Variation In Shape Research Articles

Phenotypic variation among four Lake Trout morphs at six locations in Lake Superior

ABSTRACT Objective The Lake Trout Salvelinus namaycush diversified into multiple morphs in many lakes of northern North America. Four morphs remain in Lake Superior, of many forms that arose since the most recent glaciation of North America. Our objective was to determine if Lake Trout phenotypic diversity was greater within or among four morphs at six geographically distant locations in Lake Superior. Methods Lake Trout were sampled using standardized multi-mesh gill nets in three depth strata at six locations in Lake Superior that were known to have multiple morphs and were assigned to one of four morphs by reconciling statistical (geometric morphometric analysis of head and body shape) and visual (agreement among three experts) assignment rules. The relative importance of morphs, locations, the interaction between morphs and locations, and residual error for describing variation in head and body shape and associated linear traits were compared. Results The same four morphs were present at nearly all locations. Variation in head and body shape, and associated linear characteristics (head depth, preorbital length, body depth, caudal peduncle length, and caudal peduncle depth), was greater among morphs than among locations. This finding supports a hypothesis that Lake Trout morphs were consistent in shape and related linear traits across a large spatial scale within an environmentally diverse large lake, thereby possibly reflecting genetic differences among morphs. In contrast, variation in linear dimensions describing fin lengths, maxillary length, and other linear segments of head and body length was greater among locations than among morphs. This finding suggests that expressions of these morphometric measures was influenced by location-specific abiotic and biotic conditions. Conclusions We conclude that Lake Trout morphs appeared to have a genetic component to their head and body shape and some other linear morphometric characteristics that was differentially expressed in relation to local environmental conditions.

Enhancing pancreatic cancer treatment: the role of H101 oncolytic virus in irreversible electroporation

BackgroundIrreversible Electroporation (IRE) offers a promising treatment for pancreatic cancer by using high-voltage pulses to kill tumor cells. But variations in tumor size and shape can lead to uneven electric fields, causing some cells to undergo only reversible electroporation (RE) and survive. However, RE can temporarily increase the permeability of the cell membrane, allowing small molecules to enter. H101 virus is an oncolytic adenovirus with deleted E1B-55kD and E3 regions that selectively targets and kills tumor cells. This study aimed to investigate whether the H101 oncolytic virus can serve as a supplementary therapeutic approach to kill tumors combined with RE.MethodsWe first explored how RE and the H101 oncolytic virus, both individually and together, affected tumor cell proliferation and migration in cellular experiments. Subsequent in vitro studies further assessed the effects of different treatments on tumor growth. To understand the mechanisms of pathway changes in tumors from different treatment groups, we analyzed tumor samples from each group using bulk RNA sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq). Additional biochemical techniques were used to validate key molecular changes.ResultsThe combination of RE with the H101 oncolytic virus effectively inhibited pancreatic cancer cell proliferation and migration. Experiments using mouse subcutaneous tumor models confirmed that the combination therapy significantly reduced tumor growth. Further analysis bulk RNA-seq and scRNA-seq revealed that this combined approach activates the JNK-MAPK pathway, inducing apoptosis and enhancing therapeutic effects.ConclusionsThis combination boosts therapeutic effectiveness by activating the JNK-MAPK pathway and promoting tumor cell apoptosis. These findings suggest that the H101 oncolytic virus could serve as a valuable adjunct to improve the efficacy of IRE treatment.

The final cut: how giant viruses of protists are released from their hosts' cells.

Viruses are the most abundant biological entities on Earth, with an estimated 1031 viruses in the biosphere. These particles serve as the crucial link between viral replication cycles in different host cells, employing a variety of release mechanisms, such as cell lysis, exocytosis, and budding. Among the diverse viral groups, giant viruses have garnered significant scientific interest due to their complex particles and genomes. Giant viruses may infect amoebae and other unicellular protists, exhibiting remarkable variation in size, shape, and symmetry. They belong to the realm Varidnaviria, kingdom Bamfordvirae, and phylum Nucleocytoviricota. This review examines the diverse viral release strategies employed by giant viruses, highlighting the mechanisms they use to exit host cells. These include the induction of cell lysis, vesicle formation, and exocytosis, which vary not only between different species but also within individual viral groups. The diversity of release mechanisms reflects the complex evolutionary adaptations of giant viruses, providing information about their biology and life cycles.

