Genomic sequencing (GS) in the neonatal period has advanced over the past several years. Results are available within days in many centers and cost-effectiveness and utility data continue to accumulate. Though less prevalent in clinical practice, prenatal GS is also demonstrating increasing evidence of efficacy. Clearly, information on a genetic disorder's presence or absence is very useful for families and providers, both during pregnancy and postnatally in the intensive care units. Precision therapies for genetic disorders continue to advance in the pediatric space and, in some instances, are being considered for prenatal therapy. Despite caring for the same families along a continuum of care, prenatal and neonatal discussions about genomic sequencing are often siloed. We urge providers in the prenatal and neonatal spaces to align genomic medicine service delivery and consider offering GS prenatally or, at least, prenatally coordinating postnatal rapid GS in the third trimester to facilitate rapid diagnosis and patient-centered care.
This study investigated electrolyte and acid-base alterations and their associations with performance in 40 Brazilian male runners during a 45-km mountain ultramarathon. The following parameters were assessed before and after the race: pH, sodium (Na+), potassium (K+), calcium (Ca2+), glucose, carbon dioxide pressure (pCO2), partial pressure of oxygen (pO2), bicarbonate (HCO3), hematocrit and lactate. Potassium levels decreased significantly across all performance groups (Fastest: p = 0.004; Moderate-Fast: p = 0.004; Moderate-Slow: p = 0.003; Slowest: p = 0.004), while lactate increased in the Fastest (p = 0.03), Moderate-Fast (p = 0.002), and Slowest (p = 0.03) groups. Sodium increased in the Moderate-Fast group (p = 0.005), whereas calcium decreased in the Slowest group (p = 0.005). Both pCO2 and HCO3 were significantly reduced across all groups (pCO2: p = 0.0003-0.0005; HCO3: p = 0.003-0.0004), and pH decreased in the Slowest group (p = 0.01). Between-group differences were observed between Fastest and Slowest for pH (p = 0.02), pCO2 (p = 0.001), and K+ (p < 0.001), and between Fastest and Moderate-Slow for Na+ (p = 0.03). Negative correlations were found between race time and post-race pH (R = -0.46), Ca2+ (R = -0.33), and Na+ (R = -0.31). In the Slowest group, Δ K2+ was strongly correlated with race time (R = -0.83; p = 0.003). Performance in a 45-km mountain ultramarathon appears to be closely associated with the ability to preserve acid-base and electrolyte homeostasis, particularly regarding potassium, sodium, calcium and pH.
Wafer-level testing of Photonic Integrated Circuits (PICs) represents a critical throughput bottleneck in silicon photonics manufacturing, particularly as co-packaged optics demand testing of thousands of optical I/O per wafer. This work introduces optimized alignment algorithms for the Technoprobe Eclipse Dynamic probe card system, which integrates electrical probes and a piezoelectrically actuated fiber array unit within a single probe head, eliminating external positioning equipment. We systematically evaluate seven alignment algorithms: Reference Coarse Scan, Reference Coarse+Fine Scan, Cross Scan, Local and Global Bayesian Optimization, Variable and Fixed Gradient Ascent. The evaluation is made across 72 simulated test cases derived from eight experimental datasets through systematic spatial windowing, combined with experimental validation. Performance is assessed under four operating regimes-high-speed (HS) and low-speed (LS) operation, each with or without hysteresis compensation (H/NH). Experimental validation across eight die positions confirms 100% success rate for both Local Bayesian (98.24% accuracy in 99.87 arbitrary units (a.u.)) and Fixed Gradient (99.18% accuracy in 154.01 a.u.) baseline algorithms. Comprehensive simulation results with improved algorithms across all four scenarios reveal distinct performance characteristics. Fixed Gradient achieves the highest reliability (95.8%) with 99.4% average accuracy across all operating conditions. Variable Gradient provides the fastest alignment (1.18 a.u. in HS-NH) with 90.3% reliability. Local Bayesian demonstrates 94.4% reliability with intermediate performance. Global Bayesian Optimization achieves the best sample efficiency (average 24 steps) but exhibits scenario-dependent reliability ranging from 88.9% (HS-H, LS-H) to 93.1% (LS-NH). For the ideal production scenario, high speed with effective hysteresis compensation (HS-NH), Fixed Gradient emerges as the optimal choice, delivering 95.8% reliability with 1.44 a.u. alignment time, resulting in the best success rate while being nearly as fast as the fastest method. Variable Gradient achieves the absolute fastest alignment (1.18 a.u.) but with 5.5% lower reliability (90.3%), making it suitable only for applications tolerating higher failure rates. Under realistic production conditions with uncompensated hysteresis (HS-H), Fixed Gradient maintains its advantage (95.8% reliability, 3.32 a.u.), while Global Bayesian degrades significantly (88.9% reliability, 4.29 a.u.). Statistical analysis using data profiles validates these methods for high-volume PIC manufacturing, with the Eclipse Dynamic system demonstrating per-die optical alignments in sub-second timescales using open-loop control hardware.
