Search Results (258)

Objectives: To investigate how the FLASH effect modulates radiation response on multiple developmental endpoints of zebrafish embryos under normoxic and hypoxic conditions, after irradiation with proton beams at a conventional and an ultra-high dose rate (UHDR). Methods: Embryos were obtained from adult zebrafish and irradiated with a 228 MeV proton beam 24 h post-fertilization (hpf) at a dose rate of 0.6 and 317 Gy/s. For the hypoxic group, samples were kept inside a hypoxic chamber prior to irradiation, while standard incubation was adopted for the normoxic group. After irradiation, images of single embryos were acquired, and radiation effects on larval length, yolk absorption, pericardial edema, head size, eye size, and spinal curvature were assessed at specific time points. Results: Data indicate a general trend of significantly reduced toxicity after exposure to a UHDR compared to conventional regimes, which is maintained under both normoxic and hypoxic conditions. Differences are significant for the levels of pericardial edema induced by a UHDR versus conventional irradiation in normoxic conditions, and for eye and head size in hypoxic conditions. The toxicity scoring analysis shows a tendency toward a protective effect of the UHDR, which appears to be associated with a lower percentage of embryos in the high score categories. Conclusions: A radioprotective effect at a UHDR is observed both for normoxic (pericardial edema) and hypoxic (head and eye size) conditions. These results suggest that while the UHDR may preserve a potential to reduce radiation-induced damage, its protective effects are endpoint-dependent; the role of oxygenation might also be dependent on the tissue involved. Full article

Background: Inflammation abrogates cellular organization and tissue homoeostasis, resulting in redness, swelling, heat, pain, and loss of function. A model of carrageenan-induced paw edema (CIE) is commonly utilized to test anti-inflammatory substances. Based on the ability of Lepisanthes alata (LA), a tropical plant that is rich in phytochemicals like polyphenols, this study assessed the optimal dose and the health benefits of LA in rats that had been induced with carrageenan to develop paw swelling. Methods: Twenty-four male Wistar rats were divided into four groups to which carrageenan was administered, after which, distilled water at oral dose (C + DW), sodium diclofenac 25 mg/kg (C + DS), LA extract in 250 mg/kg (C + LA250), and 500 mg/kg (C + LA500) was given, respectively. Paw edema was assessed in 24 h. Pain was assessed using the Rat Grimace Scale (RGS), cytokines, antioxidant activity, and tissue changes. Results: LA at 250 and 500 mg/kg significantly decreased paw edema and inflammatory markers in the results of both studies. Remarkably, LA 250 mg/kg significantly decreased RGS scores as well as IL-1β, TNF-α, and histological inflammation but had a positive effect on T-SOD levels. Conclusions: LA extract, especially at 250 mg/kg, shows potent anti-inflammatory, analgesic, and antioxidant properties in CIE rats. Full article

Background: Retinal diseases are becoming an important public health issue, with early diagnosis and timely intervention playing a key role in preventing vision loss. Optical coherence tomography (OCT) remains the leading non-invasive imaging technique for identifying retinal conditions. However, distinguishing between diabetic macular edema (DME) and macular edema resulting from retinal vein occlusion (RVO) can be particularly challenging, especially for clinicians without specialized training in retinal disorders, as both conditions manifest through increased retinal thickness. Due to the limited research exploring the application of deep learning methods, particularly for RVO detection using OCT scans, this study proposes a novel diagnostic approach based on stacked convolutional neural networks. This architecture aims to enhance classification accuracy by integrating multiple neural network layers, enabling more robust feature extraction and improved differentiation between retinal pathologies. Methods: The VGG-16, VGG-19, and ResNet50 models were fine-tuned using the Kermany dataset to classify the OCT images and afterwards were trained using a private OCT dataset. Four stacked models were then developed using these models: a model using the VGG-16 and VGG-19 networks, a model using the VGG-16 and ResNet50 networks, a model using the VGG-19 and ResNet50 models, and finally a model using all three networks. The performance metrics of the model includes accuracy, precision, recall, $F_2$-score, and area under of the receiver operating characteristic curve (AUROC). Results: The stacked neural network using all three models achieved the best results, having an accuracy of 90.7%, precision of 99.2%, a recall of 90.7%, and an $F_2$-score of 92.3%. Conclusions: This study presents a novel method for distinguishing retinal disease by using stacked neural networks. This research aims to provide a reliable tool for ophthalmologists to improve diagnosis accuracy and speed. Full article

