Although ceratopsid dinosaurs possess a characteristically hypertrophied narial region, soft-tissue anatomy associated with such a skeletal structure and their biological significance remain poorly understood. The present study provides the first comprehensive hypothesis on the soft-tissue anatomy in the ceratopsid rostrum based on the Extant Phylogenetic Bracket approach. Several cranial specimens of Triceratops including the computed tomography-scan data of an isolated premaxilla as well as those of phylogenetically diverse ceratopsids were examined and compared to the anatomical features of the rostrum in extant reptiles. The resulting hypothesis includes the narial neurovascular pathways and locations of the nasal gland and nasolacrimal duct. Particularly, the narial innervation pattern in ceratopsids is inferred to be unique among reptiles and is suggested to have evolved in response to the enlargement of the naris. In addition, respiratory turbinates are inferred to have been present in ceratopsids for the first time based on an osteological correlate and would likely have served for cephalic thermal regulation as in extant birds and mammals. Acquisition of such a structure might have mitigated a thermal problem associated with the large size of the ceratopsid head.

The tibial slope is a well-known risk factor for anterior cruciate ligament (ACL) injury. As machine learning continues to progress, it has become an increasingly explored tool for clinical screening and risk factor analysis. This study aims to develop and validate a prognostic machine learning model to predict the outcome of ACL injury from tibial anatomic parameters and identify the most predictive features. A pre-published dataset of coronal, medial and lateral tibial slopes and medial tibial depth was constructed using magnetic resonance imaging scans taken from 104 subjects (44 males: 22 injured, 22 uninjured; 60 females: 27 injured, 33 uninjured). The dataset was split into train-validation and test sets to ensure robust model evaluation. AutoGluon-enabled machine learning models, including XGBoost, LightGBM, CatBoost, TabPFN, TabM, TabICL, MITRA and their weighted ensembles were trained and tuned with respect to the F2-score across ten different random seeds. Two instances of the best-performing model were developed: a default tested model (weighted ensemble from the default seed of 42) and a full-dataset model (weighted ensemble retrained on the entire dataset). Global SHapley Additive exPlanations analysis was used to elucidate the most predictive features, and local SHapley Additive exPlanations analysis to provide interpretability for individual predictions. The default tested model achieved a 73.60% validation F2-score. On the test set, it demonstrated a 95.44% test balanced accuracy, 95.24% F1-score, 98.04% F2-score, 100% ROC AUC, 90.91% precision and 100% recall. The full-dataset model achieved an 81.30% validation F2-score. The relative importance of tibial anatomical features were identified. Overall, the study presented two prognostic models with moderately high predictive power to identify subjects with high likelihood of ACL injury. Decreased medial tibial depth along with increased medial and lateral tibial slopes were reported as top predictors for ACL injury. These models can potentially be integrated into clinical practice to assist clinicians in predicting the likelihood of ACL injury, but require external validation. Level III, case-control study.

Time-difference electrical impedance tomography (EIT) is gaining widespread use for bedside lung monitoring in intensive care patients suffering from lung-related diseases. It involves collecting voltage measurements from electrodes placed on the patient's thorax, which are then used to reconstruct impedance images. This study investigates how incorporating anatomical information from CT data into the widely used GREIT reconstruction algorithm affects EIT images and improves their interpretability. Based on clinically motivated lung state scenarios, we simulated EIT measurements to assess how the GREIT parameters influence the result of EIT image reconstruction, particularly with respect to noise performance and image accuracy. We introduce quality measures that allow us to perform a quantitative assessment of reconstruction quality. We incorporate the anatomical features of a patient from CT data by customizing the background conductivity and the distribution of GREIT training targets. Our analysis confirmed that unphysiological background conductivity assumptions can lead to misleading EIT images, whereas physiological values, although more accurate, come with higher noise sensitivity. By increasing the number of GREIT training targets inside the lung and adapting the respective weighting radius, we significantly improved the anatomical accuracy of the EIT images. When applied to clinical EIT data from a representative ARDS patient, these adjustments in the reconstruction setup substantially enhanced the interpretability of the resulting EIT images. Incorporating CT-based anatomical data in the GREIT reconstruction significantly enhances the clinical applicability of EIT in lung monitoring. The improved interpretability of EIT images facilitates better-informed clinical decisions and the individualized adjustment of ventilation strategies for critically ill patients.

