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Impacts of cellulase and xylanase addition on antibiotic resistance and microbial community during dairy manure composting

Background Composting is a transformation and biodegradation process that converts organic biomass into valuable products while also removing antimicrobial resistance genes (ARGs). Promoting lignocellulose biodegradation is essential for enhancing composting efficiency and improving the quality of compost derived from agricultural organic waste. This study aims to explore the effects of cellulase and xylanase on the composting process of cow manure, with a focus on their impact on key physicochemical properties, microbial communities, and antibiotic resistance genes (ARGs). Methods Dairy manure compost was carried out for 30 days with cellulase and xylanase treatment. The physicochemical characteristics (pH, organic matter (OM), total nitrogen (TN), available nitrogen (AN), germination index (GI), humic acid (HA), and fulvic acid (FA)) of the compost samples were measured, along with enzymatic activities, including cellulase activity (CA), urease activity (UA), alkaline phosphatase (ALP), and dehydrogenase activity (DHA). Furthermore, bacterial communities and ARGs were analyzed using 16S rRNA gene sequencing and high-throughput quantitative PCR. Additionally, network properties, redundancy analysis, and variation partitioning analysis were conducted. Results Enzyme additions significantly enhanced composting efficiency, which improved temperature regulation and increased nitrogen content. Cellulase notably accelerated the degradation of organic matter, enhanced microbial diversity, and reduced ARG abundance, while xylanase played a crucial role in stabilizing pH and temperature during the later stages, facilitating nitrogen retention and compost maturity. Additionally, microbial community dynamics were closely linked to ARG patterns, indicating that enzymatic treatments can optimize composting processes while mitigating the spread of resistance genes. Conclusion The findings highlight the complementary roles of these enzymes in improving composting outcomes and suggest strategies for sustainable waste management. These findings provide valuable insights for improving the composting efficiency and quality of compost derived from agricultural organic waste.

Adaptive or maladaptive music-listening coping strategy: How does neuroticism use music after experiencing a romantic relationship breakup?

Romantic relationship breakups are common experiences among young people and are associated with negative emotions that can jeopardize psychological well-being. Additionally, those with higher neuroticism may have greater emotional sensitivity towards the impact of music, as they tend to exhibit more negative and unstable emotional traits. As a result, they may be more inclined to control emotions by using music as a coping strategy. However, existing literature has rarely explored the differential roles of adaptive and maladaptive music-listening coping, as well as the mechanisms linking neuroticism and negative emotions associated with romantic breakups. To fill these gaps, the current study recruited 389 college students who had experienced at least one romantic breakup lasting two months or longer within the past five years. Participants completed a battery of questionnaires assessing relevant variables. Correlational analyses indicated that neuroticism and negative emotions related to romantic breakups were positively correlated with maladaptive music-listening coping. Conversely, neuroticism was negatively correlated with adaptive music-listening coping, while no discernible connection between adaptive music listening coping and negative emotions evoked by romantic breakups. Structural equation modeling suggested that neuroticism predicted emotional response to breakups through maladaptive music-listening coping, rather than adaptive music-listening coping. Theoretical and practical implications were discussed.

Mathematical modelling of tissue growth control by positive and negative feedbacks

This study investigates the regulation of tissue growth through mathematical modeling of systemic and local feedback mechanisms. Employing reaction-diffusion equations, the models explore the dynamics of tissue growth, emphasizing endocrine signaling and inter-tissue communication. The analysis identifies critical factors influencing the emergence of spatial structures, bifurcation phenomena, the existence and stability of stationary pulse and wave solutions. It also elucidates mechanisms for achieving coordinated tissue growth. In particular, if negative feedback is sufficiently strong, their final finite size is provided by a stable pulse, otherwise they manifest unlimited growth in the form of a wave. These findings contribute to the theoretical insights into biological processes such as embryogenesis, regeneration, and tumor development, while highlighting the role of feedback systems in maintaining physiological homeostasis.