The Complete Ammonium and Nitrate Removal via Denitratation-Anammox over Nitrite (CANDAN) is a promising low-carbon strategy for sustainable nitrogen removal; however, the mechanistic linkage between extracellular polymeric substances (EPS), aggregation behavior, granule size differentiation, and microbial assembly remains unclear. Here, size-fractionated granules from a CANDAN reactor were systematically investigated to establish a multi-scale framework linking EPS structural properties to aggregation-driven granule organization and microbiome assembly. Medium-sized granules (0.5-1.0 mm) exhibited the highest aggregation capacity (74.5%) and fastest aggregation kinetics, indicating a cohesive and dynamically stable matrix. This aggregation advantage was closely associated with optimized functional performance, including high specific anammox activity (8.76 ± 1.36mg N g-1 VSS h-1), the highest nitrate reduction and nitrite production rates, and a high nitrite transformation ratio (90.1%), reflecting efficient pathway coupling in CANDAN systems. EPS analyses revealed that aggregation and stability were governed primarily by structural organization rather than bulk EPS content. Medium-sized granules were characterized by a lower protein-to-polysaccharide ratio, enriched hydrophobic functional groups, and β-sheet-dominated protein conformations, which collectively enhanced intercellular cohesion and stabilized the EPS matrix. This structurally optimized aggregation regime further shaped microbial assembly, promoting the enrichment and coordination of Candidatus Brocadia and Thauera. Overall, this study identifies aggregation capacity as a key mechanistic driver linking EPS structural properties to granule size differentiation and microbial assembly, highlighting granule size as a mesoscale regulator bridging physicochemical structure and ecological function.
Accurate prescription and monitoring of resistance training (RT) load require ensuring that the external load prescribed by the coach reflects the internal demands experienced by the athlete. Although repetitions in reserve (RIR) have been proposed as a practical method for quantifying proximity to failure, their use in isolation assumes that identical RIR values correspond to equivalent physiological stimuli across different repetition ranges and intensities. This assumption does not necessarily reflect comparable internal loading conditions. To address this limitation, the concept of "level of effort"-defined as the "relationship between the repetitions performed and the maximum number of repetitions that could be completed with a given load"-offers a proportion-based and more comprehensive representation of exertion. When quantified through movement velocity, the level of effort integrates two critical variables: relative intensity (via the fastest repetition velocity) and fatigue development (via velocity loss), allowing accurate estimation of the percentage of repetition capacity utilized within a set. This approach enables practitioners to derive RIR from an objective measure of actual effort, thereby enhancing the precision of RT prescription and monitoring.