Mangrove constitutes a critical component of transitional ecosystems that bridge terrestrial and marine environments, providing substantial ecological contributions to both environments. Mangrove taxa have undergone extensive physiological and anatomical adaptations to optimize survival and reproductive success within the unique environmental conditions of intertidal habitats. Specialized adaptive structures in mangrove species include modified root systems, salt‐secreting glands, and salt tolerance mechanisms. Mangrove substrate toxicity elicits tannin synthesis in mangroves, leading to the accumulation of these contents within plant tissues. Tannin accumulation in plants within specific zones should correlate with developmental patterns specific to that region, since tannins are produced to counteract toxicity linked to mangrove habitats. Tannin quantification using the Prussian blue assay is based on the production of ferric ferrocyanide precipitates via ferrous ion oxidation by tannin compounds. The majority of plant specimens exhibited the highest tannin production in the stem bark, which was consistent with anatomical characteristics, given that this tissue region comprises highly metabolically active cells. Xylocarpus moluccensis exhibited higher tannin concentrations in root bark compared to stem bark, indicating effective adaptation to its landward zone habitat. These tannins may function to mitigate the toxicity of ferric ions present in the muddy substrate. Plants in the seaward zone, including Avicennia alba and Sonneratia caseolaris , were found to synthesize tannins in stems, bark, and leaves. The leaf anatomy of these species features salt‐secreting glands that facilitate salt excretion from leaves, thereby providing adequate space within the leaf tissue for tannin accumulation.

Computer-Assisted Intervention has the potential to revolutionize modern surgery, with surgical scene understanding serving as a critical component in supporting decision-making and improving procedural efficacy. While existing AI-driven approaches alleviate annotation burdens via self-supervised spatial representation learning, their lack of explicit temporal modeling during pre-training fundamentally restricts the capture of dynamic surgical contexts, resulting in incomplete spatiotemporal understanding. In this work, we introduce the first video-level surgical pre-training framework that enables joint spatiotemporal representation learning from large-scale surgical video data. To achieve this, we constructed a large-scale surgical video dataset comprising 3650 videos and 3.55 million frames, spanning more than 20 surgical procedures and over 10 anatomical structures. Building upon this dataset, we propose SurgVISTA (Surgical Video-level Spatial-Temporal Architecture), a reconstruction-based pre-training method that jointly captures intricate spatial structures and temporal dynamics. Additionally, SurgVISTA incorporates image-level knowledge distillation guided by a surgery-specific expert model to enhance the learning of fine-grained anatomical and semantic features. To validate its effectiveness, we established a comprehensive benchmark comprising 13 video-level datasets spanning six surgical procedures across four tasks. Extensive experiments demonstrate that SurgVISTA consistently outperforms both natural- and surgical-domain pre-trained models, demonstrating strong potential to advance intelligent surgical systems in clinically meaningful scenarios.

In the present communication, Paxillus mandalensis belonging to the family Paxillaceae is described from Uttarakhand, India. P. mandalensis is characterized by infundibuliform pileus with decurrent yellowish‐brown lamellae, inrolled margins, ellipsoidal and smooth basidiospores, abundant pleurocystidia with hooked‐shaped apex, presence of clamp connections in the pileipellis and occurring under Quercus leucotrichophora , and strong pleasant fruity smell. P. mandalensis is described here as a new species from the Indian Himalaya with detailed morphological description accompanied with color photographs of the basidiomata, and illustrations of the main anatomical features and nuclear ribosomal internal transcribed spacer‐based molecular phylogeny.

The functionality of the hip joint is primarily determined by the anatomical relationship between acetabulum and femur. Impairment of this relationship can lead to diseases such as femoroacetabular impingement and hip osteoarthritis. In patients undergoing total hip arthroplasty, accurate placement of the acetabular and femoral components in accordance with native 3-dimensional anatomy (3D) is crucial for obtaining prosthesis stability and survival, also for preventing postoperative complications such as wear, dislocation and osteolysis. Therefore, 3D determination of native anatomical features of the hip joint is highly important. A total of 100 adults were randomly selected. Right femur and acetabulum were segmented using MIMICS program. 2D and 3D measurements of femoral anteversion according to posterior condylar and transepicondylar axis, acetabular anteversion, acetabular inclination and combined anteversion were determined. The differences between gender groups and the correlations of two- and three-dimensional measurement results were evaluated. According to 2D and 3D measurements, statistically significant differences were observed between gender groups in all parameters except for 2D acetabular inclination. A very strong correlation was observed between 3D femoral anteversion measurements performed using the posterior condylar axis and transepicondylar axis. Our findings revealed statistically significant differences between 2D and 3D measurements in most parameters, which have clinical relevance. A very strong correlation between femoral anteversion measurements obtained using the transepicondylar and posterior condylar axes supports the intraoperative use of the transepicondylar axis reliably. We believe the data obtained from our study will contribute to understand the 3-dimensional native anatomy of the hip joint.

