Search Results (2,222)

Accurate correction of gridded numerical weather prediction precipitation forecasts remains challenging because many end-to-end deep learning correction models treat meteorological variables as undifferentiated data channels and therefore provide limited physical interpretability. Inspired by general principles of biological environmental sensing, selective information processing, and regulatory constraint learning, this study proposes PCPNet, a bio-inspired and physically constrained precipitation correction framework. The framework does not imitate a specific biological organ or species; instead, it abstracts three information-processing principles into a meteorological correction task. First, key weather-system cues, including low-level shear lines, trough-ridge effects, upper-level jet-stream forcing, vorticity-divergence-related vertical motion, and water-vapor flux convergence, are quantified as structured diagnostic fields. This transforms the subjective synoptic diagnosis of forecasters into automated grid-based sensing features. Second, these diagnostic cues are fused with numerical weather prediction variables and terrain descriptors in an encoder–attention–decoder network, allowing the model to emphasize dynamically important precipitation-triggering regions. Third, water-vapor conservation and terrain-forcing relationships are embedded as differentiable constraint losses, providing training-time constraint-based regulation that guides the corrected precipitation field toward physically consistent solutions. The method is evaluated from 2021 to 2023 in Hunan Province, China, using hourly numerical weather prediction model outputs as input features, China Meteorological Administration Land Data Assimilation System gridded analysis data as the training target, and independent meteorological station observations for strict cross-validation. PCPNet reduces the mean absolute error by 22.1% compared with the uncorrected China Meteorological Administration Land Data Assimilation System gridded precipitation products and outperforms Linear Regression, Bagging, Boosting, Multi-Layer Perceptron, TabNet, and Tree-based Progressive Regression Models by 12.9%, 13.5%, 16.9%, 10.8%, 14.9%, and 15.9%, respectively. The single-day event analysis provides an initial demonstration of heavy precipitation recovery capability, while comprehensive validation across long-term continuous weather events is planned for future operational deployment to further verify model stability. These results indicate that bio-inspired sensing and regulatory constraint learning can improve both the accuracy and interpretability of precipitation nowcasting correction. Full article

Background/Objectives: Intraoperative neuromonitoring (IOM) is commonly used in instrumented spine surgery; however, its utility is often debated. We sought to determine if IOM changes were independently associated with specific postoperative outcomes in minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF). Methods: We performed a retrospective analysis of patients who underwent MIS-TLIF with IOM at a single institution. Collected data included demographics, comorbidities, surgical history, operative indications, operative spinal levels, IOM findings, and postoperative outcomes. Single and multivariate logarithmic regression analyses were performed to assess the correlation of each preoperative variable with IOM alerts, as well as the association between IOM alerts and postoperative outcomes. Results: A total of 439 patients were identified, 21 of whom experienced an IOM alert. No preoperative variables were significantly associated with IOM alerts. However, the presence of an IOM alert significantly increased the log odds of postoperative foot drop (1.93–6.55, p < 0.001), for which there was also a high specificity (95.9%) and negative predictive value (99.8%). However, likely due to low event rates, IOM had a low negative predictive value (16.7%). Further multivariate analysis also identified an IOM alert as a significant predictor of postoperative neurological deficits and chronic complications, although these pooled categories included foot drop. When IOM subtypes were investigated, both the SSEP and MEP significantly increased the log odds of postoperative foot drop (p < 0.001). Conclusions: An IOM alert during MIS-TLIF may be associated with chronic complications and postoperative neurological deficits, particularly foot drop. These findings highlight IOM’s potential use as an effective intraoperative screening tool to rule out iatrogenic foot drop but also its limited value to independently predict rare postoperative complications. Full article