Anopheles gambiae s.l. is the major malaria vector in sub-Saharan Africa, and increasing pyrethroid resistance threatens vector control. This study investigated the prevalence of knockdown resistance (kdr) mutations and pyrethroid susceptibility in An. gambiae s.l. populations from Kwara State, North-Central Nigeria. A total of 250 An. gambiae s.l. mosquitoes were collected from three Local Government Areas. Molecular analysis identified An. coluzzii (31.2%, 95% CI: 25.7-37.3%), An. gambiae s.s. (16.8%, 95% CI: 12.6-22.0%), and An. arabiensis (13.6%, 95% CI: 9.9-18.4%), while 38.4% failed amplification. All populations were resistant to permethrin, deltamethrin, and alphacypermethrin (mortality < 90%), with mortality ranging from 23% to 64% across locations. Knockdown times were fastest with deltamethrin (KDT₅₀: 32.75-52.80 min) and slowest with permethrin (KDT₅₀: 39.41-93.34 min). Kdr genotyping showed 41.6% homozygous resistant (RR) and 58.4% homozygous susceptible (rr) mosquitoes; no heterozygotes were detected. These findings indicate widespread pyrethroid resistance partially mediated by kdr mutations, with significant variation among locations and sibling species. The absence of heterozygotes suggests strong selection pressure, emphasizing the need for resistance monitoring and strategic vector control interventions.
Older adults represent the fastest-growing demographic group initiating hemodialysis (HD) in the United States. Compared with older adults who do not receive HD, they commonly report a lower quality of life (QOL). However, their perspectives on QOL are poorly understood. The objective of this study was to identify and characterize QOL priorities of older adults receiving HD. Cross-sectional study using Q-methodology. Participants were recruited from dialysis centers in and around Durham, North Carolina. Each participant sorted 35 QOL statements based on the level of agreement (eg, agree, disagree, or neutral). Factor analysis of the Q-sorts was performed using the PQ Method software. Factors were interpreted and described as QOL priorities. Demographic and clinical characteristics were summarized overall and based on factors. 29 older adults were recruited with a mean age of 76.2 ± 5.6 years, a median dialysis vintage of 3 (1-4.8) years, and 18 (62.1%) women. Ten (34%) participants screened positive for frailty questionnaire responses and 16 (55.2%) participants reported using an assisted device. Factor analysis revealed the following 2 distinct QOL prioritization profiles: (1) "Everyday Well-Being" and (2) "Safety and Security." "Everyday Well-Being," defined using 16 Q-sorts, represented a perspective that highly valued cognitive function (memory/thinking ability), spirituality, adequate pain control, and well-functioning dialysis access. "Safety and Security," defined using 11 Q-sorts, represented a perspective that highly valued socioeconomic stability, including financial stability, access to reliable transportation, and safety. We observed no difference in age, dialysis vintage, or performance on cognitive, physical function, and frailty assessments between participants whose Q-sorts defined each prioritization profile. Cross-sectional design, confinement to 1 geographical region. Using Q-methodology, we identified 2 dominant profiles of QOL priorities among older adults receiving HD. These findings highlight heterogeneity in what matters most to older adults receiving HD and the need for personalized, patient-centered approaches to evaluating and improving their QOL. Older adults receiving hemodialysis (HD) experience unique challenges, yet their perspectives on quality of life (QOL) are not well understood. We examined the QOL priorities of older adults receiving HD through a series of rankings and identified 2 distinct priority profiles. The first group of older adults focused on their everyday well-being, maintaining cognitive function, pain management, and functional dialysis access. The second group prioritized safety and security, including socioeconomic stability and recovery after dialysis treatments. Understanding what matters most to older adults receiving HD will facilitate individualized, patient-centered care and development of patient-centered interventions to improve the QOL of older adults.
The radioactivity of the α particle is among the most compelling evidence for the existence of cluster structures in atomic nuclei. During the decay process, a pre-existing α particle tunnels through the potential barrier formed by the residual nucleus1,2. The degree of preformation of the α particle, a strongly bound system of two protons and two neutrons, is extracted from the data by dividing the α-decay probability by the barrier penetrability for a given particle energy. The preformation probability changes rapidly near nuclear shell closures, which is direct evidence that clustering is connected to nuclear structure3. Enhanced preformation was observed in the lightest α-particle emitters, spherical tellurium and xenon isotopes decaying to magic isotopes of tin. Here we show the most extreme case of α-particle preformation from the measurement of the decay of tellurium-104 (104Te). With a half-life of 7. 2 - 1.5 + 2.3 ns , 104Te is the fastest ground-state α-emitting nucleus known so far. The deduced preformation demonstrates that the enhancement is greater for 104Te than for any other nucleus. One nuclear model that can explain our observation postulates that the α particle can exist only in the low-nuclear-matter-density regions on the surface of the nucleus. The uniquely high preformation for 104Te is attributed to its relation to doubly magic tin-100 (100Sn), creating conditions conducive to form an α particle.
