Search Results (6,296)

Background: Natriuretic peptides, including B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), are established biomarkers of myocardial stress and circulatory overload. Although originally validated for diagnosis and exclusion of heart failure, their diagnostic and prognostic applications have expanded significantly in the context of critical illness. However, interpretation in critically ill patients is complicated by confounding factors such as systemic inflammation and renal dysfunction. Objective: This review synthesizes current evidence on the diagnostic, monitoring, and prognostic applications of natriuretic peptides in critically ill adults. It further outlines practical considerations, confounding variables, and emerging complementary biomarkers pertinent to clinical decision-making. Methods: A structured search of PubMed, Embase, and the Cochrane Library (January 2000 to October 2025) identified studies evaluating BNP, NT-proBNP, and atrial natriuretic peptide (ANP) in intensive care unit (ICU) patients. Eligible studies and review articles assessed diagnostic utility, volume status, hemodynamic monitoring, and prognostic performance. Narrative synthesis was employed using information obtained from eligible studies. Results: Twenty-four studies met the inclusion criteria. BNP and NT-proBNP facilitate differentiation between cardiogenic and noncardiogenic respiratory failure, identification of mixed shock states, and assessment of volume status when used in association with other modalities such as echocardiography and ultrasonography. Elevated natriuretic peptide concentrations consistently predict mortality, acute kidney injury, prolonged mechanical ventilation, and adverse outcomes in several disease states, including sepsis, acute respiratory distress syndrome [ARDS], postoperative cardiac dysfunction, and COVID-19-related critical illness. However, interpretation remains limited by confounders, including renal impairment, age, systemic inflammation, brain injury, mechanical ventilation, and right-ventricular strain/dysfunction. Conclusions: Natriuretic peptides serve as valuable adjuncts for diagnostic assessment, hemodynamic monitoring, and risk stratification in the ICU. When interpreted with attention to biological kinetics and clinical context, these biomarkers enhance multimodal monitoring and support individualized management. Future research should refine ICU-specific cutoffs and assess natriuretic peptide–guided therapeutic strategies in prospective multicenter trials. Full article

Chronic pain is the leading cause of disability worldwide and frequently co-occurs with mild traumatic brain injury among Veterans (mTBI + CP), creating complex treatment challenges and a need for novel, non-pharmacological interventions. This study evaluated a pilot intervention combining intermittent theta burst stimulation (iTBS), a neuromodulatory approach, with the evidence-based LoveYourBrain Yoga program to enhance rehabilitation outcomes. In a six-week open-label trial, ten Veterans with mTBI + CP received weekly iTBS followed by yoga sessions. Pilot quantitative outcomes included quality of life (Traumatic Brain Injury Quality of Life [TBI-QoL]) and functional ability (Mayo Portland Adaptability Inventory-4 [MPAI-4]), assessed pre- and post-intervention, alongside qualitative semi-structured interviews and interdisciplinary clinical notes. Significant improvements were observed in TBI-QoL Fatigue (p = 0.021) and MPAI-4 Grief and Loss (p = 0.016), with clinically meaningful but non-significant gains in Ability and Adjustment. Qualitative findings revealed improved pain management and enhanced self-management, with participants describing better emotional regulation, more effective coping strategies, and stronger social connections. Some benefits were more evident in qualitative data than in standardized measures. These pilot findings suggest that combining iTBS with mind–body therapy may provide complementary tools for pain management and functional recovery in Veterans with mTBI + CP, supporting further investigation of integrated neuromodulation and behavioral interventions. Full article

Background and Objectives: Endoscope-assisted posterior fossa decompression with duraplasty (PFDD) is a minimally invasive alternative treatment for Chiari I malformation; however, its comparative effectiveness remains unclear. Therefore, this study aimed to compare the outcomes of conventional open decompression with those of endoscope-assisted minimally invasive decompression combined with duraplasty to assess the balance between limited surgical exposure and associated technical challenges. Materials and Methods: This retrospective single-center study compared 22 patients who underwent endoscope-assisted PFDD with a historical cohort of 16 patients treated with conventional open PFDD. Patients with C1–2 instability, prior craniovertebral surgery, or concomitant pathology requiring an alternative surgical strategy were excluded. The clinical outcomes, radiological findings, surgical variables, and complications were analyzed. Results: Clinical improvement, overall recovery, and 3-month Chicago Chiari Outcome Scale (CCOS) scores were comparable between the groups. The endoscopic group had higher CCOS scores at discharge. Syrinx resolution rates were similar, whereas postoperative cisterna magna expansion was more limited in the endoscopic cohort. The endoscopic approach was associated with a significantly shorter incision length and earlier mobilization. The rates of complications, including pseudomeningocele, cerebrospinal fluid fistula, and wound infection, did not differ significantly between the groups. Conclusions: Endoscope-assisted PFDD may be a less invasive alternative with comparable short-term clinical and radiological outcomes. Despite the technical challenges related to a limited working corridor, it can be considered a feasible option for selected patients. Full article