Long term trends in NHS inpatient bed provision in England, 1960–2020

Objectives To examine the reduction in NHS inpatient hospital beds in England from 1960 until 2020, including five categories: Acute, Geriatric, Maternity, Mental Illness and Learning Disability beds; and to measure regional differences at the end of the study period. Design Retrospective observational study. Setting NHS in England. Participants Inpatient hospital beds. Main outcome measures NHS inpatient bed provision per 100,000 population. Rate of reduction calculated as percentage change each year. NHS bed provision in 7 regions of England compared for the year 2019/20. Results NHS inpatient bed provision declined for sixty consecutive years. The overall reduction was 78.0% between 1960 and 2020. Greatest reduction was in Learning Disability beds (98.7%), followed by Mental Illness (90.6%), Geriatric (75.0%), Maternity (67.4%) and the least reduction in Acute beds (63.0%). There were two periods of accelerating rates of bed reduction, the first in the 1980s, and the second in the 2000s. At the end of the study period there was significant regional variation in bed numbers. Conclusions Bed reductions were a constant feature, with important differences between bed categories and across time. This needs to be addressed when planning for future pandemics and winter bed pressures. By the end of the study the NHS was no longer providing the same level of inpatient care in different regions of England, particularly for Learning Disability.

Unearthing prehistoric diets: First evidence of horse meat consumption in Early Bronze Age Sicily

This paper presents the earliest documented evidence for the presence and consumption of horse meat in Early Bronze Age Sicily, significantly revising previous understandings of equid use on the island. Multidisciplinary analyses involving proteomics and lipidomics were performed on ceramic vessels from the Castelluccian settlement at Polizzello Mountain (Caltanissetta), revealing residues consistent with equine-derived substances. Proteomic data unequivocally identified equine serum albumin in multiple pottery fragments, demonstrating active consumption or processing of horse-derived substances within a ceremonial or dietary context. Lipid residues further supported this interpretation, indicating the presence of animal fats and vegetable-derived substances within the pottery. These findings substantially alter existing models of horse domestication, utilization, and dietary practices in prehistoric Sicily, suggesting a far earlier and more complex human-equid relationship. Furthermore, the integration of biomolecular data enhances our understanding of intercultural interactions, ritual behaviors, and economic strategies in the central Mediterranean during the third millennium BCE.

Optical detection of single sub-15 nm objects using elastic scattering strong coupling

Abstract Metallic nano-objects play crucial roles in diverse fields, including biomedical imaging, nanomedicine, spectroscopy, and photocatalysis. Nano-objects smaller than 15  nm exhibit extremely low scattering cross-sections, posing a significant challenge for optical detection. An approach to enhance optical detection is to exploit nonlinearity of strong coupling regime, especially for elastic scattering, which is universal to all objects. However, there is still no observation of the strong coupling of elastic light scattering from nano-objects. Here, we demonstrate the strong coupling of elastic light scattering in self-assembled plasmonic nanocavities formed between a gold nanoprobe and a gold film. We employ this technique to detect individual objects with diameters down to 1.8 nm. The resonant mode of the nano-object in the nanocavity environment strongly couples with the nanocavity mode, revealing anti-crossing scattering modes under dark-field spectroscopy. The experimental result agrees with numerical calculations, which we use to extend this technique to other metals. Furthermore, our results show that scattering cross-section ratio of the nano-object scales with the electric field to fourth power, similar to surface-enhanced Raman spectroscopy. This work establishes a new possibility of elastic strong coupling and demonstrates its applicability for observing small, non-fluorescent, Raman inactive sub-15 nm objects, complementary to existing microscopes.

Optimizing gene prioritization for clinical diagnosis of metabolic genetic disorders

The expansion of next-generation sequencing has generated vast genomic datasets, but translating this information into clinically actionable tools for inherited metabolic disorders (IMDs) remains challenging. In this study, we systematically mapped gene–phenotype associations in IMDs using curated data from OMIM, ClinVar, Orphanet, and the Genetic Testing Registry (GTR). From 372 OMIM entries, we identified 228 genes definitively associated with metabolic diseases (GAMD). These genes displayed uneven chromosomal distribution, wide variability in pathogenic variant load, and strong clustering of phenotypes, particularly among amino acid metabolism disorders. Autosomal recessive inheritance was predominant. Integrating variant pathogenicity, phenotype prevalence, and diagnostic test availability, we designed two evidence-based diagnostic panels. The Subnotification Panel highlights under-tested but clinically relevant genes linked to more prevalent IMDs, aiming to address diagnostic underrepresentation. The Initial Screening Panel prioritizes genes with a high proportion of pathogenic variants, broad test accessibility, and strong clinical relevance, offering an efficient tool for first-line diagnostics. By bridging the gap between large-scale genomic information and precision clinical application, these panels provide a scalable and strategic framework to enhance diagnostic accuracy, support early intervention, and improve equity in the management of metabolic diseases.