Controlling catalyst microenvironments using proton shuttles and hydrogen bond donors in the secondary coordination sphere is a promising approach for developing catalysts that can affect multiproton and multielectron transfer processes. In this context, three palladium calixpyrrole complexes with pendent amine (1), amide (2), and carbamate (3) groups were examined as electrocatalysts for the hydrogen evolution reaction (HER). Building on prior studies showing that the palladium complexes generated catalytically active heterogeneous HER catalysts in the presence of p-toluenesulfonic acid monohydrate, 1-3 were evaluated using the significantly milder proton source anilinium tetrafluoroborate. The active catalytic species for all three systems was found to be solution-based, and kinetic analysis uncovered a first-order dependence on acid, as well as large H/D kinetic isotope effect values, which were consistent with proton-coupled electron transfer being rate-limiting. The calixpyrrole complexes displayed exceptional activity, achieving kobs and turnover frequency values of 4.65 × 106 s-1, 4.19 × 106 s-1, and 3.09 × 106 s-1 for 1, 2, and 3, respectively. These catalytic activities and rate constants approached the diffusion rate limit and ranked among the fastest HER catalysts to date.
Women are the fastest-growing demographic in the United States military and face increased risks for alcohol-related problems. Motherhood often protects against alcohol misuse in civilian populations; however, it is not known if the demands of multiple, competing intersecting roles of reserve soldiers can complicate this. We hypothesize that civilian mothers will endorse fewer alcohol problems than non-mothers, but that this protective effect will not extend to women in military roles. Data are drawn from women (N = 411) in Operation: SAFETY (Soldiers and Families Excelling Through the Years). The Alcohol Use Disorder Identification Test (AUDIT) was used to assess alcohol use (AUDIT Total, AUDIT ≥ 8, Consumption, Dependence, Alcohol-Related Harm), the Patient Health Questionnaire assessed depression, and the PTSD-Checklist for DSM-5 assessed PTSD. T-test and chi-square tests compared potential covariates. Logistic and negative binomial regressions examined alcohol use outcomes based on maternal status for civilian and military women separately. Adjusted models controlled for mothers' age, education, depression, and PTSD symptoms. Motherhood status significantly influenced alcohol use outcomes. Compared to non-mothers, civilian mothers reported significantly fewer alcohol-related problems in all unadjusted and adjusted models (ps < 0.05). However, among women in USAR/NG roles, there was no significant difference in any alcohol use outcome by maternal status. Motherhood status was associated with lower risk alcohol use among civilian women. However, this protective relationship was not observed among women in USAR/NG roles. Subsequent research is needed to help better understand the alcohol use of military mothers.
Understanding the molecular basis of phenotypic trait variation is key in improving field performance in plants. Many plants have high within seed source phenotypic variation, making trait-based inferences for performance difficult and inaccurate. Our study combined machine learning methods along with genomics and transcriptomics to understand the molecular drivers of important seedling traits in ponderosa pine. We measured height, specific leaf area, biomass related traits, d13C, d15N, percent carbon, percent nitrogen in well-watered and drought conditions using species' range-wide seed sources. Seedlings from California's seed sources were the fastest growing, while the ones from Montana and Wyoming were the slowest. Despite differences in growth, common responses to drought were seen across all regions. Needles per bundle was shown to be an extremely useful trait to screen for growth strategies of a seed source. We identified one to 36 unique genes (2-209 SNPs) per trait that provided accurate predictions for most traits (2-37% mean absolute percent error). We show that prediction accuracy is trait dependent, mostly higher for traits with high heritability and lower in traits sensitive to environmental change. Drought-stressed seed sources from contrasting elevations showed differential expression of phenylpropanoids, terpenoids and carotenoids genes. Our predictive models show promise for future studies to predict phenotypes upon germination instead of waiting several years to measure specific traits. This will allow for a faster, more accurate selection of best suited individuals and seed sources for any site, resulting in more efficient and successful outplanting.