Intrapopulational variation in head shape correlates with soil structure heterogeneity in a head‐first burrowing amphisbaenian, Trogonophis wiegmanni

Intrapopulational variation in head shape correlates with soil structure heterogeneity in a head‐first burrowing amphisbaenian, <i>Trogonophis wiegmanni</i>

Dynamic Frequency-Decoupled Refinement Network for Polyp Segmentation

Polyp segmentation is crucial for early colorectal cancer detection, but accurately delineating polyps is challenging due to their variations in size, shape, and texture and low contrast with surrounding tissues. Existing methods often rely solely on spatial-domain processing, which struggles to separate high-frequency features (edges, textures) from low-frequency ones (global structures), leading to suboptimal segmentation performance. We propose the Dynamic Frequency-Decoupled Refinement Network (DFDRNet), a novel segmentation framework that integrates frequency-domain and spatial-domain processing. DFDRNet introduces the Frequency Adaptive Decoupling (FAD) module, which dynamically separates high- and low-frequency components, and the Frequency Adaptive Refinement (FAR) module, which refines these components before fusing them with spatial features to enhance segmentation accuracy. Embedded within a U-shaped encoder–decoder framework, DFDRNet achieves state-of-the-art performance across three benchmark datasets, demonstrating superior robustness and efficiency. Our extensive evaluations and ablation studies confirm the effectiveness of DFDRNet in balancing segmentation accuracy with computational efficiency.

Differences in Pelvic Muscular Shape and Thickness in Women With and Without Significant Bladder Descent.

Pelvic organ prolapse (POP) is the descent of pelvic organs, causing patient discomfort. Despite its increasing prevalence, agreement in the field as to the cause is elusive. Weakness in pelvic floor muscles is implicated, but specific structural changes remain unclear. This study aimed to identify such differences in the levator ani, hypothesizing differences in pelvic muscle shape between greater and lesser bladder descent. We reviewed our patient database for cystocele diagnoses via MR defecography, including patients with static axial MRIs and dynamic midsagittal defecography. Patients were divided into two groups based on bladder descent relative to the genital hiatus (a measure our group had previously used). We used a statistical shape model of levator shapes to compare the groups. Additionally, we conducted MRI-based measurements (thickness of the obturator internus and anterior pelvic area) which have previously shown differences in similar groups. Among 67 cystocele patients, 28 had greater bladder descent. The shape model identified significant variation in pelvic floor shape, specifically near the arcus tendineus levator ani (ATLA). The MRI-based measurements showed an increase in anterior pelvic area (53.8 ± 6.0 vs. 58.0 ± 5.3 cm2, p < 0.001) with increased prolapse severity and thinning of obturator's along the ATLA (16.2 ± 2.7 vs. 13.9 ± 2.2mm, p < 0.001), specifically in the region around the insertion of the levators and obturators. Patients with greater bladder descent exhibited a larger anterior pelvic area, thinner obturators, and greater pelvic floor muscle descent, potentially due to muscle detachment at DeLancey's level II support.

