Search Results (99)

Emergency medical services confront significant challenges in delivering timely patient assessments within geographically isolated or disaster-impacted regions. While drones (unmanned aircraft systems, UAS) show transformative potential in healthcare, standardized protocols for drone-assisted patient evaluations remain underdeveloped. This study introduces the ABCD-IN-BARS protocol, a 9-step telemedicine checklist integrating patient-assisted maneuvers and drone technology to systematize remote emergency assessments. A wait-list randomized controlled trial with 68 first-aid-trained volunteers evaluated the protocol’s feasibility. Participants underwent web-based modules and in-person simulations and were randomized into immediate training or waitlist control groups. The ABCD-IN-BARS protocol was developed via a content validity approach, incorporating expert-rated items from the telemedicine literature. Outcomes included time-to-assessment, provider confidence (Modified Cooper–Harper Scale), measured at baseline, post-training, and 3-month follow-up. Ethical approval and informed consent were obtained. Most of the participants can complete the assessment with a cue card within 4 min. A mixed-design repeated measures ANOVA assessed the effects of Time (baseline, post-test, 3-month follow-up within subject) on assessment durations. Assessment times improved significantly over three time points (p = 0.008), improving with standardized protocols, while patterns were similar across groups (p = 0.101), reflecting skill retention at 3 months and not affected by injury or not. Protocol adherence in simulated injury identification increased from 63.3% pre-training to 100% post-training. Provider confidence remained high (MCH scores: 2.4–2.7/10), and Technology Acceptance Model (TAM) ratings emphasized strong Perceived Usefulness (PU2: M = 4.48) despite moderate ease-of-use challenges (EU2: M = 4.03). Qualitative feedback highlighted workflow benefits but noted challenges in drone maneuvering. The ABCD-IN-BARS protocol effectively standardizes drone-assisted emergency assessments, demonstrating retained proficiency and high usability. While sensory limitations persist, its modular design and alignment with ABCDE principles offer a scalable solution for prehospital care in underserved regions. Further multicenter validation is needed to generalize findings. Full article

Magnoliids represent one of the most basal lineages within angiosperms, and their ancestral floral morphology provides crucial insights into the evolution of flowers in angiosperms. MCM1-AGAMOUS-DEFICIENS-SRF (MADS)-box transcription factors play crucial roles in specifying floral organs. To understand their evolutionary history and functional divergence in magnoliids, we identified MADS-box genes, and conducted phylogenetic and expression analysis in 33 magnoliids and 8 other angiosperm plants. A total of 1310 MADS-box genes were identified and classified into Type I and Type II. The expansion of MADS-box genes in magnoliids mainly arose from whole-genome duplication events. In Liriodendron chinensis and Chimonanthus praecox, we identified floral homeotic MADS-box genes that are orthologous to the ABCDE model genes of floral organ identity determination. The broad expression pattern of A and B genes in floral organs and overlapping activity of ABCDE-model genes are consistent with the “shifting−fading borders” scheme proposed in basally diverging angiosperm lineages. Our results not only elucidate the driving forces underlying the diversification of MADS-box genes in magnoliids, but also shed light on the evolutionary models of floral development in angiosperms. Full article

Accurate skin lesion classification is crucial for the early detection of malignant lesions, including melanoma, as well as improved patient outcomes. While convolutional neural networks (CNNs) excel at capturing local morphological features, they struggle with global context modeling essential for comprehensive lesion assessment. Vision transformers address this limitation but suffer from quadratic computational complexity O(n²), hindering deployment in resource-constrained clinical environments. We propose DermaMamba, a novel dual-branch fusion architecture that integrates CNN-based local feature extraction with Vision Mamba (VMamba) for efficient global context modeling with linear complexity O(n). Our approach introduces a state space fusion mechanism with adaptive weighting that dynamically balances local and global features based on lesion characteristics. We incorporate medical domain knowledge through multi-directional scanning strategies and ABCDE (Asymmetry, Border irregularity, Color variation, Diameter, Evolution) rule feature integration. Extensive experiments on the ISIC dataset show that DermaMamba achieves 92.1% accuracy, 91.7% precision, 91.3% recall, and 91.5% mac-F1 score, which outperforms the best baseline by 2.0% accuracy with 2.3× inference speedup and 40% memory reduction. The improvements are statistically significant based on a significance test (p < 0.001, Cohen’s d > 0.8), with greater than 79% confidence also preserved on challenging boundary cases. These results establish DermaMamba as an effective solution bridging diagnostic accuracy and computational efficiency for clinical deployment. Full article

