neonates in comparison to a rectal thermometer.

Gadopiclenol Enables Reduced Gadolinium Dose While Maintaining Quality of Pulmonary Arterial Enhancement for Pulmonary MRA: An Opportunity for Improved Safety and Sustainability.

Rationale And Objectives: Pulmonary magnetic resonance angiography (MRA) is an imaging method with proven utility for the exclusion of pulmonary embolism and avoids the need for ionizing radiation and iodinated contrast agents. High-relaxivity gadolinium-based contrast agents (GBCAs), such as gadopiclenol, can be used to reduce the required gadolinium dose for pulmonary MRA. The aim of this study was to compare the contrast enhancement performance of gadopiclenol with an established gadobenate dimeglumine-enhanced pulmonary MRA protocol.

Free-Breathing Respiratory Triggered High-Pitch Lung CT: Insights From Phantom and Patient Scans.

Objective: Respiratory motion can affect image quality and thus affect the diagnostic accuracy of CT images by masking or mimicking relevant lung pathologies. CT examinations are often performed during deep inspiration and breath-hold to achieve optimal image quality. However, this can be challenging for certain patient groups, such as children, the elderly, or sedated patients.

Design of ()-3-(5-Thienyl)carboxamido-2-aminopropanoic Acid Derivatives as Novel NMDA Receptor Glycine Site Agonists: Variation in Molecular Geometry to Improve Potency and Augment GluN2 Subunit-Specific Activity.

NMDA receptor ligands have therapeutic potential in neurological and psychiatric disorders. We designed ()-3-(5-thienyl)carboxamido-2-aminopropanoic acid derivatives with nanomolar agonist potencies at NMDA receptor subtypes (GluN12/A-D). These compounds are superagonists at GluN1/2C compared to glycine and partial to full agonists at GluN1/2A and GluN1/2D but display functional antagonism at GluN1/2B due to low agonist efficacy.

Dipnictogen Radical Chemistry: A Dithorium-Supported Distibene Radical Trianion.

Although two examples of σ-bonded -bent [RSbSbR] (R = bulky organo- or Ga-groups) that formally contain the Sb radical trianion moiety are known in p-block chemistry, d- or f-element Sb radical trianion complexes, with or without R-substituents, have remained elusive. Here, we report that reduction of a 77:23 mix of [{Th(Tren)}(μ-η:η-Sb)] (, Tren = {N(CHCHNSiPr)}):[{Th(Tren)}(μ-SbH)] () with 1.5 equiv of KC in the presence of 1.

Oral Exposure to Toxin A Aggravates Food Allergy by Intestinal Barrier Destruction, Mast Cell Activation, and Th2-Biased Immune Responses.

Food allergy is a complex disease, with multiple environmental factors involved. Considering the regulatory effect of toxin A (Tcd A) on biological processes of allergic reactions, the role of oral exposure to Tcd A on food allergy was investigated. The intestinal permeability and β-hexosaminidase were promoted by Tcd A using the in vitro Caco-2 and HT-29 cells coculture monolayer and bone marrow-derived mast cell (MCs) degranulation model.

Retraction Note: Performance evaluation of deep learning techniques for lung cancer prediction.

[This retracts the article DOI: 10.1007/s00500-023-08313-7.].

Determination of Cyazofamid and Its Metabolite in Rice Based on Magnetic Zirconia Nanoparticles Sample Cleanup and Its Application to a Dissipation and Residue Study.

An analytical method was developed for the determination of cyazofamid (CZFM) and its metabolite CCIM in rice, employing magnetic zirconia nanoparticles (MZNPs) for sample cleanup. MZNPs were synthesized through a one-step hydrothermal process and characterized by multiple techniques. Samples of rice plant, rice hull, and brown rice were extracted using acetonitrile/water, followed by salting out.

High-pressure and low-temperature behaviour of organic ferroelectric (R)-3-quinuclidinol.

High-pressure and low-temperature structural changes in the ferroelectric phase of (R)-3-quinuclidinol are analysed. The changes in unit-cell volume and parameters are continuous both on cooling and under increasing pressure. The anisotropy of the structural strain, however, is found to be different.

Quality of life disparities among Mexican people with systemic lupus erythematosus.

Higher prevalence and worst outcome have been reported among people with systemic lupus erythematosus with non-European ancestries, with both genetic and socioeconomic variables as contributing factors. In Mexico, studies assessing the inequities related to quality of life for Systemic Lupus Erythematosus patients remain sparse. This study aims to assess the inequities related to quality of life in a cohort of Mexican people with SLE.

Burden of diabetic ketoacidosis and its predictors among diabetic patients in Ethiopia: Systematic review and meta-analysis.

Background: Multiple studies across Ethiopia have investigated the occurrence of DKA, showing significant variations and conflicting findings. This systematic review and meta-analysis seek to consolidate the overall prevalence of diabetic ketoacidosis and its associated factors in the Ethiopian context.

Methods: The study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines.

Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors.

This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), the following ML models were looked at: Linear Regression (LR), Support Vector Regressor (SVR), Random Forest (RF), Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Using a dataset of 40,000 observations, the models were assessed based on R-squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE).