Defining the Problem Hypertension (HTN) is a critical public health issue and a leading risk factor for cardiovascular disease (CVD) and stroke, driving significant global morbidity and mortality (GBD 2017 Causes of Death Collaborators, 2018; Mills, Stefanescu, & He, 2020). The relationship between HTN and CVD is well documented, as elevated blood pressure damages arterial walls, leading to heart failure if untreated (American Heart Association, 2023). In the United States, nearly half of adults, or about 47%, are affected by HTN or rely on medication to manage it (Centers for Disease Control and Prevention, 2019). The economic impact is profound; HTN is the most costly aspect of CVD, with expenses stemming from hospitalizations, medications, and reduced productivity (Heidenreich et al., 2011).

Alzheimer‘s disease, the most common type of dementia, is a serious neurodegenerative disorder for which there is currently no cure. The research was carried out in order to determine the significance of Mir 30c, and Mir 155 in serving as a diagnostic biomarker .The microarray data set GSE138260 was obtained from the GEO database hosted by the NCBI. Blood samples were collected from 30 individuals with Alzheimer‘s disease and 30 individuals without the condition. RNA was extracted from the serum samples, converted to cDNA, and then the real-time PCR method was used to measure the expression level of Mir 30c and Mir 155 . The study‘s finding indicated that the copy number levels of Mir 30c and Mir 155 were increased. Bioinformatics analysis revealed that these microRNA target pathways are associated with Alzheimer‘s disease. The cut-off value for this Mir´s demonstrates the trade-off between sensitivity and specificity in diagnostic testing.

Incipient species often coexist in sympatry before complete reproductive isolation has evolved between them. How do they persist in the face of gene flow? The challenge is more extreme than ordinary coexistence not only because gene flow erodes and recombines genetic differences, but also because selection against hybrids can destabilize population sizes. We estimated gene flow and selection against hybrid genotypes between sympatric limnetic and benthic species of threespine stickleback in two British Columbia lakes. First-generation hybrids are present at a rate of about 2%. To estimate selection, we compared the frequency distribution of ancestry proportions between juvenile and adult samples. We also used genomic simulation with assortative mating in an ecological model to determine how much selection is required to reproduce observed genotype frequencies. Results from the two approaches were comparable and yielded estimated selection coefficients S against the least fit ancestry proportion between 0.5 – 0.6. Surprisingly, selection was found to be only slightly weaker than that leading readily to collapse and fusion in our simulations, suggesting that sympatric stickleback species are close to a coexistence boundary. Moderately strong selection appears to be required for coexistence with even low levels of gene flow. We suggest that ecological differences between species play an enhanced role in coexistence when gene flow occurs, which may help to explain why we have so many cases of young sympatric species with large ecological and phenotypic differences.

Fitness surfaces offer a valuable tool for bridging the gap between captive breeding programs and wild populations. By quantifying the relationship between individual phenotypes for a trait and their reproductive success in captive and wild settings, fitness surfaces can help identify the impacts of captive selection and phenotypic plasticity. Measuring fitness surfaces in captive and wild populations would allow us to predict the success of reintroduction efforts and help inform the selection of release candidates. Overall, the inclusion of fitness surface estimates into conservation breeding programs increases the effectiveness of reintroduction efforts and should help improve our understanding of evolution at the interface of human management and wildlife populations.

The global shift toward renewable energy has necessitated the development of efficient power generation methods to address the intermittency and variability of sources like solar photovoltaic (PV) systems. The performance of PV systems is significantly influenced by Maximum Power Point Tracking (MPPT) algorithms, which ensure optimal power extraction. This study compares two widely adopted MPPT algorithms: Perturb and Observe (P&O) and Incremental Conductance (IC). Both methods are tested under varying environmental conditions, such as irradiance and temperature, using MATLAB/Simulink simulations to assess their efficiency and accuracy in tracking the Maximum Power Point (MPP). While P&O is simpler and commonly used in commercial systems, it oscillates around the MPP, leading to potential power loss. In contrast, the IC algorithm provides greater precision but requires higher computational resources. Simulation results showed that both algorithms effectively tracked the MPP under controlled conditions, though IC demonstrated a more stable performance during rapid changes in irradiance and temperature. This research offers practical insights into the suitability of these MPPT algorithms for specific PV applications, contributing to improved efficiency in renewable energy systems.

