Procrustes Analysis Research Articles

Palatal canine impaction is associated with craniofacial shape in humans.

It is unclear whether palatal canine impaction is related to genetic or local/environmental factors. If a genetic origin is assumed, then it could be expected that palatal canine impaction is associated with overall craniofacial development. Within this context, the aim of this study was to evaluate the craniofacial morphology of individuals with palatal canine impaction and compare it to a matched group of normal controls. The sample for this investigation comprised 404 individuals (232 females and 172 males). Half of these individuals presented with unilateral or bilateral palatal canine impaction confirmed clinically and radiographically. The other half were matched for sex and age with the first half and comprised individuals without tooth impaction, apart from third molars. The shape of the craniofacial structures was outlined on calibrated cephalometric images through 15 curves and 127 landmarks (11 fixed and 116 semi-landmarks). Shape configurations were superimposed using Procrustes Superimposition and the resulting shape coordinates were reduced into principal components for all subsequent analyses. The effect of palatal canine impaction on craniofacial shape was assessed with regression models, separately in females and males. All statistical tests were performed assuming a type-1 error of 5%. Individuals with palatally impacted canines appear to have a less convex face, a more brachyfacial skeletal pattern, and a sagittally extended premaxilla. In females effect sizes ranged between η2 = 0.136-0.397 (P < 0.05) and in males between η2 = 0.125-0.396 (P < 0.05, apart from the entire craniofacial configuration: P = 0.259). Palatal canine impaction was not confirmed through cone beam computer tomography images in all patients, however, in those cases, the treatment history confirmed the diagnosis. Palatal canine impaction is related to a distinct craniofacial shape in females and males. These findings allow for speculation that palatal canine impaction is affected by genetic pathways involved in overall craniofacial development.

The Correlation Between Static and Dynamic Facial Asymmetry in Unilateral Cleft Lip and Palate.

Assess the relationship between static and dynamic facial asymmetry in unilateral cleft lip and palate during maximum smile. Retrospective cross-sectional study. Multidisciplinary dentofacial planning clinic. Thirty-one surgically managed non-syndromic unilateral cleft lip and palate patients between the ages of 13 to 17 years. Dynamic three-dimensional (3D) facial images (four-dimensional [4D]) throughout the course of a maximum smile were captured using video stereophotogrammetry at a rate of 60 frames per second, which generated 180 3D images/expression. A generic facial mesh containing more than 7000 vertices was superimposed onto the 3D facial images to quantify and track facial asymmetry throughout the captured sequence. Partial ordinary Procrustes analysis was utilized to calculate an asymmetry score at the rest position, maximum smile, and at the point of maximum mathematical asymmetry. The relationships between the asymmetry at rest and the asymmetry at the point of maximum smile (static 3D), and the maximum mathematical asymmetry (dynamic 4D) were evaluated. Asymmetry scores were higher at maximum smile than at rest. Maximum mathematical asymmetry was observed in most cases during the relaxation phase. Static asymmetry at rest and maximum smile was strongly correlated with the maximum mathematical asymmetry (r = 0.941, P < .001). Static 3D asymmetry at both rest and maximum smile are strongly correlated with dynamic 4D facial asymmetry. The use of 4D imaging, combined with generic mesh conformation and dense correspondence analysis, provides a valid objective measure of facial asymmetry.

Comparying two methods of disparity analysis of the anterior portion of m1 in the gray voles (Rodentia, Arvicolini) in a model sample: frequency analysis of morphotypes and geometric morphometrics

An analysis of disparity of the anterior portion of m1 shape in the gray voles in an artificial sample consisting of 5 groups with different frequency distributions of 5 morphotypes was carried out. Two main approaches were applied: (a) traditional analysis of frequency distribution of discrete morphotypes and (b) geometric morphometrics (GM) based on a strictly quantitative description of the shape of anterior portion of m1. The groups were compared quantitatively: Cavalli-Sforz–Edwards’ coefficient was applied in the first case, while the thin plate spline and Procrustes analyses in the second; their results were analyzed using a number of standard statistical methods (dispersion analysis, discriminant analysis, multidimensional scaling). Disparity within the groups was assessed using Shannon entropy index and averaged Procrustes distance. Traditional and GM approaches were shown to provide very similar results, with GM having a number of important advantages by being strictly quantitative. The second approach is recommended as the basic to replace the traditional one for explorations in disparity of tooth crown shape in the voles.

