Healthcare Utilization and Costs Among Commercially Insured Infants With and Without Medically Complex Conditions.

Background: Little is known about healthcare use and costs for commercially insured infants in the first year of life following a Neonatal Intensive Care Unit (NICU) hospitalization.

Purpose: To evaluate healthcare utilization and costs in the 12-months after a neonatal hospitalization among commercially insured infants, comparing infants with and without medically complex conditions.

Methods: This retrospective, cross-sectional, cohort study uses data from the IBM MarketScan Commercial database (2015-2019).

Diversity of intestinal microbiota and inflammatory cytokines after severe trauma.

Accumulating evidence has reported that the intestinal microbiota could play important roles in the occurrence and progression of severe trauma. However, the hypothesized potential targeted intestinal microbiota to mediate and regulate the levels of inflammatory cytokines and promote rapid recovery of body after severe trauma remains unclear. This study was aimed to explore the changes and correlation of intestinal microbiota and inflammatory cytokines in rats with severe crush and fracture trauma.

Association of clinical biomarker-based biological age and aging trajectory with cardiovascular disease and all-cause mortality in Chinese adults: a population-based cohort study.

Background: Evidence on the association of clinical biomarker-based biological age (BA) with cardiovascular disease (CVD) and mortality remains insufficient, particularly concerning aging trajectories' relationship with these two outcomes.

Methods: Seventy-five thousand five hundred thirty-seven Chinese adults from the Kailuan study who participated in the first checkup (2006-2007) were included. BA was predicted by 32 clinical indicators using deep neural networks models.

Combination therapy of pulsed dye laser and ablative fractional carbon dioxide laser for the treatment of pediatric postburn scar: a systematic review.

This study aims to determine the effectiveness of combining pulsed dye laser (PDL) and ablative fractional carbon dioxide laser (AFCL) in the treatment of scars in pediatric patients, as well as to identify appropriate treatment parameters, initial treatment timing, and treatment intervals through a systematic literature review. A literature search was conducted between April 6, 2014 and April 6, 2024 in four databases to select studies on the effects of the combination of carbon dioxide fractional laser and pulsed dye laser therapy in children hypertrophic burn scars. This systematic literature review included 497 participants across 8 studies, with individual study sample sizes ranging from 17 to 125 participants.

Insights into incompatible plasmids in multidrug-resistant Raoultella superbugs.

The emergence of multidrug-resistant (MDR) Raoultella isolates is linked to the acquisition of antibiotic resistance genes (ARGs) with plasmids playing a pivotal role in this process. While plasmid-mediated transmission of ARGs in Raoultella has been extensively reported, limited attention has been given to genetically dissecting the modular structures of plasmids. This study aims to elucidate the genomic features of novel incompatible plasmids in MDR Raoultella by presenting 13 complete plasmid sequences from four isolates, along with an analysis of 16 related plasmids from GenBank.

Longitudinal Measures of Cardiovascular Risk Factors Are Associated with Subfertility in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

Introduction: Previous reports have noted associations between subfertility in women and increased risk of cardiovascular disease (CVD) events in later life. However, reports conflict regarding the associations between subfertility and CVD risk factors. Using data from a population-based cohort of Black and White women, we examined the association between longitudinal assessments of CVD risk factors and subfertility.

Evaluating Intervention Reporting in Nursing Journal RCTs Using the TIDieR Checklist: A Cross-Sectional Study.

Aim: To assess the completeness of intervention reporting in randomised controlled trials (RCTs) published in nursing journals based on the Template for Intervention Description and Replication (TIDieR) checklist.

Design: A cross-sectional study.

Methods: RCTs published in English in nursing journals between January 2022 and December 2022 were identified through PubMed.

DGNMDA: Dual Heterogeneous Graph Neural Network Encoder for miRNA-Disease Association Prediction.

In recent years, numerous studies have highlighted the pivotal importance of miRNAs in personalized healthcare, showcasing broad application prospects. miRNAs hold significant potential in disease diagnosis, prognosis assessment, and therapeutic target discovery, making them an integral part of precision medicine. They are expected to enable precise disease subtyping and risk prediction, thereby advancing the development of precision medicine.

Trajectories of depressive symptoms in a population-based cohort of Black and White women from late reproductive age through the menopause transition: a 30-year analysis.

Objective: The aim of this study was to examine how depressive symptoms change in midlife and across the menopause transition.

Methods: We conducted a secondary analysis of data from a prospective population-based cohort, the Coronary Artery Risk Development in Young Adults study. We included women (n = 2,160) with ≥3 responses to the Center for Epidemiologic Studies Depression Scale (CES-D) beginning at examination year 5, at approximately 30 years of age, and again at years 10, 15, 20, 25, 30, and 35 (ages 35 through 60 years).

AI-Based Hematological Age Predictors and the Association Between Biological Age Acceleration and Type 2 Diabetes Mellitus - Chongqing Municipality, China, 2015-2021.

Introduction: Biological age (BA) can represent the actual state of human aging more accurately than chronological age (CA).

Methods: Using hematological data from 112,925 participants in southwestern China, collected between 2015 and 2021, this study constructed BA predictors using 7 machine learning (ML) methods (tailored separately for male and female populations). This study then analyzed the association between BA acceleration and type 2 diabetes mellitus (T2DM) within this data using logistic regression.

Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations.