Background/Objectives: Miniscrew-assisted rapid palatal expansion (MARPE) is an effective treatment for maxillary transverse deficiency in skeletally mature patients. However, resistance of the midpalatal suture may limit treatment success. Surgical corticopunctures have been proposed to facilitate suture opening, while digital planning and 3D-printed surgical guides may improve procedural accuracy and safety. This study aims to evaluate the clinical effectiveness and safety of MARPE combined with surgically guided midpalatal corticopunctures in adult patients. Methods: A retrospective observational study was conducted on 15 adult patients (at least 20 years old) presenting with maxillary transverse deficiency and midpalatal suture maturation stages D or E. All patients underwent corticopuncture-assisted MARPE using patient-specific 3D-printed surgical guides designed through CBCT-based virtual planning. Treatment success was assessed by postoperative cone-beam computed tomography (CBCT), which evaluated midpalatal suture opening and transverse expansion. Clinical records were reviewed for complications, mini-implant stability, and postoperative outcomes. Results: Successful opening of the midpalatal suture was achieved in 13 of 15 patients, corresponding to a success rate of 86.7%. Among successful cases, the mean suture expansion measured on CBCT was 3.6 ± 0.9 mm. The customized surgical guides demonstrated adequate intraoral fit and enabled accurate execution of the planned corticopunctures in all cases. No intraoperative guide-related complications were reported. Postoperative healing was uneventful, with only mild and transient discomfort observed. No infections, excessive bleeding, significant soft-tissue injuries, damage to adjacent anatomical structures, or adverse events related to the corticopuncture procedure were recorded. Mini-implant stability was maintained in the majority of patients throughout the expansion phase. Conclusions: Within the limitations of this retrospective single-arm study, corticopuncture-assisted MARPE performed using customized 3D-printed surgical guides was feasible and associated with a high rate of successful midpalatal suture opening and few complications. The technique demonstrated a high rate of suture opening, clinically significant skeletal expansion, and a low incidence of complications. Digital planning and guided execution may enhance treatment precision and improve clinical outcomes in MARPE procedures. Full article

Background/Objectives: Linear accelerator (LINAC)-based radiosurgery (SRS) is a well-established, non-invasive treatment for pharmacologically refractory trigeminal neuralgia. Despite its widespread use, long-term efficacy and recurrence rates remain incompletely defined, highlighting the need for extended follow-up studies to assess outcome durability. Methods: All patients diagnosed with trigeminal neuralgia and treated with LINAC-based SRS (60 Gy, 1–2 mm from the nerve root entry zone) between 2012 and 2019 at a single institution, a national reference center, were recruited for this study. Patients were divided into two categories based on the nature of their neuralgia: typical or atypical. Pain control was assessed using the Barrow Neurological Institute (BNI) scale at 12, 36 and 60 months, as well as time to improvement, recurrence, and adverse effects. Results: A total of 112 patients were analyzed, with a mean follow-up period of 105.14 (SD 30.65) months. Statistically significant differences in the success of pain control (BNI I–III) between patients with typical and atypical neuralgia were observed at all evaluated time points (12 months: 87.1% vs. 44.0%, 36 months: 77.0% vs. 22.0%, and 60 months: 60.7% vs. 18.0%) (p < 0.001). The mean time to improvement was 6.32 (SD 6.61) weeks (range 0–50), and the recurrence rate following initial improvement was 47.1%. Treatment-related adverse clinical events occurred in 5.4% of patients. Conclusions: Long-term pain control is achieved in refractory trigeminal neuralgia cases with LINAC-based SRS, especially in typical cases, with a low incidence of complications. Full article

Transient extrusion defects are a fundamental process control challenge in fused granular fabrication (FGF), arising from the finite melt pressurization time of screw-driven extruders at each start–stop event. This study presents an integrated experimental and analytical framework for the characterization and open-loop feedforward compensation of these transient dynamics, demonstrated on two composite thermoplastic feedstocks: a recycled random polypropylene (RPP1) and a 20 wt% wood-fiber-reinforced polypropylene composite (WFPP). Unlike prior filament- or single-material feedforward strategies, this framework derives and statistically validates material-specific compensation parameters across two rheologically distinct feedstocks. Single-layer road experiments were conducted on a custom instrumented FGF platform across a 2³⁻¹ half-fraction factorial design varying melt temperature, print acceleration, and nozzle diameter, with screw speed stepped among 20, 40, and 80 RPM to excite transient states; deposited road geometry was digitized and spatially registered to the synchronized process signals. Main-effects regression confirmed that nozzle diameter is the dominant predictor of mean road width, while screw velocity exerts a significant negative effect attributable to speed-dependent backflow. Prediction-error minimization on the pooled multi-experiment dataset yielded a parsimonious first-order transfer function, G(s) = 0.990/(1 + 1.909s), whose time constant is physically attributed to melt compressibility in the barrel volume upstream of the nozzle restriction. This model was embedded in a G-code post-processor implementing two sequential corrections: a material-specific steady-state slip gain and a discrete linear-advance term parameterized by the identified time constant. For RPP1 at the nominal gain, the print latency interquartile range decreased from 5–20 mm to 2–8 mm without degrading steady-state dimensional accuracy; the combination of nominal gain with active retraction further reduced latency to near-zero. Analysis of covariance (ANCOVA) confirmed that optimal feedforward gains are statistically material-dependent across all three quality metrics (p < 0.05), providing statistical justification for material-specific compensator parameterization. The results establish a practical, hardware-agnostic route to reduce transient deposition defects in pellet-based additive manufacturing, extensible to additional feedstocks. Full article

