The aim of this study was to ascertain the clinical features that facilitate the differentiation of malignant melanoma of the skin (MM) from suspicious benign skin lesions (SBSLs). From December 2021 to February 2026, a database of 126 excised skin lesions (ESLs) was generated including 106 cases of SBSLs, 13 of non-nodular melanomas (NNMs), and seven of nodular melanomas (NMs). The ESLs were evaluated according to the ABCDE criteria, the 7-PCL scale, and other clinical signs of suspected MM, such as the ugly duckling sign. Fisher's exact test, revealed that, in comparison to SBSLs, all MM cases exhibited a higher propensity for evolution in size, shape or color within six months (p<0.001), firm to touch (p=0.002), rapid growth within six weeks/atypical skin lesion de novo (p<0.001), inflammation (p=0.034), oozing or crusting (p=0.004), and sensory changes including itching (p=0.023). In Firth's penalized logistic regression, for NNMs alone, no clinical feature exhibited a statistically significant higher frequency compared to SBSLs. In multivariate analysis, rapid growth within six weeks/atypical skin lesion de novo was the only clinical feature statistically more frequent in NMs alone than SBSLs [odds ratio (OR)=14.71, 95% confidence interval (CI)=1.02-2583, p=0.049] and in all MM cases compared to SBSLs (OR=4.83, 95%CI=1.04-27.29, p=0.045). Rapid lesion growth within six weeks/atypical skin lesion de novo represents the primary independent clinical feature distinguishing MM from SBSLs. Conversely, standard structural metrics like a diameter greater than 6 mm fail to provide a statistically reliable differentiation between MM and SBSLs during initial clinical inspection in multivariate analysis.

Prunus serotina (Ehrh.) is a deciduous tree that has spread quickly across Europe in recent decades, raising concern due to its negative ecological and socioeconomic impacts. Although recognised as an invasive species in many European countries, it is not included among the European Union’s invasive alien species of concern. This review summarises current knowledge on taxonomy, biology and management. To prevent misidentifications, we present taxonomic challenges and key morphological characteristics. Prunus serotina grows best on nutrient-rich, well-drained substrates and benefits from canopy disturbances or forest management. Key traits contributing to its invasion success include rapid juvenile growth, high and early seed production, vegetative reproduction, sapling bank formation, and allelopathy. High herbivory and pathogen pressure on native tree species also enhance P. serotina establishment and spread. Management strategies include mechanical, chemical and biological control methods, as well as management aimed at reducing forest susceptibility to invasion by enhancing resilience and, in some cases, accepting P. serotina in the forest. Across Europe, management is context-dependent: eradication is prioritised in the Czech Republic due to its limited distribution, while in Germany, Belgium, Poland, and the Netherlands, integration into structurally diverse forests and resilience enhancement are emphasised, often combined with targeted control in protected areas. Overall, P. serotina is an invasive species with negative impacts. In isolated populations of P. serotina, the aim should be to eradicate the species in order to limit further spread. In valuable ecosystems where complete eradication is unfeasible, the goal is to suppress P. serotina. • Review of taxonomy, biology, ekology and invasion history of Prunus serotina . • Key invasiveness traits: rapid growth, high seeding, sapling bank, resprouting. • Management strategies are context-dependent across European regions. • Eradication is prioritised in areas with limited distribution.

Engineering Escherichia coli for high-level poly(3-hydroxybutyrate) production: Recent advances and future perspective.

