Search Results (446)

Among brain regions, the cerebellum (CBL) has traditionally been associated with motor control. However, increasing evidence from connectomics and functional imaging has expanded this view, revealing its involvement in a wide range of cognitive and integrative processes. Despite this emerging relevance, the CBL has received comparatively less attention in aging research, which has focused mainly on other central nervous system (CNS) regions such as the neocortex and hippocampus. This review synthesizes the current evidence on glial cell aging across the CNS, emphasizing how cerebellar circuits follow distinct trajectories in terms of cellular remodeling, transcriptional reprogramming, and structural vulnerability. Recent findings highlight that cerebellar astrocytes and microglia exhibit specific signatures related to aging compared to their cortical counterpart, including moderate reactivity, selective immune response, and spatial reorganization. Cerebellar white matter (WM) undergoes structural alteration, suggesting that oligodendroglial cells may undergo region-specific alterations, particularly within WM tracts, although these aspects remain underexplored. Despite the presence of glial remodeling, the CBL maintains a notable degree of structural and functional integrity during aging. This resilience may be the result of the CBL’s ability to maintain synaptic adaptability and homeostatic balance, supported by its highly organized and compartmentalized architecture. A better understanding of the dynamics of cerebellar glial cells in aging may provide new insight into the mechanisms of brain maintenance and identify potential biomarkers for healthy brain aging. Full article

Sustainability represents a significant global challenge, requiring a balance between environmental impact and the use of natural resources. White biotechnology, which uses microorganisms and enzymes for environmentally friendly products and processes, offers promising solutions to support a growing population. Within this context, the yeast Yarrowia lipolytica stands out, so we investigated the generation of biomass from two wild strains (ATCC 9773 and NRRL Y-50997) using different carbon sources. Additionally, protein content and amino acid profiles were assessed via standardized analytical methods to evaluate their potential as nutritional yeasts. Both strains demonstrated potential as nutritional yeasts, with biomass productivities of up to 35.5 g/L and 42 g/L, respectively. The protein content was high, with 58.8% for ATCC 9773 and 58.2% for NRRL Y-50997. Furthermore, the strains presented essential amino acid contents of 62.6% and 41.5%, with lysine being the most abundant amino acid. These findings underscore the versatility and productivity of Y. lipolytica, highlighting its potential for sustainable biotechnological applications such as single-cell protein production. Full article

Introduction: The sodium-to-potassium (Na:K) ratio in the diet is a critical biomarker for cardiovascular and metabolic health, yet global adherence to recommended levels remains poor. Objectives: The objective of this study was to identify dietary determinants of the dietary Na:K ratio and its associations with micronutrient intake and diet quality. Methods: An observational cross-sectional survey was conducted in a representative sample of manufacturing workers through a combined stratified proportional and two-stage probability sampling plan, with strata defined by company size and industrial sector from the state of Rio Grande do Norte, Brazil. Dietary intake was assessed using 24 h recalls via the Multiple Pass Method, with Na:K ratios calculated from quantified food composition data. Diet quality was assessed with the Diet Quality Index-International (DQI-I). Multiple linear regression was used to analyze associations of Na:K ratio with the study variables. Results: The survey was conducted in the state of Rio Grande do Norte, Brazil, in 921 randomly selected manufacturing workers. The sample mean age was 38.2 ± 10.7 years, 55.9% males, mean BMI 27.2 ± 4.80 kg/m². The mean Na:K ratio was 1.97 ± 0.86, with only 0.54% of participants meeting the WHO recommended target (<0.57). Fast food (+3.29 mg/mg per serving, p < 0.001), rice, bread, and red meat significantly increased the ratio, while fruits (−0.16 mg/mg), dairy, white meat, and coffee were protective. Higher Na:K ratios were associated with lower intake of calcium, magnesium, phosphorus, and vitamins C, D, and E, as well as poorer diet quality (DQI-I score: −0.026 per 1 mg/mg increase, p < 0.001). Conclusions: These findings highlight the critical role of processed foods in elevating Na:K ratios and the potential for dietary modifications to improve both electrolyte balance and micronutrient adequacy in industrial workers. The study underscores the need for workplace interventions that simultaneously address sodium reduction, potassium enhancement, and overall diet quality improvement tailored to socioeconomic and cultural contexts, a triple approach not previously tested in intervention studies. Future studies should further investigate nutritional consequences of imbalanced Na:K intake. Full article