Strong earthquakes cause severe casualties and economic losses. Accurate and rapid magnitude estimation can enable timely emergency response and effectively mitigate earthquake disasters. Current mainstream algorithms rely on broadband seismic or strong-motion data, but during strong earthquakes, near-field clipping and a limited P-wave time window lead to significant underestimation of magnitudes. High-Rate Global Navigation Satellite System (HR-GNSS) data, which directly records ground displacement, can overcome the near-field clipping issue and holds significant potential for magnitude estimation in moderate-to-large earthquakes. With the application of deep learning in seismology, combining HR-GNSS data with deep learning can enable fast and accurate magnitude estimation. By simulating numerous earthquake ruptures and their HR-GNSS displacement waveforms, we trained a deep learning model for near real-time magnitude estimation. Results show high accuracy for moderate earthquakes (Mw 6.3+) in single-fault scenarios. In multi-fault scenarios, without requiring prior source location knowledge, the model quickly estimates magnitudes for major earthquakes (Mw 7.0+) near predefined faults based on GNSS displacement waveforms. Testing on the 2019 Ridgecrest earthquake sequence indicates that within 30 s, the estimated magnitudes stabilize close to the actual magnitudes with an error of less than 0.15 magnitude units. Compared to the peak displacement (Pd) method based on broadband seismic waves and the HR-GNSS regression method, our approach offers superior timeliness and accuracy without needing prior epicenter location information. Uncertainty tests show that for large earthquakes (Mw 7.2+), the method achieves 99% accuracy within 40 s. Overall, the model performs best for Mw 7.2+ events, retains limited applicability for Mw 6.3–7.2 events, and is less stable below Mw 6.3. Full article

Background and Objectives: Hypoxia is the most common adverse event in patients undergoing procedural sedation. Burn-related pain is severe and often requires high doses of opioids and anxiolytics, increasing the risk of respiratory depression. This study aimed to compare the effectiveness of high-flow nasal oxygen (HFNO) and standard nasal oxygen (SNO) in preventing hypoxia during deep sedation in patients with minor and moderate burns. Materials and Methods: This single-center prospective observational study enrolled 76 adult patients (ASA I–III) with minor to moderate burns undergoing supine-position procedures under sedation. Patients were allocated to HFNO (n = 38) or SNO (n = 38) groups according to a pre-specified, non-randomized allocation rule based on an alternating/sequential assignment by admission order. Peripheral oxygen saturation (SpO₂), Bispectral Index (BIS), and Near-Infrared Spectroscopy (NIRS) were monitored throughout. Desaturation was defined as SpO₂ ≤ 90%; severe hypoxia as SpO₂ < 75%. Sedation depth was standardized using BIS (target: 60–80). Propofol–ketamine-based induction was used in all patients. Results: Groups were comparable in demographics, comorbidities, burn characteristics, and procedural duration. SpO₂ ≤ 90% occurred in 79% of SNO patients vs. 11% in the HFNO group (p < 0.001). SpO₂ between 75 and 90% was observed in 68% of SNO vs. 0% of HFNO patients (p < 0.001), and SpO₂ < 75% in 26% vs. 0% (p < 0.001). Airway interventions—jaw thrust, flow increase, and FiO₂ increase—were significantly more frequent in the SNO group (84% vs. 2.6%, 84% vs. 11%, and 84% vs. 5.3%, respectively; all p < 0.001). No significant between-group differences were noted in procedure interruptions, laryngospasm, BIS, NIRS, or hemodynamic parameters. Conclusions: HFNO significantly reduced the incidence of hypoxia and the need for airway interventions compared with SNO during deep sedation in minor and moderate burn patients. These findings suggest that HFNO may represent a preferable oxygenation strategy in this population; given the observational design of this study, confirmation in randomized controlled trials is warranted before this can inform routine practice recommendations. Full article