Background: Patients after a transient ischemic attack (TIA) are at high risk of subsequent stroke. There are various scores that aim to accurately identify patients at the highest risk of stroke. However, without comparisons between these scores, it is still unknown which is the score with the best predictive utility. Our study aims to identify the risk stratification score with the highest utility to identify patients at high risk for stroke within 90 days after a TIA. Methods: The MEDLINE and Scopus databases were systematically searched on 1 December 2023 for observational cohort studies assessing the ability of a score to predict a stroke within the first 90 days from the index TIA event. Only studies that had a direct comparison of at least two scores were included. A random-effects network meta-analysis was performed. Sensitivity and specificity, along with relevant 95% credible intervals, and between-score and between-study heterogeneity were estimated. We also estimated relative sensitivities and relative specificities compared with the ABCD2 score. We ranked each score according to its predictive accuracy based on both sensitivity and specificity estimates, using the diagnostic odds ratio (DOR) and the summary receiver operating characteristic (SROC) curve. Results: Our systematic review highlighted 9 studies including 14 discrete cohorts. The performance of all scores to identify patients at high risk for stroke recurrence within 90 days following a TIA was low (pooled sensitivity range 48–64%, pooled specificity range 59–72%). In the network meta-analysis, we analyzed 6 studies with 11 discrete cohorts, including data from 8217 patients. The ABCD3-I score demonstrated the highest DOR, followed by the ESRS, ABCD, California, and ABCD2. The SROC curves demonstrate no significant differences in the performance of the scores, using the ABCD score as the common comparator. Conclusions: In this systematic review and network meta-analysis of observational cohort studies of patients who experienced TIA and were followed for the occurrence of subsequent stroke, we failed to identify a score performing significantly better for the prediction of stroke at 90 days. New models are needed for the prediction and stroke risk stratification following a TIA. Full article

The accurate segmentation of pigmented skin lesions is a critical prerequisite for reliable melanoma detection, yet approximately 30% of lesions exhibit fuzzy or poorly defined borders. This ambiguity makes the definition of a single contour unreliable and limits the effectiveness of computer-assisted diagnosis (CAD) systems. While clinical assessment based on the ABCDE criteria (asymmetry, border, color, diameter, and evolution), dermoscopic imaging, and scoring systems remains the standard, these methods are inherently subjective and vary with clinician experience. We address this challenge by reframing segmentation into three distinct regions: background, border, and lesion core. These regions are delineated using superpixels generated via the Simple Linear Iterative Clustering (SLIC) algorithm, which provides meaningful structural units for analysis. Our contributions are fourfold: (1) redefining lesion borders as regions, rather than sharp lines; (2) generating superpixel-level embeddings with a transformer-based autoencoder; (3) incorporating these embeddings as features for superpixel classification; and (4) integrating neighborhood information to construct enhanced feature vectors. Unlike pixel-level algorithms that often overlook boundary context, our pipeline fuses global class information with local spatial relationships, significantly improving precision and recall in challenging border regions. An evaluation on the HAM10000 melanoma dataset demonstrates that our superpixel–RAG–transformer (region adjacency graph) pipeline achieves exceptional performance (100% F1 score, accuracy, and precision) in classifying background, border, and lesion core superpixels. By transforming raw dermoscopic images into region-based structured representations, the proposed method generates more informative inputs for downstream deep learning models. This strategy not only advances melanoma analysis but also provides a generalizable framework for other medical image segmentation and classification tasks. Full article

