Characteristics of osteoclasts at different developmental stages and therapeutic strategies.

Marine biodegradable polymers and zooplankton: A case study on the effects of PHBV microplastics on Artemia franciscana.

Understanding conical penetration into layered biological materials requires capturing the coupled influences of anisotropy, curvature, layer architecture, and developmental evolution of material properties. However, existing computational studies typically assume adult bone, neglect multilayer skull structure, or simplify cortical anisotropy. Here, we develop a multilayer finite element framework that integrates age-dependent cortical thickness, diploë formation, anisotropic elastic behavior, and Hill-type anisotropic yield to resolve penetration mechanics across developmental stages. A data-driven strategy is used to estimate geometry and material properties by fitting a monomolecular growth model to experimental measurements of thickness, modulus, and strength spanning infancy through adulthood, producing a continuous and physiologically realistic map of skull property evolution. The model is validated against independent wedge-indentation experiments and reference finite element simulations, demonstrating close agreement in force-displacement behavior and subsurface stress distributions. Results reveal that age-driven changes in cortical thickness and stiffness produce more than a three-fold variation in penetration depth and a four-fold variation in penetration depth as a percentage of the outer cortical layer thickness, under identical loading. Marked differences in shear-stress localization and plastic-zone morphology highlight how layer geometry and anisotropic stiffness collectively govern penetration resistance. These findings provide new mechanistic insight into the indentation response and pin slippage of layered cranial bone and underscore the importance of age-specific material modeling. The framework has direct implications for biomechanical safety when using head-immobilization devices, particularly in pediatric neurosurgery, where predictive modeling of tool-bone interaction can inform improved device design, force recommendations, and clinical practice.

Effects and mechanisms of the photocatalytic activity of copper sulfide-modified covalent organic framework on the growth of Ulva prolifera seedlings at different developmental stages

For more than four decades, no standardized study design or workflow has been established for systematic entomotoxicological research in forensic casework. This study aimed to develop a universal rearing protocol for fly larvae grown on drug-spiked tissue surrogate and a standardized workflow for the qualitative analysis of pharmacologically active compounds (PACs) in insects of different developmental stages. Larvae of Protophormia terraenovae and Lucilia sericata were reared on minced meat serving as tissue surrogate. First-instar larvae were transferred to minced meat spiked with diazepam, amitriptyline, pipamperone, or lamotrigine, each triturated with placebo tablets. Actively feeding and post-feeding third-instar larvae were soaked for 24 h in ethanol (30 mL, 70:30, v:v), and both the larvae and the soaking solution were analysed using LC-MS/MS. The larval extraction method was optimized by replacing pure acetonitrile with an acetonitrile-methanol mixture and introducing centrifugation at -10°C. PAC detection was achieved in both larvae and soaking solution, confirming the sensitivity and applicability of the method. The workflow was further validated using authentic postmortem case samples. These findings demonstrate that ethanol-soaked larvae can be used effectively for both toxicological and entomological analyses. Overall, this study provides a universal and standardized workflow that simplifies and strengthens the application of entomotoxicology in forensic casework.

Non-suicidal self-injury in individuals with attention-deficit/hyperactivity disorder: A systematic review and Meta-analysis with Age- and Sex-stratified findings.

Preharvest sorbitol application modulates phytohormone profiles and enhances nutraceutical quality of extra-early nectarine (Prunus persica).

Single-cell RNA and ATAC sequencing reveals cell subsets characteristics in adipose-derived stem cells.

Comprehensive characterization of transcriptional regulation during HCG-induced follicle maturation in mandarin fish (Siniperca chuatsi): Insights from transcriptomics.

Construction of Kongyu 131 mutant library provides genetic resources for rice functional genomics and germplasm improvement.

Life course central depressive symptoms among the moderately depressed population: From adolescence to old age.

Orlistat impairs Chlamydia trachomatis development by disrupting its developmental cycle.

Duck β-defensin 10 inhibits Salmonella enterica by disrupting bacterial membrane integrity and its association with gut microbiota dynamics.

The Pma-PABP4 gene, regulated by Pma-miR-1444, participates in Pinctada fucata gonad development.

