Search Results (3,911)

The dual imperative of mitigating carbon emissions and maximizing hydrocarbon recovery has amplified global interest in carbon capture, utilization, and storage (CCUS) technologies. These integrated processes hold significant promise for achieving net-zero targets while extending the productive life of mature oil reservoirs. However, their effectiveness hinges on a nuanced understanding of the complex interactions between geological formations, reservoir characteristics, and injection strategies. In this study, a comprehensive machine learning-based framework is presented for estimating CO₂ storage capacity and enhanced oil recovery (EOR) performance simultaneously in subsurface reservoirs. The methodology combines simulation-driven uncertainty quantification with supervised machine learning to develop predictive surrogate models. Simulation results were used to generate a diverse dataset of reservoir and operational parameters, which served as inputs for training and testing three machine learning models: Random Forest, Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN). The models were trained to predict three key performance indicators (KPIs): cumulative oil production (bbl), oil recovery factor (%), and CO₂ sequestration volume (SCF). All three models exhibited exceptional predictive accuracy, achieving coefficients of determination (R²) greater than 0.999 across both training and testing datasets for all KPIs. Specifically, the Random Forest and XGBoost models consistently outperformed the ANN model in terms of generalization, particularly for CO₂ sequestration volume predictions. These results underscore the robustness and reliability of machine learning models for evaluating and forecasting the performance of CO₂-EOR and sequestration strategies. To enhance model interpretability and support decision-making, SHapley Additive exPlanations (SHAP) analysis was applied. SHAP, grounded in cooperative game theory, offers a model-agnostic approach to feature attribution by assigning an importance value to each input parameter for a given prediction. The SHAP results provided transparent and quantifiable insights into how geological and operational features such as porosity, injection rate, water production rate, pressure, etc., affect key output metrics. Overall, this study demonstrates that integrating machine learning with domain-specific simulation data offers a scalable approach for optimizing CCUS operations. The insights derived from the predictive models and SHAP analysis can inform strategic planning, reduce operational uncertainty, and support more sustainable oilfield development practices. Full article

Background: Intracranial atherosclerotic disease (ICAD) remains a major global cause of ischemic stroke—particularly in Asian, Black, and Hispanic populations—and is characterized by high recurrence rates despite advances in intensive medical management. Objectives: This review synthesizes current evidence on surgical and endovascular approaches for ICAD, including extracranial–intracranial bypass, encephaloduroarteriosynangiosis, angioplasty, and hybrid revascularization strategies. Methods: We performed a structured narrative literature search of PubMed and Scopus. Searches were conducted up to 1 October 2025 using combinations of subject headings and keywords, including “intracranial atherosclerotic disease”, “ICAD”, “intracranial stenosis”, “bypass”, “encephaloduroarteriosynangiosis”, “angioplasty”, “stenting”, “revascularization”, and “stroke”. We also scanned reference lists of key articles and relevant reviews. Non-English language articles were excluded. Results: While randomized trials such as SAMMPRIS, VISSIT, and CASSISS reaffirm intensive medical management as first-line therapy, emerging data suggest that surgical revascularization may benefit select patients with hemodynamic compromise refractory to medical therapy. Recent studies incorporating physiologic imaging—such as PET, SPECT, and perfusion MRI—have refined patient selection, reducing perioperative risk and improving long-term outcomes. Innovations in indirect revascularization, hybrid procedures, and intraoperative imaging continue to expand therapeutic possibilities. However, evidence remains heterogeneous, underscoring the need for well-powered randomized trials integrating modern surgical techniques, objective hemodynamic endpoints, and AI-enhanced imaging analytics. Conclusions: While intensive medical management remains the first-line standard of care, select patients with refractory, hemodynamically significant ICAD may benefit from direct, indirect, or hybrid surgical revascularization. Future directions emphasize personalized, physiology-based management frameworks that combine medical, surgical, and technological advances to optimize stroke prevention and long-term vascular outcomes in ICAD. Full article