Background and Objectives: Hyperphosphatemia is a key component of chronic kidney disease-mineral and bone disorder and is associated with higher rates of cardiovascular events and mortality in patients undergoing dialysis. Phosphate binders are essential for phosphorus reduction, and their evaluation relies on several factors, such as chemical composition, binding capacity, and safety profile. Unfortunately, long-term management is hindered by high pill burden and poor adherence. Magnesium phosphate binders have proven effectiveness in reducing phosphate levels. Nevertheless, despite their efficacy, they are not widely used in clinical settings because of concerns related to their use. This study assessed the efficacy of low-dose magnesium carbonate as a phosphate binder in patients undergoing chronic dialysis, focusing on its biochemical control, tolerability, and cost-effectiveness. Materials and Methods: A prospective observational study was conducted on 54 hemodialysis patients with end-stage renal disease at a single dialysis center. Patients were taking either 250 mg magnesium carbonate or 2400 mg sevelamer carbonate for 3 months. Results: Both groups showed decreased phosphorus levels, with a 14.2% significant reduction in the magnesium carbonate group (p < 0.001) and a 5.1% reduction in the sevelamer carbonate group. At the end of the study, no significant differences were observed between the groups (p = 0.682). In the magnesium carbonate group at month 3, compared to baseline, no significant differences were detected in other laboratory parameters reflecting calcium–phosphorus metabolism (Ca—p = 0.681, PTH—p = 0.126). Simultaneously, good compliance without clinically relevant gastrointestinal side effects was observed, including the absence of clinically significant hypermagnesemia. Conclusions: The phosphorus-lowering potential of low-dose magnesium carbonate is non-inferior to that of low-dose sevelamer carbonate. However, its favorable safety profile, low incidence of adverse effects, and cost-effectiveness make it a promising option in clinical practice, further highlighting the need for better recognition by physicians. Full article

In a closed-inventory large language model (LLM) system such as Online-CADCOM, which recommends engineering tools from a verified inventory, we measure inventory non-compliance, that is, a mention-level event in which the model recommends a tool not present in the verified inventory. We use this inventory-relative sense of hallucination throughout: an out-of-inventory mention may be a fabricated tool or a real commercial tool absent from the curated inventory, so the metric reports inventory non-compliance rather than factual fabrication. We evaluate a three-mechanism mitigation stack consisting of database-grounded context injection, fixed vocabulary constraints, and enforced JavaScript Object Notation (JSON) output across three commercial LLM providers (OpenAI, Anthropic, Google), two model generations, and two output modes (standard and reasoning), totaling 6912 Application Programming Interface (API) calls over 12 configurations. Under a recall-equalized detector adopted as the primary metric, the inventory non-compliance rate, which we denote the hallucination rate (HR) following common usage, decreases from roughly 69–80% to 4–13% under the full architecture. The cross-provider average is similar across the two generations tested (8.5% Generation 1 (Gen1), 6.9% Generation 2 (Gen2)), although per-provider directions diverge. We also examine the C3 configuration, in which only JSON output enforcement is active without grounding. A naive detector reports a large hallucination increase over the unconstrained baseline (+10.1 percentage points (pp) Gen1, +15.1 pp Gen2), but we show this gap is largely a detection-format artifact: structured JSON fields make out-of-inventory tools easy to extract, whereas the same real tools are frequently missed in free text. Under a recall-equalized detector the gap narrows to +2.6 pp (Gen1) and +4.8 pp (Gen2) and remains statistically significant only for two current-generation models, indicating a small, current-generation effect rather than a universal one. Reasoning-mode models provide no statistically significant improvement under architectural constraints. A frequency-weighted audit shows that the majority of remaining out-of-inventory mentions correspond to real engineering tools absent from the platform’s inventory. Under the full architecture, roughly half of responses (pooled $P_{\mathrm{any}}\approx 49.5\%$) still contain at least one such mention, indicating that handling unseen tools remains an open challenge for closed-inventory recommendation systems. Our evidence comes from a single engineering platform with four related electronic-design and power-electronics domains, so the findings characterize this setting rather than recommendation domains in general. Full article

