Narrative generation and narrative recall recruit different executive functions in preschoolers with and without developmental language disorder.

Children with developmental language disorder (DLD) are poor at story-telling and show weaknesses in various executive functions (EFs). Narrative tasks are frequently used in clinical assessment to capture the linguistic vulnerabilities of individuals with DLD. But we know little about the demands of different narrative tasks on EFs.

Generation, manipulation, detection and biomedical applications of magnetic droplets in microfluidic chips.

Microfluidic systems incorporating magnetic droplets have emerged as a focal point of significant interest within the biomedical domain. The allure of these systems lies in their capacity to offer precise control, enable contactless operation, and accommodate minimal sample concentration requirements. Such remarkable features serve to mitigate errors arising from human operation and other factors during cell or molecular detection.

Exploring the influence of environmental indicators and forecasting influenza incidence using ARIMAX models.

Background: Influenza is a respiratory infection that poses a significant health burden worldwide. Environmental indicators, such as air pollutants and meteorological factors, play a role in the onset and propagation of influenza. Accurate predictions of influenza incidence and understanding the factors influencing it are crucial for public health interventions.

Revealing degradation pathways of soluble and dissolved organic matter in alluvial-lacustrine aquifer systems impacted by high levels of geogenic ammonium.

The excessive presence of geogenic ammonium (NH) in groundwater poses a global environmental concern, commonly linked to the degradation of nitrogen-containing dissolved organic matter (DOM). However, there is a gap in systematic studies on the combination of soluble organic matter (SOM) in sediments and DOM in groundwater, with few indoor incubation experiments to validate their degradation pathways. This study utilized ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry to analyze the molecular characteristics of DOM and SOM in aquifer systems affected by geogenic NH.

β-Lactoglobulin-based aerogels: Facile preparation and sustainable removal of organic contaminants from water.

Economically and efficiently removing organic pollutants from water is still a challenge in wastewater treatment. Utilizing environmentally friendly and readily available protein-based natural polymers to develop aerogels with effective removal performance and sustainable regeneration capability is a promising strategy for adsorbent design. Here, a robust and cost-effective method using inexpensive β-lactoglobulin (BLG) as raw material was proposed to fabricate BLG-based aerogels.

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models.

Background: Influenza is a highly contagious respiratory disease that presents a significant challenge to public health globally. Therefore, effective influenza prediction and prevention are crucial for the timely allocation of resources, the development of vaccine strategies, and the implementation of targeted public health interventions.

Method: In this study, we utilized historical influenza case data from January 2013 to December 2021 in Fuzhou to develop four regression prediction models: SARIMA, Prophet, Holt-Winters, and XGBoost models.

Source-oriented health risk assessment of groundwater nitrate by using EMMTE coupled with HHRA model.

Conventional concentration-oriented approaches for nitrate risk diagnosis only provide overall risk levels without identifying risk values of individual sources or sources accountable for potential health risks. Therefore, a hybrid model combining the end-member mixing model tool on Excel™ (EMMTE) with human health risk assessment (HHRA) was developed to assess the source-oriented health risks for groundwater nitrate, particularly in the Poyang Lake Plain (PLP) region. The results indicated that the EMMTE and the Bayesian stable isotope mixing model (MixSIAR) exhibited remarkable consistency in source apportionment of groundwater nitrate.

Burdock miR8175 in diet improves insulin resistance induced by obesity in mice through food absorption.

The incidence of type 2 diabetes mellitus (T2DM) induced by obesity is rapidly increasing. Although there are many synthetic drugs for treating T2DM, they have various side effects. Here, we report that miR8175, a plant miRNA from burdock root, has effective antidiabetic activity.

Learning verbs in English and Korean: The roles of word order and argument drop.

To learn new words, particularly verbs, child learners have been shown to benefit from the linguistic contexts in which the words appear. However, cross-linguistic differences affect how this process unfolds. One previous study found that children's abilities to learn a new verb differed across Korean and English as a function of the sentence in which the verb occurred (Arunachalam et al.

Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater.

Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors.

Integrating machine learning and nontargeted plasma lipidomics to explore lipid characteristics of premetabolic syndrome and metabolic syndrome.

Objective: To identify plasma lipid characteristics associated with premetabolic syndrome (pre-MetS) and metabolic syndrome (MetS) and provide biomarkers through machine learning methods.

Methods: Plasma lipidomics profiling was conducted using samples from healthy individuals, pre-MetS patients, and MetS patients. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were employed to identify dysregulated lipids in the comparative groups.

Evaluating the risk of developing hyperuricemia in patients with type 2 diabetes mellitus using least absolute shrinkage and selection operator regression and machine learning algorithm.

Background: Hyperuricemia is a common complication of type 2 diabetes mellitus and can lead to serious consequences such as gout and kidney disease.