Wastewater-based surveillance is an effective method to monitor community health by detecting pathogens excreted from large populations. Traditionally, wastewater analyses are considered privacy-preserving since samples are pooled. However, advances in molecular resolution may challenge this assumption. This study investigated whether a rare SARS-CoV-2 variant detected in a hospital sewershed could be linked to a specific patient. During 2023, wastewater samples were collected weekly and analyzed for SARS-CoV-2 concentrations and variant composition using droplet digital PCR (ddPCR) and tiled sequencing. During the same period, nasal swab samples from hospital patients were sequenced for comparison. While wastewater was dominated by Omicron lineages, several weeks showed a sharp increase in SARS-CoV-2 concentrations, with over 80% belonging to the Delta lineage AY.25—rare globally since 2022. Nasal swab sequencing identified one patient carrying AY.25, whose admission and discharge coincided with the emergence and disappearance of AY.25 in the hospital’s wastewater. The temporal pattern and sequence similarity suggest that the Delta signal might have originated from this single patient, with sequence differences potentially reflecting intrahost divergence. These findings indicate that, under certain conditions, wastewater signals can be attributed to individuals, highlighting the need to keep in mind the ethical considerations surrounding privacy and data use while benefiting the community through wastewater surveillance. Full article

Early-life respiratory syncytial virus (EL-RSV) infection has been implicated in long-term pulmonary disease in children. In these studies, neonatal BALB/c mice were infected at day 7 of life, leading to >35% losses in critical lung function, airway mucus metaplasia, and transcriptional hallmarks of mucus hypersecretion four weeks after RSV infection. While EL-RSV minimally reshaped the resident lung microbiota, it led to significant gut dysbiosis, including a long-term reduction of Proteobacteria that can be a source of protective metabolites related to barrier and immune function. Subsequent studies assessing whether a common infant antibiotic (ampicillin) could mitigate EL-RSV-induced lung alterations revealed further severe gut microbiome alterations and, on its own, later in life, recapitulated the full spectrum of RSV-associated alterations in lung function. Metagenomic inference showed that both RSV and ampicillin administered during early life reduced biosynthetic pathways for microbiome-derived metabolites, which are known to reinforce tight junctions, regulate inflammation, and preserve extracellular matrix elasticity. The shared loss of these metabolic programs provides a mechanistic bridge linking distinct early-life exposures to the microbiome changes and airway mechanical deficits later in life. Collectively, the data suggest that RSV and/or antibiotic-triggered gut dysbiosis is the primary insult that likely promotes improper lung maturation/repair through a metabolite-mediated mechanism and may suggest metabolite restoration as a strategy to promote proper developmental lung function. Full article

Calcium phosphate cements (CPCs) and biomaterials, such as mesoporous bioactive glass (MBG), are critical for bone tissue engineering. This study aimed to 3D-print CPC scaffolds modified with MBG to enhance their osteogenic potential and regenerative ability. MBG powder was synthesized and characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), and nitrogen adsorption–desorption techniques. A commercial CPC ink (hydroxyapatite/α-tricalcium phosphate) was mixed with 5% MBG (w/w; CPC/MBG), and, after rheological assessment, the mixture was used to obtain scaffolds via 3D printing. These scaffolds were then tested for chemical, morphological, and mechanical properties, as well as ion release analysis. Unmodified CPC 3D-printed scaffolds served as controls. Biological experiments, including cell viability, DNA content, cell adhesion/spreading, and osteogenic gene expression, were performed by seeding alveolar bone-derived mesenchymal stem cells onto the scaffolds. Statistics were performed using Student’s t-test and ANOVA with post hoc tests (α = 5%). MBG characterization showed a typical mesoporous structure with aligned microchannels and an amorphous structure. Both formulations released calcium and phosphate ions; however, CPC/MBG also released silicon. Cell viability, adhesion/spreading, and DNA content were significantly greater in CPC/MBG scaffolds compared to CPC (p < 0.05) after 3 and 7 days of culture. Furthermore, CPC/MBG supported increased expression of key osteogenic genes, including collagen (COL1A1), osteocalcin (OCN), and Runt-related transcription factor 2 (RUNX2), after 14 days (p < 0.05). The combination of CPC ink with MBG particles effectively enhances the biocompatibility and osteogenic potential of the scaffold, making it an innovative bioceramic ink formulation for 3D printing personalized scaffolds for bone regeneration. Full article

Invasive species and changing thermal structure are widely recognized as drivers of change to freshwater ecosystems, yet the interactions of these two drivers have rarely been studied. This study conducted a secondary analysis of a large federal database (GLANSIS) of literature used in assessing the current risk of potential nonindigenous species to the Great Lakes (watchlist species) to evaluate how increased water temperatures would impact the risk of establishment posed by these species. Our analysis found that 46% of the current watchlist species would pose a higher potential risk while 7% would pose a lower potential risk. Lake Superior and Lake Huron exhibited significant increases in the number of species likely to find a suitable habitat. Full article