Metagenomic profiling of cecal microbiota and antibiotic resistome in rodents

The rodent gut microbiota is a known reservoir of antimicrobial resistance, yet the distribution of antibiotic resistance genes (ARGs) within rodent cecal microbial communities and the specific bacterial species harboring these ARGs remain largely underexplored. This study employed high-throughput sequencing of 122 samples from five distinct rodent species to comprehensively profile the diversity and distribution of ARGs and to identify the bacterial hosts of these genes. A gene catalog of the rodent cecal microbiome was constructed, comprising 22,757,369 non-redundant genes. Analysis of the microbial composition and diversity revealed that Bacillota and Bacteroidota were the dominant bacterial phyla across different rodent species, with significant variations in species composition among the rodents. In total, 3703 putative antimicrobial resistance protein-coding genes were identified, corresponding to 392 unique ARG types classified into 32 resistance classes. The most enriched ARGs in the rodent cecal microbiome were associated with multidrug resistance, followed by glycopeptide and elfamycin antibiotics. Procrustes analysis demonstrated a correlation between the structure of the microbial community and the resistome. Metagenomic assembly-based host tracking indicated that most ARG-carrying contigs originated from the bacterial family Oscillospiraceae. Additionally, 130 ARGs showed significant correlations with mobile genetic elements. These findings provide new insights into the cecal microbiota and the prevalence of ARGs across five rodent species. Future research on a wider range of wild rodent species carrying ARGs will further elucidate the mechanisms underlying the transmission of antimicrobial resistance.

3D Head Pose Estimation via Normal Maps: A Generalized Solution for Depth Image, Point Cloud, and Mesh

Head pose estimation plays a crucial role in various applications, including human–machine interaction, autonomous driving systems, and 3D reconstruction. Current methods address the problem primarily from a 2D perspective, which limits the efficient utilization of 3D information. Herein, a novel approach, called pose orientation‐aware network (POANet), which leverages normal maps for orientation information embedding, providing abundant and robust head pose information, is introduced. POANet incorporates the axial signal perception module and the rotation matrix perception module, these lightweight modules make the approach achieve state‐of‐the‐art (SOTA) performance with few computational costs. This method can directly analyze various topological 3D data without extensive preprocessing. For depth images, POANet outperforms existing methods on the Biwi Kinect head pose dataset, reducing the mean absolute error (MAE) by ≈30% compared to the SOTA methods. POANet is the first method to perform rigid head registration in a landmark‐free manner. It also incorporates few‐shot learning capabilities and achieves an MAE of about on the Headspace dataset. These features make POANet a superior alternative to traditional generalized Procrustes analysis for mesh data processing, offering enhanced convenience for human phenotype studies.

Shift in potential pathogenic bacteria during permafrost degradation on the Qinghai-Tibet Plateau

Permafrost acts as a potential pathogen reservoir. With accelerating climate change and intensifying permafrost degradation, the release of these pathogens poses significant threats to ecosystems and public health. However, the changes in pathogenic communities during permafrost degradation remain unclear. This study utilized quantitative PCR and Illumina high-throughput sequencing to analyze the composition and quantities of potential pathogenic bacteria in four types of permafrost soil on the northeast edge of the Qinghai-Tibet Plateau (QTP): sub-stable permafrost (SSP), transition permafrost (TP), unstable permafrost (UP), and extremely unstable permafrost (EUP). The results showed that during permafrost degradation, the quantity of potential pathogenic bacteria decreased from 7.8 × 106 to 3.1 × 106 copies/g. Both the Richness and Shannon indices initially declined from SSP, to TP, UP, and then began to rise when permafrost degraded to EUP. A total of 216 potential pathogenic bacterial species were identified, including 166 animal pathogens, 28 zoonotic pathogens, and 22 plant pathogens. The pathogenic community intergroup differences (ANOSIM), unique taxa, and dominant pathogen analysis indicated the significant changes in pathogenic communities during permafrost degradation. The potential pathogenic community was significantly influenced by non-pathogenic bacterial communities (Procrustes analysis), with soil moisture being the primary environmental factor, followed by TDS, soil organic carbon, and total nitrogen. SourceTracker2 analysis indicated that the majority of potential pathogenic bacteria in the soil originated from external sources, only a small portion coming from the permafrost itself. These findings suggest that a large number of pathogens were released into the environment while also preserving amount from external sources. It elucidates that each stage of permafrost degradation presents unique biosecurity risks. This study highlights the release and redistribution of pathogenic bacteria associated with the potential public health risks. It provides the crucial insights into the ecological dynamics of permafrost degradation, emphasizing the need for ongoing monitoring and proactive management strategies.

