Search Results (1,478)

Red blood cell (RBC), accounting for approximately 45% of total blood volume, are essential for oxygen delivery and carbon dioxide removal. Their unique biconcave morphology, high surface area-to-volume ratio, and remarkable deformability enable them to navigate microvessels narrower than their resting diameter, ensuring efficient microcirculation. RBC deformability is primarily determined by membrane viscoelasticity, cytoplasmic viscosity, and cell geometry, all of which can be altered under various physiological and pathological conditions. Reduced deformability is a hallmark of numerous diseases, including sickle cell disease, malaria, diabetes mellitus, sepsis, ischemia–reperfusion injury, and storage lesions in transfused blood. As these mechanical changes often precede overt clinical symptoms, RBC deformability is increasingly recognized as a sensitive biomarker for disease diagnosis, prognosis, and treatment monitoring. Over the past decades, diverse techniques have been developed to measure RBC deformability. These include single-cell methods such as micropipette aspiration, optical tweezers, atomic force microscopy, magnetic twisting cytometry, and quantitative phase imaging; bulk approaches like blood viscometry, ektacytometry, filtration assays, and erythrocyte sedimentation rate; and emerging microfluidic platforms capable of high-throughput, physiologically relevant measurements. Each method captures distinct aspects of RBC mechanics, offering unique advantages and limitations. This review synthesizes current knowledge on the pathophysiological significance of RBC deformability and the methods for its measurement. We discuss disease contexts in which deformability is altered, outline mechanical models describing RBC viscoelasticity, and provide a comparative analysis of measurement techniques. Our aim is to guide the selection of appropriate approaches for research and clinical applications, and to highlight opportunities for developing robust, clinically translatable diagnostic tools. Full article

The bidirectional flow of population between urban and rural areas, not limited to rural-to-urban migration, influences the sustainable development of agricultural economic resilience in multiple ways. This study employs panel data from 31 provincial-level regions in China spanning 2017–2022 to comprehensively examine the impact of bidirectional urban–rural mobility on diverse dimensions of agricultural economic resilience, while further investigating its underlying mechanisms. Benchmark regression shows that the bidirectional urban–rural mobility exerts a suppressive effect on the agricultural economic resilience. Mechanism analyses indicate that such mobility contributes to strengthening agricultural economic resilience by catalyzing land-scale operational efficiency and amplifying labor productivity gains and that the advancement of smart agriculture technologies effectively mitigates the inhibitory impacts of bidirectional mobility on agricultural economic resilience. Furthermore, according to heterogeneity analysis, the mobility exerts a suppressive effect on the resistance (Res.) and reconstruction (Recons.) of agricultural economic resilience, while concurrently enhancing its restoration (Rest.). Meanwhile, the bidirectional mobility has significantly impeded the agricultural economic resilience of the eastern, central, and western regions, as well as the primary grain-producing areas, production and marketing balance areas, and the primary grain-selling areas. Further investigation reveals that the reverse mobility has a positive effect on the resistance but a negative effect on its restoration and reconstruction. Full article