In high-frequency (HF) power converters, precise dv/dt control is critical for ensuring system stability, efficiency, and electromagnetic compatibility. Conventional discrete capacitor-based closed-loop dv/dt sensors often face challenges related to limited gain, bandwidth, and reliability, particularly when controlling devices with low reverse transfer capacitance ( C RSS ). This paper proposes a discrete synchronous capacitive dv/dt sensor (syncFET dv/dt sensor) that enhances closed-loop dv/dt control performance in megahertz (MHz) power converter applications by integrating a syncFET with an active gate driver (AGD), leveraging GaN technology to improve feedback gain without the design complexities of integrated circuits. Experimental validation using a 10 MHz, 24 V buck converter demonstrates a reduction in the turn-on dv/dt of the low-side switch from -15 V/ns to -10 V/ns with a 0.1 pF sensor capacitor, achieving nanosecond-level response times for reliable dv/dt regulation during switching transients. Additionally, PSpice simulations confirm the syncFET dv/dt sensor’s capability to generate stronger feedback currents, and when coupled with the AGD, reduce the gate current for dv/dt control while maintaining system stability. By harnessing GaN technology, the proposed sensor supports the high switching frequency requirements of MHz power converters, improving both efficiency and control reliability.

The increasing adoption of wearable devices, point-of-care diagnostics, and telemedicine has the potential to transform primary care. However, their effectiveness ultimately depends on whether patients act upon the data they generate. This challenge extends beyond technology into the realm of human behavior, as seen in the persistent rise of obesity despite widespread access to weight-monitoring tools. The Health Belief Model and Transtheoretical Model highlight that awareness alone is insufficient to drive behavior change—psychological, social, and economic barriers often prevent individuals from progressing to action. Similarly, Social Cognitive Theory emphasizes the role of self-efficacy and social support in sustaining health-related behaviors. Studies indicate that wearable devices increase awareness but do not necessarily lead to long-term behavior change without additional interventions, such as structured programs, health coaching, and social reinforcement. Insights from behavioral economics, including nudging techniques and motivational interviewing, further suggest that the way health choices are framed can significantly impact patient adherence. To bridge the gap between awareness and action, primary care must integrate behavioral support with health technologies, ensuring that patients receive not only data but also the motivation and resources needed to implement meaningful lifestyle changes.

not-yet-known not-yet-known not-yet-known unknown Ecological theory assumes generally that predators hunt as solitary individuals, an assumption that is violated in social predators. We applied a behaviorally-based group foraging model, predicting that group hunting should depress lion fitness due to reduced searching efficiency. Hence, hunting groups > 4 females should be unsustainable. So how do prides of a dozen or more lions persist? Here we show that females in large prides typically fragment into small hunting groups well approximated by an exponential distribution of group size typical of fission-fusion social systems. As a result, the average size of hunting groups falls well within sustainable limits. Our models suggest that fragmentation into smaller groups has a strongly stabilizing effect on predator-prey interactions, allowing lions to persist even when living in large prides in the highly productive Serengeti ecosystem, despite the substantial fitness cost of social foraging.

not-yet-known not-yet-known not-yet-known unknown Ongoing climate change is increasing the flammability of vegetation, ensuing intensified fire episodes in the boreal forest of eastern North America. Fire activity of the last decades suggests that we are probably at a tipping point in terms of fire regimes, raising new questions about the impact of these fires on the biodiversity and structure of the boreal forest. By integrating a compelling paleo-dataset (charcoal, pollen, chironomids, testate amoebae) with model simulations of vapor pressure deficit (VPD) and plant-available soil water (ASW) spanning the last 8,000 years, we demonstrate that drier spring conditions over the past 4,000 years led to fewer but larger and more severe fire episodes, peaking during the last 250 years. This shift in the fire regime fostered a parallel rise in fire-prone conifer species across landscapes, notably Pinus banksiana Lamb. (jack pine). We infer that the predicted increase in VPD along with decrease in ASW triggered by climate change will alter the fire regime and will amplify the transition towards more pyrogenic vegetation within the boreal forest of eastern North America