Correspondence model-based approach for evaluating static and dynamic joint distance measurements

Evaluations of 3D joint space measurements between study groups have traditionally relied on surface regional divisions, which attenuate the impact of shape on joint measurements. Advancements in morphometric analyses have enabled evaluation of population-based shape variations as they relate to disease progression and deformity. Specifically, correspondence model-based shape analyses offer co-registered landmarks that address shape variability in joint structures and can be utilized for comparison of joint space measurements. This study proposes a method using correspondence models to perform group-wise statistical analyses in static or quasi-static positions during movement, offering a more comprehensive assessment of joint space variability. The primary objective was to verify and validate the measurement methods of a developed open-source toolbox. Testing was performed with surface meshes of varying edge length (0.5-, 1-, and 2-mm) and with different expected joint space distances (1- and 4-mm). Validation testing of accuracy revealed <1% error for 0.5- and 1-mm mesh edge lengths for 4 mm joint space, sensitivity testing demonstrated best results for 0.5 mm edge length, and repeatable/reliable measurements yielded low coefficient of variation and high intraclass correlation coefficient. These findings support the use of correspondence model-based approaches for robust and accurate analysis of joint measurements related to anatomical features. This method addresses limitations in traditional techniques by incorporating shape variability, providing a practical tool for assessing joint-level disease and deformity. Future work will focus on evaluating the application of this approach in diverse clinical scenarios, including highly deformed joint structures.

Investigating opening shape variations and their effect on castellated beam performance

Investigating opening shape variations and their effect on castellated beam performance

SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification

Waste management handles all kinds of waste, including household, industrial, municipal, organic, biomedical, biological, and radioactive wastes. People still face challenges in proper disposal methods for different types of waste, including landfill-bound items, recyclable materials, and biodegradable waste. Inadequate waste management poses a significant and multifaceted global challenge. The conventional method of segregating waste is a time-consuming and ineffective method that wastes human power and money. To address this issue in real time, sophisticated and sustainable waste management systems need to be implemented. The latest advancements in computer vision and deep learning offer efficient solutions for effective recycling and waste management. Existing deep learning models exhibited various limitations, such as detection accuracy and computational inefficiency, particularly when dealing with objects of varying sizes and exhibiting high degrees of visual similarity. These limitations generate various challenges in effectively capturing and representing the nuanced features of visually similar objects. To address this problem, we proposed the stacking of an enhanced Swin Transformer, improved ConvNeXt, and a spatial attention mechanism. The enhanced Swin transformers incorporate two key components- hierarchical feature extraction and shifting window mechanism to extract the global features from the garbage images effectively. The shifting window mechanism extracts the most important features from various regions of the images to identify the objects. In contrast, the hierarchical feature extraction captures long-range dependencies within the image to effectively identify different types of garbage. The improved ConvNext block with optimized parameterization extracts the local features of the image. This enhanced feature extraction capability enables the model to effectively discern fine-grained details of individual garbage particles, such as shape, texture, and subtle variations in color and appearance, leading to more accurate classification results. When we evaluated the performance of the proposed model using the publicly available Garbage Classification dataset, it attained 98.97% accuracy, 98.42% Precision, and 98.61% Recall. Due to its lightweight and low computational time and power, the proposed model surpasses the existing state-of-the-art deep learning models.

Unveiling Nature's Architecture: Geometric Morphometrics as an Analytical Tool in Plant Biology.

Geometric morphometrics (GMM) is an advanced morphometric method enabling quantitative analysis of shape and size variations in biological structures. Through high-resolution imaging and mathematical algorithms, GMM provides valuable insights into taxonomy, ecology, and evolution, making it increasingly relevant in plant science. This review synthesizes the existing literature and explores methodological details, research questions, and future directions, establishing a strong foundation for further study in plant biology. Following PRISMA 2020 guidelines, a rigorous literature search finally identified 83 studies for review. The review organized data on plant species, organs studied, GMM objectives, and methodological aspects, such as imaging and landmark positioning. Leaf and flower structures emerged as the most frequently analyzed organs, primarily in studies of shape variations. This review assesses the use of GMM in plant sciences, identifying knowledge gaps and inconsistencies, and suggesting areas for future research. By highlighting unaddressed topics and emerging trends, the review aims to guide researchers towards methodological challenges and innovations necessary for advancing the field.