Background: Regional cerebral blood flow (rCBF) is a putative biomarker for neuropsychiatric disorders, including major depressive disorder (MDD). Methods: Here, we show that rCBF can be predicted from resting-state functional MRI (rsfMRI) at the voxel level while correcting for partial volume averaging (PVA) artifacts. Cortical patterns of MDD-related CBF differences decoded from rsfMRI using a PVA-corrected approach showed excellent agreement with CBF measured using single-photon emission computed tomography (SPECT) and arterial spin labeling (ASL). A support vector machine algorithm was trained to decode cortical voxel-wise CBF from temporal and power-spectral features of voxel-level rsfMRI time series while accounting for PVA. Three datasets, Amish Connectome Project (N = 300; 179 M/121 F, both rsfMRI and ASL data), UK Biobank (N = 8396; 3097 M/5319 F, rsfMRI data), and Amen Clinics Inc. datasets (N = 372: N = 183 M/189 F, SPECT data), were used. Results: PVA-corrected CBF values predicted from rsfMRI showed significant correlation with the whole-brain (r = 0.54, p = 2 × 10⁻⁵) and 31 out of 34 regional (r = 0.33 to 0.59, p < 1.1 × 10⁻³) rCBF measures from 3D ASL. PVA-corrected rCBF values showed significant regional deficits in the UKBB MDD group (Cohen’s d = −0.30 to −0.56, p < 10⁻²⁸), with the strongest effect sizes observed in the frontal and cingulate areas. The regional deficit pattern of MDD-related hypoperfusion showed excellent agreement with CBF deficits observed in the SPECT data (r = 0.74, p = 4.9 × 10⁻⁷). Consistent with previous findings, this new method suggests that perfusion signals can be predicted using voxel-wise rsfMRI signals. Conclusions: CBF values computed from widely available rsfMRI can be used to study the impact of neuropsychiatric disorders such as MDD on cerebral neurophysiology. Full article

Introduction: Learning disabilities (LD) compromise academic achievement in approximately 5–10% of school-aged children, yet the neurophysiological signatures that could facilitate earlier detection or stratification remain poorly defined. Resting-state electroencephalography (rs-EEG) offers millisecond resolution and is cost-effective, but its findings have never been synthesized systematically across pediatric LD cohorts. Methods: Following a PROSPERO-registered protocol (CRD420251087821) and adhering to PRISMA 2020 guidelines, we searched PubMed, Embase, Web of Science, Scopus, and PsycINFO through 31 March 2025 for peer-reviewed studies that recorded eyes-open or eyes-closed rs-EEG using ≥ 4 scalp electrodes in children (≤18 years) formally diagnosed with LD, and compared the results with typically developing peers or normative databases. Four reviewers independently screened titles and abstracts, extracted data, and assessed the risk of bias using ROBINS-I. Results: Seventeen studies (704 children with LD; 620 controls) met the inclusion criteria. The overall risk of bias was moderate, primarily due to small clinic-based samples and inconsistent control for confounding variables. Three consistent electrophysiological patterns emerged: (i) a 20–60% increase in delta/theta power over mesial-frontal, fronto-central and left peri-Sylvian cortices, resulting in markedly elevated θ/α and θ/β ratios; (ii) blunting or anterior displacement of the posterior alpha rhythm, particularly in language-critical temporo-parietal regions; and (iii) developmentally immature connectivity, characterized by widespread slow-band hypercoherence alongside hypo-connected upper-alpha networks linking left-hemisphere language hubs to posterior sensory areas. These abnormalities were correlated with reading, writing, and IQ scores and, in two longitudinal cohorts, they partially normalized in parallel with academic improvement. Furthermore, a link between reduced posterior/overall alpha and neuroinflammation has been found. Conclusions: Rs-EEG reveals a robust yet heterogeneous electrophysiological profile of pediatric LD, supporting a hybrid model that combines maturational delay with persistent circuit-level atypicalities in some children. While current evidence suggests that rs-EEG features show promise as potential biomarkers for LD detection and subtyping, these findings remain preliminary. Definitive clinical translation will require multi-site, dense-array longitudinal studies employing harmonized pipelines, integration with MRI and genetics, and the inclusion of EEG metrics in intervention trials. Full article