The number of thoracolumbar vertebrae (NTLV) and the number of ribs (NR) are economically important traits in pigs due to their influence on carcass length and meat yield. Although VRTN is an established key gene, it fails to fully account for population-level variation in vertebral count, necessitating a further exploration of its genetic mechanisms. Given the efficacy of crossbred populations in mapping the genetic determinants of phenotypic variation, we analyzed 439 pigs from a Landrace × Yorkshire cross. Genotyping was performed via a 50 K SNP chip. Both NTLV and NR showed high heritability (0.700 and 0.752, respectively), while the number of lumbar vertebrae (NLV) showed limited variation (92.5% of pigs had NLV = 6). Using the BLINK model, four significant loci were identified. The most significant SNP, rs3469762345, located in the intergenic region between ABCD4 and VRTN, corresponds to a previously known QTL. Additionally, three novel variant sites (rs81211244, rs81347323, and rs81416674) were identified within or near the ALDH7A1, PTPRT, and PAK1 genes, which are known to play a role in bone development. This study uncovers novel swine candidate genes associated with vertebral and rib number variation, subsequently facilitating targeted research into their molecular mechanisms. Full article

Gene replacement using adeno-associated viral (AAV) vectors has become a major therapeutic avenue for neurodegenerative diseases (NDD). In single-gene diseases with loss-of-function mutations, the objective of gene therapy is to express therapeutic transgenes abundantly in cell populations that are implicated in the pathological phenotype. X-ALD is one of these orphan diseases. It is caused by ABCD1 gene mutations and its main clinical form is adreno-myelo-neuropathy (AMN), a disabling spinal cord axonopathy starting in middle-aged adults. Unfortunately, the main cell types involved are yet poorly identified, complicating the choice of cells to be targeted by AAV vectors. Pioneering gene therapy studies were performed in the Abcd1^-/y mouse model of AMN with AAV9 capsids carrying the ABCD1 gene. These studies tested ubiquitous or cell-specific promoters, various routes of vector injection, and different ages at intervention to either prevent or reverse the disease. The expression of one of these vectors was studied in the spinal cord of a healthy primate. In summary, gene therapy has made promising progress in the Abcd1^-/y mouse model, inaugurating gene replacement strategies in AMN patients. Because X-ALD is screened neonatally in a growing number of countries, gene therapy might be applied in the future to patients before they become overtly symptomatic. Full article

This study quantifies the uncertainty in monthly streamflow predictions under future climate scenarios in two periods (near and far future) for the Riu Mannu di Narcao basin in Sardinia, Italy. The sources of uncertainty include the hydrological model structure, model parameters, and variability in climatic inputs derived from global and regional climate models (GCM-RCM coupling) and representative concentration pathways (RCPs). Three conceptual and lumped hydrological models (GR3M, ABCD, and IHACRES) were combined with four climate models and two RCPs (RCP 4.5 and RCP 8.5) to assess future streamflow. Monte Carlo simulations were performed to evaluate parameter uncertainty, and the analysis of variance (ANOVA) method was applied to quantify the different sources of uncertainty. The results reveal that, as a single source, GCM-RCM coupling is the largest contributor, accounting for 47.32% (54.64%) of total near (far) future monthly streamflow projection uncertainties, followed by the hydrological model structure at 16.02% (21.09%), RCP scenarios at 15.35% (8.54%), and parameter uncertainty at 0.79% (1.39%). A consistent decline in median monthly streamflow is projected, especially during winter months (December to February), raising a concern about water availability in the region. Our study quantified different sources of uncertainty in monthly streamflow predictions under climate change, disentangling the roles of the hydrological model, model parameters, climate model, and climate scenario for reliable future streamflow projections. Full article

Background: X-ALD is a white matter (WM) disease caused by mutations in the ABCD1 gene encoding the transporter of very-long-chain fatty acids (VLCFAs) into peroxisomes. Strikingly, the same ABCD1 mutation causes either devastating brain inflammatory demyelination during childhood or, more often, progressive spinal cord axonopathy starting in middle-aged adults. The accumulation of undegraded VLCFA in glial cell membranes and myelin has long been thought to be the central mechanism of X-ALD. Methods: This review discusses studies in mouse and drosophila models that have modified our views of X-ALD pathogenesis. Results: In the Abcd1 knockout (KO) mouse that mimics the spinal cord disease, the late manifestations of axonopathy are rapidly reversed by ABCD1 gene transfer into spinal cord oligodendrocytes (OLs). In a peroxin-5 KO mouse model, the selective impairment of peroxisomal biogenesis in OLs achieves an almost perfect phenocopy of cerebral ALD. A drosophila knockout model revealed that VLCFA accumulation in glial myelinating cells causes the production of a toxic lipid able to poison axons and activate inflammatory cells. Other mouse models showed the critical role of OLs in providing energy substrates to axons. In addition, studies on microglial changing substates have improved our understanding of neuroinflammation. Conclusions: Animal models supporting a primary role of OLs and axonal pathology and a secondary role of microglia allow us to revisit of X-ALD mechanisms. Beyond ABCD1 mutations, pathogenesis depends on unidentified contributors, such as genetic background, cell-specific epigenomics, potential environmental triggers, and stochasticity of crosstalk between multiple cell types among billions of glial cells and neurons. Full article