Accurate segmentation of key tumor subregions in adult gliomas from Magnetic Resonance Imaging (MRI) is of critical importance for brain tumor diagnosis, treatment planning, and prognosis. However, this task remains poorly investigated and highly challenging due to the considerable variability in shape and appearance of these areas across patients. This study proposes a novel Deep Learning architecture leveraging modality-specific encoding and attention-based refinement for the segmentation of glioma subregions, including peritumoral edema (ED), necrotic core (NCR), and enhancing tissue (ET). The model is trained and validated on the Brain Tumor Segmentation (BraTS) 2023 challenge dataset and benchmarked against a state-of-the-art transformer-based approach. Our architecture achieves promising results, with Dice scores of 0.78, 0.86, and 0.88 for NCR, ED, and ET, respectively, outperforming SegFormer3D while maintaining comparable model complexity. To ensure a comprehensive evaluation, performance was also assessed on standard composite tumor regions, i.e., tumor core (TC) and whole tumor (WT). The statistically significant improvements obtained on all regions highlight the effectiveness of integrating complementary modality-specific information and applying channel-wise feature recalibration in the proposed model. Full article

Ocular diseases can significantly affect vision and overall quality of life, with diagnosis often being time-consuming and dependent on expert interpretation. While previous computer-aided diagnostic systems have focused primarily on medical imaging, this paper proposes VisionTrack, a multi-modal AI system for predicting multiple retinal diseases, including Diabetic Retinopathy (DR), Age-related Macular Degeneration (AMD), Diabetic Macular Edema (DME), drusen, Central Serous Retinopathy (CSR), and Macular Hole (MH), as well as normal cases. The proposed framework integrates a Convolutional Neural Network (CNN) for image-based feature extraction, a Graph Neural Network (GNN) to model complex relationships among clinical risk factors, and a Large Language Model (LLM) to process patient medical reports. By leveraging diverse data sources, VisionTrack improves prediction accuracy and offers a more comprehensive assessment of retinal health. Experimental results demonstrate the effectiveness of this hybrid system, highlighting its potential for early detection, risk assessment, and personalized ophthalmic care. Experiments were conducted using two publicly available datasets, RetinalOCT and RFMID, which provide diverse retinal imaging modalities: OCT images and fundus images, respectively. The proposed multi-modal AI system demonstrated strong performance in multi-label disease prediction. On the RetinalOCT dataset, the model achieved an accuracy of 0.980, F1-score of 0.979, recall of 0.978, and precision of 0.979. Similarly, on the RFMID dataset, it reached an accuracy of 0.989, F1-score of 0.881, recall of 0.866, and precision of 0.897. These results confirm the robustness, reliability, and generalization capability of the proposed approach across different imaging modalities. Full article

Objectives: The early detection of low bone mineral density (BMD) is essential for preventing osteoporosis and related complications. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its cost and limited availability restrict its use in large-scale screening. This study investigated whether raw bioelectrical impedance analysis (BIA) data combined with explainable machine learning (ML) models could accurately classify osteopenia in women aged 40 to 55. Methods: In a cross-sectional design, 138 women underwent same-day BIA and DXA assessments. Participants were categorized as osteopenic (T-score between −1.0 and −2.5; n = 33) or normal (T-score ≥ −1.0) based on DXA results. Overall, 24.1% of the sample were classified as osteopenic, and 32.85% were postmenopausal. Raw BIA outputs were used as input features, including impedance values, phase angles, and segmental tissue parameters. A sequential forward feature selection (SFFS) algorithm was employed to optimize input dimensionality. Four ML classifiers were trained using stratified five-fold cross-validation, and SHapley Additive exPlanations (SHAP) were applied to interpret feature contributions. Results: The neural network (NN) model achieved the highest classification accuracy (92.12%) using 34 selected features, including raw impedance measurements, derived body composition indices such as regional lean mass estimates and the edema index, as well as a limited number of categorical variables, including self-reported physical activity status. SHAP analysis identified muscle mass indices and fluid distribution metrics, features previously associated with bone health, as the most influential predictors in the current model. Other classifiers performed comparably but with lower precision or interpretability. Conclusions: ML models based on raw BIA data can classify osteopenia with high accuracy and clinical transparency. This approach provides a cost-effective and interpretable alternative for the early identification of individuals at risk for low BMD in resource-limited or primary care settings. Full article