Pickleball is the fastest growing sport in North America and is popular among older adults, yet the physical and cognitive benefits of this sport in older adults remain relatively unexplored. The purpose of this study was to address this gap in literature by measuring physical and cognitive data in older pickleball players. A cross-sectional study compared pickleball players to a control group of non-pickleball players, all over the age of 55 years. The following dependent variables were measured: (a) balance, (b) grip strength, (c) leg strength (d) aerobic fitness, (e) cardiometabolic risk factors, (f) cognitive function, (g) self-reported physical activity, and (h) quality of life. Significant between-group differences were detected with independent samples t tests, where the alpha level was .05. Fourteen pickleball players (Mage = 68.07 ± 6.86 years, 57% female) and 14 non-pickleball players (Mage = 69.36 ± 5.49 years, 50% female) participated in this study. Despite similar levels of self-reported physical activity (p = .47) between groups, pickleball players had significantly better balance (p = .02) and significantly higher leg strength (p = .01). No other significant differences in outcome measures were found. This study suggests that pickleball is a beneficial sport for balance and leg strength in older adults, regardless of physical activity levels. Significance/Implications: Poor balance is a risk factor for falls in older adults. Implementing pickleball programs could help to reduce fall risk among older adults, even in those already active.
Background: The benefit of pharmaceutical innovation manifests when patients access treatment. Following regulatory approval in Europe and Canada, reimbursement decisions depend on health technology assessments (HTAs), which can be prolonged. To quantify the impact of delays on patients, we evaluated market access timelines for olaparib, osimertinib, durvalumab, acalabrutinib, and trastuzumab deruxtecan across six high-income countries with established HTA systems (Canada, England, France, Germany, Italy, Spain). Methods: Time to access was from regulatory approval to reimbursement. Survival benefit was median overall survival (OS) and progression-free survival (PFS) assessed versus the comparator at approval and the latest data cut-off. The number of eligible patients per year multiplied by the years to patient access and survival benefit reflects the lost survival benefit. Results: Efficacy benefits observed at approval continued to the latest data cut-offs. The mean time to patient access was 18 months. Although this varied by country and treatment, with England and Germany typically being the fastest and France and Spain the slowest, timelines often exceeded the 180-day EU target despite identical evidence used in HTA submissions. This resulted in an estimated mean of 2836 patients being unable to access treatment and 3391 OS-derived and 2739 PFS-derived life-years lost. Conclusions: Access processes must evolve to ensure the timely realization of new medicines' benefits.
Poly-(lactide) (PLA) homopolymer embrittles under ambient conditions within two days after melt processing through physical aging, which restricts its growth as a sustainable alternative to petroleum-derived, nondegradable plastics. Block polymers containing PLA and immiscible rubbery segments have shown promising mechanical longevity, though only at very high total molar masses. To elucidate the basic architectural and morphological features of such aging-resistant materials, we used a straightforward two-step synthetic route to generate a library of n-arm block polymer plastics (n = 1-4) with poly-(γ-methyl-ε-caprolactone) (PγMCL) as the rubbery core and poly-(l-lactide) (PLLA) as the outer block, fixing PLLA content at 80 wt %. Triblocks and star-blocks (i.e., n ≥ 2) exhibited high tensile toughness that persisted over long aging times even in samples with poorly entangled PLLA matrices. Crystallinity and architectural purity also promoted mechanical longevity. Calorimetry revealed that the most mechanically long-lived specimens, with M PLLA < 35 kg mol-1, exhibited the fastest physical aging, which we ascribed to a coupling of block dynamics near the segregated PγMCL domain interfaces. Our results broaden the scope of viable block polymer architectures for PLLA mechanical longevity to more synthetically accessible macromolecules that are practically advantageous for scalability and melt processing.