Background: Methylmalonic acidemia (MMA) is one of the most common hereditary organic acid metabolism disorders that endangers the lives and health of infants and children. Early detection and intervention before the appearance of a newborn's clinical symptoms can control disease progression and prevent or mitigate its serious consequences.

Methods: 42,004 newborns from two Chinese populations were included in the study.

Ginsenoside Rg1 enriches gut microbial indole-3-acetic acid to alleviate depression-like behavior in mice via oxytocin signaling.

Background And Purpose: Although a large collection of data has shown that ginsenosides, the major active ingredients from Ginseng, have neuroprotective and anti-depressant effect, the mechanism of action is incompletely understood. This study aims to elucidate the antidepressant mechanism of ginsenoside Rg1 (Rg1), a poorly absorbed ginsenoside, from the perspective of gut microbe to brain signaling.

Methods: A mouse model of depression was induced by unpredictable mild stress (UMS).

Lactobacillus rhamnosus GG and Bifidobacterium animalis subsp. lactis BB-12 promote infected wound healing via regulation of the wound microenvironment.

Infected wounds can result in complex clinical complications and delayed healing, presenting a significant global public health challenge. This study explored the effects of topical application of two probiotics, Lactobacillus rhamnosus GG (LGG) and Bifidobacterium animalis subsp. lactis BB-12, on the microenvironment of infected wounds and their impact on wound healing.

Stabilization effect of nano-SiO@iron-phosphorus on ferrallisols, calcareous soil and organic soil heavily polluted by heavy metals: A fast reaction curing stabilization process.

The remediation of soil pollution by heavy metals (HMs) presents a significant challenge in environmental restoration. Stabilization remediation technology has proven effective in treating HMs contaminated soil. However, its development is constrained by drawbacks such as slow reaction kinetics and low adsorption capacity.

Spatial-temporal evolution patterns of influenza incidence in Xinjiang Prefecture from 2014 to 2023 based on GIS.

Using GIS technology, this study investigated the spatiotemporal distribution pattern of influenza incidence in Xinjiang from 2014 to 2023 based on influenza surveillance data. The study revealed a noticeable fluctuation trend in influenza incidence rates in Xinjiang, particularly notable spikes observed in 2019 and 2023. The results of the 3-year moving average showed a significant long-term upward trend in influenza incidence rates, confirmed by Theil-Sen method (MAD = 2.

Clinical significance of serum soluble scavenger receptor CD163 in patients with lupus nephritis.

Background: The soluble CD163 (sCD163) was elevated in systemic lupus erythematosus (SLE) patients.

Purpose: To study whether serum sCD163 could be used to predict the occurrence and prognosis of lupus nephritis (LN).

Research Design: The recruited patients were classified into different groups according to standard identification criteria.

One-Pot Synthesis of Color-Tunable Narrow-Bandwidth Ag-In-Ga-Zn-S Semiconductor Nanocrystals for Quantum-Dot Light-Emitting Diodes.

I-III-VI type semiconductor nanocrystals (NCs) have attracted considerable attention due to their environmental friendly nature and large-scale tunable emission. Herein, we report the successful synthesis of full-spectrum (470 to 614 nm) Ag-In-Ga-Zn-S (AIGZS) NCs by precisely regulating the In/Ga ratios using a facile one-pot method. Intriguingly, the photoluminescence (PL) peak width exhibits a continuous narrowing trend with extended reaction time, ultimately reaching a full width at half-maximum (fwhm) of 34 nm for green AIGZS NCs.

Replicon-Based Typing About IncG Plasmids and Molecular Characterization of Five IncG Plasmids Carrying Carbapenem Resistance Gene .

Purpose: To investigate the genetic diversity of IncG plasmids, we have proposed a typing scheme based on replicon and performed comparative genomic analysis of five IncG plasmids from China.

Methods: p30860-KPC, p116965-KPC, pA1705-KPC, pA1706-KPC and pNY5520-KPC total in five IncG plasmids from clinical isolates of and , respectively, were fully sequenced and were compared with the previously collected reference plasmid p10265-KPC.

Results: Based on phylogeny, IncG-type plasmids are divided into IncG-I to IncG-VIII, the five plasmids belong to IncG-VIII.

Construction of an interface interaction in a g-CN/CdS/NiS for photoreforming of plastic and clean hydrogen regeneration.

Converting plastics into organic matter by photoreforming is an emerging way to deal with plastic pollution and produce valuable organic matter. Water shortage can be alleviated by using seawater resources. To solve these problems, we synthesize a ternary heterostructure composite g-CN/CdS/NiS.

Mechanistic study of pre-eclampsia and macrophage-associated molecular networks: bioinformatics insights from multiple datasets.

Background: Pre-eclampsia is a pregnancy-related disorder characterized by hypertension and proteinuria, severely affecting the health and quality of life of patients. However, the molecular mechanism of macrophages in pre-eclampsia is not well understood.

Methods: In this study, the key biomarkers during the development of pre-eclampsia were identified using bioinformatics analysis.

Deep learning-based automated scan plane positioning for brain magnetic resonance imaging.

Background: Manual planning of scans in clinical magnetic resonance imaging (MRI) exhibits poor accuracy, lacks consistency, and is time-consuming. Meanwhile, classical automated scan plane positioning methods that rely on certain assumptions are not accurate or stable enough, and are computationally inefficient for practical application scenarios. This study aims to develop and evaluate an effective, reliable, and accurate deep learning-based framework that incorporates prior physical knowledge for automatic head scan plane positioning in MRI.