Search Results (606)

In this study, we present a pilot investigation using a single Purple Heart plant (Tradescantia pallida) to explore whether bioelectrical signals for dual-purpose classification tasks: environmental state detection and human emotion recognition. Using an AD8232 ECG sensor at 400 Hz sampling rate, we recorded 3 s bioelectrical signal segments with 1 s overlap, converting them to mel-spectrograms for ResNet18 CNN (Convolutional Neural Network) classification. For lamp on/off detection, we achieved 85.4% accuracy with balanced precision (0.85–0.86) and recall (0.84–0.86) metrics across 2767 spectrogram samples. For human emotion classification, our system achieved optimal performance at 73% accuracy with 1 s lag, distinguishing between happy and sad emotional states across 1619 samples. These results should be viewed as preliminary and exploratory, demonstrating feasibility rather than definitive evidence of plant-based emotion sensing. Replication across plants, days, and experimental sites will be essential to establish robustness. The current study is limited by a single-plant setup, modest sample size, and reliance on human face-tracking labels, which together preclude strong claims about generalizability. Full article

During the Late Miocene, Bramatherium was the main representative of the giraffid subfamily Sivatheriinae in the Indian Subcontinent, with sparse and uncertain records from adjacent regions. In the present paper, we describe and compare two ossicones of the same individual, unearthed from the Upper Miocene site of Fourka in Chalkidiki Peninsula, Northern Greece, and attribute them with certain confidence to the species Bramatherium perimense. The definite record of Bramatherium so far away from the Indian Subcontinent and in close proximity to the well-known Pikermian sivatheriine Helladotherium duvernoyi enabled us to re-discuss both the intrageneric diversity of Bramatherium and the debatable Bramatherium–Helladotherium taxonomy. Our review allows us (i) to recognize only two Bramatherium species in Asia: the large-sized B. grande and the smaller B. perimense and (ii) to confirm and further support with morphological and biogeographic evidence the synonymy of Helladotherium with Bramatherium. Full article

Accurate and reliable credit risk classification is fundamental to the stability of financial systems and the efficient allocation of capital. However, with the rapid expansion of customer information in both volume and complexity, traditional rule-based or purely statistical approaches have become increasingly inadequate. Motivated by these challenges, this study introduces a domain-constrained stacking ensemble framework that systematically integrates business knowledge with advanced machine learning techniques. First, domain heuristics are embedded at multiple stages of the pipeline: threshold-based outlier removal improves data quality, target variable redefinition ensures consistency with industry practice, and feature discretization with monotonicity verification enhances interpretability. Then, each variable is transformed through Weight-of-Evidence (WOE) encoding and evaluated via Information Value (IV), which enables robust feature selection and effective dimensionality reduction. Next, on this transformed feature space, we train logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), and a two-layer stacking ensemble. Finally, the ensemble aggregates cross-validated out-of-fold predictions from LR, RF and XGBoost as meta-features, which are fused by a meta-level logistic regression, thereby capturing both linear and nonlinear relationships while mitigating overfitting. Experimental results across two credit datasets demonstrate that the proposed framework achieves superior predictive performance compared with single models, highlighting its potential as a practical solution for credit risk assessment in real-world financial applications. Full article

Background/Objectives: Lumbosacral transitional vertebra (LSTV) is a common anatomical variant, but its identification on plain radiographs is often inconsistent. This inconsistency can lead to clinical complications such as chronic low back pain, misinterpretation of spinal parameters, and an increased risk of wrong-level surgery. This study aimed to develop and validate a deep learning-based artificial intelligence (AI) model for the automated detection of LSTV on plain lumbar radiographs. Methods: This retrospective observational study included a total of 3116 standing lumbar lateral radiographs. The presence or absence of lumbosacral transitional vertebra (LSTV) was definitively established using whole-spine imaging, CT, or MRI. Multiple deep learning architectures, including DINOv2, CLIP (ViT-B/32), and ResNet-50, were initially evaluated for binary classification of LSTV. Among these, the ResNet-50 model with partial fine-tuning achieved the best test performance and was subsequently selected for fivefold cross-validation using the training set. Model performance was assessed using accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC), and interpretability was evaluated using gradient-weighted class activation mapping (Grad-CAM). Results: On the independent test set of 313 radiographs, the final model demonstrated robust diagnostic performance. It achieved an accuracy of 76.4%, a sensitivity of 85.1%, a specificity of 61.9%, and an AUC of 0.84. The model correctly identified 166 out of 195 LSTV cases and 73 out of 118 normal cases. Conclusions: This AI-based system offers a highly accurate and reliable method for the automated detection of LSTV on plain radiographs. It shows strong potential as a clinical decision-support tool to reduce diagnostic errors, improve pre-operative planning, and enhance patient safety. Full article

