Search Results (4,473)

Background: Electrocardiograms (EKGs) are essential tools in emergency medicine, often used to evaluate chest pain, dyspnea, and other symptoms suggestive of cardiac dysfunction. Yet, EKGs are not universally administered to all emergency department (ED) patients. Understanding and predicting which patients receive an EKG may offer insights into clinical decision making, resource allocation, and potential disparities in care. This study examines whether integrating structured clinical data with free-text patient narratives can improve prediction of EKG utilization in the ED. Methods: We conducted a retrospective observational study to predict electrocardiogram (EKG) utilization using data from 13,115 adult emergency department (ED) visits in the nationally representative 2021 National Hospital Ambulatory Medical Care Survey–Emergency Department (NHAMCS-ED), leveraging both structured features—demographics, vital signs, comorbidities, arrival mode, and triage acuity, with the most influential selected via Lasso regression—and unstructured patient narratives transformed into numerical embeddings using Clinical-BERT. Four supervised learning models—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF) and Extreme Gradient Boosting (XGB)—were trained on three inputs (structured data only, text embeddings only, and a late-fusion combined model); hyperparameters were optimized by grid search with 5-fold cross-validation; performance was evaluated via AUROC, accuracy, sensitivity, specificity and precision; and interpretability was assessed using SHAP values and Permutation Feature Importance. Results: EKGs were administered in 30.6% of adult ED visits. Patients who received EKGs were more likely to be older, White, Medicare-insured, and to present with abnormal vital signs or higher triage severity. Across all models, the combined data approach yielded superior predictive performance. The SVM and LR achieved the highest area under the ROC curve (AUC = 0.860 and 0.861) when using both structured and unstructured data, compared to 0.772 with structured data alone and 0.823 and 0.822 with unstructured data alone. Similar improvements were observed in accuracy, sensitivity, and specificity. Conclusions: Integrating structured clinical data with patient narratives significantly enhances the ability to predict EKG utilization in the emergency department. These findings support a personalized medicine framework by demonstrating how multimodal data integration can enable individualized, real-time decision support in the ED. Full article

The MIM1-BH3 mimetic, which inhibits the Mcl-1 antiapoptotic protein, may be an efficacious molecule able to induce apoptosis. Previously, we found that moxifloxacin (MXFL) is able to modulate Mcl-1 protein expression. Therefore, in the current study, we assessed the impact of the MXFL, MIM1, and MXFL/MIM1 mixtures on viability and apoptosis in amelanotic A375 and melanotic G361 melanoma cells. The obtained results showed that MXFL and MIM1 exerted high cytotoxic and proapoptotic potential. In the case of two-component models, we have demonstrated that the use of the MIM1 and MXFL mixtures resulted in a significant intensification of both cytotoxic and proapoptotic activity, shown as a modulatory effect on the early and late phases of apoptosis toward the analyzed melanoma cells when compared with MIM1 or MXFL alone. We report, for the first time, the high proapoptotic activity of MIM1 and MXFL applied in a two-component model toward melanoma cells, pointing to the Mcl-1 protein as an important molecular target. The observed potential synergistic mode of action—expressed as cytotoxic and proapoptotic activity enhancement, detected for MIM1 and MXFL—may represent a new direction for further in vitro and in vivo experiments concerning the role of the Mcl-1 protein in the treatment of melanoma. Moreover, the presented results certainly contribute to expanding the knowledge of the pharmacology of both fluoroquinolones and BH3 mimetics, and also enable a better understanding of melanoma cell biology. Full article