not-yet-known not-yet-known not-yet-known unknown Pleistocene glaciations have shaped much of the population divergence events in the coniferous forests of North America. However, while the evidence for forest fragmentation and population divergence associated with glacial cycles is well-established in western North America, whether glaciation has served a similar role in the boreal forests of eastern North America is unclear. Here, we present the first analyses for an avian hybrid zone in boreal eastern North America between two subspecies of Palm Warblers (Setophaga palmarum). Using both genomic and plumage datasets, we characterize the divergence history of the two subspecies and relate our findings to the larger biogeographic patterns in the region. The Palm Warbler subspecies diverged in the Pleistocene (around 775 KYA) and appears to have experienced near-continuous gene flow since initial splitting with little evidence for reproductive isolation. Demographic modelling indicates that following divergence, the western subspecies expanded eastwards in breeding range and displaced the genetic ancestry of its eastern counterpart, resulting in the current hybrid zone. The timing and patterns of divergence for the Palm Warbler subspecies is largely congruent with the sole other known case of avian divergence in the region, which likely reflects a shared biogeographic history involving multiple eastern boreal refugia. However, the apparent ongoing collapse of the Palm Warbler subspecies post-divergence suggests that the differentiation generated through these eastern refugia were likely not sufficient in establishing strong reproductive isolation, which perhaps explain why speciation events have been relatively rare in the eastern boreal forests of North America.

The generation and maintenance of biodiversity are driven by population divergence and speciation. We investigated divergence, gene flow, and speciation in Beringia, a region at the top of the North Pacific Ocean with a history of dramatic landscape alteration through Pleistocene glacial cycles. These cycles repeatedly split and connected the Asian and North American continents, separating and reconnecting avian populations. Glacial refugia within Beringia also isolated some populations for a time before potentially enabling them to reunite during interglacial periods. Prior work suggests gene flow plays an important role in the divergence of Beringian birds. To improve our understanding of the generation of avian diversity in Beringia, we tested models of demographic history in 11 lineages from five avian orders (Anseriformes, Gaviiformes, Charadriiformes, Piciformes, and Passeriformes) using population-, subspecies-, and species-level pairwise comparisons. We sequenced an average of 3,710 ultraconserved element (UCEs) loci from the nuclear genomes of these taxa to examine genetic differentiation and test models of divergence through diffusion analysis for demographic inference (δaδi). All of the inferred best-fit models of divergence included gene flow. Together with prior work, this corroborates that divergence with gene flow is the predominant mode of divergence and speciation in Beringian birds.

Urbanization presents unique environmental pressures that drive rapid evolutionary adaptations, particularly in species inhabiting fragmented and anthropogenic landscapes. In this study, we investigate the genomic differentiation between urban and non-urban populations of Anolis carolinensis, focusing on two main aspects: (1) the effect of habitat fragmentation on inbreeding and mutational load (2) genomic adaptation to the urban habitat. Using genome-wide scans of selection and analyses of genetic diversity, we identify key genomic regions exhibiting significant divergence between urban and non-urban populations. These regions are enriched for genes associated with immunity, behavior, and development, suggesting that urban adaptation is polygenic and involves traits related to stress response, locomotion, and thermoregulation. By comparing candidate genes linked to urban adaptation in another Anolis species, A. cristatellus, we detect potential signatures of convergent evolution in loci involved in immune response and behavior, further supporting the hypothesis that urban environments exert similar selective pressures across species. These results provide evidence for polygenic adaptation and highlight the complexity of urban evolution. Future work with denser population sampling and time-series data will be essential to confirm the role of urban selective pressures and track the genetic dynamics of urban populations over time.