Secondary cleft lip nasal deformity presents a persistent challenge in reconstructive surgery, with fundamental differences existing between unilateral and bilateral presentations that dictate distinct management approaches. This systematic review delineates the contrasting anatomical underpinnings of these deformities, where unilateral cases are characterized by marked asymmetry and bilateral cases by a symmetric deficiency marked by severe columellar shortening. It further synthesizes the evolution of assessment methodologies, from traditional anthropometry to advanced three-dimensional (3D) technologies like stereophotogrammetry and CT reconstruction, which enable precise preoperative planning. The review elaborates on differentiated repair strategies, emphasizing symmetry restoration in unilateral deformities versus midline structural reconstruction in bilateral cases, often necessitating substantial costal cartilage grafts. Despite advancements, challenges remain in achieving long-term stability and managing soft tissue limitations. The integration of computational modeling, artificial intelligence (AI), and tissue engineering represents the future direction for progressing toward personalized and predictable reconstruction. This synthesis provides a comprehensive framework to guide clinical decision-making and future research.

This study aimed to investigate the relationship between palate morphology, masticatory muscle thickness, choanae structure, and sphenoidale foramina in individuals with temporomandibular dysfunction (TMD), and to determine how variations in these parameters affect temporomandibular joint (TMJ) function. Cone beam computed tomography (CBCT) scans of 36 individuals with TMD and 36 healthy controls, aged 18 to 69 years, were retrospectively analyzed. The possible relationships between TMD and the morphometry of the hard palate, nasi choanae, and sphenoidale foramina were evaluated, and thickness measurements of the masticatory muscles (masseter, temporalis, lateral, and medial pterygoideus) were also correlated with TMD. Significant relationships were found between TMD and the morphometric features of the craniofacial structures. Statistically significant relationships were found between age and the masseter, temporalis, and medial pterygoid muscle thicknesses in individuals who had TMD (P<0.05). In addition, a significant difference was observed in the hard palate transverse width according to gender in the TMD group (P<0.05). In the control group, a significant relationship was found between medial pterygoid thickness on both sides and left foramen ovale length and hard palate transverse width values depending on gender (P<0.05). Significant differences were found in foramen rotundum width measurements in the comparison of the TMD and control groups (P<0.05). This study demonstrates the relationship between craniofacial morphology, masticatory muscle thickness, and TMD. The findings suggest that anatomic features of the hard palate and sphenoid region may contribute to TMJ function and deepen the understanding of TMD's structural basis.

Central lumbar spinal stenosis, a prevalent degenerative spinal disorder, severely impacts the quality of life for those affected. Axial and sagittal MRI images offer diverse information on tissue structure and lesions, which is crucial for accurate diagnosis. However, MRI-based diagnostic approaches still have poor lesion localization, insufficient cross-view alignment, underutilization of multi-view MRI information, and limited generalization across patient variability. To address these problems, we proposed an Encompassing Lumbar Central Spinal Stenosis Grading Model via Multi-view MRI Image Fusion called ELSG-MF. ELSG-MF consists of three stages: the first stage utilizes the extraction of robust pseudo-labels through a contrast-driven consistency reinforcement technique to guide Med-SAM in localizing and segmenting spinal tissue components. The Sagittal-Axial Pairing (SAP) Algorithm was developed by stage2 to integrate the spatial anatomical relationship between the vertebral body and the intervertebral disc, facilitating the correlation pairing between sagittal and axial images. Stage3 subsequently innovated the multi-view Adaptive Fusion (M²AF) module, which enables adaptive dynamic fusion of anatomical features across views. M²AF enhances the extraction of contextual complementary information, and significantly improves the model's capacity to detect subtle variations in the degree of narrowness. A series of studies show that our model achieves an overall accuracy of 0.8631, AUC of 0.96, and F1-score of 0.8614. These results indicate that our model substantially outperforms mainstream approaches, attaining superior segmentation and grading accuracy, exhibiting robust generalization and clinical application potential.

