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Improving food packaging safety through cold plasma-treated edible films with Carum copticum extracts
Whole-body inhalation study of nanoparticle-enhanced vegetable oil metalworking fluids in mice for assessing occupational health risks
Abstract The increasing demand for sustainable machining necessitates the development and toxicological evaluation of environmentally friendly alternatives to conventional metalworking fluids (MWFs). This study investigated the respiratory and systemic effects of a nanoparticle-enhanced vegetable oil-based MWF (NPVO-MWF) using a whole-body inhalation exposure model in male C57BL/6 mice. Both sub-acute (4-week) and sub-chronic (13-week) exposures were performed, followed by detailed bioanalytical and histopathological assessments. Cytokine analyses (IL-1β, TNF-α, IL-6) via ELISA and RT-PCR revealed no significant pro-inflammatory responses. Reactive oxygen species (ROS) levels in blood, bronchoalveolar lavage fluid, and lung homogenates remained unchanged, indicating an absence of oxidative stress. Histopathological analysis using hematoxylin and eosin staining showed mild epithelial hyperplasia in sub-chronic exposures. Sirius Red staining revealed minimal collagen deposition and slight reductions in pulmonary airspace. No substantial evidence of lung injury, pulmonary toxicity, or carcinogenicity was observed. This study represents one of the first applications of a whole-body inhalation model for evaluating NPVO-MWFs, addressing a critical gap in occupational health risk assessment. The findings indicate that NPVO-MWFs present low toxicological risk under the tested conditions and offer a viable, sustainable alternative to conventional MWFs. Additional chronic exposure studies are recommended to further establish their occupational safety.
Development SPE-LC-MS/MS method for determination of WHO AWaRe Reserve antibiotics in hospital wastewater
Abstract Overuse and inadequate legal regulation of the use of antibiotics have led to antimicrobial resistance, which threatens healthcare by reducing the effectiveness of treatments and promoting multidrug-resistant “superbugs”. The World Health Organization created the AWaRe (Access, Watch, Reserve) classification to categorize antimicrobials according to their therapeutic value, emphasizing prudent use. The most important group in terms of protecting effectiveness is the Reserve group. The aim of the study was to develop a method for the determination of the following Reserve antibiotics in hospital wastewater: aztreonam, linezolid, meropenem, tigecycline, vaborbactam, cilastatin, fosfomycin, and ceftazidime. Twenty-six extraction procedures were tested and the one with the best recoveries for all antimicrobials (31.5–103.7%) was selected. The extracts were analyzed by liquid chromatography-tandem mass spectrometry. The method was validated and applied to the determination of the selected pharmaceuticals in effluents from 16 hospitals in Poland, with Reserve antibiotics detected in each sample at concentrations ranging from 1.89 ng L− 1 to 22.49 µg L− 1. This is the first country-scale methodological study on Reserve antibiotics in hospital wastewater, emphasizing the need for early environmental monitoring and the potential integration of such strategies into healthcare systems to mitigate the global antimicrobial resistance crisis.
Analysis of Z-Score and total score of athleticism on drafted and undrafted players from the NFL scouting combine
Forest land cover optimization for water management in the Ichawaynochaway creek basin
Survey and diversity assessment of key insect communities in different grassland types in Inner Mongolia
The chain mediation effect of rumination and worry between the intentionality and content dimensions of mind wandering and internalizing symptoms of depression and anxiety
Abstract Rumination and worry, as maladaptive emotion regulation strategies, perpetuate internalizing symptoms of depression and anxiety. However, examinations of dysfunctional mind wandering (MW)—internally oriented thoughts that contribute to emotion dysregulation—and its underlying the cognitive mechanisms related to internalizing symptoms remains limited. This study aimed to identify dysfunctional types of MW associated with internalizing symptoms of depression and anxiety by distinguishing between the intentionality and content of MW. The results indicate that trait rumination and worry sequentially mediate the relationship between the frequency of unintentional MW, which encompasses vague, future-oriented, and negative content, and internalizing symptoms. Furthermore, both single and chained mediation effects were identified in the relationship between unintentional negative MW and internalizing symptoms, with worry acting either as a sole mediator or as a subsequent mediator following rumination in a chain mediation pathway. This study offers novel insight into the distinct roles of rumination and worry as maladaptive emotion regulation strategies, particularly regarding dysfunctional MW types and their contributions to internalizing symptoms of depression and anxiety.
Bioinformatics analysis and preliminary validation of autophagy-related genes in asthma disease
Robustness of quantum correlations in photonic systems under non-Markovian dephasing: theoretical analysis in the experimental range
Rice QTL hotspots related with seed grain size, shape, weight, and color based on genome wide association study and linkage mapping
Abstract Rice is a staple crop worldwide, with seed traits such as size, shape, weight, and color playing crucial roles in agricultural productivity and consumer preferences. Despite significant progress, the genetic basis underlying the variation in hulled and unhulled seed grain traits remains partially unexplored. This study presents a comprehensive analysis combining GWAS and QTL mapping to dissect the genetic architecture of hulled and unhulled seed characteristics in rice. The aim is to identify quantitative trait loci (QTLs) associated with these traits using an integration of multi-model approach genome-wide association studies (GWAS) and linkage mapping analysis. The study analyzed 244 local rice varieties for GWAS and 90 Recombinant Inbred Lines for linkage mapping analysis. The traits observed included hulled and unhulled seed grain area, perimeter, length, width, length-to-width ratio, circularity, weight, and color (RGB, HSV, Lab, yCbCr). A total of 23 QTL regions were identified, with two major QTL hotspots located on chromosomes 7 and 2. Specifically, QTL hotspots on chromosome 7 were associated with grain size, shape, and weight, while those on chromosome 2 were linked to seed color. A total of 530 SNPs significantly associated with the traits were distributed across 12 rice chromosomes, corroborating the QTL hotspot regions. Six genes on chromosome 7 and seven genes on chromosome 2 were proposed as candidate genes regulating seed grain traits. These findings provide valuable insights into the genetic control of rice seed traits and offer potential targets for breeding programs aimed at improving rice quality and yield.