Background/Objectives: Albumin supplementation is widely used for hypoalbuminemia treatment in patients with critical illness, especially those with cirrhosis. However, studies have demonstrated that routine albumin administration is not always advantageous. We examined how albumin supplementation affects survival outcomes in patients with sepsis with hypoalbuminemia. Methods: This study was conducted by researchers in Taiwan using data from the TriNetX research platform, covering the period from 1 April 2014 to 30 April 2024. This platform aggregates real-world data from healthcare organizations worldwide. From this dataset, 1,147,433 patients who developed sepsis and hypoalbuminemia with albumin levels <3.5 g/dL were identified. The study population was stratified into two groups on the basis of whether they received albumin infusion or not. To compare outcomes, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated between propensity-score-matched patients who did and did not receive albumin supplementation. Subgroup analysis by albumin levels was conducted. Results: Albumin infusion was linked to increased risks of 30-day mortality (HR [95% CI] = 1.800 [1.774–1.827], p < 0.05), shock (HR [95% CI] = 1.436 [1.409–1.465], p < 0.05), septic shock (HR [95% CI] = 1.384 [1.355–1.415], p < 0.05), hypovolemic shock (HR [95% CI] = 1.496 [1.391–1.608], p < 0.05), cardiogenic shock (HR [95% CI] = 1.553 [1.473–1.637], p < 0.05), heart failure (HR [95% CI] = 1.098 [1.080–1.116], p < 0.05), and pulmonary edema (HR [95% CI] = 1.479 [1.438–1.520], p < 0.05). The subgroup analysis by albumin levels revealed a trend of increased mortality risk with albumin supplementation in patients with high baseline albumin levels. Conclusions: Patients with sepsis with hypoalbuminemia who received albumin supplementation exhibited high 30-day mortality rates and increased risks of shock, heart failure, and pulmonary edema compared with those who did not. These findings indicate that routine albumin administration may be linked with unfavorable outcomes in these patients. Full article

Stroke is still considered a predominant cause of morbidity and mortality, for which research on prevention and cure has been sought to prevent neuronal damage after a stroke incident. In this research, we evaluated the protective effects of virgin coconut oil (VCO) using behavioral, morphophysiological, and gene expression parameters using an ischemic stroke surgical rat model using Sprague Dawley (SD) rats. Eight-week-old SD rats were subjected to repeated oral administration (5 mL/kg/day) of either 1% Tween 80 or VCO. For behavioral and morphophysiological parameters, surgery was performed for each group, after which neurological scoring was performed at 4 h, 24 h, 48 h, 5 d, and 10 d. Further, hematological and brain morphology assessment was performed after euthanasia and necropsy of the animals. For gene expression studies, surgery was performed with animals sacrificed at different time points (baseline, before surgery, 4 h, 24 h, and 48 h after surgery) to collect the brain. Results of the study showed that there are differences in the neurological scores between the two treatments 24 h, 48 h, and 5 d after surgery. Brain morphology assessment also showed favorable results for VCO for infarct size, edema, and hypoxic neurons. Gene expression studies also showed positive results with an increase in the relative expression of angiogenin (Ang), angiopoietin (Angpt 1), Parkin, dynamin-related protein 1 (Drp 1), mitofusin 2 (Mfn 2), and mitochondrial rho (Miro) and decreased relative expression of caspase 3, receptor for advanced glycation end-product (Rage), and glyceraldehyde-3-phosphate dehydrogenase (Gapdh). In summary, the current study shows that VCO may have protective effects on the brain after stroke, which may be explained by the results of the gene expression studies. Full article