Background: Accurate estimation of the postmortem interval (PMI) is critical in forensic death investigations. Traditional signs of death—algor mortis, livor mortis, and rigor mortis—are generally reliable only within the first two to three days after death, with their accuracy decreasing as decomposition progresses. This paper presents a systematic review conducted in accordance with PRISMA guidelines, aiming to evaluate and compare current methods for estimating the PMI. Specifically, the study identifies both traditional and modern techniques, analyzes their advantages, limitations, and applicable timeframes, critically synthesizes the literature, and highlights the importance of combining multiple approaches to improve accuracy. Methods: A systematic search was conducted in the PubMed, Scopus, and Web of Science databases, following the PRISMA guidelines. The review included original articles and reviews that evaluated PMI estimation methods (through thanatological signs, entomology, microbial succession, molecular, imaging, and omics approaches). Extracted data included study design, methodology, PMI range, and accuracy information. Out of the 1245 identified records, 50 studies met the inclusion criteria for qualitative synthesis. Results: Emerging methods, such as molecular markers, microbial succession, omics technologies, and advanced imaging show improved accuracy across extended postmortem intervals. RNA degradation methods demonstrated higher accuracy within the first 72 h, while entomology and microbial analysis are more applicable during intermediate and late decomposition stages. Although no single method is universally reliable, combining traditional and modern approaches tailored to case-specific factors improves overall PMI estimation accuracy. Conclusions: This study supports the use of an integrative, multidisciplinary, and evidence-based approach to improve time-since-death estimation. Such a strategy enhances forensic outcomes by enabling more precise PMI estimates in complex or delayed cases, increasing legal reliability, and supporting court-admissible expert testimony based on validated, multi-method protocols. Full article

Bone-related defects present a key challenge in orthopaedics. The current gold standard, autografts, poses significant limitations, such as donor site morbidity, limited supply, and poor morphological adaptability. This study investigates the potential of scaffold geometry to induce osteogenic differentiation of human adipose-derived stem cells (hADSCs) through mechanotransduction, without the use of chemical inducers. Four distinct poly-(L)-lactic acid (PLA) scaffold architectures—Traditional Cross (Tc), Triangle (T), Diamond (D), and Gyroid (G)—were fabricated using fused filament fabrication (FFF) 3D printing. hADSCs were cultured on these scaffolds, and their response was evaluated utilising an alkaline phosphatase (ALP) assay, immunofluorescence, and extensive proteomic analyses. The results showed the D scaffold to have the highest ALP activity, followed by Tc. Proteomics results showed that more than 1200 proteins were identified in each scaffold with unique proteins expressed in each scaffold, respectively Tc—204, T—194, D—244, and G—216. Bioinformatics analysis revealed structures with complex curvature to have an increased expression of proteins involved in mid- to late-stage osteogenesis signalling and differentiation pathways, while the Tc scaffold induced an increased expression of signalling and differentiation pathways pertaining to angiogenesis and early osteogenesis. Full article

Congenital cataracts (CCs) are a leading cause of preventable childhood blindness, with genetic factors playing a crucial role in their etiology. Nance–Horan syndrome (NHS) is a rare X-linked dominant disorder associated with CCs but is often underdiagnosed due to variable expressivity, particularly in female carriers. Objective: This study aimed to explore the genetic landscape of CCs in a Swiss cohort, focusing on two novel NHS and one novel GJA8 variants and their phenotypic presentation. Methods: Whole-exome sequencing (WES) was conducted on 20 unrelated Swiss families diagnosed with CCs. Variants were analyzed for pathogenicity using genetic databases, and segregation analysis was performed. Clinical data, including cataract phenotype and associated systemic anomalies, were assessed to establish genotype–phenotype correlations. Results: Potentially pathogenic DNA sequence variants were identified in 10 families, including three novel variants, one in GJA8 (c.584T>C) and two NHS variants (c.250_252insA and c.484del). Additional previously reported variants were detected in CRYBA1, CRYGC, CRYAA, MIP, EPHA2, and MAF, reflecting genetic heterogeneity in the cohort. Notably, NHS variants displayed significant phenotypic variability, suggesting dose-dependent effects and X-chromosome inactivation in female carriers. Conclusions: NHS remains underdiagnosed due to its variable expressivity and the late manifestation of systemic features, often leading to misclassification as isolated CC. This study highlights the importance of genetic testing in unexplained CC cases to improve early detection of syndromic forms. The identification of novel NHS and GJA8 variants provides new insights into the genetic complexity of CCs, emphasizing the need for further research on genotype–phenotype correlations. Full article