Dictionary Learning Method Based on K-Sparse Approximation and Orthogonal Procrustes Analysis for Reconstruction in Bioluminescence Tomography.

Bioluminescence tomography (BLT) is one kind of noninvasive optical molecular imaging technology, widely used to study molecular activities and disease progression inside live animals. By combining the optical propagation model and inversion algorithm, BLT enables three-dimensional imaging and quantitative analysis of light sources within organisms. However, challenges like light scattering and absorption in tissues, and the complexity of biological structures, significantly impact the accuracy of BLT reconstructions. Here, we propose a dictionary learning method based on K-sparse approximation and Orthogonal Procrustes analysis (KSAOPA). KSAOPA uses an iterative alternating optimization strategy, enhancing solution sparsity with k-coefficients Lipschitzian mappings for sparsity(K-LIMAPS) in the sparse coding stage, and reducing errors with Orthogonal Procrustes analysis in the dictionary update stage, leading to stable and precise reconstructions. We assessed the method performance through simulations and in vivo experiments, which showed that KSAOPA excels in localization accuracy, morphological recovery, and in vivo applicability compared to other methods.

Dental arch shape in twins: A morphometric study of genetic influences

The objective of this study was to assess the relative contribution of genes to shape variation in the permanent dental arches in individuals of Western European descent. The dental casts from 64 monozygotic and 38 dizygotic twins, housed in the Adelaide Dental School's twin record collection, Australia, were assessed. The subjects were of Western European descent, with a mean age of 19.4 ± 5.4 years. Dental casts were scanned using a 3-dimensional scanner (3Shape E4, 3Shape, Copenhagen, Denmark), and landmarks were placed on incisal edges and cusp tips of canines, premolars, and molars. Procrustes superimposition and principal components analysis were applied to examine shape variation. Two-block partial least-squares analysis was used to assess shape covariation between arches. Structural equation modeling was utilized to decompose observed shape variation into genetic and environmental components using the normal assumptions of the twin model. The first 3 principal components (PCs) of the maxillary and mandibular arch were meaningful, accounting for 53% and 50% of the variation in shape space, respectively. The PCs represented shape variability as follows: PC1 - arch depth-width ratio, PC2 - arch taper, canine position (and first premolar rotation for the mandibular arch), and PC3 - incisor displacement and rotation. Genetic modeling indicated that a model incorporating additive genetic and unique environmental factors optimally explained the observed variation for all meaningful PCs. Within shape space, most of the variation in maxillary and mandibular arches exhibited moderate to high heritability (h2= 0.61-0.74). Maxillary and mandibular dental arches had strong and significant shape covariation, with high heritability in their reciprocal influences on shape (h2= 0.72-0.74; rpls coefficient= 0.87; P<0.05). In this cohort, dental arch shape variation was predominantly influenced by genetic factors. High covariation and heritability were observed between the maxillary and mandibular dental arches. This information may help inform decisions around orthodontic intervention.

A Cephalometric Study Of Vertical Skeletal Changes After Extraction And Non-Extraction Fixed Orthodontic Treatment Of Class I Malocclusion In North Indian Population