The prophylactic extraction of third molars is highly dependent on the surgeon’s experience as the common practices and guidelines contradict. The purpose of this study was to evaluate the eruption status of impacted third molars using deep learning-based artificial intelligence (AI) and to develop a model that predicts their final positions at an early stage to aid clinical decisions. In this retrospective study, 1102 panoramic radiographs (PANs) were annotated by three expert dentists to classify eruption status as either initial or definitive. A dataset was created and two deep learning architectures, InceptionV3 and ResNet50, were tested through a three-phase protocol: hyperparameter tuning, model evaluation, and assessment of preprocessing effects. Accuracy, recall, precision, and F1 score were used as performance metrics. Classical machine learning (ML) algorithms (SVM, KNN, and logistic regression) were also applied to features extracted from the deep models. ResNet50 with preprocessing achieved the best performance (F1 score: 0.829). Models performed better with definitive cases than with initial ones, where performance dropped (F1 score: 0.705). Clinically, the model predicted full eruption or impaction with 83% and 75% accuracy, respectively, but showed lower accuracy for partial impactions. These results suggest that AI can support early prediction of third molar eruption status and enhance clinical decision-making. Deep learning models (particularly ResNet50) demonstrated promising results in predicting third molar eruption outcomes. With larger datasets and improved optimization, AI tools may achieve greater accuracy and support routine clinical applications. Full article

Background and Objectives: Pulmonary sequestration (PS) is a rare congenital lung malformation. In adults, intralobar disease with recurrent infection or hemoptysis predominates. Cross-sectional imaging (CTA/MRA) is central to mapping the aberrant systemic supply; catheter angiography is used when noninvasive imaging is inconclusive or when an endovascular procedure is planned. We aimed to synthesize adult PS cases treated with endovascular or hybrid approaches and to summarize case selection, techniques, and outcomes. Methods: We conducted a PRISMA-2020-informed systematic review. We searched PubMed and Scopus from 1 January 2000 to 31 May 2025. Two reviewers extracted data independently; due to heterogeneity, we performed a narrative synthesis and a JBI-adapted qualitative risk-of-bias appraisal. Eligible studies enrolled adults (≥18 years) with imaging-confirmed PS treated with embolization, stent-graft exclusion, or hybrid therapy; prespecified outcomes included technical and clinical success, complications, recurrence, and re-intervention. The review was not registered. Results: Of 93 records screened, 41 publications reporting 48 adults were included. Twenty-five patients were managed endovascularly and 23 with hybrid therapy. Intralobar sequestration predominated (36/48); feeding arteries most often arose from the descending thoracic aorta (28/48). Complications were reported in 10 cases, mostly minor; three embolization cases required re-intervention. Conclusions: Endovascular therapy is useful for selected anatomies and urgent bleeding control, while hybrid strategies may benefit large, complex, or aneurysmal feeding arteries. The evidence base is limited to small case reports/series with heterogeneous outcome definitions and follow-up, precluding quantitative synthesis. Standardized outcome definitions, structured follow-up, and prospective registries are needed. Full article