Background: Infectious diseases accounted for approximately 18.4% of global mortality in 2019. According to the World Health Organization (WHO), vaccines are available for about 30 potentially lethal diseases. Vaccination prevents substantial mortality and hospitalization. However, its ability to improve overall public health depends on equitable access across all populations, regardless of race, ethnicity, education, or socioeconomic status. Objectives: This study aims to examine how disparities in social determinants of health (SDOH) affect COVID-19 vaccination uptake across Jefferson County, Kentucky. Using ZIP code–level spatial mapping, this study investigates the intersection of SDOH, racial composition, and geographic characteristics to identify inequities and inform equitable interventions. Methods: Data from the Kentucky Immunization Registry (KYIR) were analyzed to assess two-dose COVID-19 vaccination rates at the ZIP code and regional levels in Jefferson County, Kentucky. Vaccination rates were stratified by race and ethnicity and linked with SDOH, including education, employment, insurance status, and income, obtained from the 2021 American Community Survey. Results: By May 2021, vaccination rates ranged from 25.9% in the West region to 57.0% in the Inner East region; by May 2022, these rates increased to 46.2% and 73.9%, respectively. White residents consistently had the highest two-dose vaccination rates (66.4% by May 2022), while Black and Hispanic residents had lower rates (45.7% and 43.9%, respectively). Vaccination rates were strongly correlated with SDOH, especially educational attainment, average family income, and employment rate, underscoring the role of socioeconomic inequities in vaccination disparities. Conclusions: Geographical and racial disparities emphasize the influence of social and economic inequality on vaccine uptake. Full article

Electrocardiography (ECG) is widely recognized as the gold standard for measuring heart rate (HR) and heart rate variability (HRV). However, photoplethysmography (PPG) presents notable advantages in terms of wearability, affordability, and ease of integration into consumer devices, despite its susceptibility to motion artifacts and the absence of standardized processing protocols. In this study, we review current ECG and PPG signal processing methods and propose a signal quality assessment and reconstruction pipeline tailored for dynamic, in-vehicle environments. This pipeline was evaluated using data gathered from participants riding in an automated vehicle. Our findings demonstrate that while blood volume pulse (BVP) derived from PPG can provide reliable heart rate estimates and support extraction of certain HRV features, its utility in accurately capturing high-frequency HRV components remains constrained due to motion-induced noise and signal distortion. These results underscore the need for caution in interpreting PPG-derived HRV, particularly in mobile or ecologically valid contexts, and highlight the importance of establishing best practices and robust preprocessing methods to enhance the reliability of PPG sensing for field-based physiological monitoring. Full article

This narrative review of rapid eye movement (REM) focuses on its primary etiology and how it fits into the larger framework of neurophysiology and general physiology. Arterial blood flow in the retina may be sensitive to the full overlying ‘weight’ of its adjacent and contiguous vitreous humor caused by the humoral mass effect in the Earth’s gravitational field. During waking hours of the day, this ‘weight’ is continuously shifted in position due to changing head position and eye movements associated with ordinary environmental observations. This reduces its impact on any one point on the retinal field. However, during sleep, the head may maintain a relatively constant position (often supine), and observational eye movements are minimal, leaving essentially one retinal area exposed at the ‘bottom’ of each eye, relative to gravity. During sleep, REM may provide a mechanism for frequently repositioning the retina with respect to the weight it incurs from its adjacent (overlying) vitreous humor. Our findings were consistent with the intermittent terrestrial nocturnal development of ‘gravitational ischemia’ in the retina, wherein the decreased blood flow is accompanied metabolically by decreased oxygen tension, a critically important metric, with a detrimental influence on nerve-related tissue generally. However, the natural mechanisms for releasing and resolving gravitational ischemia, which likely involve glymphatics and cerebrospinal fluid shifts, as well as REM, may gradually fail in old age. Concurrently associated with old age in some individuals is the deposition of alpha-synuclein and/or tau in the retina, together with similar deposition in the brain, and it is also associated with the development of Parkinson’s disease and/or Alzheimer’s disease, possibly as a maladaptive attempt to release and resolve gravitational ischemia. This suggests that a key metabolic parameter of Parkinson’s disease and Alzheimer’s disease may be a lack of oxygen in some neural tissues. There is some evidence that oxygen therapy (hyperbaric oxygen) may be an effective supplemental treatment. Many of the cardinal features of spaceflight-associated neuro-ocular syndrome (SANS) may potentially be explained as features of gravity opposition physiology, which becomes unopposed by gravity during spaceflight. Gravity opposition physiology may, in fact, create significant challenges for humans involved in long-duration space travel (long-term microgravity). Possible solutions may include the use of artificial gravitational fields in space, such as centrifuges. Full article