Electroencephalogram (EEG)-based identification offers a promising biometric solution by leveraging the uniqueness of individual brain activity patterns. This study proposes a framework based on a convolutional autoencoder (CAE) along with a traditional classifier for identifying individuals using EEG brainprints. The convolutional autoencoder extracts a compact and discriminative representation from the topographic data cubes that capture both spatial and temporal dynamics of neural oscillations. The latent tensor features extracted by the CAE are subsequently classified by a machine learning module utilizing Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) models. EEG data were collected under three conditions—resting state, music stimuli, and cognitive task—to investigate a diverse range of neural responses. Training and testing datasets were extracted from separate sessions to enable a true longitudinal analysis. The performance of the framework was evaluated using the Area Under the Curve (AUC) and accuracy (ACC) metrics. The effect of subject identifiability was also investigated. The proposed framework achieved a performance score up to a maximum AUC of 99.89% and ACC of 96.98%. These results demonstrate the effectiveness of the proposed automated subject-specific patterns in capturing stable EEG brainprints and support the potential of the proposed framework for reliable, session-independent EEG-based biometric identification. Full article

This research examines road users’ willingness to pay for enhanced active mobility infrastructure at King Mongkut’s Institute of Technology Ladkrabang (KMITL), a suburban university campus in Bangkok, Thailand. The study addresses the need for sustainable transportation solutions in middle-income urban environments by analyzing factors that influence walking and cycling adoption among university community members. The research employed a comprehensive mixed-methods framework combining qualitative SWOT analysis, a stated preference survey of 400 participants, and regularized logistic regression modeling with cross-validation. The analysis revealed that specific infrastructure improvements significantly increase the likelihood of active mobility adoption. Rest areas demonstrated the strongest positive association (OR = 2.15, 95% CI: 1.08–4.27, p = 0.029), followed by CCTV security systems (OR = 1.89, 95% CI: 0.98–3.65, p = 0.047), and improved public transport connectivity (OR = 2.84, 95% CI: 1.42–5.68, p = 0.003). Demographic analysis uncovered notable resistance patterns, with male participants (OR = 0.48, 95% CI: 0.26–0.89, p = 0.020) and higher-income individuals showing reduced willingness to transition from motorized transportation. Using the Contingent Valuation Method with proper bias mitigation strategies, the study quantified potential behavioral changes, projecting a 12–18 min daily increase in active mobility engagement. This enhancement would generate measurable health benefits valued at 2840–4260 THB per person annually using WHO-HEAT methodology. The research contributes valuable insights to the limited body of active mobility literature from Southeast Asian suburban contexts, providing a replicable framework for similar investigations. Full article

Background: Maintaining thermal homeostasis is a basic function of the human body. This homeostasis depends largely on the body’s nutritional status and other conditions related to it. Aim: The present study investigated the impact of 8 days of water-only fasting (8DW-F) on selected features of thermal homeostasis, taking into account somatic, metabolic, and circulatory changes in middle-aged men. Methods: A total of 13 healthy men took part in the experiment. Volunteers were examined twice: after a mixed diet (C) and after using 8DW-F. At baseline, the following were recorded: body mass (BM), body fat (FM), fat-free mass (FFM), and total water (TBW), along with basal metabolic rate (BMR) and body surface area (BSA). Then, after 30 min of sitting under thermoneutral conditions, the following measurements were taken: eardrum temperature (Ti), skin temperatures (Tsk), heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), oxygen uptake (VO₂), and respiratory exchange ratio (RER). The following were then calculated: average body (MTB) and skin temperature (MTsk), resting metabolic rate (RMR), body to skin temperature gradient (g), and whole-body thermal conductivity (C). Results: The results showed that 8DW-F cause a significant reduction in most somatic variables as well as SBP and BMR (p < 0.001), RMR (p < 0.05) with no changes in Ti, MTsk, MTB, or C and g (p = 0.09). There were also significant correlations between Δ MTB × Δ BMR (p < 0.05) and Δ RMR × Δ VO₂ (p < 0.001). Moreover, changes in the C range correlated with Δ RMR (p < 0.005) and Δ DBP (p < 0.05). Conclusions: 8DW-F reduced resting metabolic heat production in the studied men, but sufficient heat conservation ensured that thermal homeostasis was maintained under thermally neutral conditions. Full article