Pleurobrachia pileus and P. bachei are among the most frequently recorded ctenophores worldwide. Despite their long-standing descriptions dating back nearly 250 years, their taxonomic boundaries remain ambiguous due to the lack of definitive diagnostic features. In Mexican waters, records of both species are primarily based on geographic distribution, with limited morphological evidence supporting their separation. This study aimed to evaluate the morphological diversity of Pleurobrachia spp. along the Mexican coast through a comprehensive morphological approach. Specimens from four sites representing two marine regions (the Gulf of Mexico and the Southern Mexican Pacific coast) were examined for phenotypic variation. A standardized methodology was developed for specimen handling, observation, and digital reconstruction of body plans, enabling the extraction of 38 discrete and continuous morphological traits. Our analysis revealed two distinct and internally consistent phenotypic groups, each corresponding to one of the two regions, with notable differences in tentacular sheath structure, tentacular canals, gastrovascular cavity pigmentation pattern, and pharyngeal morphology. A clinal pattern in body size was observed, with smaller specimens in the north and larger ones in the south. Importantly, neither phenotype matched the diagnostic traits of P. pileus or P. bachei, suggesting that the Mexican populations represent separate, previously unrecognized species. These findings highlight the necessity to re-evaluate the taxonomy of Pleurobrachia in these regions and contribute valuable morphological data toward resolving longstanding questions about species boundaries within this genus. Full article

This study investigates the behaviour of dense silty sands with kaolinite clay under static drained/undrained conditions at low confining stress. Conventional laboratory tests assessed the mixtures’ physical properties, but standard void ratio methods proved inadequate for silty sands with kaolinite. Despite targeting 80% relative density, specimens exhibited loose sand behaviour in both drained and undrained tests. With increasing kaolinite content, conventionally reconstituted mixtures exhibit reduced peak stress ratios up to 10% fines, with little change beyond, while critical ratios generally rise at 25 kPa but remain unchanged or decrease slightly at 50 kPa. Analytical redefinition of minimum/maximum void ratios (based on sand–clay volumetric fractions) improved specimen reconstitution, yielding dense behaviour matching that of the host sand. The alternatively reconstituted mixtures display increasing drained peaks and minor changes in undrained peaks with increasing kaolinite content, with critical ratios increasing markedly at 25 kPa and only slightly at 50 kPa. However, this analytical void ratio determination method is limited to non-expansive, low-plasticity clays. Void ratios in silty sands with clay mineras are influenced by confining stress, drainage, saturation, clay content, and the sand skeleton structure. Unlike pure sands, these mixtures exhibit variable void ratios due to changes in the clay phase under different saturation levels. A new evaluation method is needed that accounts for clay composition, saturation-dependent consistency, and initial sand skeleton configuration to characterise these soils accurately. The findings highlight the limitations of conventional approaches and stress the need for advanced frameworks to model complex soil behaviour in geotechnical applications. Full article

Asthma is a chronic inflammatory disease with a heterogeneous course, often progressing silently from mild symptoms to severe, treatment-refractory disease. Current guidelines recommend biologic therapies after failure of high-dose inhaled corticosteroids and additional controllers, typically in patients with frequent exacerbations. This reactive approach may delay intervention until irreversible airway remodeling has occurred, limiting the potential benefits of biologic therapy. Therefore, severe asthma may be envisioned as the consequence of missed opportunities for early interventions. Early initiation of biologic therapy—guided by biomarkers such as blood eosinophil count and fractional exhaled nitric oxide (FeNO), as well as symptom burden and risk of lung function decline—may prevent progression to severe asthma and improve remission rates. This position paper advocates for a shift from severity-based to risk-based treatment strategies, recommending earlier biomarker assessment, redefinition of escalation criteria, and clinical trials designed to evaluate biologics in symptomatic non-exacerbating patients. By recognizing persistent inflammation and progression risk earlier in the disease course, clinicians may have a critical opportunity to alter the trajectory of asthma, reduce long-term morbidity, and achieve sustained control before irreversible damage occurs. Full article

Introduction: Canine sinonasal aspergillosis (SNA) can present singular as a primary disease or secondary to concurrent sinonasal pathology. We hypothesized that treatment response and prognosis differ between both forms, particularly when sinusitis is present. Methods: In this retrospective study, 30 dogs with SNA were categorized as either group pA (primary aspergillosis) or group sA (secondary aspergillosis; with additional sinonasal pathology). History, diagnostics, endoscopic therapeutic intervention of affected nose and sinus, and follow-up data were analyzed. Results: Group pA included 19/30 dogs (63%), with 15 dogs (79%) showing concurrent sinusitis. Group sA included 11/30 dogs (37%; additional conditions: foreign bodies, dental pathologies, frontal bone fracture). Only 2/11 sA dogs (18%) had sinusitis. Follow-ups in group pA were more frequent than in group sA (p = 0.04). Need for re-treatments differed significantly between groups (p = 0.02) and in dogs with sinusitis, regardless of group (p < 0.001). In group sA, treating the underlying condition plus single endoscopic debridement ± antifungal therapy led to clinical resolution in 11 of 12 dogs (92%). Conclusions: Primary SNA is frequently associated with sinusitis, requires aggressive repeated antifungal therapy, and may not achieve a definitive cure. Secondary SNA is usually confined to the nasal cavity, responds well to underlying condition treatment, carries better prognosis, and requires fewer antifungal treatments. Full article