Foliar fungal endophytes are microbial symbionts that inhabit the leaves of nearly all plant species and can significantly influence host performance, but the relative influence of dispersal limitation, host filtering, and environmental variation on endophyte communities remains poorly understood. We co-sampled fungal endophyte communities from three herbaceous plant species across a complex landscape of the Sierra Nevada, California spanning 100 km where environmental and spatial distance are largely uncorrelated. Our results reveal that across all three host taxa, spatial distance was the primary driver of endophyte community composition, with similarity declining with distance regardless of environmental variation. By contrast, host identity and environmental factors were the predominant predictors of endophyte diversity, with hosts showing differing responses to environmental gradients of temperature, precipitation, solar radiation, and vegetation cover. While most fungal taxa were unique to a single host species at the site level, host filtering was inconsistent at larger spatial scales. Overall, our study reveals that spatial, environmental, and host factors drive different aspects of foliar fungal endophyte community structure, with interactive effects highlighting the context-dependent nature of microbial community assembly.

not-yet-known not-yet-known not-yet-known unknown Background: Cardiovascular diseases are the main causes of mortality and functional disability. It is important to understand that hemodynamic and blood pressure control mechanisms help to understand the origin and development of cardiovascular dysfunctions, since the baroreflex mechanism influences vascular sympathetic control. The objective of this review was to seek an answer to the following guiding question: “Can vascular hemodynamic dysfunction interfere, depending on the location of the alteration, with heart rate variability?” Methodology: This is a review of the English-language literature on vascular dysfunctions that can lead to hemodynamic changes and their impact on cardiac autonomic modulation using the strategy: ((”Vascular Diseases”) AND (“heart rate variability”) AND (hypertension) AND (”Middle Aged” OR Elderly OR Aged)) inserted in the EBSCO, EMBASE, PUBMED, SCIENCE DIRECT, SCOPUS, WEB OF SCIENCE databases in the period between December 2023 and February 2024, which resulted in 2804 articles found, published between 2018 and 2023. Results: The studies described here related arterial dysfunction and low heart rate variability; hemodynamic disturbance as a source of changes in heart rate variability and sympathetic imbalance; vascular obstructive disorders and cardiac autonomic dysfunction. Other results were presented where they clarify that endothelial dysfunction and blood pressure also have an impact on autonomic dysfunction. However, it was identified by one article that the difference in interarm pressure is not associated with dysfunction in cardiac autonomic control. Conclusion: changes in sympathovagal balance detected through the assessment of heart rate variability may be a predictor of changes in vascular dynamics.

TitleSuccessful Treatment of Infantile Medulloblastoma and Concurrent Left Medial Temporal Lobe Arteriovenous Malformation

Embryonal rhabdomyosarcoma (RMS) of the nasosinusal region is an uncommon pediatric malignancy, with an estimated incidence of 4.3 cases per million children annually. This report presents a case of embryonal nasosinusal RMS in a 12-year-old child managed at our institution, alongside a review of the literature. We discuss the epidemiology, diagnostic challenges, and therapeutic approaches associated with this rare tumor, providing insights to enhance clinical management and improve prognosis in pediatric patients.

Purpose: To evaluate the safety and efficacy of multimodality treatment with vincristine, actinomycin-D, and cyclophosphamide (VAC) therapy, surgery, and radiotherapy according to the U.S. Intergroup Rhabdomyosarcoma Study IV (IRS-IV), and to establish a central review system and standard treatment for intermediate-risk pediatric rhabdomyosarcoma in Japan. Patients and methods: The JRS-I was a single-arm, phase II trial for intermediate-risk rhabdomyosarcoma treatment with open enrollment from June 2004 to March 2009. Patients received 12 cycles of VAC every 3 weeks for 42 weeks, with local therapy beginning after week 12. The endpoints were progression-free survival (PFS), overall survival (OS), and incidence of hepatic veno-occlusive disease (VOD). Results: Thirty-one eligible patients were enrolled, and at a median follow-up of 5.2 years, the 3-year PFS and OS for patients were 74.2% ± 7.9% (95% CI 55.0%-86.2%) and 90.3% ± 5.3% (95% CI 72.9%-96.8%), respectively. VOD occurred in 3 (8%) of the 40 evaluable patients, but all recovered, and there were no deaths. Conclusion: The VAC regimen for intermediate-risk rhabdomyosarcoma with the first central review system in Japan is safe and feasible, and these findings can be positioned as basic data for improving treatment outcomes in Japan.