A Comprehensive Morphological, Biochemical, and Sensory Study of Traditional and Modern Apple Cultivars

Apples (Malus domestica Borkh.) represent one of the most widely cultivated and consumed fruits globally, with significant genetic diversity among cultivars. This study aimed to evaluate the morphological, biochemical, and organoleptic characteristics of 34 apple cultivars, including ancient Romanian varieties, internationally old and modern cultivars, and new selections. The assessment was conducted to identify valuable traits for breeding programs and commercial applications. Morphological analysis revealed significant variation in fruit size, shape, and weight, with international ‘classic’ cultivars exhibiting larger dimensions on average. Biochemical profiling indicated notable differences in moisture content, total soluble solids, titratable acidity, and carotenoid levels, with some traditional cultivars demonstrating high nutritional potential. Texture analysis showed variations in peel hardness, flesh firmness, and toughness, influencing storage capacity and consumer preference. Organoleptic evaluations highlighted the superior sensory attributes of cultivars such as ‘Golden Orange’, ‘Jonathan’, ‘Kaltherer Böhmer’, and ‘Golden Delicious’, which ranked highest in terms of taste, aroma, and juiciness. Statistical analyses, including principal component and hierarchical clustering analyses, further distinguished cultivars based on their physicochemical and sensory profiles. The findings emphasize the importance of genetic diversity in apples in maintaining a resilient and sustainable assortment. This study provides valuable insights for breeding programs and for orchard, market, and apple industry development. We also highlight future directions, promoting the conservation and strategic use of both traditional and modern cultivars.

Complex and Dynamic Gene-by-Age and Gene-by-Environment Interactions Underlie Functional Morphological Variation in Adaptive Divergence in Arctic Charr (Salvelinus alpinus).

The evolution of adaptive phenotypic divergence requires heritable genetic variation. However, it is underappreciated that trait heritability is molded by developmental processes interacting with the environment. We hypothesized that the genetic architecture of divergent functional traits was dependent on age and foraging environment. Thus, we induced plasticity in full-sib families of Arctic charr (Salvelinus alpinus) morphs from two Icelandic lakes by mimicking prey variation in the wild. We characterized variation in body shape and size at two ages and investigated their genetic architecture with quantitative trait locus (QTL) analysis. Age had a greater effect on body shape than diet in most families, suggesting that development strongly influences phenotypic variation available for selection. Consistent with our hypothesis, multiple QTL were detected for all traits and their location depended on age and diet. Many of the genome-wide QTL were located within a subset of duplicated chromosomal regions suggesting that ancestral whole genome duplication events have played a role in the genetic control of functional morphological variation in the species. Moreover, the detection of two body shape QTL after controlling for the effects of age provides additional evidence for genetic variation in the plastic response of morphological traits to environmental variation. Thus, functional morphological traits involved in phenotypic divergence are molded by complex genetic interactions with development and environment.

Betta fish species classification using light weight deep learning algorithm

Betta fish sellers and breeders often face challenges in accurately identifying Betta fish species due to variations in colors, patterns, and shapes, leading to potential financial losses and deceptive transactions. To address this issue, we developed a mobile application that employs MobileNet, a deep learning (DL) technique, to classify Betta fish species. The dataset, acquired from online stores, comprises 400 images, with 100 images representing each of the four studied Betta fish species: comb tail, delta tail, spade tail, and veil tail. Prior to model implementation, the dataset undergoes pre-processing with data augmentation techniques, including rotation, shear, zoom-in, horizontal flip, and brightness adjustments, enhancing the model performance. Training utilizes 80% of the data, with the remaining 20% allocated for testing. Three distinct MobileNet models are developed for males, females, and both genders combined, achieving accuracies of 70, 83.75, and 65%, respectively. These trained models are the foundation for a mobile application developed for the Android platform that enables users, particularly Betta fish sellers, and breeders, to efficiently classify Betta fish species, empowering them to set accurate prices based on the identified species.