Ozone (O₃) has re-emerged in periodontology for its antimicrobial, oxygenating, and immunomodulatory actions, yet its role in regeneration remains contentious. This narrative review synthesizes current evidence on adjunctive ozone use in periodontal therapy, delineates cellular constraints—especially in periodontal ligament fibroblasts (PDLFs)—and explores mitigation strategies using bioactive compounds and advanced delivery platforms. Two recent meta-analyses indicate that adjunctive ozone with scaling and root planing yields statistically significant reductions in probing depth and gingival inflammation, with no significant effects on bleeding on probing, plaque control, or clinical attachment level; interpretation is limited by heterogeneity of formulations, concentrations, and delivery methods. Mechanistically, ozone imposes a dose-dependent oxidative burden that depletes glutathione and inhibits glutathione peroxidase and superoxide dismutase, precipitating lipid peroxidation, mitochondrial dysfunction, ATP depletion, and PDLF apoptosis. Concurrent activation of NF-κB and upregulation of IL-6/TNF-α, together with matrix metalloproteinase-mediated extracellular matrix degradation and tissue dehydration (notably with gaseous applications), further impairs fibroblast migration, adhesion, and ECM remodeling, constraining regenerative potential. Emerging countermeasures include co-administration of polyphenols (epigallocatechin-3-gallate, resveratrol, curcumin, quercetin), coenzyme Q10, vitamin C, and hyaluronic acid to restore redox balance, stabilize mitochondria, down-modulate inflammatory cascades, and preserve ECM integrity. Nanocarrier-based platforms (nanoemulsions, polymeric nanoparticles, liposomes, hydrogels, bioadhesive films) offer controlled ozone release and co-delivery of protectants, potentially widening the therapeutic window while minimizing cytotoxicity. Overall, current evidence supports ozone as an experimental adjunct rather than a routine regenerative modality. Priority research needs include protocol standardization, dose–response definition, long-term safety, and rigorously powered randomized trials evaluating bioactive-ozone combinations and nanocarrier systems in clinically relevant periodontal endpoints. Full article

Taxonomic clarity within the genus Antithamnion is critical for understanding its molecular phylogeny and biodiversity. Here we report Antithamnion hubbsii for the first time from the Korean coast. This finding highlights the need to re-evaluate its relationship with the previously reported, morphologically very similar A. nipponicum in this region, raising the question of whether the newly identified A. hubbsii represents a local variant of A. nipponicum or a recently introduced invasive species via nearby ports. Specimens collected from Gangneung were analyzed using plastid-encoded rbcL and psaA genes, confirming their identity as A. hubbsii. Morphological features such as indeterminate lateral axes, oppositely arranged pinnae and pinnules, and distinctive adaxial gland cells supported this identification. Molecular analyses revealed minimal divergence between A. hubbsii and A. nipponicum (1–3 bp in rbcL, none in psbA), and contrasting results from different species delimitation methods. Phylogenetic analyses nevertheless placed the Korean specimens in a strongly supported A. hubbsii/A. nipponicum clade. Taken together, our results suggest that the North American invasive A. nipponicum and the Korean A. hubbsii may represent a single species with broad intraspecific variation. Definitive resolution will require molecular analyses of the type specimens of both taxa. Full article