A retrospective analysis was conducted on the clinical data and dynamic monitoring of asparaginase activity in two pediatric patients with high-risk acute lymphoblastic leukemia (ALL) who developed hypersensitivity reactions following pegaspargase (PEG-asp) treatment. Case 1: A 4-year-old male developed lip swelling, abdominal pain, and dyspnea after the fourth dose of PEG-asp, but asparaginase activity remained >100 U/L, suggesting a non-antibody-mediated mechanism. Case 2: A 1-year-old male presented with rash, vomiting, and mucosal edema after the fourth dose, accompanied by a rapid decline in asparaginase activity (<100 U/L from day 7 onward), confirming antibody-mediated hypersensitivity. This report highlights the utility of asparaginase activity monitoring in distinguishing hypersensitivity mechanisms and guiding therapeutic decisions, such as switching enzyme formulations.

Considerable variation exists in the literature relating to vocal cord and/or ventricle (VC/V) surgical procedures, as an adjunct to laryngoplasty or as a sole treatment for laryngeal hemiplegia. This includes whether the procedure is necessary, which side to operate on, unilateral or bilateral procedure, which exact structure to remove, the timing as related to the laryngoplasty if an adjacent, and the complications resulting from the procedure elected, such as contributing to aspiration and dysphagia. This paper describes a novel approach, which is waiting until the final abduction post laryngoplasty is ascertained and then electing to operate only when noise and athletic performance suggests that a VC/V procedure is indicated. The novel technique was to use a modified punch intranasally in the standing horse under endoscopic guidance, similarly to an epiglottic entrapment hook, to transect the left vocal cord only in a minimalistic approach. This was ultimately successful in minimising the respiratory noise and returning the horse to competitive form 2 ½ years after a laryngoplasty, that had gradually lost abduction and settled in a grade 4 (Dixon)/Grade B (Rakestraw) position. A first unsuccessful partial transection of the leading edge was followed by a second total transection which appeared as apparently successful. This is a low-cost technique, within the realms of many practitioners, that deserves more evaluation both post laryngoplasty and as a sole treatment for laryngeal hemiplegia .

Background: Lung cancer remains a leading cause of cancer-related mortality globally, underscoring the urgent need for the identification of novel biomarkers and therapeutic targets. This study is aimed at investigating the expression and prognostic significance of NAD+ metabolism-related genes in lung cancer patients. Methods: Gene expression profiles, clinical data, and single nucleotide mutation data were sourced from the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were identified utilizing the R package ’limma’ based on a criterion of |log2Fold Change| > 0.5 and an adjusted P-value < 0.05. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were conducted with the aid of the ’clusterProfiler’ R package. Prognostic models were developed through univariate Cox regression and LASSO Cox regression, and their validity was confirmed through Kaplan-Meier survival analysis. A nomogram was constructed by integrating clinical data with risk scores. Furthermore, competing endogenous RNA (ceRNA), RNA-binding protein (RBP)-mRNA, and mRNA-transcription factor (TF) networks were established. Results:Our analyses identified 1743 differentially expressed genes (DEGs) between lung cancer and normal samples, with 945 genes upregulated and 798 genes downregulated. Among the NAD+ metabolism-related DEGs, 324 were upregulated and 15 were downregulated. Intersection analysis revealed 29 key genes, which are involved in processes such as negative regulation of immune system processes. The prognostic model identified four key genes—CENPF and HJURP—as significantly associated with overall survival (OS). The construction of competing endogenous RNA (ceRNA), transcription factor (TF), and RNA-binding protein (RBP) networks elucidated potential regulatory mechanisms involving these genes. Analyses of tumor mutation burden (TMB) and immune checkpoint activity indicated higher TMB and differential expression of immune checkpoints in high-risk groups. Drug sensitivity analysis revealed potential chemotherapeutic agents tailored to different risk groups, and DGIdb identified drug-gene interactions, particularly between SLC34A2 and LIFASTUZUMAB VEDOTIN. Conclusion: This study systematically explored the expression patterns and prognostic significance of NAD+ metabolism-related genes in lung cancer, providing valuable insights for personalized treatment strategies.