The mammalian amygdala is located in the temporal lobe of the telencephalon and plays a key role in limbic processing. Recently, our group proposed a radial morphological model to understand the glutamatergic (pallial) part of this nuclear complex in terms of separate progenitor domains. This model explains the amygdala region as consisting of several adjacent developmental radial progenitor units, disposing their distinct periventricular, intermediate, and superficial strata from the ventricle to the pial surface. It was expected that cell populations belonging to specific progenitor domains would present greater molecular similarity to each other than to neighboring developmental units. In this work, we aim to corroborate the existence of several radial domains in the pallial amygdala at the transcriptomic level. snRNAseq experiments in the amygdala of adult mice of both sexes indicated that at low resolution, the whole pallial amygdala was found to divide into two super-radial domains distinguished by differential expression of Slc17a6 and Slc17a7; the former partly imitates molecularly the subpallial (output) amygdalar regions, whereas the rest of the pallial amygdala is molecularly more akin to the surrounding cortical areas. In addition, our snRNAseq transcriptomic analysis fully supports the postulated amygdalar radial model of four main radial domains. Full article

Background/Objectives: Microvascular complications are a major source of disability in type 2 diabetes mellitus (T2DM). We investigated whether body composition indices derived from multifrequency bioelectrical impedance analysis (BIA) independently predict neuropathy, retinopathy, nephropathy, and stroke, and whether they improve risk discrimination beyond the established clinical variables. Methods: In this cross-sectional analytical study (March 2024–February 2025), 124 adults with T2DM ≥ 12 months attending the outpatient diabetes clinic of the Universidad Técnica de Ambato (Ecuador) were enrolled. After an overnight fast and 15 min supine rest, thirteen whole-body BIA metrics including skeletal muscle mass (SMM), intracellular water (ICW), phase angle (PhA), and visceral fat area (VFA) were obtained with a segmental analyzer (InBody S10). Complications were ascertained with standard clinical and laboratory protocols. Principal component analysis (PCA) summarized the correlated BIA measures; multivariable logistic regression (adjusted for age, sex, diabetes duration, HbA1c, BMI, and medication use) generated odds ratios (ORs) per standard deviation (SD). Discrimination was assessed with bootstrapped receiver-operating characteristic curves. Results: The first principal component, driven by SMM, ICW, and PhA, accounted for a median 68% (range 65–72%) of body composition variance across all complications. Each SD increase in SMM lowered the odds of neuropathy (OR 0.54, 95% CI 0.41–0.71) and nephropathy (OR 0.70, 0.53–0.92), whereas VFA raised the risk of neuropathy (OR 1.55, 1.22–1.97) and retinopathy (OR 1.47, 1.14–1.88). PhA protected most strongly against stroke (OR 0.55, 0.37–0.82). Composite models integrating SMM, PhA, and adiposity indices achieved AUCs of 0.79–0.85, outperforming clinical models alone (all ΔAUC ≥ 0.05) and maintaining good calibration (Hosmer–Lemeshow p > 0.20). Optimal probability cut-offs (0.39–0.45) balanced sensitivity (0.74–0.80) and specificity (0.68–0.72). Conclusions: A lean tissue BIA signature (higher SMM, ICW, PhA) confers independent protection against neuropathy, retinopathy, nephropathy, and stroke, whereas visceral adiposity amplifies the risk. Because the assessment is rapid, inexpensive, and operator-independent, routine multifrequency BIA can be embedded into diabetes clinics to triage patients for early specialist referral and to monitor interventions aimed at preserving muscle and reducing visceral fat, thereby enhancing microvascular risk management in T2DM. Full article