The electrical ventricular storm (VES) is defined as multiple sustained ventricular arrhythmias arising in a short time, often refractory to standard antiarrhythmic treatment. The three pillars of the physiopathogenesis of the VES are autonomic dysfunction, triggers, and an altered ventricular substrate. Incessant or highly recurrent ventricular arrhythmia impacts the hemodynamic status by worsening heart failure and increasing mortality. A stepwise, team-based, and tailored therapeutic approach is required to stop ventricular arrhythmia and regain the hemodynamic and electric stability of the patient. The authors focused on describing all currently available therapeutic approaches for VES, intending to establish the best VES therapeutic approaches. This process involves considering the patient’s specific condition, responses to previous treatments, and the potential risks and benefits of each approach. The options range from adjusting antiarrhythmic therapy to reprogramming of the ICD, sedation, epidural anaesthesia, stellate ganglia anaesthetic block, and the use of ECMO or left ventricular assist devices and radiofrequency catheter ablation. Particular attention is paid to the detailed management of genetic primary arrhythmia syndromes like long-QT syndrome, catecholaminergic polymorphic ventricular tachycardia, Brugada syndrome and Wolff–Parkinson–White syndrome, early repolarisation syndrome, right ventricular arrhythmogenic dysplasia, and idiopathic ventricular fibrillation. After overcoming the acute events of VES and obtaining hemodynamic stability, the treatment should shift toward an optimal balance of heart failure therapy, controlling the substrate by revascularisation procedures and resolving other pathology-generating ventricular arrhythmias. This article provides a comprehensive overview of ESV’s current management options using the most efficient strategies known to date. Full article

The impact of five different nets—conventional black, grey, white, and photoselective red and yellow—on the performance of “Gala Redlum” apples was evaluated over a five-year period (2020–2024) and compared to an uncovered control. The cumulative production over this period, ranked from highest to lowest, was as follows: white net (182.4 t/ha), grey net (178.5 t/ha), yellow net (175.8 t/ha), black net (175.5 t/ha), red net (169.5 t/ha), and uncovered control (138.8 t/ha). Vegetative growth results were inconsistent among the studied years. The cumulative photosynthetic rate (An) was slightly higher under the white net (57.9 µmol m⁻² s⁻¹). Fv/Fm values remained closest to optimal levels under the black and grey nets. Netting effectively protected fruits from elevated temperatures, particularly under the grey net, and reduced sunburn damage, with the grey, black, and yellow nets performing best in this regard. Overall profitability was increased by netting: the black net provided the highest cumulative income per hectare over a five-year period (EUR 72,315) alongside the second-lowest sunburn loss (0.69%), while the yellow net also showed strong economic performance (€64,742) with a moderate sunburn loss (1.26%) compared to the red net. Fruit dry matter and soluble solids content (SSC) were generally higher in the uncovered control, whereas °Hue values tended to be higher under the red and yellow nets. In summary, the black and yellow nets provided more balanced microclimatic conditions that enhanced tree performance, particularly under heat stress, leading to improved yield and profitability. However, the economic feasibility of each net type should be evaluated in relation to its installation and maintenance costs. Full article

Automatic Speaker Verification (ASV) systems are increasingly employed to secure access to services and facilities. However, recent advances in speech deepfake generation pose serious threats to their reliability. Modern speech synthesis models can convincingly imitate a target speaker’s voice and generate realistic synthetic audio, potentially enabling unauthorized access through ASV systems. To counter these threats, forensic detectors have been developed to distinguish between real and fake speech. Although these models achieve strong performance, their deep learning nature makes them susceptible to adversarial attacks, i.e., carefully crafted, imperceptible perturbations in the audio signal that make the model unable to classify correctly. In this paper, we explore adversarial attacks targeting speech deepfake detectors. Specifically, we analyze the effectiveness of Basic Iterative Method (BIM) attacks applied in both time and frequency domains under white- and black-box conditions. Additionally, we propose an ensemble-based attack strategy designed to simultaneously target multiple detection models. This approach generates adversarial examples with balanced effectiveness across the ensemble, enhancing transferability to unseen models. Our experimental results show that, although crafting universally transferable attacks remains challenging, it is possible to fool state-of-the-art detectors using minimal, imperceptible perturbations, highlighting the need for more robust defenses in speech deepfake detection. Full article