Background: Orthodontic treatments frequently involve tooth extractions to address crowding and protrusion, but the effects of these extractions on vertical skeletal changes are still debated. Research has extensively covered aspects like soft tissue response and smile aesthetics, yet there is no consensus on their impact on vertical dimensions. This issue is particularly pertinent for hyperdivergent individuals, who make up about 22% of orthodontic patients. A proposed technique for such cases includes counterclockwise rotation of the lower jaw and advancement of posterior teeth to manage open bites or excessive vertical facial height. This study aims to compare vertical skeletal changes in Class I malocclusion patients undergoing extraction versus non-extraction fixed orthodontic treatments. Material and Methods: We analysed pre- and post-treatment lateral cephalometric radiographs from 60 Class I crowding patients, evenly split into extraction and non-extraction groups. Eight vertical skeletal parameters were assessed and compared statistically between the two groups. Superimposition analysis of radiograph tracings was used to explore vertical changes related to molar mesialization, particularly in the extraction group. Results: The extraction group demonstrated significant reductions in vertical skeletal dimensions compared to the non-extraction group. Measurements including FMA, SN-GoGn, Y-axis, SN-PP, and PP-MP showed significant differences, with reductions in the extraction group (P = 0.001). Procrustes superimposition indicated effective molar mesialization in the extraction group, which was not observed in the non-extraction group. Conclusion: Extraction of first premolars in fixed orthodontic treatment leads to a notable decrease in vertical skeletal dimensions, in contrast to the slight increase seen with non-extraction treatments. This reduction is largely due to molar mesialization, which enhances vertical skeletal dimensions and treatment stability in Class I crowding cases.

Phenotypic divergence of Glossina morsitans (Diptera: Glossinidae) populations in Zambia: Application of landmark-based wing geometric morphometrics to discriminate population-level variation.

An important consequence of the discontinuous distribution of insect populations within their geographic range is phenotypic divergence. Detection of this divergence can be challenging when it occurs through subtle shifts in morphological traits with complex geometries, such as insect wing venation. Here, we used landmark-based wing geometric morphometrics to investigate the population-level phenotypic variation of the two subspecies of Glossina morsitans, G. m. centralis Machado and G. m. morsitans Westwood that occur in Zambia. Twelve homologous landmarks digitised on the right wings of 720 specimens collected from four and five sites (80 per site with 1:1 sex ratio) within the G. m. centralis and G. m. morsitans range respectively, were subjected to generalised Procrustes analysis to obtain wing centroid size (CS) and wing shape variables. Linear permutation models and redundancy analysis were then used to compare CS and wing shape between male and female G. morsitans, the two subspecies G. m. centralis and G. m. morsitans, the sexes of each subspecies and between sample locations within each subspecies range, respectively. Significant differences in CS and wing shape were observed between G. morsitans sexes, subspecies and sample locations within each subspecies range. A neighbour-joining cladogram derived from the analysis of Procrustes distances showed that tsetse within each subspecies range were highly divergent. We conclude that G. morsitans populations in Zambia exhibit significant population-level variation in fly size and wing shape which suggests high levels of population structuring. The main drivers of this structuring could be random genetic drift in G. m. centralis demes and local adaptation to environmental conditions in G. m. morsitans populations. We therefore recommend molecular studies to estimate the levels of gene flow between these populations and identify possible barriers to genetic flow.

Aktivitas Antioksidan dan Profil Sensori Minuman Sari Kacang Merah (Phaseolus vulgaris L.) dengan Penambahan Ekstrak Jahe Merah

The diversification and product development of kidney bean and ginger products have not yet been fully explored, especially in relation to antioxidant activity and sensory profiles. This study aims to evaluate the antioxidant activity, total phenolic compounds (TPC), sensory profile, and consumer acceptance of a kidney bean drink with added red ginger extract. Three variations of the kidney bean drink were tested, each containing different concentrations of red ginger extract: 0, 4, and 8%. Antioxidant activity was measured using the DPPH (2,2-diphenyl-1-picrylhydrazyl) method, while TPC was determined using the Folin Ciocalteu method. Sensory analysis was conducted using the free choice profiling (FCP) method, with results analyzed through generalized procrustes analysis (GPA) to identify the sensory characteristics of the samples. Additionally, a hedonic test was used to assess the level of panelists' preference for each sample. The results showed that the addition of red ginger extract significantly affected (p&lt;0.05) the antioxidant activity, TPC, sensory profile, and consumer acceptance of the kidney bean drink. Antioxidant activity demonstrated a substantial percentage of DPPH inhibition, ranging from 38.01 to 58.00%. TPC content values ranged from 0.91 to 1.80 mg GAE/g. The kidney bean drink exhibited various sensory attributes, including brown color, ginger aroma, caramel aroma, sweet taste, spicy taste, beany taste, liquid mouthfeel, creamy mouthfeel, spicy aftertaste, and beany aftertaste. The hedonic test results showed that panelists' preferences ranged from neutral to somewhat liking, with scores between 4.00 and 5.10.