Background: Hyaluronic acid (HA) has emerged as a favored adjunct to restore volume after blepharoplasty and is very effective in the treatment of postoperative hollowness, sagging, and asymmetry. Its efficacy, rate of complications, and optimal injection technique are different in different clinical studies. Hyaluronidase has been studied by diverse methods in the treatment of HA complications, including chronic edema and surgical distortion. This study critically evaluated the efficacy, safety, and technical aspects of HA in the context of blepharoplasty outcomes. Methods: A systematic review was performed to evaluate the use of HA and hyaluronidase for post-blepharoplasty volume rejuvenation and the treatment of complications. Studies describing HA injection technique, time interval between blepharoplasty and injection, volumetric maintenance, complication rates, esthetic and functional results, and patient satisfaction scores were considered. Risk of bias was estimated with the ROBINS-I tool. Results: Sample sizes across the five included studies ranged from 5 to 109 patients, and follow-up intervals ranged from 1 month to 7 years. The age of patients ranged from 31 to 76 years, and females accounted for 86% of the participants in some studies. Injection of HA successfully restored meaningful volume, with retention persisting for over 12 months in the majority of cases. HA preoperative injection caused significant patient satisfaction in a short duration and was not associated with severe complications; delayed injection caused slight distortions in some revision operations. Lipofilling showed a reduced rate of complications (12%) compared with isolated blepharoplasty (20%), suggesting its utility as an adjuvant procedure of volume restoration. Hyaluronidase successfully treated recalcitrant edema, with improvements ranging from 50% to 100%, while the application of adjuvant RF microneedling caused complete remission (100%) in subjects with multiple treatments. The application of ultrasound imaging made measurements more precise, although methods of clinical assessment were significantly heterogeneous among the studies. Conclusions: HA displayed efficacy in terms of efficient volume restoration after blepharoplasty, especially when technique, time, and filler selection are meticulously optimized. In comparison to lipofilling, HA is seen as somewhat safer because of its reversibility and lower likelihood of adverse vascular events. Nonetheless, considerable variability in filler type, amount, timing of administration, and result evaluation constrains conclusive clinical recommendations. The use of hyaluronidase is an effective remedial approach for overcorrection or ongoing edema. Full article

Background/Objectives: We sought to determine if glibenclamide, a sulfonylurea receptor 1-transient receptor potential melastatin 4 (SUR1-TRPM4) channel blocker, reduces cerebral edema and improves neurological functioning in aneurysmal subarachnoid hemorrhage (aSAH). Methods: Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, a systematic search was conducted in PubMed, Cochrane Library, Web of Science, and SCOPUS for studies evaluating glibenclamide in aSAH patients. Primary outcomes included scores on the modified Rankin Scale (mRS) at discharge and the Subarachnoid Hemorrhage Early Brain Edema Score (SEBES) at ten days post-intervention. Secondary outcomes included adverse events, and safety and efficacy endpoints. Random-effects models were employed for meta-analyses. Results: Three studies utilizing oral glibenclamide (n = 245) met inclusion criteria. Oral glibenclamide demonstrated no significant improvements in mRS scores [MD −0.19 with 95% CI (−2.05, 1.66)] at discharge, [MD 0.06, (−0.60, 0.71)] at 3 months, and [MD 0.4, (−0.67, 0.87)] at 6 months; functional independence [risk ratio (RR) 1.05, (0.81, 1.36)]; independent ambulation [RR 1.07, (0.77, 1.48)]; mortality [RR 0.79, (0.42, 1.50)]; or delayed cerebral ischemia [RR 0.58, (0.31, 1.09]). Hypoglycemia risk was significantly higher in the glibenclamide group [RR 3.92, (1.14, 13.49)]. Conclusions: Oral glibenclamide offers a novel approach to addressing cerebral edema in aSAH but shows limited clinical efficacy in improving functional and neurological outcomes in subtherapeutic doses. Its safety profile is acceptable, though hypoglycemia risk necessitates careful monitoring. Further research is required to optimize dosing, timing of intervention, and patient selection to enhance therapeutic outcomes. By contrast, intravenous administration of therapeutic doses of glibenclamide offers a promising avenue for future studies in the management of aSAH by taking advantage of the favorable pharmacokinetics of this route of administration. Full article