Clinical performance validation of an integrated cartridge based bedside blood gas analyzer system in the acute care setting
Abstract This study aims to evaluate the clinical performance of the EG-i30 blood gas analyzer and its test cartridge (EG10+), a maintenance-free electrochemical point-of-care blood gas analyzer system (referred to as EG), in comparison with the established ABL90 FLEX blood gas analyzer system (referred to as ABL) in the acute care setting. A total of 216 clinical residual samples from 94 patients were analyzed using both systems. Key blood gas and electrolyte parameters, including pH, pO2, pCO2, K+, Na+, iCa2+, Cl−, Lac, Glu, and Hct, were measured. Performance was assessed using statistical methods including Bland-Altman plots, Pearson’s correlation, concordance correlation coefficient (CCC), and Passing-Bablok regression. ROC curve analysis evaluated the EG’s diagnostic performance for hyperlactatemia, hypokalemia, and hyperkalemia. The EG demonstrated excellent correlation with the ABL, with r values ranging from 0.969 to 0.992 and CCC values between 0.958 and 0.991 for all parameters. Bias analysis at the medical decision levels showed that all parameters were within the allowable error limits. ROC analysis for Lac and K+ revealed high sensitivity and specificity. The EG provides reliable and accurate blood gas analysis comparable to the ABL, offering a portable, cost-effective solution for rapid diagnostics in emergency and critical care settings.
Evaluation of transduction efficiency in pancreatic beta and alpha cells utilizing various AAV serotypes
A predictive model for electrospun based Polyvinyl alcohol (PVA) nanofibers diameter using an artificial neural network
DEM calibration insights on the role of particle shape for sub 2 mm particles
Abstract This study introduces a comprehensive calibration technique for discrete element method (DEM) simulations. Its focus is on particles smaller than 2 mm and this showcase shows comparison between spherical and polyhedral particle shape calibration. Very fine powders or particulate materials with small particles are usually calibrated with upscaling. Unfortunately, some applications are dependent heavily on a quite precise particle size range, such as abrasion, crushing, pneumatic conveying, feeding, and dosing. Traditional DEM simulations often rely on spherical or multi-spherical particle models, which lack the precision needed, particularly due to the surface waviness introduced in the latter case. This limitation impacts dynamic industrial applications like mixing, hopper discharge, and abrasion. To address this gap, we present a comparative calibration approach for spherical and polyhedral particles, using silica sand as the test material. The calibration combines static and dynamic parameters such as rolling resistance, particle-to-particle restitution, and wall friction, validated through experiments on a powder flow calibration stand. Results revealed significant differences in flow dynamics, highlighting the enhanced realism of polyhedral models despite increased computational demands. This work provides a comprehensive framework for DEM calibration of fine particulate materials, specifically validated for particle sizes between 400 and 1500 µm, improving simulation accuracy and extending applicability across various industrial processes.
Ensemble learning for biomedical signal classification: a high-accuracy framework using spectrograms from percussion and palpation
Oil removal from wastewater with biomass-derived hydrochars laboratory insights
Enhancing urban quality of life evaluation using spatial multi criteria analysis
Natural experiments from Earth Hour reveal urban night sky being drastically lit up by few decorative buildings
The prognostic significance of the geriatric nutritional risk index in postoperative parotid gland carcinoma
Abstract The impact of the Geriatric Nutritional Risk Index (GNRI) on the prognosis of postoperative parotid gland carcinoma (PGC) remains unclear. This study investigates the role of GNRI in predicting disease-free survival (DFS) and overall survival (OS) in postoperative PGC patients and develops a predictive model. We conducted a retrospective analysis of 389 postoperative PGC patients treated from May 2008 to June 2019 at two regional medical centers in China. The independent prognostic factors were identified by univariate and multivariate Cox regression analyses. Then, two nomograms were established based on these independent prognostic factors and verified by a series of methods. The GNRI was identified as an independent prognostic factor in postoperative patients with PGC. A higher GNRI value indicated a worse prognosis for the patient. Based on the recognized independent prognostic factors—such as surgical margin, perineural invasion, extranodal extension (ENE), age-adjusted Charlson comorbidity index (ACCI), American Joint Committee on Cancer (AJCC) stage, and GNRI—two nomograms for overall survival (OS) and disease-free survival (DFS) were developed. The concordance index (C-index) for DFS was 0.712 and 0.730, while for OS it was 0.697 and 0.722 in the training and validation groups, respectively. These results demonstrate a significant improvement over the traditional AJCC staging system. Additionally, the area under the curve (AUC) values in both the training and validation sets were impressive, with all AUC scores exceeding 0.7. Decision curve analysis (DCA) also indicated substantial clinical benefits. The GNRI is an important predictive index in postoperative patients with PGC, which is not limited to the elderly. The newly developed nomograms provide a new tool of prognostic evaluations for postoperative patients with PGC.