Snapdragon (Antirrhinum majus) serves as a model system for dissecting floral morphogenesis mechanisms. Petal malformation in A. majus impacts ornamental value, but its genetic basis remains poorly understood. We compared transcriptomes of the wild-type (Am11) and a petal-malformed mutant (AmDP2) to identify 2303 differentially expressed genes (DEGs), including E-class MIKC-type MADS-box genes SEP3 (AmMADS25/61/20/26) and SEP2 (AmMADS85). Weighted gene co-expression network (WGCNA), protein-protein interaction (PPI), qRT-PCR and virus-induced gene silencing (VIGS) analyses revealed interactions between SEP2/SEP3 and C/A/B-class MADS-box genes (AG, AP1, AP3), co-regulated MADS transcription factors (MTFs) AGL15 (AmMADS16), and auxin signaling genes (SAUR1, IAA13). qRT-PCR validated upregulation of SEP3 and downregulation of SEP2 in AmDP2. Our results suggest that E-class MADS-box genes are associated with petal malformation through coordinated interactions with hormonal pathways. These findings provide candidate targets for further functional studies in snapdragon. Full article

Background/Objectives: Access to healthy and affordable food remains a challenge for under-resourced communities due to uneven food distribution and the need for reliable transportation. This study developed and evaluated an interactive Geographic Information System (GIS)-based food asset map for a low-income community in Windham, Connecticut to improve awareness of food resources and expand opportunities for fresh food access. Methods: Using the human-centered design (HCD) framework and the Asset-Based Community Development (ABCD) model, the map integrates food locations, transportation routes, and assistance eligibility. Internal pilot testing (n = 8) identified usability issues, leading to updates such as mobile compatibility and user guides. Usability testing (n = 74) assessed navigation performance and user feedback through task-based evaluations and surveys. Categorical map usability, sociodemographic, diet, and health characteristics were tested for participants with food security (yes/no) or digital literacy (passed/failed). Results: Food-secure participants showed higher usability success than food-insecure individuals (p < 0.05), while those relying on food assistance faced greater challenges (p < 0.05). Individuals rating their diet as “very good/excellent” were most likely to pass the map usability testing (p < 0.05), whereas younger, college-educated, employed participants and those with vehicles trended toward passing (p < 0.1). Participants generally reported the map easy to navigate, especially those with food security. Conclusions: The asset map promotes food resource awareness and addresses barriers such as limited public transportation information. Additional efforts are needed to support food-insecure users in utilizing digital food access resources. This study contributes to initiatives to improve food access, digital inclusion, and community engagement in under-resourced communities. Full article

Background and Objectives: Type 2 diabetes (T2D), closely associated with obesity, contributes to increased morbidity and mortality due to complications such as cardiometabolic disease. This review aims to evaluate the effectiveness of metabolic and bariatric surgeries (MBS) and endoscopic bariatric therapies (EBTs) in achieving diabetes remission and to examine key predictors influencing remission outcomes. Materials and Methods: This review synthesizes data from studies on MBS and EBT outcomes, focusing on predictors for diabetes remission such as preoperative insulin use, diabetes duration, HbA1c, and C-peptide levels. Additionally, predictive scoring systems, including the Individualized Metabolic Surgery (IMS), DiaRem, Advanced-DiaRem, ABCD, and Robert et al. scores, were analyzed for their utility in forecasting remission likelihood. Results: Key predictors of T2D remission include shorter diabetes duration, lower HbA1c, and higher C-peptide levels, while prolonged insulin use, and higher insulin doses are associated with lower remission rates. Scoring models like IMS and DiaRem demonstrate that lower scores correlate with a higher likelihood of remission, especially for procedures such as Roux-En-Y gastric bypass (RYGB). RYGB generally shows higher remission rates compared to sleeve gastrectomy (SG), particularly among patients with mild disease severity, while EBTs like ESG and IGBs contribute 5–20% total weight loss (TWL) and moderate glycemic control improvements. Conclusions: Both MBS and EBTs are effective for T2D management, with predictive scoring models aiding in individualized patient selection to optimize remission outcomes. Further research to validate these predictive tools across diverse populations could enhance treatment planning for both surgical and endoscopic interventions. Full article