Increasingly stringent regulations regarding climate policy and the sustainable development paradigm determine the transformation of contemporary multi-family housing typology, manifested by a growing share of single-aspect micro-apartments (units with exterior exposure on only one facade). This article identifies the phenomenon of the energy-efficiency paradox, wherein highly insulated buildings successfully trap winter heat but inadvertently escalate summer cooling demands. Consequently, the primary operational challenge becomes limiting excessive solar heat gains in summer, which directly translates into high cooling energy demand, rather than solely mitigating heat losses in winter. Sustainable construction requires moving beyond the narrowly defined reduction of envelope thermal transmittance towards holistic adaptation to climate change and ensuring adequate indoor environmental quality. The methodology is based on a coupled energy-economic analysis, evaluating thermal balances and their direct financial implications for end-users. The variant analysis of solar heat gains conducted for a reference 30 m² dwelling in Warsaw proves that architectural optimization should not be determined solely by short-term investment profit maximization. Effective engineering optimization in construction requires the implementation of a full building life cycle perspective. Unfavorable glazing orientation and the lack of cross-ventilation necessitate the use of energy-intensive air-conditioning systems, which directly increases the building’s carbon footprint and generates hidden operating costs (differences reaching over 145 PLN annually for heating and approximately 70 PLN for cooling). The findings highlight the necessity for a critical reevaluation of design priorities for compact apartments, integrating social justice (by reducing information asymmetry in the real estate market, where buyers are often unaware of these future cooling burdens) with long-term economic rationality and the resilience of the built environment to extreme weather events. Full article

Background: Ankle osteoarthritis (OA) differs fundamentally from knee OA: it is predominantly post-traumatic, affects younger and more active patients, and frequently arises from focal osteochondral lesions of the talus (OCLT) rather than diffuse degeneration. Cell-based and orthobiologic therapies—bone marrow aspirate concentrate (BMAC), bone marrow-derived cell transplantation (BMDC), adipose-derived mesenchymal stromal cells (ADMSCs), stromal vascular fraction (SVF), micro-fragmented adipose tissue (mFAT), and peripheral blood-derived products—have been proposed as joint-preserving options, but the evidence base has not been mapped in a way that separates degenerative post-traumatic ankle OA from focal chondral repair, or that distinguishes cells given as a standalone injection from cells given alongside a therapeutic operation. Methods: We conducted a systematic scoping review following the PRISMA-ScR framework. Human clinical studies applying cell-based therapies to post-traumatic ankle OA and/or OCLT were charted by population, cell source and preparation, mode of delivery, concomitant procedures, follow-up, and reported clinical and structural outcomes. Mode of delivery—standalone intra-articular injection versus adjunct to a concomitant surgical procedure—was pre-specified as a primary analytic axis, because it determines whether an observed effect can be attributed to the cell product at all. Given anticipated clinical and product heterogeneity and the near-absence of controlled trials of standalone injection, no meta-analysis was undertaken; the objective was to map the evidence, characterise its structure, and identify gaps. Results: Eleven clinical studies were charted. The dominant structural feature of this literature is that in nine of 11 studies the cells were co-administered with a therapeutic surgical procedure—marrow stimulation, autologous osteochondral transplantation, supramalleolar or calcaneal osteotomy, or joint debridement—so that in no charted study can the contribution of the cells be separated from that of the operation. This attribution problem, rather than any efficacy estimate, is the principal finding of the review. The remaining evidence is small, heterogeneous, and uniformly non-randomised (Level of Evidence III–V). Only two studies used standalone injection, and for degenerative post-traumatic ankle OA specifically, the standalone-injection evidence consists of a single case report. Reported clinical outcomes (AOFAS, VAS, FAOS/KOOS, Tegner) and structural surrogates (MOCART, T2-mapping, second-look arthroscopy) were generally favourable, and adverse events were mild and self-limiting; however, no study demonstrated histologically confirmed hyaline regeneration, and no adequately powered randomised trial of standalone injection for degenerative post-traumatic ankle OA was identified. Conclusions: Cell-based therapies for post-traumatic ankle OA and OCLT show promising but preliminary, hypothesis-generating signals within a fragmented evidence base in which the cellular contribution is confounded by concomitant surgery in nine of 11 charted studies; on present evidence, the field cannot claim an independent effect for the cell product. The knee OA evidence cannot be extrapolated to the ankle because of the joint’s distinct biology, aetiology, and lesion pattern. Adequately powered randomised trials of standalone intra-articular injection in well-defined degenerative post-traumatic ankle OA, using standardised product characterisation and a core outcome set with quantitative structural endpoints, are the principal advance needed. Full article