Thyroid cancer, the fastest-growing endocrine malignancy, is shifting from morphological evaluation to molecular-functional imaging. This review systematically evaluates the translational value of multimodal ultrasound technologies-high-frequency ultrasound (HFUS), elastography, contrast-enhanced ultrasound (CEUS), and super-resolution imaging (SRI)-across the entire "screening-diagnosis-treatment-follow-up" continuum of thyroid cancer management. A systematic literature synthesis was performed, aggregating data from clinical studies and preclinical trials that assessed multimodal ultrasound technologies in thyroid cancer. Key quantitative parameters extracted for analysis included: microcalcification detection rate using HFUS with artificial intelligence (AI), diagnostic specificity based on elastography (Emax cutoff) combined with molecular biomarkers (VEGF, PD-L1), spatial resolution and microvascular metrics (microvessel density [MVD], microvascular flow rate [MFR]) achieved by SRI, and complete ablation rate of ultrasound-guided ablation coupled with targeted microbubble technology. Emerging evidence on ultrasound radiomics and genomics was also reviewed. Morpho-functional dual-modal assessment using 10-24 MHz HFUS probes integrated with AI achieved a 91.4% detection rate for microcalcifications (<1 mm). Quantitative elastography parameters (Emax ≥30.65 kPa) combined with molecular imaging biomarkers (VEGF, PD-L1) elevated diagnostic specificity to 93.6%. SRI broke the 50 µm resolution barrier, enabling three-dimensional microvascular topology reconstruction and quantification of MVD and MFR. Ultrasound-guided ablation together with targeted microbubble technology attained a 92.3% complete ablation rate for microcarcinomas. The review further identified frontier integration of ultrasound radiomics and genomics as multidimensional evidence for precision management. Multimodal ultrasound technologies (HFUS, elastography, CEUS, SRI) provide robust translational value across the thyroid cancer care continuum, significantly improving detection, diagnostic specificity, microvascular imaging, and therapeutic efficacy, thereby supporting precision thyroid cancer management.
Vertical climbing performance is a critical but often overlooked factor in the household colonization process by triatomine vectors. This study evaluated the climbing efficiency of seven Mexican triatomine species (Triatoma longipennis, T. mazzottii, T. pallidipennis, T. rubida, T. picturata, Paratriatoma lecticularia, and Hospesneotomae protracta) across four common regional building materials: unplastered brick, plastered brick, wood, and mesh screen. A fifth material, plastered brick with oil-based paint, was also tested. Ascent times to a height of 25 cm were recorded under scotophase conditions. Results showed that oil-based paint acted as an absolute physical barrier, with a 100% failure rate across all species. For the remaining materials, a general linear model (R2 = 0.891) revealed highly significant interactions between species and substrates (p < 0.001). Although masonry surfaces significantly hindered the movement of H. protracta, these species exhibited high efficiency on wood and mesh screen. Conversely, T. longipennis was highly efficient on brick but slower on organic substrates. In almost all cases, mesh screen allowed for the fastest ascent times, suggesting it may facilitate rapid movement if compromised. These findings demonstrate that triatomine climbing ability is species-specific and highly dependent on surface micro-rugosity. We conclude that housing improvement strategies, specifically the use of smooth, non-porous wall coatings, are essential components of integrated vector management. Such interventions, combined with modern surveillance tools, can significantly reduce the risk of domestic infestation and Chagas disease transmission in endemic regions of Mexico.