Gender prediction using geometric morphometry with parameters of the cranium obtained from computed tomography images

Purpose: The gender difference of the cranium skeleton is of great importance in forensic anthropology and forensic medicine sciences. This study is based on this hypothesis and the gender prediction rate was obtained by processing cranium images obtained from computed tomography (CT) using geometric morphometry. Materials and Methods: CT images of 200 individuals between the ages of 25 and 65 were used in our study. The images were opened at the personal workstation Horos Medical Image Viewer (Version 3.0, USA) program and processed with 3D Curved Multiplanar Reconstruction (MPR). The line passing through the nasion and inion points of the images obtained as a result of the process was determined, and all images were brought to the orthogonal plane. Later, the images were overlapped and saved in JPEG format with 100% magnification. JPEG images saved were converted into TPS format, and 21 homologous landmarks were placed. Generalized Procrustes Analysis (GPA) and Principal Component Analysis (PCA) were applied to the coordinates of landmarks, and shape variations and dimensionality were corrected by gathering the images to the center of gravity. Next, Linear Discriminant Analysis (LDA) was applied to the coordinates, the dimensionality of which was corrected. Results: The study found that 74.465% of the coordinates of 21 homologous landmarks gathered to the center of gravity could be explained with the first three PCs. As a result of the LDA applied to these coordinates, a gender prediction rate of 86.5% was obtained. In addition, a slight difference was found between the GPA sum of squares and the tangent sum of squares (0.57). Conclusion: The images of the cranium obtained from CT showed a high dimorphism by geometric morphometry analysis.

Evaluation of age estimation using alveolar bone images

ObjectiveThe purpose of this study is to examine the time-related changes of alveolar bone in 2D images quantitatively and to estimate age groups based on the change index. Materials and methodsThe 238 panoramic X-ray images and 140 CT panoramic reconstructed images of the permanent dentition period were used to examine age-related changes. Comparisons between the younger age group and each of the other age groups were calculated using the landmark method of Procrustes analysis. As aging changes were observed in each age group, age estimation was performed using antemortem panoramic X-ray images and postmortem CT images so that they could be used in practice. The CT images used in the age estimation were performed using forty-two postmortem CT panoramic reconstructed images of known age submitted to the judicial autopsy. ResultsBoth panoramic and CT images showed changes in the alveolar bone over time. Age estimation using postmortem CT images provided a certain assessment. ConclusionIn this study, clinically observed changes in alveolar bone over time were quantified on the images. Furthermore, the possibility of age estimation by alveolar bone was also suggested. The use of an updatable clinical database that can be stored in coordinate values offers the potential for age estimation in line with the times.

Microbial communities and mobile genetic elements determine the variations of antibiotic resistance genes for a continuous year in the urban river deciphered by metagenome assembly

Antibiotic resistance genes (ARGs) have become emerging environmental contaminants influenced by intricate regulatory factors. However, there is a lack of comprehensive studies on the evolution and distribution of ARGs over a full year in urban rivers, which serve as significant reservoirs of ARGs due to dynamic human activities. In this study, we conducted a 12-month metagenomic assembly to explore the microbial communities, ARGs, mobile genetic elements (MGEs) coexisting with ARGs, ARGs hosts, and the impact of environmental factors. Bacitracin (32%–47%) and multidrug (13%–24%) were detected throughout the year, constituting over 60% of the total abundance, making them the primary ARGs types. The assembly mechanisms of microbial communities and ARGs were primarily driven by stochastic processes. Integrase, IntI1, recombinase, and transposase were identified as the main MGEs coexisting with ARGs. Procrustes analysis revealed a significant structural association, indicating that the composition of host communities likely plays crucial roles in the seasonal composition and distribution of ARGs. Human pathogenic bacteria (HPBs) were identified in the summer, autumn, and winter, with Escherichia coli, Klebsiella pneumoniae, Acinetobacter lwoffii, and Burkholderiales bacterium being the primary HPBs. Mantle tests and PLS-PM equation analysis indicated that microbial communities and MGEs are the most critical factors determining the distribution and composition of ARGs in the river. Environmental factors (including water properties and nutrients) and ARGs hosts influence the evolution and abundance of ARGs by directly regulating microbial communities and MGEs. This study provides critical insights into risk assessment and management of ARGs in urban rivers.