The Flaviviruses Dengue virus (DENV), West Nile virus (WNV), Zika virus (ZIKV), and Yellow Fever virus (YFV), are mosquito-borne viruses that represent a persistent challenge to global health due to the emergence and re-emergence of outbreaks of significant magnitudes. Their positive-sense RNA genome, about 11,000 nucleotides long, encodes structural and nonstructural proteins. These viruses evolve rapidly through mutations and genetic recombination, which can lead to more virulent and transmissible strains. Although whole-genome sequencing is ideal for studying their evolution and geographic spread, its cost is a limitation. We investigated the genetic variability of DENV, ZIKV, WNV, and YFV to identify genomic regions that accurately reflect the phylogeny of the complete coding sequence and evaluated the utility of these regions in reconstructing the geographic dispersal patterns of viral genotypes and lineages. Publicly available sequences from GenBank were examined to assess variability, reconstruct phylogenies, and identify the most informative genomic regions. Once representative regions were identified, they were used to infer the global phylogeographic structure of each virus. The virus depicted distinct variation patterns, but conserved regions of high and low variability were common to all. Highly variable regions of ~2700 nt offered greater resolution in phylogenetic trees, improving the definition of internal branches and statistical support for nodes. In some cases, combined multiple highly variable regions enhanced phylogenetic accuracy. Phylogeographic reconstruction consistently grouped sequences by genotype and geographic origin, with temporal structuring revealing evolutionarily distinct clusters that diverged over decades. These findings highlight the value of targeting genomic regions for phylogenetic and phylogeographic analysis, providing an efficient alternative for genomic surveillance. Full article

Cardiac surgery, now a routine medical intervention, was once deemed unthinkable—not merely due to technical limitations, but because of deep-seated cultural, religious, and philosophical prohibitions. This article traces the historical and ethical trajectory of the human heart from a sacred, inviolable symbol of the soul to a surgically accessible organ. Through an interdisciplinary lens that integrates medical history, anthropology, theology, and contemporary bioethics, we examine how shifts in metaphysical belief, technological progress, and moral reasoning gradually legitimized cardiac intervention. From ancient Egyptian funerary rites and classical cardiocentric models to medieval religious taboos and Enlightenment redefinitions of the body, the heart’s transformation reflects broader changes in how humanity conceives life, death, and identity. The emergence of modern cardiac surgery, especially heart transplantation and extracorporeal technologies, raised new ethical dilemmas, challenging the boundaries between tissue and meaning, biology and personhood. This study argues that despite its clinical secularization, the heart retains a unique symbolic gravity that continues to shape public perception and professional responsibility. In the age of precision medicine, cardiac surgery remains not only a technical act but an existential gesture—a transgression that demands both scientific mastery and moral reverence. Full article

Background/Objectives: Head and neck cancer (HNC) is a heterogeneous group of malignancies in which staging plays a critical role in guiding treatment and prognosis. Large language models (LLMs) such as ChatGPT, DeepSeek, and Grok have emerged as potential tools in oncology, yet their clinical applicability in staging remains unclear. This study aimed to evaluate the accuracy and concordance of LLMs compared to clinician-assigned staging in patients with HNC. Methods: The medical records of 202 patients with HNC, who presented to our center between 1 January 2010 and 13 February 2025, were retrospectively reviewed. The information obtained from the hospital information system by a junior researcher was re-evaluated by a senior researcher, and standard staging was completed. Except for the stage itself, the data used for staging were provided to a blinded third researcher, who then entered them into the ChatGPT, DeepSeek, and Grok applications with a staging command. After all staging processes were completed, the data were compiled, and clinician-assigned stages were compared with those generated by the LLMs. Results: The majority of the patients had laryngeal (45.5%) and nasopharyngeal cancer (21.3%). Definitive surgery was performed in 39.6% of the patients. Stage 4 was the most common stage among the patients (54%). The overall concordance rates, Cohen’s kappa values, and F1 scores were 85.6%, 0.797, and 0.84 for ChatGPT; 67.3%, 0.522, and 0.65 for DeepSeek; and 75.2%, 0.614, and 0.72 for Grok, respectively, with no statistically significant differences between models. Pathological and surgical staging were found to be similar in terms of concordance. The concordance of assessments utilizing only imaging, only pathology notes, only physical examination notes, and comprehensive information was evaluated, revealing no significant differences. Conclusions: Large language models (LLMs) demonstrate relatively high accuracy in staging HNC. With careful implementation and with the consideration of prospective studies, these models have the potential to become valuable tools in oncology practice. Full article