Objetive: Cancer is considered one of the main health problems worldwide and patients undergo sometimes aggressive treatments that can lead to relapses or readmissions that decimate their quality of life. The aim of this research was to know the prevalence and characteristics of resilience in cancer patients and how the psychological and social factors could influence the perception of the disease. Methods: Participants with different diagnosis of cancer were recruited (N = 61). Resilience was measured with the 14 items (RS-14) Wagnild and Young Resilience Scale, anxiety with Hospital Anxiety and Depression Scale and Assessment of the patient’s social environment wit APGAR score. Results: 50.8% women aged 35 to 82 years, all diagnosed with cancer (breast 18%, lung 29.5%, colon 9.8%, among others). Of these, 11.5% had not received oncological treatment, and 93.4% underwent surgery. The majority were non-smokers (82%) and 57.4% were retired. Respiratory (24.6%) and cardiovascular (23%) comorbidities were the most prevalent. In a survey, 54.1% reported having family members with cancer, and 36.1% indicated that a lack of free time negatively impacted their quality of life. The correlation analysis revealed a non-significant negative relationship between resilience and age (r=-0.023; p=0.863) and a positive correlation with BMI (r=0.088; p=0.510). Anxiety was associated with a 70% decrease in the likelihood of resilience (OR=0.72). Conversely, depression (OR=1.22) and APGAR scores (OR=1.12) were linked to a 20% increase in the likelihood of resilience. Conclusion: Our results support the idea that resilience plays a crucial role in managing mental health and quality of life in cancer patients.

How do dictators successfully counterbalance (fragment their coercive apparatus) despite the significant risk of military retaliation? Drawing on recent insights that the timing of coup-proofing is essential to its success, I argue that dictators are more likely to increase counter-balancing efforts in the aftermath of failed coups. I test this proposition in a difference-in-differences framework, using novel data on coups and counterbalancing. I find a statistically significant, albeit moderate effect of coup failure. I substantiate my analysis with two illustrative examples from Sierra Leone and Turkey that probe the plausibility of my theorized mechanism. My findings contribute to the growing literature on the effects of failed coups by opening up the discussion on their long-term structural consequences for the dictator’s security apparatus.

This study investigates how extremist insurgencies in one state can intensify social conflict in a bordering state, focusing on the 2015 Burkina Faso insurgency and its impacts on northern Ghana. Building on past research, we theorize four pathways that can link insurgency to social conflict across the border. We use a mixed-methods approach, combining synthetic control models, fixed-effects panel data analyses, and extensive fieldwork across multiple communities, and find clear support for two pathways: insurgents using Ghana as a place for obtaining resources and diverted security forces creating vacuums exploited by bandits. The findings show that research and policy should consider more the interaction across multiple types of violence and varied geopolitical spaces in other susceptible world regions.

Accurate estimation of parameter is the core of data analysis in contemporary decision making in real life domain. The pursuit for reliable, cost efficient and data driven tools for data analysis is constant endeavor in statistical community. This research studies the optimization of finite population mean estimate within the framework of stratified ranked set sampling (SRSS), using auxiliary information and machine learning (ML) techniques. The emphasis is on increasing efficiency, especially in the context of complex datasets such as those resulting from COVID-19 epidemiological investigations. The primary aim of this paper is the development of efficient formulation of mean estimator of finite population under ranked set sampling using auxiliary information and stratification using machine learning methods, such as K-means clustering. This paper explores these developments to provide a robust and efficient methodology for estimating population mean in complex, real-world scenarios. The derivation of bias and mean squared error has been done to theoretically validate our methodology. To empirically validate the performance of the proposed estimators, we have used real data sets of different nature including COVID-19 as case study. For stratification using K-means clustering we have considered the COVID-19 data. through simulation study subject to varying conditions, the stability of the proposed estimators has been assessed. the finding suggests the significant contribution of our methodology to statistical community in making reliable inferences and well-informed decisions.