Antarctic lake viromes reveal potential virus associated influences on nutrient cycling in ice-covered lakes.

The McMurdo Dry Valleys (MDVs) of Antarctica are a mosaic of extreme habitats which are dominated by microbial life. The MDVs include glacial melt holes, streams, lakes, and soils, which are interconnected through the transfer of energy and flux of inorganic and organic material via wind and hydrology. For the first time, we provide new data on the viral community structure and function in the MDVs through metagenomics of the planktonic and benthic mat communities of Lakes Bonney and Fryxell. Viral taxonomic diversity was compared across lakes and ecological function was investigated by characterizing auxiliary metabolic genes (AMGs) and predicting viral hosts. Our data suggest that viral communities differed between the lakes and among sites: these differences were connected to microbial host communities. AMGs were associated with the potential augmentation of multiple biogeochemical processes in host, most notably with phosphorus acquisition, organic nitrogen acquisition, sulfur oxidation, and photosynthesis. Viral genome abundances containing AMGs differed between the lakes and microbial mats, indicating site specialization. Using procrustes analysis, we also identified significant coupling between viral and bacterial communities (p = 0.001). Finally, host predictions indicate viral host preference among the assembled viromes. Collectively, our data show that: (i) viruses are uniquely distributed through the McMurdo Dry Valley lakes, (ii) their AMGs can contribute to overcoming host nutrient limitation and, (iii) viral and bacterial MDV communities are tightly coupled.

Predicting cognitive load with EEG using Riemannian geometry-based features

Objective. We show that electroencephalography (EEG)-based cognitive load (CL) prediction using Riemannian geometry features outperforms existing models. The performance is estimated using Riemannian Procrustes Analysis (RPA) with a test set of subjects unseen during training.Approach. Performance is evaluated by using the Minimum Distance to Riemannian Mean model trained on CL classification. The baseline performance is established using spatial covariance matrices of the signal as features. Various novel features are explored and analyzed in depth, including spatial covariance and correlation matrices computed on the EEG signal and its first-order derivative. Furthermore, each RPA step effect on the performance is investigated, and the generalization performance of RPA is compared against a few different generalization methods.Main results. Performances are greatly improved by using the spatial covariance matrix of the first-order derivative of the signal as features. Furthermore, this work highlights both the importance and efficiency of RPA for CL prediction: it achieves good generalizability with little amounts of calibration data and largely outperforms all the comparison methods.Significance. CL prediction using RPA for generalizability across subjects is an approach worth exploring further, especially for real-world applications where calibration time is limited. Furthermore, the feature exploration uncovers new, promising features that can be used and further experimented within any Riemannian geometry setting.

Comparison of the reverse scan technique with an intraoral scanner and the traditional impression technique

Intraoral scanners have many advantages but have limited applicability for extensive tooth-supported or implant-supported prostheses because of merging errors. The purpose of this study was to compare the reverse scan technique (RST) with an intraoral scanner using the traditional impression technique both in vitro and in vivo. A participant was scanned 10 times with an intraoral scanner. Then, the RST was performed 3 times in the oral cavity. One of the intraoral scans was chosen to make a 3-dimensionally (3D) printed cast. The printed cast was scanned 10 times with a laboratory scanner (Control cast) and 10 times with an intraoral scanner (IOS cast). The RST was performed 10 times (RST cast), and 10 dental impressions were made using the traditional splinted technique on the same cast (Impression cast). A laboratory scanner was used to obtain standard tessellation language (STL) files of the tested methods. A newly developed pyramid replacement method was used to evaluate accuracy. This method uses modified virtual abutments with integrated pyramids that determine the exact measurement points. The obtained data were processed using Procrustes analysis and statistically analyzed (α=.05). The Procrustes distances were Control cast 0 to 0.4µm (median 0.3µm), RST cast 5.6 to 6.9µm (median 6.2µm), Impression cast 5.4 to 7.1µm (median 6.5µm), and IOS cast group 4.5 to 41.2µm (median 5.8µm). In the participant, the Procrustes distance values were RST intraoral 9.5 to 9.6µm (median 9.5µm) and IOS intraoral 5.7 to 18.3µm (median 10.9µm). The reverse scan technique is an acceptable fully digital replacement for traditional impression making. Using an IOS to obtain a 3D cast of an implant-supported interim prosthesis with scannable implant analogs is not recommended. It is more beneficial to use laboratory scanners rather than intraoral scanners for the digitization of precision improvement devices such as bonded interim implant-supported prostheses with a scannable implant analog or solid index.