Unique plastisphere viromes with habitat-dependent potential for modulating global methane cycle

Assessing the genetic diversity of Ethiopian indigenous goat ecotypes at the hemoglobin locus and its associations with morphometric traits

Genetic variation is the baseline for viability, fitness, survivability, and improvement of livestock raised under diverse agroclimatic conditions. The study aimed to assess the genetic variation in the population of goats at the hemoglobin (Hb) locus and its association with morphometric traits. The blood samples were collected from 225 mature goats of both sexes. Morphometric traits, including body weight, chest girth, chest depth, body length, rump length, rump height, rump width, height at withers, fore canon circumference, and ear length, were measured to examine associations with the Hb genotype. The red blood cells were subjected to gel electrophoresis to determine hemoglobin variants. Hemoglobin polymorphisms were analyzed using the Pop gene (ver.32) and the associations with morphometric traits were analyzed using the statistical analysis system. Three Hb genotypes, HbAA, HbAB, and HbBB were detected with genotypic frequencies of 0.34, 0.47, and 0.19, respectively. HbAA was most frequent in highland goats (47%), while HbAB was the predominant genotype in lowland and midland populations. A significant deviation (p < 0.05) from the Hardy-Weinberg Equilibrium (HWE) was observed for the midland goats, while those in the lowland and highland were under HWE. The heterozygosity ranged from 0.36-0.61, indicating population variability and potential for genetic improvement. Hemoglobin showed significant (p < 0.05) influence on most of the morphometric traits in which goats with the homozygous HbBB genotype exhibited superior performance compared to other genotypes. In conclusion, hemoglobin polymorphism could be a viable option for assessing genetic diversity and may serve as a potential genetic marker to support selective breeding programs.

Whole-genome methylation profiling of extracellular vesicle DNA in gastric cancer identifies intercellular communication features

Spatial distribution and cluster analysis of road traffic accidents in Nepal

Background Road traffic accidents (RTAs) continue to pose a significant menace to global public health in the form of a high incidence of mortality, disability and economic expense. Their space-time trends are of importance for policy decision-making. This particular study employed spatial analysis to identify high-risk zones and found significant clustering of accidents in urban centers as well as increasing semi-urban and rural vulnerabilities, supporting the need for safety interventions and road infrastructure improvements in Nepal. This paper aims to determine and analyze the incidence of RTAs in Nepal from 2019 to 2022, primarily focusing on vehicle-types and spatial distribution. Methods Data from all seven provinces and Kathmandu Valley Traffic Police Office were analyzed to examine RTAs patterns across 77 districts of Nepal. The data were processed and visualized using Quantum GIS (QGIS), and spatial analysis performed using Global and Local Moran’s I statistics, along with Local Indicators of Spatial Association (LISA), to identify spatial clusters of accidents. Results This study identified statistically significant spatial clustering of vehicle types involved in RTAs. High-High (HH) clusters, indicating areas with elevated accident rates surrounded by similarly high-risk zones were concentrated in urban centers particularly Kathmandu, Lalitpur, and Bhaktapur. Conversely, Low-Low (LL) clusters, reflecting lower accident rates in sparsely populated regions, were observed in rural areas. Temporal analysis revealed a steady rise in RTAs incidence, with rates increasing from 63.35 per 100,000 population in 2019–2020 (Moran’s I = 0.741) to 94.46 in 2020–2021 (Moran’s I = 0.595) and 123.05 in 2021–2022 (Moran’s I = 0.556). Conclusion This present study observed the growing incidence of RTAs in Nepal. The results highlight the critical need for geographically tailored road safety interventions with priority given to urban and semi-urban zones. Effective strategies should emphasize enhanced road traffic law enforcement, strict regulation of commercial and two-wheeled vehicles as well as targeted infrastructure upgrades in an effective manner.

Natural allelic variation in SW14 determines seed weight and quality in soybean

Assessing the impact of community-based health insurance on health service utilization and out-of-pocket payments in Dangila Wereda, Awi zone, Ethiopia

Spatio-temporal evolution and convergence patterns of E-commerce development in China: Regional disparities and policy implications

The rapid development of e-commerce has become a key driver of economic transformation and regional development in China. However, significant spatial and temporal disparities persist across regions. Understanding these disparities is essential for promoting balanced growth and maximizing the potential of e-commerce in fostering regional economic integration. However, existing studies often focus on isolated temporal trends or spatial patterns, lacking a comprehensive analysis that integrates spatial-temporal dynamics and examines the convergence trends of e-commerce development. This study aims to address these gaps by investigating the spatial-temporal distribution characteristics of e-commerce in China and assessing its convergence trends across different regions. This study utilizes panel data from 31 Chinese provinces spanning the period 2013-2023, employing spatial statistical methods, σ-convergence and β-convergence models, and regression analysis to identify the key factors influencing the observed disparities. The study finds that China’s e-commerce development is characterized by significant regional differences, the coexistence of polarization and low density, and different regional convergence trends in different regions, which provides an important theoretical basis for formulating differentiated development strategies, strengthening cross-regional infrastructure synergies, and digital technology innovation.