Background: Hypoglossal nerve stimulation (HNS) is an established surgical therapy for adults with moderate-to-severe obstructive sleep apnea (OSA) who are intolerant to positive airway pressure. Although aggregate response rates of ~70–80% have been reported, substantial variability across clinical settings remains poorly understood. Prior meta-analyses have largely emphasized pooled continuous outcomes, limiting interpretation of responder-based endpoints and drivers of between-study heterogeneity. Methods: A PRISMA-compliant systematic review and meta-analysis was performed. MEDLINE, Embase, and Cochrane CENTRAL were searched from inception through 31 December 2025. Eligible studies enrolled adults with OSA treated with implantable HNS, reported Sher-defined response (≥50% AHI reduction and residual AHI < 20 events/hour), and/or continuous outcomes, and included ≥20 patients. Random-effects models (REML) were applied. Heterogeneity was quantified using I² and τ², with prediction intervals. Meta-regression assessed baseline AHI, BMI, and follow-up duration. Subgroup analyses examined device laterality, stimulation modality, sleep assessment method, and follow-up. Results: Thirty-eight studies (39 cohorts; n = 3220) were included. The pooled Sher response rate was 74.0% (95% CI 67.6–79.5%). Heterogeneity was substantial. HNS significantly improved all continuous outcomes (AHI −23.3 events/hour; ESS −4.5 points; ODI −14.5 events/hour). Comparative analyses favored HNS over surgical comparators, inactive stimulation, and delayed treatment. Revision and explantation rates were 5% and 4%, respectively. Meta-regression showed no significant effects of baseline AHI, BMI, or follow-up, explaining negligible variance. Subgroups suggested numerically higher response with breathing-synchronized stimulation, but heterogeneity remained high. Conclusions: HNS achieves Sher response in approximately three-quarters of appropriately selected CPAP-intolerant OSA patients, with durable clinical benefits and a favorable safety profile. Persistent unexplained heterogeneity highlights limitations of conventional predictors and underscores the need for more granular response determinants. Full article

Background/Objectives: Keratoconus (KC) is a chronic disease that causes progressive corneal thinning and steepening, thereby negatively impacting visual acuity. Although corneal topography and keratometry are the primary measures to diagnose KC, access to these methods can be limited by various factors. To address these limitations, this study evaluates a novel low-cost deep-learning algorithm that infers keratometric categories from smartphone-assisted Placido ring photographs. Methods: Development utilized 1240 healthy control eye images and 188 K1-labeled KC images for pretraining, without using their K1 labels. A Variational Autoencoder with KL divergence regularization (AutoEncoderKL) was trained on this pool; its encoder generated latent features for KC images (n = 535). A held-out set (n = 70) with Pentacam keratometry was labeled by K1 into <40 D, 40–47 D, and >47 D. An ensemble classifier chosen via grid search and cross-validation used the encoder features. Performance was assessed for accuracy, precision, recall, and F1-score. Results: The model achieved 91% accuracy across all classes. Precision of the model was 0.77 (<40 D), 0.98 (40–47 D), and 0.86 (>47 D); recall was 0.83, 0.91, and 1.00; and F1-scores were 0.80, 0.94, and 0.92, respectively. Notably, the model achieved perfect recall for the >47 D K1 category. Conclusions: A smartphone-assisted Placido ring imaging approach was able to predict K1-based keratometric categories without requiring tomographic or keratometric measurements as model inputs at inference. These findings provide preliminary proof-of-concept for the potential use of smartphone-assisted Placido ring images as a low-cost approach for K1-based stratification. Larger externally validated studies across different sites, devices, operators, printed Placido discs, acquisition conditions, and patient populations are required before clinical utility can be assessed. Full article