Introduction Transcranial magnetic stimulation (TMS) is increasingly used in clinical and research settings, often requiring the operator to remain in close proximity to the stimulation coil. While regulatory guidelines exist for patient safety, the workplace exposure assessment, particularly its dependence on operator anatomy, remains limited. This study aimed to comprehensively evaluate the electric field (E-field) induced in TMS operators under realistic working conditions, with a focus on how inter-subject anatomical variability affects compliance with international safety guidelines. Methods Numerical simulations were performed using four anatomically detailed virtual human models exposed to a circular TMS coil in clinically relevant positions. Two coil heights (chest and abdomen) and three coil-to-operator distances (12 cm, 22 cm, 40 cm) were analyzed. The induced E-field was computed using magneto-quasi-static solvers, and the results were compared with the ICNIRP basic restriction for occupational exposure (1.13 V/m) and with the experimental threshold for peripheral neurostimulation (4 V/m). Whole-body percentiles, localized distributions, and anatomical cross-sections were evaluated to characterize inter-subject variability. Results At 40 cm, all models and exposure scenarios were compliant with ICNIRP limits. At 22 cm, most configurations remained compliant, though some models slightly exceeded the reference level, particularly in the abdominal region. At 12 cm, the induced E-field systematically exceeded the occupational limit across all models, while remaining below the neurostimulation threshold. Anatomical features, such as subcutaneous adipose tissue thickness and tissue discontinuities, were found to strongly influence field localization and intensity, especially at closer distances. Conclusion Operator exposure to TMS is influenced by both coil positioning and individual anatomical characteristics. While increasing distance ensures compliance and reduces variability, closer configurations may require tailored assessments or mitigation strategies. These findings highlight the importance of considering inter-subject variability in the evaluation of operator exposure and suggest that anatomical models may underestimate variability in real clinical contexts. A limitation of this study is the assumption of a static operator not manually holding the coil, a common condition in clinical practice that warrants further investigation.

Jaw cysts are a diverse group of intraosseous lesions commonly encountered in oral and maxillofacial pathologies. Several studies have addressed their distribution and clinicopathological features; however, further large-scale analyses using standardized classification systems may enhance cross-regional comparability and diagnostic consistency. We aimed to evaluate the demographic and anatomical characteristics of jaw cysts over an almost 50-year period. We retrospectively reviewed 19,352 histologically confirmed jaw cysts diagnosed between 1975 and 2024. Each case was reclassified according to the 2022 WHO classifications for head and neck tumors. Patient age, sex, cyst type, and anatomical location data were collected and descriptively analyzed to identify trends across different cyst categories. Odontogenic cysts comprised the majority of cases. Radicular cysts were the most common, followed by dentigerous cysts and odontogenic keratocysts. Non-odontogenic cysts mainly consisted of surgical ciliated cysts and nasopalatine duct cysts. Bone cysts (simple bone cysts and aneurysmal bone cysts), which lack an epithelial lining and were therefore analyzed separately, were infrequent. A male predominance was observed overall, with sex- and age-related patterns differing according to cyst type. Mandibular involvement was more common than maxillary involvement, and several cysts showed specific anatomical predilections. These findings highlight distinct demographic and anatomical characteristics across cyst categories. This large retrospective study provides a detailed epidemiological profile of jaw cysts. The findings revealed distinct patterns according to cyst type, age, sex, and anatomical site, providing a valuable reference for diagnostic refinement and future comparative studies of oral and maxillofacial pathology.

Background and Objectives: Atherosclerosis continues to be a major determinant of the global health burden, with ischemic heart disease representing one of the leading causes of morbidity and mortality worldwide. Although cardiovascular (CV) prevention strategies focus on pro-atherogenic lipoproteins, such as LDL-C, non-HDL-C, and apoB, the balance between atherogenic and anti-atherogenic lipoproteins may better reflect the overall atherogenic burden. Apolipoprotein B (apoB) reflects the total number of circulating atherogenic particles, whereas apolipoprotein A-I (apoA) is the main protein component of HDL, the major anti-atherogenic lipoprotein. Integrating these two parameters into the apoB/apoA ratio results in a composite biomarker that reflects this balance. In this study, we aimed to evaluate whether the apoB/apoA ratio can predict the presence and the severity of coronary artery disease (CAD) in a cohort from an Eastern European hospital, under moderate-intensity statin treatment. Additionally, we assessed whether lipoprotein(a) [Lp(a)] provides any additional diagnostic value. Materials and Methods: We consecutively enrolled 121 statin-treated patients, who presented for elective invasive coronary angiography. Patients with history of coronary revascularization or acute coronary syndrome were excluded. The study cohort was further divided into two groups, according to the severity of coronary stenosis: 69 patients with non-significant CAD (N-CAD) and 52 patients with hemodynamically significant CAD (S-CAD). Apolipoprotein B, apolipoprotein A-I, and lipoprotein(a) were measured using a standardized immunoturbidimetric assay, at the moment of enrollment. The severity of coronary stenosis was measured using Quantitative Coronary Analysis (QCA) software and the total coronary atherosclerotic burden of each patient was quantified using the Gensini score. Results: The apoB/apoA ratio was significantly higher in the S-CAD groups, compared with N-CAD patients (0.53 ± 0.16 vs. 0.73 ± 0.18). Furthermore, in the apoB/apoA-based analysis, the Gensini score increased progressively across the three tertiles (8.55 ± 19.60 vs. 14.57 ± 21.65 vs. 29.8 ± 27.78, p = 0.000) and so did the percentage of patients with three-vessel disease (5% vs. 19.5% vs. 32.5%, p = 0.000) and left main disease (5% vs. 7.3% vs. 20%, p = 0.031). The apoB/apoA ratio showed a significant correlation with the severity of CAD, as expressed by the Gensini score (r = 0.513, p &lt; 0.001, 95% CI: 0.357–0.641). The association between apoB/apoA ratio and the presence and severity of CAD expanded beyond group comparison. In the logistic regression, this biomarker proved to be a valuable predictor for S-CAD (per SD increase: OR 2.509, 95% CI: 1.441–4.369, p = 0.001), three-vessel disease (per SD increase: OR 2.339, 95% CI: 1.427–3.892, p = 0.001), and left main disease (per SD increase: OR 2.771, 95% CI: 1.489–5.156, p = 0.001). The apoB/apoA ratio remained significant after adjusting for other CV risk factors and independent to LDL-C, as shown by the analysis that we performed among the lowest LDL-C tertile patients. Participants with S-CAD showed higher concentrations of Lp(a). However, adding this lipoprotein to the multivariate analysis, resulted only in a marginal improvement in the predictive power. Conclusions: The ApoB/apoA ratio emerged as an independent predictor for hemodynamically significant coronary stenosis and for CAD severity. Additionally, higher apoB/apoA values were associated with anatomical high-risk features, such as three-vessel disease or left main disease. In contrast, Lp(a) did not provide a substantial increase in the predictive power of multivariate models in this stable CAD cohort.