Modification of Gas Inlet Design in Pyrolysis Reactors by using Computational Fluid Dynamics for the Optimization of Bio-Oil Production from Biomass Waste Mixture

The bio-oil production process from biomass waste can be carried out by using a pyrolysis reactor. Pyrolysis is a thermochemical decomposition process of organic materials through a heating process without oxygen, where the raw material will undergo a chemical structure breakdown into a gas phase. The nitrogen gas is needed to suppress or remove the oxygen during the pyrolysis process. Nitrogen flow in a good biomass pyrolysis reactor needs to pay attention to the speed of nitrogen without ignoring the volume of gas storage. For this reason, one thing that can be studied further is the geometry of the inlet of the biomass pyrolysis device. Inlet geometry can be varied based on several parameters, including variations in inlet shape that can affect flow pressure. Therefore, in this research, calculations will be carried out using computational fluid dynamics to obtain optimal outlet velocity and pressure drop results. The simulation will be carried out using inlet discharge data, namely 1 L/min, 2 L/min and 3 L/min which is converted into inlet velocity data. The results show that the modified inlet gas produces a flow rate with a lower pressure and also spreads the nitrogen gas more evenly inside the reactor compared to the unmodified inlet gas.

Foramina and canals of skull base in Holstein cattle: a computed tomography study.

The aim of this study was to describe the comprehensive morphological and morphometric features of the foramina and canals at the base of the cranial cavity in Holstein cattle using CT images. The study was performed on 14 adult Holstein cow head cadavers. Images taken with MSCT were transferred to the DICOM Viewer program. The MPR and 3D reconstructive tools of the program were used to analyse the foramina and canals. Although they varied in shape and size, foramina and canals were found bilaterally in all animals. It was observed that the orbitorotund foramen, jugular foramen and oval foramen had a canalicular structure, with the distance between the extra-intra cranial openings measured as being 15.0 mm, 5.9 mm and 6.2 mm, respectively. The hypoglossal canal, which was found to be single in 43%, double in 50% and triple in 7% in each body half, was the canal with the most variation in number and shape. The orbitorotund foramen, a canal with an area of 180.6 mm² and a diameter of 18.1 × 12.4 mm, was widest at the skull base, while the optic canal was the narrowest and longest opening with an area of 33.4 mm², a diameter of 8.4 × 5.5 mm, and a length of 17.5 mm. This study shows that our knowledge of skull base morphometry in animals is still extremely limited. Although our study was conducted on a limited number of materials, it could be of benefit to both regional anatomy knowledge in terms of the data presented, and to veterinary anatomists, radiologists and clinicians in terms of methodology.

Micro‐CT Characterization of the Chang'e‐5 Lunar Regolith Samples

AbstractChang'e‐5 (CE‐5) lunar regolith samples were scanned using X‐ray micro‐computed tomography (micro‐CT), and over 0.7 million particles were extracted from the images through machine learning‐based segmentation. This is the largest three‐dimensional (3D) image data set on lunar regolith particles to date, offering a unique opportunity to study the key characteristics of the lunar regolith. The image intensity was correlated with mineral density, allowing for the assessment of the bulk density (1.58 g/cm3), true density (3.17 g/cm3), and mineralogy of the lunar regolith. Glass and plagioclase contributed 45.6 wt.% of the samples, while pyroxene and olivine made up 49.7 wt.%, and ilmenite accounted for 4.7 wt.%. The median grain size of CE‐5 was 57.5 μm, smaller than the Apollo 11, 16 and Luna 16, 20 and 24 samples. Spherical harmonic (SH) analysis and aspect ratio (AR) measurement revealed that the CE‐5 lunar regolith particles have more complex shapes than two common terrestrial soils and exhibit less spherical shapes than Apollo 11, 16 and Luna 16, 20 and 24 samples. We recommend using size and shape characteristics cautiously when inferring the lunar regolith maturity because the intrinsic crystal size of the protolith and complex lunar surface weathering can cause significant size and shape variations. Additionally, characterizing particle shapes requires a large sample size (&gt;1,000) to prevent skewed results from outliers. Our non‐destructive examination method offers a novel and appealing approach for analyzing critical physical, mineralogical, and morphological properties of million‐scale extraterrestrial soil particles, paving the way for future deep space explorations.