Improved diffusion mapping combined with procrustes analysis for capturing local-global data structures in industrial process monitoring

BackgroundProcess monitoring, by providing early warnings of abnormal operating states resulting from process faults, facilitates the maintenance of normal production and ensures process safety. In the domain of industrial process monitoring, capturing the local-global structural features of data and acquiring an explicit mapping relationship for dimensionality reduction projection holds significant importance for online fault detection in industrial processes. MethodsThis study introduces an Improved Diffusion Mapping and Procrustes analysis (IDM-P) method for this purpose. Initially, considering the multiscale and correlation among industrial data features, the Mahalanobis distance is incorporated to improve the diffusion mapping algorithm. Utilizing this method allows for the concurrent capture of both local and global data structures, leading to a more efficient extraction of data-representative features, which enhances the accuracy of fault detection. Procrustes analysis is then used to obtain an explicit mapping matrix between high-dimensional data and low-dimensional manifolds, improving the efficiency of the key feature extraction of the new samples. Finally, this matrix is utilized to construct process monitoring statistics for fault detection. Significant FindingsThe method's effectiveness was validated through experiments on the TEP dataset and actual industrial data, demonstrating that IDM-P maintains higher accuracy and achieves optimal fault detection compared to other methods.

Metagenomic insights into resistome, mobilome and virulome in different fecal waste

Fecal waste is a significant source of antimicrobial resistance (AMR) pollution and provides valuable insights into the AMR development in animal and human populations within the “One health” framework. Various genetic elements, including antibiotic resistance genes (ARGs), biocide and metal resistance genes (BMGs), mobile genetic elements (MGEs), and virulence factor genes (VFGs), are crucial AMR risk determinants (ARDs). However, few studies focused on compositional characteristics of ARDs in different feces. Here, we analyzed 753 public metagenomes from human, pig, chicken, and cattle feces, revealing significant differences in ARD richness and abundance across fecal types, notably lowest in cattle samples. Tetracycline, multi-metal, and -biocide resistance genes were dominant resistome. A few core genes contributed to 25.6%–91.1% of gene abundance, and their correlations were stronger in cattle samples. Procrustes analysis showed that microbial composition had higher correlations with ARGs (M2 = 0.579) and BMGs (M2 = 0.519). Gammaproteobacteria was identified as major ARD-hosts especially in human and pig feces, and they mainly carried multi-resistance genes. MGEs exhibited direct positive effects on ARGs and BMGs, indirectly impacting VFGs. Utilizing random forest methods, we identified 42 indicator genes for tracking AMR pollution originating from fecal sources in the environments. This study offers new insights into understanding and controlling the AMR pollution of fecal waste from human and food animals.

Characterizing prostate zonal shape changes associated with 5α-reductase inhibitors using MRI.

Benign prostatic hyperplasia (BPH) is a prevalent medical disorder that primarily affects elderly males. It is distinguished by enhanced angiogenesis of the prostate, aggravating lower urinary tract symptoms (LUTS) and diminishing overall quality of life. Dutasteride, a 5α-reductase inhibitor, has emerged as a significant therapeutic choice for BPH owing to its efficacy in reducing prostate volume. The objective of this study is to analyze alterations in the shapes of prostate zones resulting from dutasteride treatment of BPH, using MRI. We examined 19 drug-administered patients and 33 non-drug-administered patients. MRI sections of all participants before and after drug treatment were collected retrospectively. The transition zone and peripheral zone of the prostate were marked with selected landmarks using TPSDIG v2.04. Generalized Procrustes Analysis was used to analyze shapes statistically. Our results showed that the 5α-reductase inhibitor significantly altered the shape of the transition zone by narrowing its posterior part. There were significant statistical differences between the drug-administered and non-drug-administered groups in the initial and final shapes of the transition zone. These findings indicate that the use of 5α-reductase inhibitors yielded favorable outcomes in terms of prostate size reduction and amelioration of symptoms associated with BPH.