A deeper knowledge of the effect of wheat origin on the volatile organic compounds (VOCs) profile of craft wheat beer is crucial for its quality improvement and local product valorisation. The VOCs profile of 17 craft wheat beers obtained by common and durum, heritage and modern, wheat varieties grown in different fields sited at different altitudes was analysed. Data were processed by multivariate analysis using different approaches. Partial least square (PLS) analysis evidenced that wheat concentration was the highest source of VOCs variance, followed by, wheat species, wheat ancientness, and altitude of cultivation. An insight into the effect of wheat concentration was given by sparse PLS analysis (sPLS). The effect of wheat variety was explored by linear discriminant analysis (LDA), which permitted to correctly classify craft beers made with wheat of different origin (species and variety) on the basis of their VOCs profile. sPLS regression analysis permitted to find a combination of VOCs able to predict the altitude of wheat cultivation as well as to correctly classify wheat beers made with wheat cultivated at different altitudes. A further \'one versus all\' approach by Soft Independent Modelling of Class Analogies (SIMCA) permitted to correctly authenticate beers made with different cereal species. Finally, shape analysis by generalized Procrustes analysis (GPA) revealed that the differences among samples were conserved and reflected from wheat kernels to wheat beers. This study suggests a promising use of volatiles fingerprinting with a combination of different statistical approaches to authenticate beer made with wheat of different origin and cultivated at different altitudes, thus stressing out the importance of territory in craft beer production, which, until now, was a neglected topic.

Acting as a central hub in regulating brain functions, the thalamus plays a pivotal role in controlling high-order brain functions. Considering the impact of preterm birth on infant brain development, traditional studies focused on the overall development of thalamus other than its subregions. In this study, we compared the volumetric growth and shape development of the thalamic hemispheres between the infants born preterm and full-term (Left volume: P = 0.027, Left normalized volume: P < 0.0001; Right volume: P = 0.070, Right normalized volume: P < 0.0001). The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus exhibit higher vulnerability to alterations induced by preterm birth. The structural covariance (SC) between the thickness of thalamus and insula in preterm infants (Left: corrected P = 0.0091, Right: corrected P = 0.0119) showed significant increase as compared to full-term controls. Current findings suggest that preterm birth affects the development of the thalamus and has differential effects on its subregions. The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus are more susceptible to the impacts of preterm birth.

The vast array of dog breeds showcases a remarkable diversity that extends to osteological differences. Exploring these morphological distinctions and establishing reference data for various dog breeds are essential steps in comprehending the evolutionary changes that dogs have undergone. In this study, we conducted linear measurements of the calcaneus and performed shape analyses on selected dog breeds to elucidate distinctive characteristics among them. X-ray images of the calcaneus from six different dog breeds-Maltese Terrier, Toy Poodle, Pomeranian, Cavalier King Charles Spaniel, French Bulldog and Golden Retriever-were utilized for this investigation. Radiological images were obtained from a medio-lateral exposure, positioned 30 cm away from the x-ray device. From these images, four linear length measurements and two angle values were extracted. Additionally, a 2D geometric morphometric analysis was conducted using 32 semi landmarks placed on the radiological images. Linear measurements were assessed using ANOVA, while principal component analysis was employed to examine shape variations across all individuals. Shape differences between species were further elucidated through canonical variates analysis. The results revealed that the Golden Retriever exhibited the highest values for linear measurements, while the Pomeranian showed the lowest. Maltese Terriers displayed the highest dorsal calcaneal angle value. Notably, there were significant differences in calcaneal body length among all breeds, except for the Toy Poodle and Cavalier King Charles Spaniel. Moreover, Maltese Terriers exhibited statistically distinct angular measurements compared to other breeds. Principal component analysis unveiled that the first principal component explained 32.69% of the total variation, with the cranial edge of the calcaneal body being closer to the body in individuals with higher values. Shape variations also indicated that Golden Retrievers displayed a broader range of shapes compared to French Bulldogs, which exhibited a more conservative distribution. While there was no clear breed-specific distinction according to the first principal component, Cavalier King Charles Spaniels generally showed lower values. In canonical variates analysis, distinctions in calcaneal shape between species were apparent, with Golden Retrievers, Cavalier King Charles Spaniels and French Bulldogs displaying positive values for the first canonical variates. The highest Procrustes distance was observed between Maltese Terriers and Cavalier King Charles Spaniels. Notably, allometry was found to be statistically insignificant. This comprehensive study utilized both linear and geometric morphometric analyses based on x-ray images, yielding promising results. The integration of imaging systems in veterinary anatomy research presents numerous opportunities for studying animal welfare and health, utilizing various materials such as bones and cadavers. These advancements hold the potential for further enhancing our understanding of animal morphology and well-being.

Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multiple independent scans. To accurately segment the hippocampal morphology from longitudinal 3T T1-weighted MR images, we propose a diffeomorphic geodesic guided deep learning method called the GeoLongSeg to mitigate the longitudinal variabilities that unrelated to diseases by enhancing intra-individual morphological consistency. Specifically, we integrate geodesic shape regression, an evolutional model that estimates smooth deformation process of anatomical shapes, into a two-stage segmentation network. We adopt a 3D U-Net in the first-stage network with an enhanced attention mechanism for independent segmentation. Then, a hippocampal shape evolutional trajectory is estimated by geodesic shape regression and fed into the second network to refine the independent segmentation. We verify that GeoLongSeg outperforms other four state-of-the-art segmentation pipelines in longitudinal morphological consistency evaluated by test-retest reliability, variance ratio and atrophy trajectories. When assessing hippocampal atrophy in longitudinal data from the Alzheimer\'s Disease Neuroimaging Initiative (ADNI), results based on GeoLongSeg exhibit spatial and temporal local atrophy in bilateral hippocampi of dementia patients. These features derived from GeoLongSeg segmentation exhibit the greatest discriminatory capability compared to the outcomes of other methods in distinguishing between patients and normal controls. Overall, GeoLongSeg provides an accurate and efficient segmentation network for extracting hippocampal morphology from longitudinal MR images, which assist precise atrophy measurement of the hippocampus in early stage of dementia.

A geometric morphometric analysis was performed on the right wing of adult Calliphora vicina (Robineau-Desvoidy) collected across 4 altitudinal levels in Sicily. The objective of this study was to assess differences in shape and centroid size (CS) between females and males and across elevations. The wings analyzed in this study were removed from adults of C. vicina collected with baited traps at 20, 700, 1,153, and 1,552; for this study, 19 landmarks were identified in each wing. The coordinates of the landmarks were aligned and superimposed to prevent variations due to position, orientation, and scale; they were then scaled to the same CS and recentered. CS and Procrustes differences were, respectively, used to assess variations in size and shape. Significant differences were observed in wing shape between males and females but not between all altitudinal levels. Female wings were found to be significantly larger than males (P < 0.01). Wings of flies collected at the highest altitudinal level resulted in significantly larger wings than those collected at lower altitudes (P < 0.001), with CS values ranging from 12.1 to 14.1. Variation in wing shape can impact thermal regulation, and therefore, oxygen content, temperature, atmospheric pressure, and solar radiation can have an effect on an insect\'s body and activity levels. At high elevations and lower temperatures, larger wings could mean less energy expenditure when flying to increase body temperature.

Analyzing anatomic shapes of tissues and organs is pivotal for accurate disease diagnostics and clinical decision-making. One prominent disease that depends on anatomic shape analysis is osteoarthritis, which affects 30 million Americans. To advance osteoarthritis diagnostics and prognostics, we introduce ShapeMed-Knee, a 3D shape dataset with 9,376 high-resolution, medical-imaging-based 3D shapes of both femur bone and cartilage. Besides data, ShapeMed-Knee includes two benchmarks for assessing reconstruction accuracy and five clinical prediction tasks that assess the utility of learned shape representations. Leveraging ShapeMed-Knee, we develop and evaluate a novel hybrid explicit-implicit neural shape model which achieves up to 40% better reconstruction accuracy than a statistical shape model and implicit neural shape model. Our hybrid models achieve state-of-the-art performance for preserving cartilage biomarkers; they\'re also the first models to successfully predict localized structural features of osteoarthritis, outperforming shape models and convolutional neural networks applied to raw magnetic resonance images and segmentations. The ShapeMed-Knee dataset provides medical evaluations to reconstruct multiple anatomic surfaces and embed meaningful disease-specific information. ShapeMed-Knee reduces barriers to applying 3D modeling in medicine, and our benchmarks highlight that advancements in 3D modeling can enhance the diagnosis and risk stratification for complex diseases. The dataset, code, and benchmarks will be made freely accessible.

BACKGROUND: Craniosynostosis, a congenital condition characterized by the premature fusion of cranial sutures, necessitates objective methods for evaluating cranial morphology to enhance patient treatment. Current subjective assessments often lead to inconsistent outcomes. This study introduces a novel, quantitative approach to classify craniosynostosis and measure its severity.
METHODS: An artificial neural network was trained to classify normocephalic, trigonocephalic, and scaphocephalic head shapes based on a publicly available dataset of synthetic 3D head models. Each 3D model was converted into a low-dimensional shape representation based on the distribution of normal vectors, which served as the input for the neural network, ensuring complete patient anonymity and invariance to geometric size and orientation. Explainable AI methods were utilized to highlight significant features when making predictions. Additionally, the Feature Prominence (FP) score was introduced, a novel metric that captures the prominence of distinct shape characteristics associated with a given class. Its relationship with clinical severity scores was examined using the Spearman Rank Correlation Coefficient.
RESULTS: The final model achieved excellent test accuracy in classifying the different cranial shapes from their low-dimensional representation. Attention maps indicated that the network\'s attention was predominantly directed toward the parietal and temporal regions, as well as toward the region signifying vertex depression in scaphocephaly. In trigonocephaly, features around the temples were most pronounced. The FP score showed a strong positive monotonic relationship with clinical severity scores in both scaphocephalic (ρ = 0.83, p < 0.001) and trigonocephalic (ρ = 0.64, p < 0.001) models. Visual assessments further confirmed that as FP values rose, phenotypic severity became increasingly evident.
CONCLUSIONS: This study presents an innovative and accessible AI-based method for quantifying cranial shape that mitigates the need for adjustments due to age-specific size variations or differences in the spatial orientation of the 3D images, while ensuring complete patient privacy. The proposed FP score strongly correlates with clinical severity scores and has the potential to aid in clinical decision-making and facilitate multi-center collaborations. Future work will focus on validating the model with larger patient datasets and exploring the potential of the FP score for broader applications. The publicly available source code facilitates easy implementation, aiming to advance craniofacial care and research.