Industrial Internet of Things (IIoT) edge computing supports latency-sensitive services through task offloading to distributed edge resources. However, large-scale emergencies such as node failures and traffic surges may trigger cascading failures, leading to severe performance degradation and poor post-crisis recovery. Existing offloading methods mainly optimize operational efficiency under normal conditions while overlooking resilience against cascading disruptions. To address this issue, we propose Cascade-Emergency Resilient Offloading (CERO), an adversarial deep reinforcement learning framework for resilient task offloading in IIoT edge computing. Distinct from existing works, CERO introduces a structure-aware shared node encoder to capture heterogeneous topological roles of edge nodes, providing critical structural information for cascade-aware decision making, and incorporates cascade-oriented adversarial training to enhance robustness against compound disturbances. CERO integrates structure-aware state representation, minimax adversarial training, and potential-based reward shaping to learn resource-allocation policies balancing task efficiency and system resilience. By interacting with dynamically generated crisis scenarios, the agent learns resilient offloading policies and achieves high post-crisis recovery performance after cascading disruptions. All performance evaluations are conducted via discrete-event simulation experiments. Simulation results for normal, single-crisis, and compound-crisis scenarios show that CERO achieves comparable task efficiency under normal conditions and significantly superior post-crisis recovery performance compared to conventional rule-based strategies. In the hardest compound-crisis case involving simultaneous node failures and load surges, CERO achieves a post-recovery task-completion rate of 97.8%, surpassing the best rule-based baseline by more than 63 percentage points. Statistical significance is confirmed by the Wilcoxon signed-rank test with Bonferroni correction over 10 independent runs. These results demonstrate that CERO effectively improves the robustness and recoverability of IIoT edge-computing systems under cascading emergency scenarios. Full article

Geopolitical disruptions at maritime chokepoints cascade through interconnected economic systems, yet the pathways along which such shocks travel and the nodes at which they are absorbed remain poorly understood. The aim of this study is to trace, within a single coupled framework, how the 2026 Strait of Hormuz oil-price shock propagated through Korean-origin aviation demand, Southeast Asian destination tourism, and the macroeconomies of four oil-importing economies, and to identify where and how the shock was absorbed. Treating the disruption as an exogenous perturbation, we follow its diffusion across four interacting nodes: oil prices, Korean-origin aviation demand to Southeast Asian destinations, destination-level tourism flows, and national macroeconomic states. Using a triple-difference design with event-study and placebo-year tests on monthly route-level data, and supported by explicit parallel-trend, control-stability, and route-classification robustness checks, we find that aviation demand to leisure routes contracted by roughly 27%, accompanied by an almost identical fall in flight frequency and an unchanged load factor—a pattern consistent with a market-clearing capacity adjustment. The effect concentrated after the March blockade and stabilized thereafter, suggesting a self-limiting rather than self-amplifying dynamic. Downstream, destination-level arrivals did not contract proportionally, plausibly buffered by source-market substitution that scales with a destination’s market diversification. Along the macroeconomic branch, the same shock co-moved with rising inflation and depreciating currencies, but the magnitude of these responses varied with fuel-pricing and exchange-rate regimes. We interpret these findings as an exploratory, systems-level account in which chokepoint oil shocks act as multi-node propagation-and-absorption processes, where resilience appears to emerge endogenously from market substitution and policy–regime heterogeneity rather than being externally imposed. Full article