Lipid metabolism is critical for the physiological activities of signal transduction, metabolic regulation, and energy provision, and Wuzhishan (WZS) pigs are a promising animal model for studying human diseases. However, lipid metabolites in the heart and liver of WZS pigs are indistinct. In this study, we detected gene expression, blood biochemical parameters, and metabolic profiles of hearts and livers of WZS and Large White (LW) pigs, and analyzed correlations between metabolites. The results showed that the fatty acid metabolic process was present in both the heart and liver, and was more dominant in the liver. Although the expression of lipid absorption-related genes of CYP7A1 increased in the liver, CEBPB levels increased in both the liver and heart; the fatty acid beta-oxidation genes RXRA and ACSS2 also showed increased expression. The quantity of metabolites related to lipid synthesis decreased in the liver, heart, and blood for WZS pigs compared to that of LW pigs, indicating a balance of lipid synthesis and breakdown for WZS pigs. Moreover, the lipid metabolites in the liver and heart exhibited strong correlations with each other and showed similar correlations to blood biochemical parameters, respectively. This study declared the balance of lipid metabolism in both the heart and liver, and identified their connections for WZS pigs. Full article

This study evaluated the effects of dietary supplementation with omega-3 polyunsaturated fatty acids from extruded linseed, alone and combined with Padina pavonica algae extract, on growth performance and metabolic status in fattening rabbits. Sixty New Zealand White rabbits were assigned to three groups, as follows: control (CNT), L (5% linseed), and LPP (3.5% linseed + 0.2% algae extract) from weaning (37 days) to slaughter (85 days). Productive performance was assessed through body weight (BW), average daily gain (ADG), feed conversion ratio (FCR), and feed intake (FI). Blood was sampled at weaning, 60 days, and slaughter and analyzed for insulin, leptin, cortisol, thyroid hormones (T3, T4), glucose, and non-esterified fatty acids (NEFAs). The L group showed significantly higher ADG (41.0 ± 1 g/d) and improved FCR (4.1 ± 0.2) compared to LPP (ADG: 37 ± 1 g/d, FCR: 4.6 ± 0.2; p = 0.001). No differences were observed in final BW or FI among groups (p < 0.001). Insulin peaked at 60 days across all groups (p < 0.001), with the LPP group showing the lowest levels (9.8 ± 0.9 µUI/mL; p = 0.043). T3 and T4 increased significantly with age (p < 0.001), and the T3/T4 ratio varied by diet and time (p = 0.005). Cortisol rose only at slaughter (p < 0.001) and negatively correlated with insulin and thyroid hormones. The results suggest that omega-3-rich nutraceuticals can enhance growth performance without disrupting metabolic balance and may modulate specific hormonal responses due to their bioactive compounds. Full article

Background: Reliable and non-invasive methods for assessing welfare in poultry are essential for improving evidence-based welfare monitoring and advancing management practices in commercial production systems. The iris-to-pupil (IP) ratio, previously validated by our group in primates and cattle, reflects autonomic nervous system balance and may serve as a physiological indicator of stress in laying hens. This study evaluated the utility of the IP ratio under field conditions across diverse commercial layer housing systems. Materials and Methods: In total, 296 laying hens (Lohmann Brown, n = 269; White Leghorn, n = 27) were studied across four locations in Canada housed under different systems: Guelph (indoor; pen), Spring Island (outdoor and scratch; organic), Ottawa (outdoor, indoor and scratch; free-range), and Toronto (outdoor and hobby; free-range). High-resolution photographs of the eye were taken under ambient lighting. Light intensity was measured using the light meter app. The IP ratio was calculated using NIH ImageJ software (Version 1.54p). Statistical analysis included one-way ANOVA and linear regression using GraphPad Prism (Version 5). Results: Birds housed outdoors had the highest IP ratios, followed by those in scratch systems, while indoor and pen-housed birds had the lowest IP ratios (p < 0.001). Subgroup analyses of birds in Ottawa and Spring Island farms confirmed significantly higher IP ratios in outdoor environments compared to indoor and scratch systems (p < 0.001). The IP ratio correlated weakly with ambient light intensity (r² = 0.25) and age (r² = 0.05), indicating minimal influence of these variables. Although White Leghorn hens showed lower IP ratios than Lohmann Browns, this difference was confounded by housing type; all White Leghorns were housed in pens. Thus, housing system but not breed was the primary driver of IP variation. Conclusions: The IP ratio is a robust, non-invasive physiological marker of welfare assessment in laying hens, sensitive to housing environment but minimally influenced by light or age. Its potential for integration with digital imaging technologies supports its use in scalable welfare assessment protocols. Full article