Shape and Size Variability of the Gynostemium in Epipactis helleborine (L.) Crantz (Orchidaceae)

Epipactis helleborine (L.) Crantz is considered a challenging and phenotypically difficult species to identify due to its wide range of morphological variability. This variability is mainly observed in the perianth parts but also extends to the gynostemium structure, which has so far been considered one of the most useful diagnostic characteristics. As a result, a simple graphic illustrating the structural pattern of gynostemium morphology has appeared in 10 different forms in available European taxonomic keys, which significantly complicates the identification of this species. A total of 122 flowers of E. helleborine were collected from four natural populations in the Lower Silesia region (Poland) between 2017 and 2019 and analysed for gynostemium morphological variation. Geometric morphometric analyses, including Procrustes ANOVA, PCA, and CVA, were used to examine gynostemium shape, with statistical tests assessing variation in size and stigma inclination angle among populations, individual plants (ramets), and years of research. Statistical analysis revealed significant positive correlations between gynostemium width and height, with significant variation in size and angle of stigma inclination, primarily driven by population, while ramet and year of research had a lesser impact. Geometric morphometric analyses indicated significant population-level variation in gynostemium shape, with principal component analysis identifying the ventral view as the most informative for discriminating these differences. The first two principal components explained the major shape variation, and canonical variate analysis confirmed that this view is most important for species identification.

Does mercury affect morphology, developmental stability and canalization of the skull in the Common wall lizard (Podarcis muralis)?

Does mercury affect morphology, developmental stability and canalization of the skull in the Common wall lizard (Podarcis muralis)?

Skull morphology in native and non-native cattle breeds in Türkiye.

This study aims to investigate morphological differences in the skulls of cattle breeds with different functional roles and geographical origins and to examine skull shape variations among breeds using geometric morphometrics methods. To this end, 95 skulls from Native (Eastern Anatolian Red and Southern Anatolian Red) and Non-native (Holstein and Simmental) breeds raised in Türkiye were analyzed. The results show a significant size difference between Native Breeds and Non-native Breeds, with the Non-native Breeds having larger skulls. The results also indicate considerable shape differences between Native and Non-native Breeds. No significant shape differences were observed between the two Native Breeds, which have shared the same geography for many years. Although no statistically substantial size difference was found between Simmental and Holstein, the nuchal region showed distinct shape differences. The nuchal part of the Simmental skull was more pronounced than other specimens. In native breeds, there was a more balanced proportion between the facial and neurocranial regions compared to the other two breeds. In Holstein skulls, the facial region was more pronounced in comparison to the neurocranial region, while in Simmental skulls, the neurocranial region was more prominent. This study provides valuable insights into the morphological characteristics of different cattle breeds, contributing to veterinary anatomy, biology, and paleontology.

Physical therapy massage robot system with human motion tracking and finger-pressing force control

Massage is a technique that heavily relies on the human senses. The application of massage to the human body is subject to many uncertainties. These include variations in the recipient's body shape and posture, as well as fluctuations in their condition, like movements and changes in stiffness. Three elements are needed to solve this problem: understanding the massage technique, determining the position to touch, and adapting to the recipient's movements during contact. The parameters of massage technique are elucidated by analyzing the massage movements of a therapist. The skeletal points of the recipient are estimated by the RGB-D camera to determine the 3D massage position of the recipient. The force feedback control, focusing on periodic input, adapts to the recipient's periodic body movements. Experiments demonstrated that the system adjusts finger-pressure position and force according to subtle recipient movements and muscle stiffness while lying down. The physical therapy massage robot autonomously massages while adapting flexibly to the recipient's condition, similar to a licensed therapist. The physical therapy massage robot system will contribute to human-robot interaction, such as providing interactive or social touch between humans and robots.