This study presents an advanced framework for fabric texture classification by leveraging macro- and micro-texture extraction techniques integrated with deep learning architectures. Co-occurrence histograms, local binary patterns (LBPs), and albedo-dependent feature maps were employed to comprehensively capture the surface properties of fabrics. A late fusion approach was applied using four state-of-the-art convolutional neural networks (CNNs): InceptionV3, ResNet50_V2, DenseNet, and VGG-19. Excellent results were obtained, with the ResNet50_V2 achieving a precision of 0.929, recall of 0.914, and F1 score of 0.913. Notably, the integration of multimodal inputs allowed the models to effectively distinguish challenging fabric types, such as cotton–polyester and satin–silk pairs, which exhibit overlapping texture characteristics. This research not only enhances the accuracy of textile classification but also provides a robust methodology for material analysis, with significant implications for industrial applications in fashion, quality control, and robotics. Full article

Background/Objectives: Cancer suffers from unresolved therapeutic challenges owing to the lack of targeted therapies and heightened recurrence risk. This study aimed to investigate the new series of hydroxamate by structurally modifying the pharmacophore of vorinostat. Methods: The present work involves the synthesis of 15 differently substituted 2H-1,2,3-triazole-based hydroxamide analogs by employing triazole ring as a cap with varied linker fragments. The compounds were evaluated for their anticancer effect, especially their anti-breast cancer response. Molecular docking and molecular dynamics simulations were conducted to examine binding interactions. Results: Results indicated that among all synthesized hybrids, the molecule VI(i) inhibits the growth of MCF-7 and A-549 cells (GI₅₀ < 10 μg/mL) in an antiproliferative assay. Compound VI(i) was also tested for cytotoxic activity by employing an MTT assay against A549, MCF-7, and MDA-MB-231 cell lines, and the findings indicate its potent anticancer response, especially against MCF-7 cells with IC₅₀ of 60 µg/mL. However, it experiences minimal toxicity towards the normal cell line (HEK-293). Mechanistic studies revealed a dual-pathway activation: first, apoptosis (17.18% of early and 10.22% of late apoptotic cells by annexin V/PI analysis); second, cell cycle arrest at the S and G2/M phases. It also promotes ROS generation in a concentration-dependent manner. The HDAC–inhibitory assay, extended in silico molecular docking, and MD simulation experiments further validated its significant binding affinity towards HDAC 1 and 6 isoforms. DFT and ADMET screening further support the biological proclivity of the title compounds. The notable biological contribution of VI(i) highlights it as a potential candidate, especially against breast cancer cells. Full article

Since its discovery in the late 19th century, spinal muscular atrophy (SMA) has had a significant medical and societal impact, primarily affecting newborns, toddlers, and young adults. While new pharmaceutical strategies are effective in treating SMA in a particular subset of patients, continued research is necessary to improve the well-being of patients. Treatments are needed for those who do not respond to newly approved drugs and older patients with significantly compromised neuron systems. After summarizing SMA genotypes, phenotypes, and approved pharmacological treatments, this review presents ongoing trials for approved and new molecules, new formulations, and administration methods. Based on the work of our lab, we also discuss nutritional interventions that aim to counteract the oxidative stress present in SMA cells. Finally, we assess rehabilitative interventions, focusing on psychological approaches. Full article

Some Cretaceous ants belonging to the stem group of Formicidae exhibit bizarre morphology. This wide range of unusual adaptive features is primarily related to the mouthparts and clypeus. The researchers were perplexed by their specific ecology, as modern ant lineages do not exhibit anything similar. Here, we report and describe a new genus based on an extraordinary and mysterious alate ant from Late Eocene Baltic amber. Undoubtedly, the new ant is classified within the subfamily Formicinae (one of the crown groups), yet it displays a highly specialised morphology and an unusual array of features that are not observed in any extant ant lineages. Neither recent nor extinct ants have such a combination of features. While the exact phylogenetic placement of the new ant remains uncertain, we offer a discussion of its potential affinities based on our constrained phylogenetic analyses. We propose that †Eridanomyrma gen. n. should be considered in the new tribe †Eridanomyrmini trib. n. This new taxon highlights the adaptive diversity of a highly specialised, extinct lineage of Eocene crown-group ants. We also present a 3D model based on X-ray computed microtomography (µCT). Full article