The usage of land on small farms in subtropical regions varies with climatic conditions. Agricultural cultivation typically occurs during the spring and summer (of the southern hemisphere), with tobacco being the primary crop on most small farms. During these seasons, livestock graze in pastures and woodlots. After the tobacco harvest (March), farmers plant winter cover crops, and by May, livestock is moved from the pastures to the agricultural areas. This study aimed to examine how grazing influences soil density, water infiltration rates, and animal behavior across different land types (pasture, native forest, eucalyptus reforestation, and agriculture) during the tobacco-growing season, and the off-season when grazing occurs on agricultural lands. It was found that forage availability and climatic conditions determined grazing duration in pastures and forests, under Integrated Crop–Livestock (ICL) systems. Higher forage volume in the agriculture area reduced grazing time and increased resting periods. Eucalyptus reforestation areas had the best soil conditions due to minimal grazing occurring there. An increase in soil bulk density and a decrease in water infiltration rates were observed at the end of the grazing period in both pasture and woodland areas. Year-round ICL systems appear to enhance soil quality through fallow periods, improving forage availability, soil moisture retention, and water infiltration as well. Full article

We studied Galápagos barn owls on Santa Cruz Island in the Galápagos Archipelago. We collected and analyzed pellets to determine diet composition. Barn-owl diet consisted—in terms of biomass—of ~89% rodents and ~10% insects. Bird remains occurred in 1% of the pellets. Foraging was studied with data loggers, a method not previously applied to the study of Galápagos barn owls. Owls rested during the day in natural and human-built roosts such as lava holes, trees, or huts. Night-time foraging was characterized by periods during which the bird moved and periods during which the bird stayed within one place, with the latter amounting to ~56% of the time away from the day roost. Birds began foraging shortly after sunset and returned to their day roost before sunrise. The duration of foraging was approximately 11 h per night. Foraging areas were small (median value: 0.28 km²). Although our data demonstrate a continued presence of the subspecies, we regard the situation for this subspecies as labile, as multiple threats, such as road kills, poisoning, and intentional killing by farmers, have increased recently, and suggest the development of a management plan to improve its conservation. Full article

Background: Transcranial direct current stimulation (tDCS) has emerged as a promising neuromodulatory tool for language rehabilitation in chronic aphasia. However, the effects of bi-hemispheric, multisite stimulation remain largely unexplored, especially in people with chronic and treatment-resistant language impairments. The goal of this study is to look at the effects on behavior and brain activity of an individualized language training program that combines bi-hemispheric multisite anodal tDCS with personalized language training for Albert, a patient with long-standing, treatment-resistant non-fluent aphasia. Methods: Albert, a right-handed retired physician, had transcortical motor aphasia (TCMA) subsequent to a left-hemispheric ischemic stroke occurring more than six years before the operation. Even after years of traditional treatment, his expressive and receptive language deficits remained severe and persistent despite multiple rounds of traditional therapy. He had 15 sessions of bi-hemispheric multisite anodal tDCS aimed at bilateral dorsal language streams, administered simultaneously with language training customized to address his particular phonological and syntactic deficiencies. Psycholinguistic evaluations were performed at baseline, immediately following the intervention, and at 1, 2, 3, and 6 months post-intervention. Resting-state fMRI was conducted at baseline and following the intervention to evaluate alterations in functional connectivity (FC). Results: We noted statistically significant enhancements in auditory sentence comprehension and oral reading, particularly at the 1- and 3-month follow-ups. Neuroimaging showed decreased functional connectivity (FC) in the left inferior frontal and precentral regions (dorsal stream) and in maladaptive right superior temporal regions, alongside increased FC in left superior temporal areas (ventral stream). This pattern suggests that language networks may be reorganizing in a more efficient way. There was no significant improvement in phonological processing, which may indicate reduced connectivity in the left inferior frontal areas. Conclusions: This case underscores the potential of combining individualized, network-targeted language training with bi-hemispheric multisite tDCS to enhance recovery in chronic, treatment-resistant aphasia. The convergence of behavioral gains and neuroplasticity highlights the importance of precision neuromodulation approaches. However, findings are preliminary and warrant further validation through controlled studies to establish broader efficacy and sustainability of outcomes. Full article