The basal nuclei are important during infancy because of the significant development of motor skills. The main aim of this study was to evaluate the shape differences of the lentiform nucleus between different age and gender groups. A total of 126 children\'s axial magnetic resonance image series were included in the presented study. These images were grouped between 1 and 5 yr old. Right and left lentiform nuclei are marked with selected landmarks using TPSDIG v2.04. Statistical shape analyses were examined by a Generalized Procrustes Analysis. Our results showed that there was no statistically significant difference in lentiform nucleus shape between genders. However, there was a difference between the shapes of the right and left lentiform nuclei between the 1-yr and 5-yr age groups. These results demonstrated the shape changes in the lentiform nucleus during the first 5 yr of life. Further clinical studies based on our results may be used to gather more detailed information about movement disorders and neuronal development.

The enduring relationship between humans and domestic sheep has evolved over millennia, showcasing diverse uses such as meat, milk, wool, leather and fur, shaped by geographical, historical, cultural and social factors. The sheep breeds discussed include the Ivesi from Southeastern Anatolia, known for its varied animal products; the resilient Turcana breed of Romania; Kosovo\'s Bardoka, valued for its triple-purpose characteristics; and Poland\'s Polish Mountain Sheep, uniquely utilized for milk production in cheese making. Sheep, with their enduring relationship with humans and significant economic importance, have attracted scientific interest in morphometric studies of their mandibles, yielding valuable data applicable across various fields including basic anatomy, veterinary clinical anatomy, zooarchaeology and veterinary forensic medicine. Traditional morphometric studies rely on statistical methods to compare length, depth and angular ratios between anatomical formations, often highlighting differences between specific points but not fully revealing shape variations between distinct groups. Geometric morphometric analysis has emerged as a preferred method in recent years, enabling shape analyses using coordinate data from various imaging techniques, facilitating a comprehensive examination of mandibular morphometrics among sheep breeds across different countries. This study involved four sheep breeds from different countries, namely İvesi from Turkey, Bardoka from Kosovo, Polish Mountain Sheep from Poland and Turcana from Romania, with a total of 70 mandibles sourced from various veterinary faculties. Mandibular photographs were meticulously captured, focusing on the right side of mandible pairs and placing landmarks and semi-landmarks along the entire edge, enabling geometric morphometric analysis using tpsUtil, tpsDig2 and MorphoJ software. The analysis included principal component analysis, canonical variate analysis and discriminant function analysis for pairwise comparisons, facilitating a comprehensive examination of mandibular shape variations among the different sheep breeds. Using geometric morphometric methods, this study analysed mandibles from four distinct sheep breeds sourced from different countries, revealing notable variations in regions such as the ramus mandibula, angulus mandibula and incisive areas, attributed to genetic, geographical and dietary influences, highlighting the importance of continued research to better comprehend these shape differences.

Dogs are animals with strong bite force. This strong bite mechanism has led to significant changes in the skeletal system such as fossa masseterica. It can be thought that one side is used more than the other side in chewing and is related to the preference of using the same side\'s hand, eye and foot. In the study, directional asymmetry and fluctuating asymmetry, which occurs as a result of chewing asymmetry, were examined on the first molar teeth and the fossa masseterica in 85 dog mandibles including a wide diversity of morphotypes. The association of high PC1 values for directional asymmetry with a pronounced cranial index, as evident in breeds like Pekingese, Pomeranian and Bulldog, indicates a potential evolutionary or selective breeding trend favouring brachycephaly. On the contrary, guardian breeds like the German shepherd and Bernese mountain dog, which typically require strong jaws for their roles, showcased reduced PC1 values, which might be related to their functional morphology. Similarly, the PCA results for the first molar teeth shape variations also highlighted the influence of cranial shape, with boxer dogs displaying notably higher PC1 values. The fluctuating asymmetrical distributions provided valuable insights into individualistic variations. Interestingly, no specific breed distribution trend was observed for these asymmetries, indicating a more individual-based variation rather than breed-based. It is essential to note that while these results provide valuable insights, further studies are required to understand the underlying causes better. Factors like genetic variations, developmental processes, dietary habits and external environmental factors could play pivotal roles in these observed morphological differences.