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H II regions and supernova remnants associated with molecular clouds:A pilot study with the SARAO MeerKAT Galactic Plane Survey
Get PDFMassive stars (mass >8 M⊙) release vast amounts of energy into the interstellar medium through their stellar winds, photoionizing radiation, and supernova explosions. These processes may compress nearby regions, triggering further star formation, but the significance of triggered star formation across the Galactic disc is not well understood. This pilot study combines 1.3GHz continuum data from the South African Radio Astronomy Observatory (SARAO) MeerKAT Galactic Plane Survey (SMGPS) with 13CO (2–1) data from the Structure, Excitation, and Dynamics of the Inner Galactic Interstellar Medium (SEDIGISM) survey to identify and examine molecular clouds associated with HII regions and supernovae remnants (SNRs). We focus on their physical properties and massive star formation potential. We identify 268 molecular clouds from the SEDIGISM tile covering the Galactic plane region 341◦ ≤ ℓ ≤ 343◦ and |b| ≤ 0.5◦, of which 90 clouds (34 per cent) are associated with SMGPS extended sources. Compared to unassociated clouds, we find that associated clouds exhibit significantly higher mean mass (∼9600 M⊙ versus ∼2500 M⊙) and average gas surface density (∼104 M⊙pc-2 versus ∼67 M⊙pc-2), and slightly elevated but comparable virial parameters. We also find that the size–linewidth scaling relation is steeper for associated clouds compared to unassociated clouds. In addition, radio luminosity shows a positive correlation with total complex mass, and the ratio Lradio/ Mcomplex increases with source size, consistent with an evolutionary sequence where expanding HII regions progressively disrupt their natal molecular environment. These findings suggest an enhanced dynamical activity for the associated clouds and support the hypothesis that feedback from massive stars influences molecular cloud properties and may trigger star formation.</p
Oxidative Stress-Driven Transcriptomic Remodeling in Human Astrocytes Reveals Network Signatures Associated with Neurodegenerative and Cardiovascular Processes
Get PDFAstrocytes are central to brain homeostasis, supporting neuronal metabolism, synaptic activity, and the blood–brain barrier. With aging, these glial cells undergo molecular and functional changes that weaken support functions and promote neuroinflammation, contributing to neurodegeneration. Yet the systems-level mechanisms by which astrocytes respond to aging-related stressors remain poorly defined in human models. Because aging also heightens risk for cardiovascular disease, cognitive impairment, type 2 diabetes, and systemic inflammation, clarifying shared astrocytic pathways is critical for understanding brain–body crosstalk. Using an in vitro human astrocyte model exposed to sublethal oxidative stress (10µM H₂O₂) as a proxy for age-related cellular stress, we profiled transcriptomic changes and identified differentially expressed genes across antioxidant defenses, proteostasis, transcriptional regulation, vesicular trafficking, and inflammatory signaling. We then performed network-prioritization analyses on a curated human protein–protein interactome: one seeded with the astrocyte oxidative stress responsive genes and six with phenotype-associated gene sets (Alzheimer’s disease, cardiovascular disease, cognitive impairment, type 2 diabetes, oxidative stress, and inflammation). Intersecting the top 5% scoring genes from each run yielded a 127-gene core shared across all seven, enriched for proteostasis, DNA repair, mitochondrial regulation, and telomere and nuclear envelope maintenance. Structure-guided analyses highlighted vulnerable interfaces, including lamin A/C–lamin B1, α-actinin–filamins, 14-3-3 dimers, and aminoacyl-tRNA synthetase assemblies, where pathogenic variants are predicted to destabilize or aberrantly stabilize protein interactions. Structure-based interface predictions also highlight potential interactions between amyloid precursor protein (APP) and valosin-containing protein (VCP), and between p53 and 14-3-3ζ, potentially linking proteostasis and stress signaling. Together, these analyses identify a conserved astrocyte-centered network signature that may relate neurodegenerative and cardiovascular processes, and prioritize structurally testable candidates for biomarker and intervention hypothesis testing
COMPASS Guidelines for Conducting Welfare-Focused Research into Behaviour Modification of Animals