The placement of hydraulic elements in existing pool-type fishways to make them more suitable for Cyprinid fish is an issue of increasing interest in fishway research. Hydrodynamic characteristics and fish behavior at the representative pool of the fishway with bottom orifices and notches were assessed at the Dagdelen hydropower plant in the Ceyhan River Basin, Türkiye. Three-dimensional velocity measurements were taken in the pool of the fishway using an Acoustic Doppler velocimeter. The measurements were taken with and without a brush block at two different vertical distances from the bottom, which were below and above the level of bristles tips. A computational fluid dynamics (CFD) analysis was conducted for the studied fishway. The numerical model utilized Large Eddy Simulation (LES) combined with the Darcy–Forchheimer law, wherein brush blocks were represented as homogenous porous media. Our results revealed that the relative submergence of bristles in the brush block plays a very important role in velocity and Reynolds shear stress (RSS) distributions. After the placement of the submerged brush block, flow velocity and the lateral RSS component were reduced, and a resting area was created behind the brush block below the bristles’ tips. Fish movements in the pool were recorded by underwater cameras under real-time operation conditions. The heatmap analysis, which is a 2-dimensional fish spatial presence visualization technique for a specific time period, showed that Capoeta damascina avoided the areas with high turbulent fluctuations during the tests, and 61.5% of the fish presence intensity was found to be in the low Reynolds shear regions in the pool. This provides a clear case for the real-world ecological benefits of retrofitting existing pool-weir fishways with such flexible hydraulic elements. Full article

Industrial building renovation is a sustainable strategy to preserve urban heritage while meeting modern needs. However, how interior material scenes affect users’ emotions, thermal perception, and functional preferences remains underexplored in adaptive reuse contexts. This study used virtual reality (VR) to examine four common material scenes—wood, concrete, red brick, and white-painted surfaces—within industrial renovation settings. A total of 159 participants experienced four Lumion-rendered VR environments and rated them on thermal perception (visual warmth, thermal sensation, comfort), emotional response (arousal, pleasure, restoration), and functional preference. Data were analyzed using repeated measures ANOVA and Pearson correlation. Wood and red brick scenes were associated with warm visuals; wood scenes received the highest ratings for thermal comfort and pleasure, white-painted scenes for restoration and arousal, and concrete scenes, the lowest scores overall. Functional preferences varied by space: white-painted and concrete scenes were most preferred in study/work settings, wood in social spaces, wood and red brick in rest areas, and concrete in exhibition spaces. By isolating material variables in VR, this study offers a novel empirical approach and practical guidance for material selection in adaptive reuse to enhance user comfort, emotional well-being, and spatial functionality in industrial heritage renovations. Full article

This paper presents the Green Watershed Index (GWI) methodology, focusing on the 17 sustainability indicators selected in the Razey watershed, NW Iran. Field surveys and data collection have provided the possibility of field inspection and measurement of the present condition of the watershed and the indicators taken. Based on the degree of compliance with the required process, each indicator was scored from 0 to 10 and classified into three categories: unsustainable, semi-sustainable, and sustainable. Using the Entropy method to assign weight to each indicator and formulating a proportional mathematical relationship, the GWI score for each sub-watershed was derived. Spatial changes regarding the selected indicators and, consequently, the GWI were detected in the study area. Development of water infrastructure, particularly in the upstream sub-watersheds, plays a great role in increasing the GWI score. The highest weight is related to environmental productivity (0.26), and the five indicators of water footprint, knowledge management and information quality system, landscape attractiveness, waste recycling, and corruption control have approximately zero weight due to their monotonous spatial distribution throughout sub-watersheds. Only sub-watershed R1 has the highest score (5.13), indicating a semi-sustainable condition. The rest of the sub-watersheds have unsustainable conditions (score below 5). Concerning the GWI, the watershed is facing a critical situation, necessitating the implementation of management and conservation strategies that align with the sustainability level of each sub-watershed. Full article