The rapid growth in global population necessitates efficient energy management solutions for sustainable living. Smart Building Energy Management Systems (SBEMS) play a crucial role in achieving this goal by leveraging automation and advanced analytics. This study proposes a novel Deep Learning and IoT-based SBEMS approach to predict energy consumption, classify buildings into energy-demand clusters, and optimize the monitoring and operation of electrical equipment. While traditional statistical methods have been widely used for load forecasting, recent advancements in deep learning provide robust alternatives to address the inherent complexity of nonlinear energy consumption patterns. This research employs regression analysis and state-of-the-art neural network architectures, including Single-Step and Multi-Step Dense Models, Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks, to enhance prediction accuracy. Additionally, K-means clustering is introduced to segment buildings into distinct energy-demand categories, ensuring optimal energy utilization. Unlike prior studies that often lack a comprehensive approach, this work integrates all critical features under a unified framework. By applying these advanced methodologies to a unique dataset, the proposed system demonstrates improved accuracy in energy load forecasting and clustering, providing a significant contribution to the field of smart building energy management. The experimental results demonstrate that CNN and LSTM models significantly outperform conventional statistical approaches in capturing nonlinear energy consumption patterns. These outcomes support proactive energy scheduling, peak-demand mitigation, and scalable smart building energy management, offering practical value for facility managers, utility operators, and policymakers.

Pyogenic granuloma (PG) is a common benign vascular lesion characterized by rapid growth and a tendency to bleed. This case series presents 5 patients with solitary PG lesions successfully treated with the topical application of table salt under occlusion. All patients achieved complete clinical and dermoscopic resolution without scarring or recurrence, and treatment was well tolerated with high patient satisfaction. Given its simplicity, safety, and cost-effectiveness, topical salt application may represent a valuable noninvasive alternative for managing PG.

LLM-assisted meta-analysis reveals a global shift toward non-radical dominance in peroxymonosulfate-based advanced oxidation.

The red swamp crayfish ( Procambarus clarkii ), an alien species native to the southern United States and northern Mexico, was introduced into China from Japan in 1929. Its prolific reproduction, rapid growth, omnivorous diet, and broad adaptability have enabled it to colonize and thrive across China. The species' considerable economic value has cemented its status as an essential component of China's aquaculture industry. However, as an invasive species, the crayfish has also had detrimental effects on China's freshwater ecosystems. Escapes from aquaculture operations and deliberate releases have inflicted significant harm on rice paddies, levees, local food webs. Prior research has often focused one-sidedly on either the invasive risks or the economic benefits of the red swamp crayfish, resulting in a lack of comprehensive evaluation of its overall impact in China. This review presents in-depth data on the proliferation of the crayfish in China, highlighting its substantial economic contributions. By examining various facets of its success as an invasive species, the review provides a holistic perspective on the crayfish, both within China and globally, and elucidates its positive and negative impacts. Specifically, P. clarkii as a driver of economic growth and a source of ecological threat, and the urgent need to balance economic utilization with effective ecological management.

A review on antibiotic use in tilapia farming: Pharmacokinetics, impacts, and potential health risks.

Rap1b promotes glioma growth and stemness via regulation of Notch1 and VEGFR2 signaling pathways.

Piaractus brachypomus (red-bellied pacu), native to the Amazon River Basin, is widely known for its rapid growth, disease resistance, and cost-effective feeding, which have led to its widespread introduction and high commercial value worldwide. Despite this, the lack of a reference genome has hindered both genetic and evolutionary studies, as well as the genetic improvement of aquaculture traits. Here, to address this gap, we report the first chromosome-level genome assembly of P. brachypomus using PacBio HiFi long-reads and Hi-C sequencing technologies. The final genome assembly has a total size of 1.34 Gb and exhibits high continuity, with contig N50 of 40.61 Mb. Approximately 99.35% of assembled sequences were anchored into 27 chromosomes, with a BUSCO completeness score of 99.8%. Genome annotation identified 44.83% of repetitive elements and predicted 25,501 protein-coding genes with 99.2% receiving functional annotations. Overall, these findings offer a framework for evolutionary studies and genetic improvement, facilitating marker-assisted and genome-wide selection for the sustainable enhancement of P. brachypomus aquaculture stocks.

Spheroid screening: A simplified model driving targeted drug discovery and clinical advances.

