Implication of transcription factor FOXD2 dysfunction in syndromic congenital anomalies of the kidney and urinary tract (CAKUT).

Congenital anomalies of the kidney and urinary tract (CAKUT) are the predominant cause for chronic kidney disease below age 30 years. Many monogenic forms have been discovered due to comprehensive genetic testing like exome sequencing. However, disease-causing variants in known disease-associated genes only explain a proportion of cases. Here, we aim to unravel underlying molecular mechanisms of syndromic CAKUT in three unrelated multiplex families with presumed autosomal recessive inheritance. Exome sequencing in the index individuals revealed three different rare homozygous variants in FOXD2, encoding a transcription factor not previously implicated in CAKUT in humans: a frameshift in the Arabic and a missense variant each in the Turkish and the Israeli family with segregation patterns consistent with autosomal recessive inheritance. CRISPR/Cas9-derived Foxd2 knockout mice presented with a bilateral dilated kidney pelvis accompanied by atrophy of the kidney papilla and mandibular, ophthalmologic, and behavioral anomalies, recapitulating the human phenotype. In a complementary approach to study pathomechanisms of FOXD2-dysfunction-mediated developmental kidney defects, we generated CRISPR/Cas9-mediated knockout of Foxd2 in ureteric bud-induced mouse metanephric mesenchyme cells. Transcriptomic analyses revealed enrichment of numerous differentially expressed genes important for kidney/urogenital development, including Pax2 and Wnt4 as well as gene expression changes indicating a shift toward a stromal cell identity. Histology of Foxd2 knockout mouse kidneys confirmed increased fibrosis. Further, genome-wide association studies suggest that FOXD2 could play a role for maintenance of podocyte integrity during adulthood. Thus, our studies help in genetic diagnostics of monogenic CAKUT and in understanding of monogenic and multifactorial kidney diseases.

Impact of antimicrobial stewardship intervention in clean and clean-contaminated surgical procedures at a Vietnamese national hospital.

OBJECTIVES: We investigated the characteristics of prophylactic antimicrobial use in clean and clean-contaminated surgical procedures and assessed the efficacy of a prophylactic antimicrobial stewardship intervention at Thong Nhat Hospital, Ho Chi Minh City, Vietnam. METHODS: A cross-sectional study was conducted on 354 patients who underwent either clean or clean-contaminated surgical procedures at Thong Nhat Hospital. Eligible patients were classified with respect to three periods of intervention from 2017 to 2020. Data collection included surgical procedures, patient characteristics, and prophylactic antimicrobial usage. We determined the efficacy of antimicrobial stewardship intervention based on comparisons among the primary outcome (the appropriateness of prophylactic antimicrobials) and secondary outcomes (postoperative antimicrobial prophylaxis (AP) prolongation, length of postoperative hospital stay, and cost of antimicrobials). RESULTS: The mean age of patients in periods 1, 2, and 3 was 54.5 ± 16.6, 50.2 ± 16.5, and 52.8 ± 17.3 years, respectively, with an overall male/female ratio of 1.1/1. No significant differences were detected in basic patient characteristics during the three periods. Majority of the surgical procedures were clean (56%-59%) and scheduled (85%-86%). Prophylactic antimicrobial stewardship intervention enhanced AP appropriateness (by 12.7%, 12.7%, and 39.0% in periods 1, 2, and 3, respectively, p < 0.001), decreased postoperative prophylactic antimicrobial duration [3.0 (0-6), 1.5 (0-5), and 0.0 (0-1) days, respectively, p < 0.001], and reduced average antimicrobial expenses (p < 0.001). CONCLUSIONS: The prophylactic antimicrobial stewardship interventions introduced at Thong Nhat Hospital had several positive impacts on the appropriateness of prophylactic antimicrobial use and treatment costs.

Missense mutations in the WD40 domain of AHI1 cause non-syndromic retinitis pigmentosa.

BACKGROUND: Recent findings suggesting that Abelson helper integration site 1 (AHI1) is involved in non-syndromic retinal disease have been debated, as the functional significance of identified missense variants was uncertain. We assessed whether AHI1 variants cause non-syndromic retinitis pigmentosa (RP). METHODS: Exome sequencing was performed in three probands with RP. The effects of the identified missense variants in AHI1 were predicted by three-dimensional structure homology modelling. Ciliary parameters were evaluated in patient's fibroblasts, and recombinant mutant proteins were expressed in ciliated retinal pigmented epithelium cells. RESULTS: In the three patients with RP, three sets of compound heterozygous variants were detected in AHI1 (c.2174G>A; p.Trp725* and c.2258A>T; p.Asp753Val, c.660delC; p.Ser221Glnfs*10 and c.2090C>T; p.Pro697Leu, c.2087A>G; p.His696Arg and c.2429C>T; p.Pro810Leu). All four missense variants were present in the conserved WD40 domain of Jouberin, the ciliary protein encoded by AHI1, with variable predicted implications for the domain structure. No significant changes in the percentage of ciliated cells, nor in cilium length or intraflagellar transport were detected. However, expression of mutant recombinant Jouberin in ciliated cells showed a significantly decreased enrichment at the ciliary base. CONCLUSIONS: This report confirms that mutations in AHI1 can underlie autosomal recessive RP. Moreover, it structurally and functionally validates the effect of the RP-associated AHI1 variants on protein function, thus proposing a new genotype-phenotype correlation for AHI1 mutation associated retinal ciliopathies.