Crime prediction in urban environments is a complex and pressing challenge driven by the intricate interplay of spatiotemporal dependencies, hierarchical geographic patterns, and socio-environmental determinants. We propose a multi-scale geo-temporal crime embedding (MSG-TCE) framework, which hierarchically models these dynamics via three novel components: a hierarchical residual temporal encoder (HRTE), a periodic transformer Encoder (PTE), and a hyperbolic spatial pooler (HSP). The HRTE captures multi-scale temporal trends by combining dilated convolutions with residual connections, while the PTE explicitly encodes periodic crime patterns using self-attention conditioned on cyclical positional encodings. The HSP maps spatial crime hotspots into hyperbolic space to better represent their inherent hierarchical structure, spanning city–district–neighbourhood–street-segment scales, and aggregates neighbourhood information via graph convolutions. These components are fused through a gated cross-attention mechanism, yielding a unified embedding for crime prediction. Experiments on real-world datasets from Chicago, Los Angeles, and New York City demonstrate that MSG-TCE achieves consistent improvements over five competitive baselines across RMSE, Precision@20, and DTW metrics, with statistically significant gains at longer prediction horizons. Ablation studies confirm the contribution of each component. Spatial visualisation maps, robustness analyses, and an exploratory covariate-augmented variant further substantiate the empirical validity of the framework. This paper also discusses limitations, including data reporting biases, the need for full covariate integration, and ethical considerations, pertaining to algorithmic fairness in crime prediction. Full article

Objective: To predict pixel-wise retinal thickness maps from near-infrared (NIR) fundus images using deep learning (DL), and to identify image features in NIR fundus photographs serving as surrogate markers of retinal thickness, with implications for decentralized diabetic macular edema (DME) screening, progression monitoring, and treatment assessment. Methods: A DL model based on a U-Net architecture was trained on paired NIR fundus and OCT images from 531 eyes across three groups: healthy controls, diabetic retinopathy (DR) without DME, and DME. Model performance was evaluated using mean absolute error (MAE), root mean squared error (RMSE), structural similarity index (SSIM), and center-involved DME (ci-DME) classification at a central subfield thickness threshold of 300 µm. Controlled image manipulation experiments, including spatial disruption of vascular patterns, relocation of hard exudates, and contrast enhancement, were performed to identify image-level features serving as surrogate markers of retinal thickness. Results: The model achieved an MAE of 30.41 ± 18.68 µm, RMSE of 36.14 ± 21.05 µm, and SSIM of 0.87 ± 0.04 across the macula, with consistent performance across ETDRS subfields. For ci-DME classification, it achieved an accuracy of 84.1%, sensitivity of 69.1%, and specificity of 88.7%. Interpretability analyses were performed as qualitative assessments to visualize image regions contributing to model predictions. These analyses highlighted retinal vascular structures, hard exudates, and local contrast variations as visual features observed in relation to model outputs. Conclusions: NIR fundus images contain sufficient structural information to support pixel-wise retinal thickness estimation, with vascular architecture, hard exudates, and local contrast variations identified as image features potentially associated with model predictions. These findings suggest that NIR-based deep learning approaches may have potential applications in the assessment of diabetic macular edema and warrant further prospective and external validation to determine their role in screening, triage support, longitudinal monitoring, and treatment-related assessment, particularly in decentralized and re-source-limited care environments. Full article

Background: Breathing exercises and respiratory muscle training (RMT) are accessible, low-cost interventions that may improve both physical and psychological health through respiratory and autonomic regulation. Despite growing interest in respiratory interventions, their combined effects on physical performance, sleep quality, and perceived stress in healthy university students remain poorly understood. Methods: This pilot pre-post experimental study was conducted in Saudi Arabia. Students aged 18–25 years with a BMI < 29.9 kg/m² participated in a 4-week intervention consisting of diaphragmatic breathing, pursed-lip breathing, and threshold-loaded inspiratory and expiratory muscle training (40–60% maximal inspiratory pressure), performed five days per week. Outcomes assessed before and after the intervention included chest expansion, breath-holding time, Timed Up-and-Go (TUG), Sit-to-Stand (STS), Pittsburgh Sleep Quality Index (PSQI), and Perceived Stress Scale (PSS). Paired statistical analyses and correlation tests were performed. Results: Forty participants (50% female; median age 22 years; BMI 23.14 ± 4.05 kg/m²) completed the study. Breath-holding time increased by 132% (p < 0.001, r = 0.87). Functional performance improved significantly, with TUG decreasing by 9% (d_z = 1.01) and STS improving by 12% (d_z = 1.12) (p < 0.001). Sleep quality improved by 26%, while perceived stress decreased by 19% (p ≤ 0.001). Significant exploratory correlations were observed between TUG and STS change scores (r = 0.49), PSQI and PSS changes (r = 0.33), and STS and PSS changes (r = 0.33). Conclusions: Participation in a four-week combined breathing exercise and respiratory muscle training program was associated with favorable within-group changes in breath-holding time, functional performance, sleep quality, and perceived stress among healthy university students. Given the single-arm design, these findings should be considered preliminary and hypothesis-generating. Randomized controlled studies are needed to determine efficacy and causal relationships. Full article