From expansion to optimization: Government health expenditure and chronic disease burden among older adults in China.

Small-cell lung cancer (SCLC) is characterized by rapid growth and a pronounced neuroendocrine phenotype, accompanied by marked metabolic plasticity. Although metabolic reprogramming is a hallmark of SCLC, the molecular mechanisms coordinating glycolytic and lipid metabolic pathways remain poorly defined. Untargeted metabolomic profiling and RNA sequencing were performed on 46 surgically resected SCLC tissues, 39 paired non-tumorous lung tissues, and corresponding serum samples to identify dysregulated metabolic pathways and key regulatory genes. NCAPG expression and function were evaluated using quantitative real-time PCR, Western blotting, Seahorse extracellular flux analysis, and xenograft mouse models. Cell proliferation, apoptosis, ATP production, and reactive oxygen species (ROS) levels were quantified using standard biochemical and flow cytometric assays. Metabolomic analysis identified 438 significantly altered metabolites in SCLC, including 215 shared between tumor tissues and serum samples, indicating systemic metabolic reprogramming. Pathway enrichment analysis revealed marked activation of glycolysis, glycerophospholipid metabolism, and oxidative phosphorylation. Transcriptomic profiling identified NCAPG as one of the most upregulated genes in SCLC (fold change = 4.7, FDR < 0.001), with elevated expression associated with advanced pathological stage and poor overall survival (HR = 1.47, P = 0.002). Functional depletion of NCAPG in H69 and H446 cells reduced cell viability by 45-60% and increased apoptosis approximately twofold. Seahorse analysis demonstrated a ~ 40% reduction in extracellular acidification rate accompanied by increased oxygen consumption, indicating a metabolic shift from glycolysis toward oxidative phosphorylation. In vivo, NCAPG knockdown suppressed xenograft tumor growth by 58% and significantly downregulated key glycolytic and glycerophospholipid enzymes, including HK2, LDHA, and CHPT1. NCAPG promotes metabolic reprogramming in SCLC by sustaining coupled glycolytic and glycerophospholipid flux, thereby supporting tumor energy production and biosynthetic demands. Targeting this NCAPG-mediated metabolic axis may represent a promising therapeutic strategy for small-cell lung cancer.

Computer vision models for precision poultry farming: A narrative review of behavioral and welfare monitoring studies.

• A sustainable NaOH-activated geopolymer composite was developed using coal fly ash and coconut pith fibers. • The composite exhibited enhanced strength and compactness through optimized NaOH concentration and fiber content. • Advanced characterization (FTIR, XRD, XRF) confirmed the formation of stable aluminosilicate and reinforcing mineral phases. • Machine learning with Bayesian optimization predicted optimal mix parameters, streamlining material design and minimizing resource use. The rapid growth in construction demand has intensified the need for sustainable binders that reduce the environmental burden associated with Portland cement. This study develops a sodium hydroxide (NaOH)-activated coal fly-ash geopolymer composite reinforced with coconut pith, an abundant agricultural by-product, to enhance mechanical performance and material sustainability. A combined experimental and machine learning (ML) framework was implemented to predict and optimize the unconfined compressive strength (UCS) of the composite. Fifteen experimental formulations were used to train ten regression models representing diverse learning biases, and an ensemble surrogate model was subsequently coupled with Bayesian optimization (BO) to identify optimal mix parameters. The BO-predicted formulation (10.8 M NaOH, 3.2 % pith) corresponded closely with the experimentally measured optimum (10 M NaOH, 3 % pith, UCS = 18.32 MPa), confirming the model’s predictive validity. The results demonstrate that integrating ML and BO enables efficient exploration of the compositional space, reducing experimental effort while improving data-driven material design. This hybrid approach establishes a scalable, resource-efficient pathway for developing low-carbon geopolymer binders that valorize agricultural waste and advance sustainable construction technologies.