Ion transport-triggered rapid flexible hydrovoltaic sensing

ADAPT-3D:accelerated deep adaptable processing of tissue for 3-dimensional fluorescence tissue imaging for research and clinical settings

Identification of BOLD engine deficiencies and suggestions for improvement based on a curated Tachina (Diptera) record set

The increasing number of Barcode of Life Database (BOLD) records per species and genus leads to contradictory species assignments within Barcode Index Numbers (BINs), serving as identifiers for the BOLD ID engine. To examine these issues, we analyzed a dataset comprising original and curated BOLD records for the genus Tachina (Insecta: Tachinidae), based on a previous publication. This dataset included both published and private records. We were able to assess the performance of the BOLD engine’s species determination algorithm, Refined Single Linkage (RESL), and compare it to Assemble Species by Automatic Partitioning (ASAP). Additionally, we investigated the usage of BINs by the BOLD v4 ID engine. Our analysis confirmed that BOLD queries primarily rely on BINs for species identification, although some cases deviated from this pattern, resulting in species matches inconsistent with the assigned BIN species. ASAP was found to be superior to RESL due to RESL’s adherence to the concept of the DNA barcoding gap. Moreover, we found that taxonomic misassignments, inconsistencies in BIN formation, and missing metadata also contribute significantly to unreliable identifications. These problems appear to stem from both algorithmic limitations and deficiencies in submission and post-submission processes. Moreover, we noted that the default mode of the BOLD v4 ID engine integrates both private and published data, leading to public records based solely on COI-based identifications. However, this issue may now be mitigated, as the BOLD v5 ID engine default mode exclusively employs published data. To enhance BOLD’s reliability, we propose improvements to submission and post-submission processes. Without such amendments, the accumulation of contradictory species assignments within BINs will continue to rise and the reliability of specimen identification by BOLD will decrease.

DeMBA: a developmental atlas for navigating the mouse brain in space and time

Abstract Studies of the adult mouse brain have benefited from three-dimensional (3D) atlases providing standardised frameworks for data analysis and integration. However, few 3D atlases exist for the developing mouse brain, and none cover more than a few ages. This fails to represent the dynamic nature of development and is insufficient for researchers whose data fall between the ages of existent atlases. Existing atlases also neglect the spatial correspondence between ages, making comparison across ages difficult. We present the Developmental Mouse Brain Atlas (DeMBA), a 4D atlas encompassing every postnatal day from 4 to 56. DeMBA was created by using existing brain templates for six developmental time points and interpolating intermediate ages. DeMBA is incorporated in software for spatial registration and analysis, enabling brain-wide quantification of features of interest. Furthermore, we provide the software package CCF translator, allowing coordinates or image volumes to be transformed between ages for comparison. These resources provide age-specific spatial frameworks incorporated in accessible analytic pipelines for developmental mouse brain data.

Impacts of external airfoil flaps on the S809 airfoil

Computational model of alpha 7 nicotinic acetylcholine receptor in thalamic reticular nucleus neurons and their involvement in network states

Human 15q13.3 microdeletion syndrome (15q13mds) is a genetic disorder caused by a heterozygous deletion of multiple genes, including the CHRNA7 gene, which encodes the α7 nicotinic acetylcholine receptor (α7 nAChR). This condition is associated with significant neurodevelopmental impairments and an increased risk of seizures, with studies indicating reduced α7 nAChR expression in affected individuals. To explore the role of α7 nAChR activity, we developed computational models of the thalamic reticular nucleus (TRN), a brain region critical for regulating thalamocortical (TC) oscillations involved in epilepsy and sleep-wake states. Using a single-compartment kinetic model of a TRN neuron embedded in a simplified thalamic network model, we demonstrate that α7 nAChR activity is necessary to modulate neuronal firing, through calcium regulation, and produce distinct wake and sleep-like states with the network. These findings suggest that α7 nAChR activity in the TRN modulates TC oscillations between sleep and wake states and can contribute to absence seizures in 15q13mds and other neurodevelopmental disorders.