Wearable laser Doppler devices are susceptible to complex noise interferences, such as Gaussian white noise, baseline drift, and motion artifacts, with motion artifacts significantly impacting clinical diagnostic accuracy. Addressing the limitations of existing denoising methods—including traditional adaptive filtering that relies on prior noise information, modal decomposition techniques that depend on empirical parameter optimization and are prone to modal aliasing, wavelet threshold functions that struggle to balance signal preservation with smoothness, and the high computational complexity of deep learning approaches—this paper proposes an ISSA-VMD-AWPTD denoising algorithm. This innovative approach integrates an improved sparrow search algorithm (ISSA), variational mode decomposition (VMD), and adaptive wavelet packet threshold denoising (AWPTD). The ISSA is enhanced through cubic chaotic mapping, butterfly optimization, and sine–cosine search strategies, targeting the minimization of the envelope entropy of modal components for adaptive optimization of VMD’s decomposition levels and penalty factors. A correlation coefficient-based selection mechanism is employed to separate target and mixed modes effectively, allowing for the efficient removal of noise components. Additionally, an exponential adaptive threshold function is introduced, combining wavelet packet node energy proportion analysis to achieve efficient signal reconstruction. By leveraging the rapid convergence property of ISSA (completing parameter optimization within five iterations), the computational load of traditional VMD is reduced while maintaining the denoising accuracy. Experimental results demonstrate that for a 200 Hz test signal, the proposed algorithm achieves a signal-to-noise ratio (SNR) of 24.47 dB, an improvement of 18.8% over the VMD method (20.63 dB), and a root-mean-square-error (RMSE) of 0.0023, a reduction of 69.3% compared to the VMD method (0.0075). The processing results for measured human blood flow signals achieve an SNR of 24.11 dB, a RMSE of 0.0023, and a correlation coefficient (R) of 0.92, all outperforming other algorithms, such as VMD and WPTD. This study effectively addresses issues related to parameter sensitivity and incomplete noise separation in traditional methods, providing a high-precision and low-complexity real-time signal processing solution for wearable devices. However, the parameter optimization still needs improvement when dealing with large datasets. Full article

The gut microbiota critically influences lipid metabolism and fat deposition in pigs, processes that underpin pork quality preferences and differentiate the meat traits of Chinese indigenous breeds (fat-type) from those of Western commercial breeds (lean-type). To explore the mechanisms underlying breed-specific fatty acid absorption, we compared the rectal and colonic microbiota and metabolite profiles of Huainan and Large White pigs using 16S rRNA sequencing and untargeted metabolomics. HN pigs exhibited enriched Lactobacillus johnsonii and Lactobacillus amylovorus, along with a significantly higher Firmicutes/Bacteroidetes ratio. Functional predictions further revealed elevated microbial pathways related to glycolysis, pyruvate metabolism, and ABC transporters in HN pigs. Conversely, LW pigs showed increased abundance of potentially pro-inflammatory bacteria and enriched pathways for lipopolysaccharide (LPS) biosynthesis. Metabolites such as 4-ethyl-2-heptylthiazole and picolinic acid were significantly upregulated in HN pigs and served as robust biomarkers (Area Under the Curve, AUC = 1.0),with perfect discrimination observed in both rectal and colonic samples. Integrative analysis identified 52 co-enriched microbial and metabolic pathways in HN pigs, including short-chain fatty acid (SCFA) production, lipid biosynthesis and transport, amino acid metabolism, ABC transporter activity, and the PPAR signaling pathway, supporting a microbiota–metabolite axis that enhances fatty acid absorption and gut immune balance. These findings provide mechanistic insight into breed-specific fat deposition and offer candidate biomarkers for improving pork quality via precision nutrition and breeding. Full article

The Unicost Set Covering Problem (USCP), an NP-hard combinatorial optimization challenge, demands efficient methods to minimize the number of sets covering a universe. This study introduces a binary White Shark Optimizer (WSO) enhanced with V3 transfer functions, elitist binarization, and chaotic maps. To evaluate algorithm performance, we employ the Relative Percentage Deviation (RPD), which measures the percentage difference between the obtained solutions and optimal values. Our approach achieves outstanding results on six benchmark instances: WSO-ELIT_CIRCLE delivers an RPD of 0.7% for structured instances, while WSO-ELIT_SINU attains an RPD of 0.96% in cyclic instances, showing empirical improvements over standard methods. Experimental results demonstrate that circle chaotic maps excel in structured problems, while sinusoidal maps perform optimally in cyclic instances, with observed improvements up to 7.31% over baseline approaches. Diversity and convergence analyses show structured instances favor exploitation-driven strategies, whereas cyclic instances benefit from adaptive exploration. This work establishes WSO as a robust metaheuristic for USCP, with applications in resource allocation and network design. Full article