The conventional drug discovery pipeline is labour-intensive, time-consuming, and costly, involving target identification, hit discovery, lead optimization, and extensive preclinical and clinical evaluation. To overcome these limitations, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, gaining widespread adoption in the pharmaceutical industry during the 2010s due to advances in computing power, data availability, and deep learning. AI-based approaches, including molecular property prediction, protein structure modelling, natural language processing, and ADME/Tox prediction, have enhanced efficiency, reduced costs, and improved decision-making across multiple stages of drug development. Several AI-guided molecules have progressed into clinical trials, with encouraging early-phase success rates, highlighting the potential of AI to accelerate innovation. However, despite more than a decade of intensive research, no AI-only originated drug has yet achieved full regulatory approval, reflecting persistent challenges consistent with Eroom's law. Key limitations include poor data quality and accessibility, lack of model interpretability, gaps between computational predictions and chemical feasibility, and the inherent complexity of biological systems that limit translational success. Furthermore, AI-driven hypothesis generation does not replace the need for scientific reasoning and experimental validation. Overall, while AI has significantly accelerated early drug discovery stages, it remains a supportive tool rather than a standalone solution, underscoring the continued need for human expertise and experimental research.

Biodiversity net gain (BNG) is a "net outcome" planning policy which aims for development projects to leave biodiversity in a better state than before they started. Understanding the origins and history of existing mandatory BNG is necessary to understand the drivers and barriers that have influenced the policy to date and could inform the development and implementation of future BNG policies. Biodiversity net gain legislation was first discussed in Parliament in England through the passage of the Environment Act (2021) and became a mandatory requirement for most terrestrial and intertidal developments in February 2024. The policy uses habitat attributes as a proxy for biodiversity and represented the widest reaching net outcome policy in the world at the point of its introduction. As such, it is expected to have a significant impact on future land use decisions in England. This paper uses a mixture of literature review and the knowledge of those involved in the early stages of this BNG policy development in England to present a timeline of the stages that have led to mandatory biodiversity net gain. In doing so, we highlight formative events and documents, as an important first step in understanding its history and understanding how this can be used to inform future biodiversity policy.

Variations characteristics of triglyceride during various stages of ovarian development in commercial production of Penaeus monodon broodstock

Mosquitoes are the deadliest organisms on Earth, as they transmit a wide range of medically important diseases, posing a major public health threat worldwide. Controlling vector-borne diseases presents numerous challenges, and the alarming rise in their incidence underscores the urgent need for innovative strategies, with genetic control offering a promising approach. Genetic engineering of mosquitoes requires a profound understanding of mosquito physiology and molecular aspects of host-pathogen interactions. Over the years, several stages of the Plasmodium parasite development within the mosquito have been extensively studied, with many molecular mechanisms successfully elucidated. However, important features of the parasite journey remain unclear, particularly the sporozoite's ability to recognize and invade the salivary glands. This process involves a complex interplay of proteins and other molecules, yet much remains to be discovered about the precise mechanisms at play. Advancing our knowledge of this critical step will be instrumental in designing more effective transgenes for genetic control strategies, particularly those aimed at mosquito population replacement.

Interdisciplinary education between nursing and engineering: A scoping review.

Introduction: Eating habits are established during the early stages of development and are shaped by family, cultural, and social factors. In Ecuador, child malnutrition in rural areas of the Central Sierra reaches 27.7% (INEC), representing a persistent public health challenge. Objective: To determine the eating habits and nutritional status of children of migrant parents. Methodology: A quantitative, descriptive, cross-sectional study was conducted with 212 children. The Krece-Plus questionnaire was applied, and anthropometric measurements were taken following international standards. Results: A total of 25.47% of schoolchildren did not consume dairy products at breakfast, 45.28% did not eat a second daily portion of fruit, and 40.57% did not include vegetables more than once a day. According to the Krece-Plus test, 14.6% showed a very poor nutritional level. Anthropometric assessment revealed 4.7% underweight, 10.8% overweight, and 5.7% obesity, totaling 21.2% malnutrition. No statistically significant association was found between eating habits and nutritional status (p = 0.177). Conclusions: Although most children exhibit relatively adequate dietary habits, important deficiencies in the consumption of healthy foods persist, and a considerable proportion shows malnutrition. Relevance: These findings highlight the nutritional vulnerability of children of migrant parents and reinforce the need for interventions aimed at improving dietary patterns and preventing short- and long-term health risks.