Dual-energy computed tomography (DECT) is a promising advancement for detecting bone edema-like lesions (BME). However, its application in horses remains limited. The aim of this study was to evaluate DECT virtual-non-calcium (VNCa) imaging in the equine foot and establish which confounding factors could influence its applicability in clinical practice. The DECT VNCa map of 14 standing and 5 cadaveric (recumbent) cases with foot-related lameness was scored in consensus by two readers in comparison to MRI. Overall, 17/19 cases demonstrated BME on MRI, whereas 2 did not. Agreement between DECT VNCa and MRI was found in 15/19 feet (78.9%). Disagreement in 4/19 cases with BME was due to sclerosis (1/19), mild BME extent on MRI (2/19), or scan artifacts (1/19). The extent of BME was significantly underestimated using DECT VNCa compared to MRI (p = 0.016). No significant correlation was found between sclerosis score and the BME extent underestimation on DECT (p = 0.056). Between standing and post-mortem cases, there was no significant difference in the agreement between DECT and MRI (p = 0.53) or DECT VNCa image quality (p = 0.22). In conclusion, DECT VNCa effectively identified moderate and severe BME, and its use was feasible in standing positioning. In case of sclerosis, a case-by-case assessment is recommended. Full article

Introduction: Airway management remains a high-risk intervention in a subset of patients, with traditional predictors like the Mallampati score demonstrating poor sensitivity and specificity. Point-of-care ultrasound (POCUS) has emerged as a transformative tool, offering real-time, objective assessment of airway anatomy to improve safety and outcomes. Methods: A narrative approach was conducted to evaluate the literature on airway ultrasound, incorporating clinical metrics and procedural applications. Results: Ultrasound has demonstrated utility in pre-intubation risk stratification using quantitative measures such as skin-to-epiglottis distance (>2.75 cm) and hyomental distance ratio (<1.2), which outperform traditional exams, especially in obese patients. Procedural uses include endotracheal tube confirmation with 98.9% sensitivity and enhanced success rates in emergent cricothyroidotomy—from 50% to nearly 100%—in patients with difficult anatomy. Dynamic applications like assessing laryngeal edema via parapharyngeal thickness offer advantages over traditional cuff leak tests. Technical considerations such as optimal probe selection, patient positioning, and interpretation of key anatomical landmarks are also discussed. Conclusions: Airway ultrasound is poised to become a standard tool in perioperative and critical care settings. The review concludes by emphasizing POCUS as an indispensable adjunct for modern airway management. Full article

Background: Acute heart failure (AHF) is a major cause of hospitalizations, posing significant challenges to healthcare systems. Despite advancements in management, the rate of poor outcomes remains high globally, emphasizing the need for timely interventions. This study aimed to identify early admission-based factors predictive of poor outcomes in hospitalized AHF patients, in order to contribute to early risk stratification and optimize patient care. Methods: This retrospective single-center study analyzed routine data of adult patients hospitalized for AHF at a public university teaching hospital in Switzerland. Outcomes included in-hospital death, intensive care (ICU) treatment, and length of hospital stay (LOHS). Potential predictors were limited to routine parameters, readily available at admission. Missing predictor data was imputed and predictors were identified by means of multivariable regression analysis. Results: Data of 638 patients (median age 84 years, range 45–101 years, 50% female) were included in the study. In-hospital mortality was 7.1%, ICU admission rate 3.8%, and median LOHS was 8 days (IQR 5–12). Systolic blood pressure ≤ 100 mmHg (Odds ratio (OR) 3.8, p = 0.009), peripheral oxygen saturation ≤ 90% or oxygen supplementation (OR 5.9, p < 0.001), and peripheral edema (OR 2.7, p = 0.044) at hospital admission were identified as predictors of in-hospital death. Furthermore, a stroke or transient ischemic attack in the patient’s history (OR 3.2, p = 0.023) was associated with in-hospital death. ICU admission was associated with oxygen saturation ≤ 90% or oxygen supplementation (OR 22.9, p < 0.001). Factors linked to longer LOHS included oxygen saturation ≤ 90% or oxygen supplementation (IRR 1.2, p < 0.001), recent weight gain (IRR 1.1, p = 0.028), and concomitant chronic kidney disease (IRR 1.2, p < 0.001). Conclusions: This study validated established predictors of AHF outcomes in a Swiss cohort, highlighting the predictive value of poor perfusion status, fluid overload, and comorbidities such as chronic kidney disease. The identified predictors imply potential for developing tools to improve rapid treatment decisions. Future research should focus on the prospective external validation of the identified predictors and the design and validation of risk scores, incorporating these parameters to optimize early interventions and reduce adverse outcomes in AHF. Full article