Across their wide geographic range (Neotropics, and as invasives in New Guinea and Florida), Nasutitermes corniger (conehead termites) live primarily above the ground surface. They build arboreal nests and foraging tunnels, or epigeal nests and tunnels on the ground surface. There are brief reports of below-ground portions of N. corniger nests and foraging tunnels as rare occurrences of structures extending underground. The entirely and partially underground nests and foraging tunnels described in this paper are distinct and novel from previous observations. They are based on multiple discoveries in areas of Broward County, Florida, where invasive conehead termite activity below ground is common. This paper expands understanding of habitat options for this ecologically agile, adaptable, economically important species. It also serves to alert inspectors in invasive termite eradication programs or pest management situations to explore cryptic locations where nests of all sizes may hide. Effective approaches for treating underground N. corniger activities are described. Full article

Background/Objectives: Differential learning (DL) amplifies natural fluctuations in movement execution and, in its more extreme forms, facilitates repetition-free training with minimal external feedback. While increasingly recognized in the field of skill acquisition, its application in anterior cruciate ligament (ACL) rehabilitation remains underexplored. Methods: This study examined the application of DL in the rehabilitation of an 18-year-old trained basketball player following left-ACL reconstruction. The athlete completed a 42-week rehabilitation program in which DL principles were incorporated throughout the pre-operative, early, mid-, and late phases, culminating in return to sport. Training included differential mobility work, motor control, plyometric exercises, and sport-specific drills. Functional recovery was evaluated using single-leg hop tests, change-of-direction tasks, and sprint performance, while self-reported knee function was monitored via the International Knee Documentation Committee (IKDC) questionnaire. Results: Results indicated substantial improvements in both functional performance and psychological readiness. The IKDC score increased from 13.8% at baseline to 95.4% postoperatively, reaching the normal functional range. An ACL-RSI score of 85.2%, and inter-limb asymmetries were reduced to below 10%. Strength, agility, and sprint performance exceeded pre-injury levels. Conclusions: DL again shows potential as an effective approach to facilitating recovery and return to sport after ACL reconstruction, but larger controlled studies are needed for validation. Full article

Background: Inflammatory bowel disease (IBD) is associated with systemic inflammation and potential cardiovascular complications. This meta-analysis evaluates long-term cardiovascular risks in IBD. Methods: Electronic databases were searched for studies examining cardiovascular, cerebrovascular, and thromboembolic risks in IBD. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were pooled using a random-effects model. Results: Fifty-three studies comprising 1,406,773 patients were analyzed. IBD was linked to increased risk of ischemic heart disease (aHR 1.25; p = 0.001) myocardial infarction (aHR 1.25; p = 0.01), acute coronary syndrome (aHR 1.43; p < 0.00001), heart failure (aHR 1.24; p < 0.00001), atrial fibrillation (aHR 1.20; p < 0.00001), and stroke (aHR 1.13; p < 0.00001). Elevated risks were also observed for peripheral arterial disease (aHR 1.41; p < 0.00001), diabetes mellitus (aHR 1.40; p < 0.00001), venous thromboembolism (aHR 1.98; p < 0.00001), deep vein thrombosis (aHR 2.85; p = 0.0004), and pulmonary embolism (aHR 1.98; p = 0.03). Importantly, IBD was associated with increased cardiovascular (aHR 1.14; p = 0.03) and all-cause mortality (aHR 1.53; p < 0.00001). Conclusions: IBD patients face higher risk for adverse cardiovascular outcomes, thromboembolic disease, and mortality, necessitating early cardiovascular risk assessment and targeted interventions in this population. Full article