Atrial fibrillation (AF) is the most prevalent sustained arrhythmia and is increasingly driven by cardiometabolic disease, including type 2 diabetes mellitus (T2DM), obesity, and insulin resistance. These conditions promote atrial electrical instability and a permissive substrate through mitochondrial dysfunction, oxidative stress, inflammation, calcium-handling abnormalities, and profibrotic signaling, culminating in atrial fibrosis and conduction heterogeneity. Metformin, the foundational glucose-lowering therapy for T2DM, exerts pleiotropic actions that intersect with these upstream pathways. Beyond glycemic control, metformin induces mild mitochondrial complex I modulation with reduction of reverse electron transfer-derived reactive oxygen species, activates adenosine monophosphate (AMP) activated protein kinase, and attenuates nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)-mediated cytokine signaling; experimental data further suggest favorable effects on adiponectin–sarcoendoplasmic reticulum calcium adenosine triphosphatase (SERCA) 2a-dependent calcium cycling, connexin expression, small-conductance Ca²⁺-activated K+ channel remodeling, lipid handling, and transforming growth factor-β (TGF)-β-associated fibrotic remodeling. Observational cohort studies have reported associations between metformin exposure and a modest reduction in incident AF, particularly with longer treatment duration and in higher-risk metabolic phenotypes; device-based surveillance cohorts support a preventive association for new-onset AF rather than reduction of established AF burden. Data after catheter ablation suggest improved freedom from recurrence in metformin-treated patients, whereas evidence in postoperative AF is largely neutral, likely reflecting distinct acute mechanisms. Collectively, metformin may be best conceptualized as a potential substrate-modifying, upstream therapy candidate; however, confounding, exposure misclassification, and heterogeneity in comparators limit causal inference, underscoring the need for prospective randomized trials with AF endpoints. In practice, integration with comprehensive risk-factor modification (blood pressure, weight, sleep apnea, and glycemic optimization) remains essential when considering AF prevention strategies. Full article

Background: There are certain disadvantages to using CAD/CAM technologies. Marginal and internal accuracy of fit is valued as one of the most important criteria for the clinical quality and success of all-ceramic crowns. The assessment of the marginal fit of lithium disilicate and zirconia CAD/CAM crowns before and after ceramic layering is crucial. Methods: One ideally prepared model tooth was duplicated into 64 plaster models. A standardized wax pattern for a monolithic crown and a coping were produced and used to mill 16 lithium disilicate monolithic crowns and 16 cores using a soft milling process. 16 zirconia crowns and 16 cores were also fabricated. A factorial design with (material) (lithium disilicate [E] or zirconia [Z]); (design) (monolithic, [M] or (core) [C]); and (finish) (as-produced [P] or veneered/glazed [G]) was used to create the following groups: ZMP, ZMG, ZCP, ZCG, EMP, EMG, ECP, and ECG (n = 8). The milled restorations were treated accordingly using ZirLiner, IPS e.max Ceram, and IPS e.max Glaze. The restorations were cemented to their dies, embedded in epoxy resin, and sectioned into two planes with a diamond saw. Vertical and horizontal marginal fit at the finishing line was measured in a standardized way at four locations (mesial, distal, facial, and lingual). Results: There were no differences, p > 0.05, between all Z groups; however, they had significantly wider horizontal gaps, p < 0.05, (116 ± 5 µm) than E groups (64 ± 13 µm). Among lithium disilicate groups, the glazed monolithic (EMG) and veneered/glazed coping (ECG) subgroups showed significantly smaller horizontal gaps (approximately 50 ± 6 µm). Statistical analysis was performed using two-way ANOVA with a significance level set at α = 0.05. Conclusions: Veneering techniques did not affect zirconia. Lithium disilicate had a better marginal fit than zirconia, but this was influenced by veneering techniques. Lithium disilicate veneering and/or glazing significantly improved the marginal fit. Full article