Stroke is the leading cause of death and disability among adults in China, with a growing disease burden. Data from the China Stroke Prevention and Treatment Report 2023 show that the incidence rate of stroke in China is approximately 246.8 per 100 000 population, with over 2 million new cases annually. Among surviving patients, 60%-70% experience varying degrees of hand dysfunction after discharge, and only 10%-20% can recover to near-normal levels. As the most refined and core motor function of the human body, hand function recovery essentially reflects motor cortical neuroplasticity (synaptic remodelling and cortical reorganisation). Its recovery directly affects the independence of activities of daily living (ADLs) such as eating, dressing and personal hygiene, markedly reducing quality of life and increasing family care burden and social medical costs.Currently, clinical rehabilitation interventions for patients who had a stroke are mostly concentrated during hospitalisation, focusing on acute-phase stability and basic function recovery. However, postdischarge rehabilitation follow-up coverage is fewer than 40%, and community rehabilitation resources are disparately distributed, leaving most patients facing the dilemma of 'interrupted rehabilitation after discharge'. Additionally, existing studies mostly focus on short-term follow-up (3-6 months) and lack systematic investigation of the long-term trajectory of hand function recovery (6 months to 1 year), key turning points and influencing factors-especially the regulatory role of multidisciplinary intervention on neuroplasticity. The integrated 'hospital-community-family' multidisciplinary collaborative management model remains underdeveloped. This study aims to describe the dynamic trajectory of hand function and overall rehabilitation outcomes in patients who had a stroke at 6 months and 1 year postdischarge, analyse the key influencing factors of hand function recovery (with a focus on the regulatory role of multidisciplinary collaborative intervention on motor cortical neuroplasticity), verify the effectiveness of the multidisciplinary collaborative management model on complications and rehabilitation satisfaction, and ultimately construct a continuous rehabilitation management model adapted to the current status of primary medical care in China. A single-centre, prospective cohort study design will be used. A total of 120 patients who had a stroke with hand dysfunction discharged from the Department of Rehabilitation Medicine, The Second People's Hospital of Hefei Guangde Road Campus between February 2026 and February 2027 will be enrolled. A multidisciplinary team (MDT) consisting of rehabilitation physicians, rehabilitation therapists, community doctors/nurses and family caregivers will be established to implement a three-stage intervention: discharge connection, community intervention and online support (incorporating neuroplasticity initiation, enhancement and maintenance strategies).Hand function (primary outcome) will be assessed using the Fugl-Meyer Assessment for Hand (FMA-Hand) at baseline (1-3 days predischarge, T0), 3 months postdischarge (T1), 6 months postdischarge (T2) and 12 months postdischarge (T3). Secondary outcomes include overall motor function (FMA Total Score, FMA-Total) and ADL (Modified Barthel Index). Influencing factor data will be collected using structured questionnaires, and neuroplasticity will be indirectly evaluated using transcranial magnetic stimulation-derived motor evoked potentials.SPSS V.26.0 software will be used for statistical analyses. Quantitative data will be expressed as (x̄±s) or (M (IQR)) depending on normality; categorical data will be presented as (n (%)). Repeated measures analysis of variance will compare functional changes across time points, and multiple linear regression will identify independent influencing factors of hand function recovery. Patients will show progressive hand function recovery within 1 year after discharge, with the fastest recovery at 3-6 months and stabilisation from 6 to 12 months. Younger age, higher baseline function, better rehabilitation adherence and active multidisciplinary intervention are associated with greater neuroplasticity and better hand function recovery. The MDT model may reduce complications and improve rehabilitation satisfaction and ADL. The results of this study will fill the data gap in long-term postdischarge rehabilitation trajectories of patients who had a stroke, clarify the regulatory role of multidisciplinary collaborative intervention on motor cortical neuroplasticity and provide scientific evidence and practical references for optimising postdischarge rehabilitation follow-up programmes and improving the primary rehabilitation service system. This study was approved by the Biomedical Research Ethics Committee of The Second People's Hospital of Hefei (No. 2024-KY-089). Written informed consent was obtained from all participants. The results will be published in peer-reviewed journals and disseminated to participants and community health institutions. ChiCTR2600119007.
Remote sensing (RS) and Artificial intelligence (AI) are increasingly applied to monitor vegetation and hydrology in the Arctic and Antarctic, where logistical and environmental constraints make fieldwork difficult. These technologies offer new opportunities to track ecological change, but the extent, consistency, and methodological quality of current applications have not been systematically reviewed. This study presents the first PRISMA 2020 based systematic synthesis of AI enhanced RS, collectively termed GeoAI, applied to Arctic and Antarctic environments (2005-2025; 116 studies). Publication activity has expanded significantly since 2018, driven by the convergence of uncrewed aerial vehicle (UAV), multispectral imaging, satellite archives, and deep learning (DL). Bibliometric and conceptual-network analyses reveal a rapid shift from isolated ecological monitoring toward integrated, data-fusion frameworks linking vegetation, hydrology, and climate processes. Classical machine learning approaches remain foundational, while DL-based convolutional neural-network architectures are emerging as powerful tools for fine-scale segmentation and prediction. Most studies still operate at the landscape scale, with few achieving full UAV-to-satellite integration, exposing persistent spatial-resolution and validation gaps. Vegetation hydrology coupling is reported in most cases, though subsurface and process-based monitoring remain limited. Spectral-index analysis reveals a persistent reliance on greenness metrics, yet there is a growing shift toward pigment, moisture, and cryptogam-sensitive indices that more accurately capture plant physiological function and microclimatic interactions. This review establishes the empirical foundation for next-generation polar monitoring, emphasising hierarchical UAV-to-satellite fusion, open benchmark datasets, and explainable, ecologically grounded AI as essential pathways for scalable, climate-adaptive conservation of Earth's fastest-changing regions.