X-adrenoleukodystrophy (X-ALD) is a peroxisomal metabolic disorder caused by mutations in the ABCD1 gene encoding the peroxisomal ABC transporter adrenoleukodystrophy protein (ALDP). Similar mutations in ABCD1 may result in a spectrum of phenotypes in males with slow progressing adrenomyeloneuropathy (AMN) and fatal cerebral adrenoleukodystrophy (cALD) dominating most cases. Mouse models of X-ALD do not capture the phenotype differences and an appropriate model to investigate the mechanism of disease onset and progress remains a critical need. Here, we generated induced pluripotent stem cell (iPSC) lines from skin fibroblasts of two each of apparently healthy control, AMN, and cALD patients with non-integrating mRNA-based reprogramming. iPSC lines expanded normally and expressed pluripotency markers Oct4, SOX2, NANOG, SSEA, and TRA-1–60. Expression of markers SOX17, Brachyury, Desmin, OXT2, and beta tubulin III demonstrated the ability of the iPSCs to differentiate into all three germ layers. iPSC-derived lines from CTL, AMN, and cALD male patients were differentiated into astrocytes. Differentiated AMN and cALD astrocytes lacked ABCD1 expression and accumulated saturated very long chain fatty acids (VLCFAs), a hallmark of X-ALD, and demonstrated differential mitochondrial bioenergetics, cytokine gene expression, and differences in STAT3 and AMPK signaling between AMN and cALD astrocytes. These patient astrocytes provide disease-relevant tools to investigate the mechanism of differential neuroinflammatory response in X-ALD and will be valuable cell models for testing new therapeutics. Full article

The MADS-box transcription factor gene family is essential for the differentiation and development of floral organs. Genome-wide and transcriptome data from Phoebe bournei provide the foundation for studying its floral development. In this study, phylogenetic relationships, protein characteristics, conserved domains, gene structures, and cis-acting elements in promoter regions of P. bournei MADS-box genes were systematically analyzed through bioinformatics methodologies. A total of 69 PbMADS genes were identified and classified into 15 subfamilies based on their phylogenetic relationships. The potential functions of these genes were inferred based on transcriptomic data and GO classification. In addition, we selected genes from the ABCDE model to analyze protein interactions and performed RT-qPCR to analyze their expression in each floral organ whorl (outer tepals, inner tepals, stamens, and carpel). Based on these analyses, we rationally constructed a model for the floral organ development in P. bournei. This study, thus, provides a theoretical reference for germplasm innovation in P. bournei and offers insights into the floral development in other Lauraceae species. Full article

Organ-specific transcriptomes provide valuable insight into the genes involved in organ identity and developmental control. This study investigated transcriptomes of floral organs and subtending bracts in wild and domesticated Gossypium hirsutum, focusing on MADS-box genes critical for floral development. The expression profiles of A, B, C, D, and E class genes were analyzed, confirming their roles in floral organ differentiation. Hierarchical clustering revealed similar expression patterns between bracts and sepals, as well as between petals and stamens, while carpels clustered with developing cotton fibers, reflecting their shared characteristics. Beyond MADS-box genes, other transcription factors were analyzed to explore the genetic basis of floral development. While wild and domesticated cotton showed similar expression patterns for key genes, domesticated cotton exhibited significantly higher expression in carpels compared to wild cotton, which aligns with the increased number of ovules in the carpels of domesticated cotton. Functional enrichment analysis highlighted organ-specific roles: genes upregulated in bracts were enriched for photosynthesis-related GO terms, while diverse functions were enriched in floral organs, supporting their respective functions. Notably, A class genes were not significantly expressed in petals, deviating from the ABCDE model, which warrants further analysis. Lastly, the ABCDE class genes exhibited differential homoeolog expression bias toward each subgenome between two accessions, suggesting that the domestication process has influenced homoeolog utilization despite functional constraints in floral organogenesis. Full article