The southern Great Xing’an Range is located in the overlap zone of the Paleo-Asian Ocean metallogenic domain and the Circum-Pacific metallogenic domain. It hosts numerous Sn-polymetallic deposits, such as Weilasituo, Bianjiadayuan, Huanggang, and Dajing, and witnessed multiple episodes of magmatism during the Late Mesozoic. The study area is situated within the Huanggangliang-Ganzhuermiao metallogenic belt in the southern Great Xing’an Range. The region has witnessed extensive magmatism, with Mesozoic magmatic activities being particularly closely linked to regional mineralization. We present petrographic, zircon U-Pb chronological, lithogeochemical, and Lu-Hf isotopic analyses of the Yexilinhundi granites. The results indicate that the granite porphyry and granodiorite were emplaced during the Late Jurassic. Both rocks exhibit high SiO₂, K₂O + Na₂O, differentiation index (DI), and 10,000 Ga/Al ratios, coupled with low MgO contents. They show distinct fractionation between light and heavy rare earth elements (LREEs and HREEs), exhibit Eu anomalies, and have low whole-rock zircon saturation temperatures (T_zr), collectively demonstrating characteristics of highly fractionated I-type granites. The εHf(t) values of the granites range from 0.600 to 9.14, with young two-stage model ages (T_DM2 = 616.0~1158 Ma), indicating that the magmatic source originated from partial melting of Mesoproterozoic-Neoproterozoic juvenile crust. This study proposes that the granites formed in a post-collisional/post-orogenic extensional setting associated with the subduction of the Mongol-Okhotsk Ocean, providing a scientific basis for understanding the relationship between the formation of Sn-polymetallic deposits and granitic magmatic evolution in the study area. Full article

Variants in ELAC2, a gene encoding the mitochondrial RNase Z enzyme essential for mitochondrial tRNA processing, have been associated with severe pediatric-onset mitochondrial dysfunction, primarily presenting with developmental delay, hypertrophic cardiomyopathy (HCM), and lactic-acidosis. We hereby report the case of a 25-year-old young woman presenting with dilated cardiomyopathy (DCM) and peripheral sensorimotor polyneuropathy, harboring a homozygous variant in ELAC2. The same variant has been reported only once so far in a case of severe infantile-onset form of HCM and mitochondrial respiratory chain dysfunction, with in vitro data showing a moderate reduction in the RNase Z activity and supporting the current classification as C4 according to the American College of Medical Genetics (ACMG) criteria (PS3, PM2, PM3, PP4). Our extensive clinical, imaging, histological, and genetic investigations support a causal link between the identified variant and the patient’s phenotype, despite the fact that the latter might be considered atypical according to the current state of knowledge. A detailed review of the existing literature on ELAC2-related disease is also provided, highlighting the molecular mechanisms underlying tRNA maturation, mitochondrial dysfunction, and the variable phenotypic expression. Our case further expands the clinical spectrum of ELAC2-related cardiomyopathies to include a relatively late onset in young adulthood and underscores the importance of comprehensive genetic testing in unexplained cardiomyopathies with multisystem involvement. Full article

In this study, 14 palynological samples and nine AMS ¹⁴C dating samples were collected from two representative black soil profiles in the Xingkai Lake Plain to examine climate changes and their impacts on environmental evolution since the Holocene. The systematic identification, analysis, and research of palynological data reveal that the black soil profiles in the Xingkai Lake Plain can be categorized into the following three distinct palynological assemblage zones: the lower zone (11.7–7.5 ka BP) is characterized by Pinus-Laevgatomonoleti-Amaranthaceae-Artemisia, having a cold, dry climate; the middle zone (7.5–2.5 ka BP) features Quercus-Juglans-Polygonum-Cyperaceae, with a warm and humid climate; and the upper zone (2.5 ka BP to present) consists of Pinus-Quercus-Betula, indicating a cold and dry climate. Furthermore, field lithostratigraphic observations of the two black soil profiles suggest that late Pleistocene loessial clay serves as the parent material in this region. Quaternary geology, section lithology, palynology, and AMS ¹⁴C dating results indicate that a significant portion of black soil in the Xingkai Lake Plain was primarily formed during the Great Warm Period following the middle Holocene. These insights not only enhance our understanding of Holocene climate dynamics in Northeast China but also provide a substantial scientific foundation for further studies on related topics. Full article