Get PDFResearchers are increasingly engaged in studies to determine and correct negative welfare consequences of animal husbandry and behaviour modification procedures, not least in response to industries’ growing need to maintain their social licence through demonstrable welfare standards that address public expectations. To ensure that welfare recommendations are scientifically credible, the studies must be rigorously designed and conducted, and the data produced must be interpreted with full regard to conceptual, methodological, and experimental design limitations. This commentary provides guidance on these matters. In addition to, and complementary with, the ARRIVE guidelines that deal with animal studies in general, there is a need for additional specific advice on the design of studies directed at procedures that alter behaviour, whether through training, handling, or restraint. The COMPASS Guidelines offer clear direction for conducting welfare-focused behaviour modification research. They stand for the following: Controls and Calibration, emphasising rigorous design, baseline measures, equipment calibration, and replicability; Objectivity and Open data, ensuring transparency, validated tools, and data accessibility; Motivation and Methods, with a focus on learning theory, behavioural science, and evidence-based application of positive reinforcers and aversive stimuli; Precautions and Protocols, embedding the precautionary principle, minimising welfare harms, listing stop criteria, and using real-time monitoring; Animal-centred Assessment, with multimodal welfare evaluation, using physiological, behavioural, functional, and objective indicators; Study ethics and Standards, noting the 3Rs (replacement, reduction, and refinement), welfare endpoints, long-term effects, industry independence, and risk–benefit analysis; and Species-relevance and Scientific rigour, facilitating cross-species applicability with real-world relevance and robust methodology. To describe these guidelines, the current article is organised into seven major sections that outline detailed, point-by-point considerations for ethical and scientifically rigorous design. It concludes with a call for continuous improvement and collaboration. A major purpose is to assist animal ethics committees when considering the design of experiments. It is also anticipated that these Guidelines will assist reviewers and editorial teams in triaging manuscripts that report studies in this context
A place-based assessment of biodiversity intactness in sub-Saharan Africa
No full textMaintaining biodiversity is central to the sustainable development agenda1. However, a lack of context-specific biodiversity information at policy-relevant scales has posed major limitations to decision-makers2,3. To address this challenge, we undertook a comprehensive assessment of the biodiversity intactness of sub-Saharan Africa4 using place-based knowledge of 200 African biodiversity experts5. We estimate that the region has on average lost 24% of its pre-colonial and pre-industrial faunal and floral population abundances, ranging from losses of <20% for disturbance-adapted herbaceous plants to 80% for some large mammals. Rwanda and Nigeria are the least intact (<55%), whereas Namibia and Botswana are the most intact (>85%). Notably, most remaining organisms occur in unprotected, relatively untransformed rangelands and natural forests. Losses in biodiversity intactness in the worst-affected biomes are driven by land transformation into cropland in grasslands and fynbos (Mediterranean-type ecosystems), by non-agricultural degradation in forests and by a combination of the two drivers in savannas. This assessment provides decision-makers with multifaceted, contextually appropriate and policy-relevant information on the state of biodiversity in an understudied region of the world. Our approach could be used in other regions, including better-studied localities, to integrate contextual, place-based knowledge into multiscale assessments of biodiversity status and impacts.</p
PyamilySeq:Exposing the fragility of conventional gene (re)clustering and prokaryotic pangenomic inference methods
No full textPangenomics has become a central framework for exploring microbial diversity and evolution, enabling researchers to distinguish genes that define shared biological function from those that drive adaptation. However, this relies on clustering genes by sequence similarity, a process that is far less deterministic than often assumed. This study introduces PyamilySeq, a transparent and flexible toolkit designed to diagnose and quantify hidden biases within gene clustering and pangenome inference methodologies. Using PyamilySeq, we can see how clustering thresholds (often hard-coded and poorly documented) and paralog handling can substantially alter gene family composition. Surprisingly, even parameters unrelated to clustering, such as decimal precision (0.8 versus 0.80), output selection, and even CPU and memory allocation, can alter gene family assignments, challenging the assumption that identical clustering thresholds yield consistent results. Furthermore, tools often fail to report biologically meaningful or representative sequences for gene families, undermining downstream analyses. These findings reveal systematic fragilities in gene clustering and pangenome construction and highlight that pangenomics is not merely a data-driven task but a methodological one, where transparency, reproducibility, and interpretability are as critical as biological insight. This work calls for a re-evaluation of how pangenomes are constructed and compared, and advocates for methodologies that make their assumptions explicit and their results verifiable.</p