Methods: Patients with type 2 diabetes mellitus from six different communities in Fuzhou were recruited from June to December 2022. Questionnaires, physical examinations, and laboratory tests were conducted to collect data on various variables.

A commercial humic acid inhibits benzo(a)pyrene biodegradation by Paracoccus aminovorans HPD-2.

Benzo(a)pyrene (BaP) is posing serious threats to soil ecosystems and its bioremediation usually limited by environmental factors and microbial activity. Humic acid (HA), a ubiquitous heterogeneous organic matter, which could affect the fate of environmental pollutants. However, the impact of HA on bioremediation of organic contamination remains controversial.

An artificial neural network model for evaluating the risk of hyperuricaemia in type 2 diabetes mellitus.

Type 2 diabetes with hyperuricaemia may lead to gout, kidney damage, hypertension, coronary heart disease, etc., further aggravating the condition of diabetes as well as adding to the medical and financial burden. To construct a risk model for hyperuricaemia in patients with type 2 diabetes mellitus based on artificial neural network, and to evaluate the effectiveness of the risk model to provide directions for the prevention and control of the disease in this population.

Electrooxidation of chlorophene and dichlorophen by reactive electrochemical membrane: Key determining factors of removal efficiency.

This study systematically investigated the variable main electrooxidation mechanism of chlorophene (CP) and dichlorophen (DCP) with the change of reaction conditions at TiO anode operated in batch and reactive electrochemical membrane (REM) modes. Significant degradation of CP and DCP was observed, that is, CP exhibited greater removal efficiency in batch mode at 0.5-3.

Prioritization of control factors for heavy metals in groundwater based on a source-oriented health risk assessment model.

Heavy metals (HMs) in groundwater seriously threaten ecological safety and human health. To facilitate the effective management of groundwater contamination, priority control factors of HMs in groundwater need to be categorized. A total of 86 groundwater samples were collected from the Huangpi district of Wuhan city, China, during the dry and wet seasons.

Synthesis of uniformly dispersed FeTiO nanodisks: a sensitive photoelectrochemical sensor for glucose monitoring in human blood serum.

A novel photoelectrochemical (PEC) sensor was constructed, using FeTiO nanodisks under visible-light irradiation, for the determination of glucose in human blood serum. The uniformly dispersed FeTiO nanodisks were synthesized for the first time by an ion exchange method and subsequent heat treatment. As excellent catalysts, the FeTiO nanodisks can directly catalyze the oxidation of glucose to produce current in the absence of glucose oxidase.

Early prediction of acute kidney injury in patients with gastrointestinal bleeding admitted to the intensive care unit based on extreme gradient boosting.

Background: Acute kidney injury (AKI) is a common and important complication in patients with gastrointestinal bleeding who are admitted to the intensive care unit. The present study proposes an artificial intelligence solution for acute kidney injury prediction in patients with gastrointestinal bleeding admitted to the intensive care unit.

Methods: Data were collected from the eICU Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care-IV (MIMIC-IV) database.

Assessment of groundwater hydrochemistry, water quality, and health risk in Hainan Island, China.

Groundwater is an important source of water for human sustenance. The determination of groundwater quality at island sites is an urgent priority in China, but there are lacking systematic reports relating to them. Here, 63 groups of groundwater samples were collected and analyzed of Hainan Island.

Rolling circle transcription amplification-directed construction of tandem spinach-based fluorescent light-up biosensor for label-free sensing of β-glucosyltransferase activity.

β-glucosyltransferase (β-GT) can specifically catalyze the conversion of 5-hydroxymethylcytosine (5-hmC) to 5-glucosylhydroxy methylcytosine (5-ghmC), and it is associated with the control of phage-specific gene expression by affecting transcription process in vivo and in vitro. The current strategies for β-GT assay usually involve expensive equipment, laborious treatment, radioactive hazard, and poor sensitivity. Here, we report a Spinach-based fluorescent light-up biosensor for label-free measurement of β-GT activity by utilizing 5-hmC glucosylation-initiated rolling circle transcription amplification (RCTA).

A polyaniline functionalized NiFeP nanosheet array-based electrochemical immunosensor using Au/CuO nanocubes as a signal amplifier for the detection of SARS-CoV-2 nucleocapsid protein.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged as a novel pathogen in 2019. The virus is responsible for a severe acute respiratory syndrome outbreak, affecting the respiratory system of infected individuals. COVID-19 is a super amplifier of basic diseases, and the disease with basic diseases is often more serious.

Priority control factors for heavy metal groundwater contamination in peninsula regions based on source-oriented health risk assessment.

Peninsula regions in China face serious environmental issues, such as heavy metal (HM) groundwater contamination. However, attempts to investigate the pollution sources and health risks of HM contamination in such regions require considerable resources and costs. Moreover, the priority control factors for groundwater HMs remain unclear.