This study examines the relationship between valuation multiples and investment performance in the U.S. stock market. Specifically, it tests whether portfolios constructed with high-multiple stocks consistently outperform portfolios with low-multiple stocks. The analysis spans the Technology, Consumer Staples, and Healthcare sectors from 2018 to 2022. A sector-based portfolio construction framework was employed using quarterly portfolio-return data. Quantitative financial modelling, including regression analysis and descriptive statistics, was applied to assess the correlation between portfolio returns and valuation multiples (P/E and EV/EBITDA), while interpreting results within the broader context of market volatility and the COVID-19 period. The results show no statistically significant relationship between valuation multiples and portfolio performance. Low-multiple portfolios demonstrated marginally higher average returns over the period, offering weak support for value-based investment strategies. Results further suggest limited standalone predictive power in high-multiple valuations. Drawing on the Efficient Market Hypothesis, Value Investing, Growth Investing, and the Fama-French Three-Factor Model, this paper empirically tests the impact of valuation multiples within a sector-based portfolio framework. Accordingly, the study adds to the asset pricing literature by offering a structured null-result framework, demonstrating that valuation multiples, when applied in isolation, may not provide sufficiently reliable standalone signals for portfolio performance. The COVID-19 period is interpreted as an economically meaningful contextual regime characterized by elevated volatility, liquidity intervention, and sectoral divergence, rather than as a formally estimated event-study framework. Full article

Lichen planus (LP) is a chronic T-cell-mediated interface dermatitis. Genital involvement is frequently refractory to topical corticosteroids and calcineurin inhibitors and may lead to fibrosis, architectural distortion, and substantial impairment in quality of life. We report the case of a 39-year-old male with a 15-year history of biopsy-confirmed genital LP unresponsive to high-potency topical corticosteroids and tacrolimus 0.1%, who received topical Rosa damascena stem cell-derived exosomes (RSCEs) at biweekly sessions for four months. Each session combined 2 mL of in-office application with superficial microneedling in hyperkeratotic areas, followed by 3 mL of the same-day home application. No concomitant topical corticosteroid or calcineurin inhibitor was used during the treatment period. Paired pre- and post-treatment 4 mm punch biopsies were obtained from the same anatomical region, processed using identical protocols, stained with hematoxylin and eosin, and reviewed by a board-certified dermatopathologist. After four months, we observed clinical resolution of pruritus and fissuring, progressive desquamation of hyperkeratotic plaques, and improved tissue elasticity. The post-treatment biopsy showed reduced hyperkeratosis and hypergranulosis, attenuation of the band-like lymphohistiocytic infiltrate, partial restoration of the dermoepidermal interface, and reduced basal vacuolar degeneration relative to baseline. No dysplastic changes or treatment-related adverse events were observed. These observations are based on a single uncontrolled case and cannot establish causality, isolate the contribution of microneedling, or demonstrate disease modification beyond the descriptive level. Histological assessment was qualitative; no semi-quantitative or immunohistochemical analysis was performed. The exosome preparation was used as a standardized commercial product and was not independently characterized in our laboratory. The findings are intended solely as hypothesis-generating. Independent characterization of the exosome preparation, immunohistochemical and ideally transcriptomic profiling of paired tissue, and prospective controlled studies are required before any therapeutic claim can be supported. Full article

Corneal fibrosis and scarring remain leading causes of vision impairment and blindness globally, particularly following trauma, infection, or surgical intervention. Macrophages, as central mediators of immune and repair responses, orchestrate key phases of corneal wound healing. Their functional states, ranging from pro-inflammatory to pro-resolving, are tightly regulated by environmental cues and timing. Following corneal injury, recruited macrophages undergo temporally distinct activation programs. Early inflammatory macrophage responses support debris clearance, pathogen defense, and initiation of stromal repair, whereas persistence of inflammatory and profibrotic macrophage signaling beyond the acute healing phase is associated with sustained TGF-β activity, fibroblast-to-myofibroblast differentiation, excessive extracellular matrix deposition, and stromal haze formation. Conversely, timely transition toward pro-resolving macrophage states promotes inflammation resolution, myofibroblast clearance, and restoration of corneal transparency. Recent single-cell transcriptomic profiling reveals substantial heterogeneity among macrophage populations in the cornea, highlighting the limitations of the oversimplified M1/M2 classification. This review aims to define how macrophage heterogeneity and temporal dynamics regulate corneal wound healing outcomes, with particular emphasis on the balance between fibrosis and regeneration, and to provide a conceptual framework relevant to both basic researchers and translational clinicians. Full article