"Pepita Jiménez" and the British critics (1882-1892):The Soul of Spain
No full textDespite the impact of Juan Valera's Pepita Jiménez on literature since its publication in 1874, it was not universally appreciated by critics in the nineteenth century. The exegesis of the novel diverged, viewing in it a possible mysticism or what could plausibly be considered a mystical satire. While bearing in mind such common criticisms in the context of Spain, this article focuses on the novel's reception by British critics between 1882 and 1892 who saw in the novel the quintessence of mystical-religious form and content, with a praise-worthy moral framework. These opinions differed from the critical views espoused by the Spanish neo-Catholic press. The critical judgments of Wentworth Webster, Edmund Gosse, Arthur Symons, and especially Coventry Patmore, among others, as well as the endorsements by William Howells and James Russell Lowell in the United States, would catapult Anglo-American interest in and recognition of the novel, to such an extent that its defects were buried for the sake of its defense of morality and religion. It would thus be judged as one of the best works of fiction published in Europe since the middle of the nineteenth century, thereby predicting the work's inclusion in the Spanish literary canon (JMGP).</p
Trust-enhanced POI recommendation algorithm using expectation-maximization
No full textPoint-of-interest (POI) recommendation systems have become increasingly important as travelers rely on mobile technologies and location-based social networks to discover new places. However, existing approaches often struggle with static user preferences, inadequate trust modeling, and extreme data sparsity. This paper introduces ExMax, a dynamic trust-enhanced recommendation framework leveraging Expectation-Maximization theory to address these limitations. ExMax employs a novel check-in matrix representation that adapts to evolving user interests, incorporates friendship network information to enhance recommendation quality, and integrates sentiment analysis to capture nuanced satisfaction signals beyond ratings. The framework’s iterative probabilistic model discovers latent features within sparse data, enabling meaningful recommendations even with limited interaction history. The algorithm exhibits time complexity for offline learning, where T represents EM iterations (typically 20–30), |R| denotes observed ratings, F indicates features, and K represents gradient steps. While sparse matrix operations and parallelization potential provide some mitigation, the iterative nature poses scalability challenges for platforms with hundreds of millions of users. Experimental evaluation on Yelp, Gowalla, and Brightkite datasets demonstrates that ExMax performs favorably compared to existing approaches across various metrics. The results suggest that integrating dynamic preference modeling, social trust signals, and contextual information offers a promising direction for location-based recommendation systems, particularly where recommendation quality justifies the computational cost. This work demonstrates how probabilistic modeling can effectively capture the dynamic and social nature of location discovery while acknowledging the inherent computational trade-offs of iterative optimization.</p
Understanding contraception-use intentions among women of reproductive age not currently using contraceptives in sub-Saharan Africa:Key insights from Demographic and Health Surveys
Get PDFBackgroundThis study assesses the prevalence of contraception-use intentions and evaluates the associated factors among non-users in sub-Saharan Africa (SSA).MethodsData from 2014–2023 Demographic and Health Surveys of 30 countries in SSA consisting of 332 986 women aged 15–49 y not already using contraception were used.ResultsThe overall prevalence was 41.18% (95% CI 41.01 to 41.34%). Zimbabwe had the highest prevalence (72.34%; 95% CI 71.11 to 73.57%), whereas Ethiopia had the lowest (15.96%; 95% CI 15.40 to 16.51%). Women aged 25–49 y had lower odds of intending to use contraception compared with those aged 15–19 y, and this was striking among those aged 45–49 y (adjusted OR [AOR]=0.06, 95% CI 0.06 to 0.07). Those with a higher level of education displayed a greater likelihood of intending to use contraception (AOR=1.93, 95% CI 1.82 to 2.05) compared with those with no education. The odds increased with the number of children born, particularly for those with ≥4 children (AOR=1.59, 95% CI 1.52 to 1.67) compared with those with no children.ConclusionsPromoting the use of contraception requires tailored, multi-pronged interventions that account for the diverse sociodemographic, fertility and informational needs of women in this population