Background: The Na⁺/K⁺-ATPase (NKA) maintains electrochemical gradients by exporting Na+ and importing K⁺ at the expense of ATP hydrolysis. Although NKA inhibition is a well-established strategy for increasing cardiac contractility, existing inhibitors such as cardiotonic steroids (CTS) are limited by serious adverse effects. N106 is a small molecule previously shown to enhance cardiac lusitropy by promoting SERCA2a SUMOylation and, intriguingly, also exerts positive inotropic effects, suggesting additional mechanisms of action. Methods: To test whether N106 directly modulates NKA, we combined ATPase activity assays with molecular docking and microsecond-scale molecular dynamics simulations. Results: Biochemical measurements showed that N106 partially inhibits NKA, achieving ~80% maximal inhibition with an IC50 of 7 ± 1 µM, while leaving the pump’s apparent affinity for Na⁺, K⁺, and ATP unchanged. Computational analyses suggest that N106 binds within the canonical CTS-binding pocket but undergoes intermittent unbinding events, consistent with the partial inhibition observed experimentally. Conclusions: These findings identify N106 as a first-in-class dual modulator of cardiac ion pumps, partially inhibiting NKA while previously shown to activate SERCA2a through enhanced SUMOylation. This combined mechanism likely underlies its positive inotropic and lusitropic effects and positions the N106 scaffold as a promising lead for developing next-generation dual-target therapeutics for heart failure. Full article

The variation in the maximum usable frequency (MUF) during geomagnetic disturbances is a key parameter for high-frequency (HF) radio communications. This study investigates MUF variability and related ionospheric parameters during the first geomagnetic superstorm of solar cycle 24, on 17 March 2015 (the Saint Patrick’s Day storm). Using Digisondes at Sao Luis (equatorial) and Campo Grande (low-latitude, near the southern crest of the Equatorial Ionization Anomaly), we analyzed storm-time changes in the F region. During the main phase, two episodes of eastward Prompt Penetration Electric Fields produced rapid uplifts of the F2-layer peak height at São Luis, reaching altitudes up to 520 km, accompanied by MUF decreases of approximately 25% relative to quiet-day values. In contrast, Campo Grande exhibited a more subdued response, with MUF deviations generally remaining within 15–20% of quiet-time conditions. During the recovery phase, the likely occurrence of a westward disturbance dynamo electric field was inferred from suppression of the Pre-Reversal Enhancement and decreased F-layer heights at São Luis. Comparative analysis highlights distinct regional responses: São Luis showed strong storm-time deviations, while Campo Grande remained comparatively stable under the impacts of Equatorial Ionization Anomaly effects. These results provide quantitative evidence of localized geomagnetic storm impacts on MUF in the Brazilian sector, offering insights that may improve space weather monitoring and HF propagation forecasting. Full article

Background: Autism spectrum disorder (ASD) and related neurodevelopmental conditions are a significant public health concern, with diagnostic delays hindering timely intervention. Traditional assessments often lead to waiting times exceeding a year. Advances in artificial intelligence (AI) and biomarker-based screening offer objective, efficient alternatives for early identification. Objective: This review synthesizes the latest evidence for AI-enabled technologies aimed at improving early ASD identification. Modalities covered include eye-tracking, acoustic analysis, video- and sensor-based behavioral screening, neuroimaging, molecular/genetic assays, electronic health record prediction, and home-based digital applications or apps. This manuscript critically evaluates their diagnostic accuracy, clinical feasibility, scalability, and implementation hurdles, while highlighting regulatory and ethical considerations. Findings: Across modalities, machine learning approaches demonstrate strong accuracy and specificity in ASD detection. Eye-tracking and voice-acoustic classifiers reliably differentiate for autistic children, while home-video analysis and Electronic Health Record (EHR)-based algorithms show promise for scalable screening. Multimodal integration significantly enhances predictive power. Several tools have received Food and Drug Administration clearance, signaling momentum for wider clinical deployment. Issues persist regarding equity, data privacy, algorithmic bias, and real-world performance. Conclusions: AI-enabled screeners and diagnostic aids have the potential to transform ASD detection and access to early intervention. Integrating these technologies into clinical workflows must safeguard equity, privacy, and clinician oversight. Ongoing longitudinal research and robust regulatory frameworks are essential to ensure these advances benefit diverse populations and deliver meaningful outcomes for children and families. Full article