The existing literature largely identifies spring as Arizona's predominant dust season, when synoptic-scale dust events are most frequent and "Fine Soil" measurements from the IMPROVE (Interagency Monitoring of Protected Visual Environments) network reach a yearly maximum. Because IMPROVE observations are primarily derived from remote monitoring sites, however, they may not reflect exposure-relevant dust seasonality in Arizona's urban areas, where anthropogenic activities can strongly influence coarse particulate matter (PM) concentrations. Consistent with this possibility, the notion of "spring as dust season" is less clear in other surface data sets that serve as dust proxies, including PM coarse and PM 10 . Here we analyze (a) regulatory monitoring of hourly PM 10 and PM coarse concentrations, (b) IMPROVE measurements of 24-hr Fine Soil and PM coarse concentrations, and (c) sub-hourly PM coarse concentrations from a low-cost urban sensor network (SUNSET, Sonoran Unified Network of Sensors for Environmental Tracking). Our analysis reveals a different picture of dust seasonality. Summer has the highest concentrations of regulatory PM 10 and PM coarse, followed by fall and then spring, whereas IMPROVE-measured Fine Soil peaks in spring. Summer also has the most PM 10 NAAQS exceedances. Seasonal patterns differ between urban and rural environments, and concentrations are generally higher in more anthropogenically influenced areas. Diurnal cycles, weekday-weekend differences, a COVID-era anomaly in 2020, and urban spatial gradients further indicate strong anthropogenic influences. Together, these results suggest that while springtime dust is climatologically important at remote sites, it does not represent exposure-relevant dust seasonality in Arizona's urban areas. Understanding the seasonal variation in airborne dust in Arizona, one of the country's fastest growing states, is important due both to the climate and health impacts of dust. Different determinations of dust's seasonal pattern arise when analyzing different data sets. Monitoring data from populated areas points toward summer being the dominant dust season, while some data from rural areas points toward spring. All data sets indicate that anthropogenic activities very strongly influence airborne dust concentrations.
Multi-protective wearables, which integrate flexible fabric substrates with conductive materials, have gained considerable attention due to their potential across a wide range of applications. However, their practical adoption is often hindered by the high hydrophilicity of these components. Here, we present a bioinspired approach utilizing in situ mineralization of copper sulfide nanospheres alongside polyhedral oligomeric silsesquioxane-derived organic-inorganic hybrid nanoclusters (HNs). The resulting wearable exhibits high mechanical durability and abrasion resistance, while simultaneously providing integrated tri-modal personal thermal management, efficient electromagnetic interference shielding (48 dB), and superhydrophobicity (153.4°). Among the thermal system, near-infrared irradiation produces the fastest heating response: at 0.5 W/cm2, the material achieves a temperature increase of 25°C within 10 s and reaches 62°C after 30 s. Under visible-light irradiation, the material achieves a higher steady-state temperature of up to 76°C, indicating efficient solar-energy utilization in the visible range. Joule heating provides stable output in the absence of light; at 4 V DC, the system stably maintains a temperature of ∼ 70°C. Together, these three modes enable adaptive thermal regulation under varied conditions. The HNs coating protect the underlying conductive network, improving long-term stability and preserving sensing responsiveness. In addition, the bioinspired surface shows markedly enhanced abrasion resistance compared with commercial polydimethylsiloxane, retaining superhydrophobicity even after 40 sandblasting cycles. Overall, this work presents a bioinspired route toward multi-protective wearables with improved wear resistance and performance stability.