Feature Selection for High-Dimensional Imbalanced Class Datasets Using Harmony Search and Kullback-Leibler Divergence
No full textHigh-dimensional imbalanced datasets pose significant challenges in pattern recognition, often leading to overfitting and classifier bias toward majority classes. While numerous feature selection algorithms exist, most struggle to effectively address both high dimensionality and class imbalance simultaneously. This paper introduces Harmony search Kullback-Leibler (HKL), a novel feature selection algorithm that integrates Kullback-Leibler divergence with the Harmony Search metaheuristic to specifically address these dual challenges. HKL establishes an information-theoretic foundation by employing KL divergence as a statistical framework to evaluate feature subsets based on their ability to separate minority and majority classes. Unlike existing Harmony Search variants that operate as class-blind optimizers treating feature selection as a generic optimization problem, HKL fundamentally shifts the paradigm by incorporating direct class distribution awareness into the optimization process. The algorithm implements a dual optimization approach that simultaneously balances classification performance metrics with class distribution divergence measures. This design specifically enhances minority class discrimination by prioritizing features that maximize the divergence between class distributions, ensuring that selected features provide discriminative power for underrepresented classes rather than simply favoring the majority class. Experimental validation across multiple high-dimensional biomedical datasets demonstrates that HKL consistently outperforms existing state-of-the-art methods in terms of AUC and G-mean metrics, with particular improvements for minority class classification. The algorithm achieves optimal performance while using substantially reduced feature subsets, often requiring only a quarter to half of the original features to maintain or exceed baseline classification accuracy. Statistical significance testing confirms that these performance improvements represent genuine algorithmic advantages rather than random variation. The proposed approach offers an effective solution to both dimensionality reduction and class imbalance challenges, providing a valuable tool for complex classification tasks across various domains
H II regions and supernova remnants associated with molecular clouds:A pilot study with the SARAO MeerKAT Galactic Plane Survey
No full textMassive stars (mass >8 M⊙) release vast amounts of energy into the interstellar medium through their stellar winds, photoionizing radiation, and supernova explosions. These processes may compress nearby regions, triggering further star formation, but the significance of triggered star formation across the Galactic disc is not well understood. This pilot study combines 1.3GHz continuum data from the South African Radio Astronomy Observatory (SARAO) MeerKAT Galactic Plane Survey (SMGPS) with 13CO (2–1) data from the Structure, Excitation, and Dynamics of the Inner Galactic Interstellar Medium (SEDIGISM) survey to identify and examine molecular clouds associated with HII regions and supernovae remnants (SNRs). We focus on their physical properties and massive star formation potential. We identify 268 molecular clouds from the SEDIGISM tile covering the Galactic plane region 341◦ ≤ ℓ ≤ 343◦ and |b| ≤ 0.5◦, of which 90 clouds (34 per cent) are associated with SMGPS extended sources. Compared to unassociated clouds, we find that associated clouds exhibit significantly higher mean mass (∼9600 M⊙ versus ∼2500 M⊙) and average gas surface density (∼104 M⊙pc-2 versus ∼67 M⊙pc-2), and slightly elevated but comparable virial parameters. We also find that the size–linewidth scaling relation is steeper for associated clouds compared to unassociated clouds. In addition, radio luminosity shows a positive correlation with total complex mass, and the ratio Lradio/ Mcomplex increases with source size, consistent with an evolutionary sequence where expanding HII regions progressively disrupt their natal molecular environment. These findings suggest an enhanced dynamical activity for the associated clouds and support the hypothesis that feedback from massive stars influences molecular cloud properties and may trigger star formation.</p