Scanning electron microscopy and morphometric analysis of the tongue in four carnivorous fish species-Dusky Grouper (Epinephelus marginatus), John Dory (Zeus faber), Squirrelfish (Sargocentron spinosissimum), and Red Lionfish (Pterois miles).

Cancer-associated thrombosis (CAT) is a major cause of morbidity and mortality in oncology. Female-specific cancers-including breast, ovarian, endometrial, and cervical malignancies-demonstrate distinct thrombotic profiles influenced by hormonal mechanisms, anatomical features, and treatment strategies. This narrative review synthesizes epidemiological evidence, mechanistic pathways, and clinical trial data to characterize CAT risk across these cancer types. Key modulators of thrombosis include hormonal exposures, tumor histology, inflammatory signaling, tissue factor expression, and therapeutic interventions such as surgery, chemotherapy, endocrine therapy, targeted agents, and immunotherapy. Despite growing understanding, current CAT risk prediction models insufficiently reflect the heterogeneity of female cancers and fail to integrate bleeding risks specific to gynecologic disease and treatment. Optimizing CAT prevention and management will require improved risk stratification tools, individualized thromboprophylaxis strategies, and incorporation of survivorship considerations, including fertility and contraception counseling. A multidisciplinary approach involving oncology, gynecology, and thrombosis specialists is essential to reduce the burden of CAT and improve outcomes for women with cancer.

Morphometric dissimilarity in association cortices linked to autism subtype with more severe symptoms.

Development of a simplified scoring system for MRI-detected retropharyngeal lymph node features to optimize AJCC 9th edition N classification in nasopharyngeal carcinoma.

Functional Shape of the Proximal Radioulnar Joint: Anatomical Characterization through Alpha and Beta Angles

Application of anatomical and histological features of testis to age estimation.

Endovascular treatment (EVT) has dramatically improved outcomes of patients suffering from acute ischemic stroke due to large vessel occlusion (LVO), becoming the standard of care. However, up to one-third of ischemic strokes are caused by distal medium vessel occlusions (DMVO), which are beyond the LVO territory. Medical management, including intravenous thrombolysis, leaves more than half of DMVO patients disabled at 3 months, with mortality exceeding 10%. In face of this grim prognosis, expanding EVT to DMVO has gained considerable interest. This review summarizes the clinical, anatomical, and imaging features of DMVO stroke, discusses recent EVT trial results and their interpretation, and outlines future directions for establishing safe and effective reperfusion strategies in this population. Recent randomized trials investigating EVT for DMVO stroke yielded neutral results overall. However, they provided important insights about patient subgroups likely to benefit from intervention and set key challenges to improving the management of patients with DMVO. While current evidence does not support routine EVT for DMVO stroke, the field is evolving rapidly. Ongoing advances in device technology, patient selection, and trial design hold promise for refining treatment and improving outcomes in carefully selected patients.