Owing to its high energy efficiency, regenerative capability, and fast dynamic response, the Electromagnetic Energy-Feeding Shock Absorber has found widespread application in automotive suspension control systems. To further improve thrust control precision, this study presents a sliding mode thrust controller designed using an improved Gray Wolf Optimization algorithm. Firstly, an improved exponential reaching law is adopted, where a saturation function replaces the traditional sign function to enhance system tracking accuracy and stability. Meanwhile, a position update strategy from the particle swarm optimization (PSO) algorithm is integrated into the gray wolf optimizer (GWO) to improve the global search ability and the balance of local exploitation. Secondly, the improved GWO is combined with sliding mode control to achieve online optimization of controller parameters, ensuring system robustness while suppressing chattering. Finally, comparative analyses and simulation validations are conducted to verify the effectiveness of the proposed controller. Simulation results show that, under step input conditions, the improved GWO reduces the rise time from 0.0034 s to 0.002 s and the steady-state error from 0.4 N to 0.12 N. Under sinusoidal input, the average error is reduced from 0.26 N to 0.12 N. Under noise disturbance, the average deviation is reduced from 2.77 N to 2.14 N. These results demonstrate that the improved GWO not only provides excellent trajectory tracking and control accuracy but also exhibits strong robustness under varying operating conditions and random white noise disturbances. Full article

Microscopic cell classification is a fundamental challenge in both clinical diagnosis and biological research. However, existing methods still struggle with the complexity and morphological diversity of cellular images, leading to limited accuracy or high computational costs. To overcome these constraints, we propose an efficient classification method that balances strong feature representation with a lightweight design. Specifically, an Inception-Linear Attention-based Lightweight Vision Transformer (ILViT) model is developed for microscopic cell classification. The ILViT integrates two innovative modules: Dynamic Inception Convolution (DIC) and Contrastive Omni-Kolmogorov Attention (COKA). DIC combines dynamic and Inception-style convolutions to replace large kernels with fewer parameters. COKA integrates Omni-Dimensional Dynamic Convolution (ODC), linear attention, and a Kolmogorov-Arnold Network(KAN) structure to enhance feature learning and model interpretability. With only 1.91 GFLOPs and 8.98 million parameters, ILViT achieves high efficiency. Extensive experiments on four public datasets are conducted to validate the effectiveness of the proposed method. It achieves an accuracy of 97.185% on BioMediTech dataset for classifying retinal pigment epithelial cells, 97.436% on ICPR-HEp-2 dataset for diagnosing autoimmune disorders via HEp-2 cell classification, 90.528% on Hematological Malignancy Bone Marrow Cytology Expert Annotation dataset for categorizing bone marrow cells, and 99.758% on a white blood cell dataset for distinguishing leukocyte subtypes. These results show that ILViT outperforms the state-of-the-art models in both accuracy and efficiency, demonstrating strong generalizability and practical potential for cell image classification. Full article

Background: Pain is a prevalent issue among breast cancer patients and survivors, with a significant proportion receiving hydrocodone for pain management. However, the rescheduling of hydrocodone from Schedule III to Schedule II by the U.S. Drug Enforcement Administration (DEA) in October 2014 raised concerns about potential barriers to opioid access for cancer patients, particularly among vulnerable populations such as dually eligible Medicare–Medicaid beneficiaries and racial/ethnic minorities. Methods: We conducted a retrospective cohort study using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data including 52,306 early-stage breast cancer patients from 2011 to 2019. We employed multivariable logistic regression models with model specification tests to stratify the subgroups and evaluate the differential effects of the policy change by Medicaid dual eligibility and race–ethnicity, while adjusting for other patient demographics, clinical characteristics, and cancer treatments. Results: The rescheduling of hydrocodone was associated with significantly different effects on prescription opioid use across subgroups, with the most pronounced reduction in hydrocodone prescription observed among dual-eligible racial/ethnic minority patients (adjusted odds ratio [AOR] = 0.57; 95% confidence interval [CI]: 0.44–0.74; p < 0.001). Non-dual-eligible patients experienced a smaller reduction in hydrocodone use (AOR = 0.84; 95% CI: 0.78–0.90; p < 0.001). Concurrently, non-hydrocodone opioid use significantly increased among non-dual-eligible non-Hispanic White patients (AOR = 1.29; 95% CI: 1.19–1.40; p < 0.001), suggesting a substitution effect, while smaller non-significant increases were observed among other subgroups. Conclusions: Hydrocodone rescheduling led to the greatest reduction in hydrocodone use among dual-eligible racial–ethnic minority patients. The corresponding increase in non-hydrocodone opioid use was limited to non-dual-eligible non-Hispanic White patients. These findings highlight the need for opioid policies that balance misuse prevention with equitable access to pain relief, particularly among underserved populations. Full article