Reductions of dry atmospheric inorganic nitrogen deposition and carbon uptake in the Yellow Sea of the Northwestern Pacific Ocean for the COVID-19 period.

Rapid self-assembly and signal amplification based on photoactive Z907 for detecting colorectal cancer biomarker vascular endothelial growth factor.

CrossFit® has experienced rapid global growth, yet scientific research often fails to reflect the realities of training and competition in this sport. Studies frequently rely on inconsistent terminology, non-specific testing protocols, and heterogeneous samples, limiting the ecological validity and practical application of findings. This critical commentary aims to evaluate the methodological challenges in CrossFit® research and to highlight the importance of contextualizing scientific inquiry through the perspectives of coaches actively working within the sport. A targeted review of the CrossFit® literature was conducted, with a focus on sampling descriptions, testing protocols, and training monitoring approaches. In addition, semi-structured interviews were conducted with five national and international-level CrossFit® coaches. Analysis of coach responses was used to contextualize gaps in the literature. Coaches reported relying primarily on competition results, training observations, and subjective feedback to guide programming, rather than standardized physical testing or technology-based monitoring. The remote nature of many coach-athlete relationships further complicates data collection and training analysis. CrossFit® research must improve its methodological rigor by adopting sport-specific assessments, clearly defining participant characteristics, and embracing the realities of coaching practice. Integrating qualitative insights and prioritizing ecological validity will help bridge the gap between science and the sport's unique demands.

Increased atmospheric carbon dioxide (CO2) emissions in the atmosphere due to excessive usage of fossil fuels, rapid industrial development and human growth have raised a global interest in the greenhouse effect. CO2 conversion is important not just because it is a greenhouse gas that causes a variety of climate consequences, but also because it is the most abundant source of valuable organic chemicals. Upgrading CO2 into valuable chemicals and materials offers a pathway toward net-zero or even carbon-negative production of fuels, pharmaceuticals, alcohols, plastics, etc. However, current CO2 conversion technologies have the problems of high operational costs, high energy consumption, limited to a few-carbon products, and a risk of secondary pollutants. Microbial electrosynthesis (MES) is a novel microbial electrochemical technology that integrates the metabolic activities or genetic behaviour of microorganisms on electrodes to convert CO2 into organics with electrical energy input. Recent developments in electrode and reactor design, synthetic biology-based strain engineering, and genetic engineering have enhanced the production rates and selectivity of MES. This review explores the transformative potential and recent progress of MES with CO2 upgrading strategies, aiming to identify the determinants of the process and its future research directions.It also highlights the current challenges of MES related to upscaling, long-term stability, selecting optimal microbial strains, achieving net-negative carbon emissions, and other operational limitations that need to be addressed for commercial viability.

Aquaculture is pivotal to global food supply and security, yet its rapid coastal growth in China has reshaped landscapes and seascapes, risking ecosystem services and water quality. We compile an annual, nationwide dataset mapping both land aquaculture ponds and marine aquaculture zones across 1986–2024 using a multi-feature machine-learning workflow on dense Landsat time series. Based on the dataset, we further unraveled spatiotemporal patterns of coastal aquaculture in China. Key findings include: (1) land aquaculture ponds grew from 6578.31 km² in 1986 to a peak of 14,577.01 km² in 2016 and decreased to 10,490.99 km² in 2024. In contrast, marine aquaculture zones continued to expand from 2115.41 km² in 1986 to 5974.34 km² in 2024; (2) coastal aquaculture exhibited a spatial pattern characterized by initial decline followed by expansion from east to west, with land aquaculture ponds declining and recovering from south to north, and marine aquaculture zones showing distinct differences between northern and southern regions; (3) the development of land aquaculture was significantly driven by policies promoting ecological sustainability, while marine pasture development encouraged the expansion of marine aquaculture. The mapped spatiotemporal distributions of coastal aquaculture provide support for sustainable coastal planning and informed management strategies in China.