Background: Unlike most cancers, breast cancer poses a persistent risk of distant recurrence—often years after initial treatment—making long-term risk stratification uniquely challenging. Current tools fall short in predicting late metastatic events, particularly for early-stage patients. Methods: We present an interpretable machine learning (ML) pipeline to predict distant recurrence-free survival at 5, 10, and 15 years, integrating Bayesian network-based causal feature selection, deep feed-forward neural network models (DNMs), and SHAP-based interpretation. Using electronic health record (EHR)-based clinical data from over 6000 patients, we first applied the Markov blanket and interactive risk factor learner (MBIL) to identify minimally sufficient predictor subsets. These were then used to train optimized DNM classifiers, with hyperparameters tuned via grid search and benchmarked against models from 10 traditional ML methods and models trained using all predictors. Results: Our best models achieved area under the curve (AUC) scores of 0.79, 0.83, and 0.89 for 5-, 10-, and 15-year predictions, respectively—substantially outperforming baselines. MBIL reduced input dimensionality by over 80% without sacrificing accuracy. Importantly, MBIL-selected features (e.g., nodal status, hormone receptor expression, tumor size) overlapped strongly with top SHAP contributors, reinforcing interpretability. Calibration plots further demonstrated close agreement between predicted probabilities and observed recurrence rates. The percentage performance improvement due to grid search ranged from 25.3% to 60%. Conclusions: This study demonstrates that combining causal selection, deep learning, and grid search improves prediction accuracy, transparency, and calibration for long-horizon breast cancer recurrence risk. The proposed framework is well-positioned for clinical use, especially to guide long-term follow-up and therapy decisions in early-stage patients. Full article

In late 2019, a new virus, SARS-CoV-2, emerged in Wuhan, China, causing COVID-19 and the subsequent global pandemic. As of 30 April 2023, more than 774 million cases of COVID-19 had been reported worldwide, including over 7.5 million in Mexico. Despite advances in vaccination, epidemic surges of COVID-19 continued to occur globally, highlighting the importance of sharing and disseminating the experiences gained during these first years to better understand the virus’s evolution and respond accordingly. For this reason, the National Council for Science and Technology (CONACYT) organized the meeting “Challenges and Opportunities for Genomic Surveillance of SARS-CoV-2 in Mexico” from 15 to 17 August 2022, to present the efforts and results accumulated over more than two years of the pandemic. In this meeting report, we summarize the key findings of each participant and provide their contact information. Full article

Korea has a high population density, considering the size of its territory. Therefore, the importance of convenient and comfortable apartment buildings and high-rise residential–commercial complex buildings has been rising. In addition, because of the improvement in the standard of living along with continuous national economic growth, the interest in well-being and the expectation of a quiet life with a comfortable and pleasant residential environment have also been increasing. However, Koreans have a lifestyle involving sitting on the floor, so floor impact noise has been occurring more and more frequently. Because of this, neighborly disputes have been a serious social problem. And lately, damage and disputes from noise between floors have been increasing much more. The present work, therefore, used waste tire chips as a resilient material for reducing floor impact noise in order to recycle waste tires effectively. Also, a compounded resilient material, which combines EPS (expanded polystyrene), a flat resilient material on the upper part, with waste tire chips for the lower part, was developed. After constructing waste tire chips at a standardized test building, experiments with both light-weight and heavy-weight floor impact noise were performed. The tests confirmed that waste tire chips, when used as a resilient material, can effectively reduce both light-weight and heavy-weight floor impact noise. Full article