Background: Stroke is a leading cause of neurological disability worldwide, with upper limb impairment affecting approximately 70% of survivors and only 5–20% achieving complete dexterity recovery at six months. Brain–computer interface (BCI) neurorehabilitation decodes motor intentions from electroencephalographic (EEG) signals to deliver synchronized functional electrical stimulation (FES) and virtual reality feedback, creating a closed-loop neurofeedback system that reinforces motor learning. While existing evidence supports BCI efficacy and safety in chronic stroke, its feasibility, safety, and cost-effectiveness during the acute and subacute phase (2 to 12 weeks post-stroke), when neuroplasticity is heightened, remain underexplored. Furthermore, there is a paucity of data regarding preliminary health economic analyses for BCI rehabilitation in acute stroke rehabilitation settings. Methods: This prospective, open-label, single-arm pragmatic feasibility pilot trial will recruit 12 patients with hemorrhagic or ischemic stroke (2–12 weeks post-stroke) undergoing inpatient rehabilitation from a public healthcare institution. Up to 15 sessions of BCI-rehabilitation of 30 min each using the recoveriX system will be supervised by a trained therapist or clinical research assistant (4–5 sessions/week over 3–4 weeks), followed by standard occupational therapy within 30–60 min of BCI-rehabilitation. Primary outcomes assessing feasibility and adherence include eligibility and recruitment rate (%/screened); tolerability using self-rated System Usability Scale (SUS) score; within-session adherence > 80%/240 trials, summated for completed trials per patient; programme completion number > 80% of scheduled (>12/15) sessions; and training-related adverse events per patient ≤ 17% (≤2/12 sessions). Secondary outcome measures include clinical efficacy by arm impairment scale using hemiplegic Upper Limb Fugl–Meyer Motor Assessment (FMA-UE), hand function using Action Research Arm Test (ARAT), admission and discharge functional status (Functional Independence Measure-FIM (18–126), Modified Barthel Index-MBI (0–100), stroke impact scale (SIS_3.0), arm, participation domains), and economic analysis. All outcomes will be measured by trained therapists/researchers at baseline week 0, week 3–4 (post-BCI-rehabilitation), and week 12 and 24 (follow-up). BCI-rehabilitation EEG-derived electrophysiological correlates of recovery will be extracted to better understand participant progress over time. An incremental cost-utility analysis will compare the BCI-rehabilitation participants against propensity-matched historical controls from the TTSH stroke rehabilitation registry (2017 to 2025), stratified by baseline motor severity. Discussion: This study will provide preliminary evidence on feasibility, tolerability, safety, clinical efficacy, and cost-effectiveness of early BCI-rehabilitation in acute/subacute stroke to better inform clinicians on its implementation. Full article

Distinguishing seizures from other causes of transient loss of consciousness in the emergency department (ED) is challenging. This PRISMA-guided systematic review evaluated serum brain injury biomarkers for the acute diagnosis of seizures in adults. We searched PubMed and Web of Science for studies published between 2015 and 2025 and included 14 studies in which blood sampling occurred shortly after the event, reflecting the ED diagnostic window. Given the heterogeneity across studies, the overall certainty of the evidence was low. Neuron-specific enolase (NSE) and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1) were consistently elevated after epileptic seizures compared to healthy controls. NSE effectively differentiated seizures from syncope, while UCH-L1 and glial fibrillary acidic protein (GFAP) distinguished epileptic from psychogenic non-epileptic seizures (PNESs). Neurofilament light chain (NfL) remained stable after a single seizure but increased markedly in status epilepticus (SE). S100B and BDNF results were inconsistent. Although no single biomarker serves as a standalone test, NSE and UCH-L1 are promising complementary diagnostic tools for identifying epileptic seizures in adults. Furthermore, NfL is a strong candidate marker for SE, reflecting neuroaxonal injury. Larger prospective, standardized studies are needed before routine ED implementation. Full article