Background: Sepsis-induced acute lung injury (ALI) is a serious disease constituting a heavy burden on society due to high mortality and morbidity. Inflammation and oxidative stress constitute key pathological mechanisms in ALI caused by sepsis. LL-37 can improve the survival of septic mice. Nevertheless, its function and underlying mechanism in sepsis-evoked ALI is elusive. Methods: The human A549 alveolar epithelial cell line was treated with LL-37 or ZBP1 recombinant vector under LPS exposure. Then, the effects on cell oxidative stress injury, inflammatory response, and autophagy were analyzed. RNA-seq analysis was performed to detect the differentially expressed genes (DEGs) between the LPS and LPS/LL-37 groups. Furthermore, the effects of LL-37 on cecal ligation and the puncture (CLP)-constructed ALI model were explored. Results: LL-37 attenuated LPS-evoked oxidative injury in human alveolar epithelial cells by increasing cell viability and suppressing ROS, malondialdehyde, and lactate dehydrogenase levels and apoptosis. Moreover, LPS-induced releases of pro-inflammatory IL-18, TNF-α, and IL-1β were suppressed by LL-37. Furthermore, LPS’s impairment of autophagy was reversed by LL-37. RNA-seq analysis substantiated 1350 differentially expressed genes between the LPS and LPS/LL-37 groups. Among them was ZBP1, a significantly down-regulated gene with the largest fold change. Moreover, LL-37 suppressed LPS-increased ZBP1 expression. Importantly, ZBP1 elevation restrained LL-37-induced autophagy in LPS-treated cells and abrogated LL-37-mediated protection against LPS-evoked oxidative injury and inflammation. LL-37 ameliorated abnormal histopathological changes, tissue edema, the lung injury score, oxygenation index (PaO2/FiO2), and glycemia contents in the CLP-constructed ALI model, which were offset through ZBP1 elevation via its activator CBL0137. Additionally, LL-37 suppressed inflammation and oxidative stress in lung tissues, concomitant with autophagy elevation and ZBP1 down-regulation. Conclusions: LL-37 may alleviate the progression of sepsis-evoked ALI by attenuating pulmonary epithelial cell oxidative injury and inflammatory response via ZBP1-mediated autophagy activation, indicating a promising approach for the therapy of ALI patients. Full article

Background: Total knee arthroplasty (TKA) is one of the most frequently performed procedures for end-stage arthritis. Effective pain control is essential for recovery, and opioids are widely used. However, patients with opioid use disorder (OUD) may be at increased risk of complications. Methods: We analyzed 2,514,099 TKA cases from the Nationwide Inpatient Sample (2016–2019), identifying 11,785 patients with OUD. After 1:1 propensity score matching, clinical and economic outcomes were compared between OUD and non-OUD patients. Results: Patients with OUD had significantly higher odds of intraoperative fracture (OR: 6.1), DVT (OR: 5.0), pneumonia (OR: 2.5), pulmonary edema (OR: 1.6), and blood transfusion (OR: 1.5) (p < 0.001). Mean hospital charges were higher (USD 68,687 vs. USD 60,984), and LOS was longer (2.8 vs. 2.5 days, p < 0.001). OUD patients were more likely to undergo revision TKA at a younger age (59.6 vs. 65.4 years, p = 0.016), with higher infection rates and greater costs. Conclusions: Patients with OUD undergoing TKA experience more complications, higher costs, and require earlier revision. Underreporting of OUD highlights the need for improved preoperative screening. Full article