Spata7 is a retinal ciliopathy gene critical for correct RPGRIP1 localization and protein trafficking in the retina.

Leber congenital amaurosis (LCA) and juvenile retinitis pigmentosa (RP) are severe hereditary diseases that causes visual impairment in infants and children. SPATA7 has recently been identified as the LCA3 and juvenile RP gene in humans, whose function in the retina remains elusive. Here, we show that SPATA7 localizes at the primary cilium of cells and at the connecting cilium (CC) of photoreceptor cells, indicating that SPATA7 is a ciliary protein. In addition, SPATA7 directly interacts with the retinitis pigmentosa GTPase regulator interacting protein 1 (RPGRIP1), a key connecting cilium protein that has also been linked to LCA. In the retina of Spata7 null mutant mice, a substantial reduction of RPGRIP1 levels at the CC of photoreceptor cells is observed, suggesting that SPATA7 is required for the stable assembly and localization of the ciliary RPGRIP1 protein complex. Furthermore, our results pinpoint a role of this complex in protein trafficking across the CC to the outer segments, as we identified that rhodopsin accumulates in the inner segments and around the nucleus of photoreceptors. This accumulation then likely triggers the apoptosis of rod photoreceptors that was observed. Loss of Spata7 function in mice indeed results in a juvenile RP-like phenotype, characterized by progressive degeneration of photoreceptor cells and a strongly decreased light response. Together, these results indicate that SPATA7 functions as a key member of a retinal ciliopathy-associated protein complex, and that apoptosis of rod photoreceptor cells triggered by protein mislocalization is likely the mechanism of disease progression in LCA3/ juvenile RP patients.

Exploring the Mechanism of Subjective Social Status on Compulsive Shopping Behavior: A Moderated Mediation Model of Self-compassion and Depression.

The present study aimed to explore the mediating role of depression in the relationship between subjective social status (SSS) and compulsive shopping behavior (CSB) and whether self-compassion (SC) played a moderating role in this model. The study was designed based on the cross-sectional method. The final sample includes 664 Vietnamese adults (Mage = 21.95, SD = 5.681 years). Participants completed an online survey, including questionnaires about SSS, CSB, depression, SC, and basic demographic information. First, the study results showed that SSS did not directly affect CSB (p > .05, 95% CI includes zero). Second, a mediating role of depression and a moderating role of SC in the research model was discovered (p < .001, 95% CI does not contain zero). Results indicated that individuals with a higher SSS experienced lower depression. Moreover, during a depressive episode, having a higher level of SC increases CSB. The study highlighted meaningful recommendations to promote consumers' mental health and healthy shopping behaviors.

Single-cell RNA sequencing analysis identifies one subpopulation of endothelial cells that proliferates and another that undergoes the endothelial-mesenchymal transition in regenerating pig hearts.

Background: In our previous work, we demonstrated that when newborn pigs undergo apical resection (AR) on postnatal day 1 (P1), the animals' hearts were completely recover from a myocardial infarction (MI) that occurs on postnatal day 28 (P28); single-nucleus RNA sequencing (snRNAseq) data suggested that this recovery was achieved by regeneration of pig cardiomyocyte subpopulations in response to MI. However, coronary vasculature also has a key role in promoting cardiac repair. Method: Thus, in this report, we used autoencoder algorithms to analyze snRNAseq data from endothelial cells (ECs) in the hearts of the same animals. Main results: Our results identified five EC clusters, three composed of vascular ECs (VEC1-3) and two containing lymphatic ECs (LEC1-2). Cells from VEC1 expressed elevated levels of each of five cell-cyclespecific markers (Aurora Kinase B [AURKB], Marker of Proliferation Ki-67 [MKI67], Inner Centromere Protein [INCENP], Survivin [BIRC5], and Borealin [CDCA8]), as well as a number of transcription factors that promote EC proliferation, while (VEC3 was enriched for genes that regulate intercellular junctions, participate in transforming growth factor ß (TGFß), bone morphogenic protein (BMP) signaling, and promote the endothelial mesenchymal transition (EndMT). The remaining VEC2 did not appear to participate directly in the angiogenic response to MI, but trajectory analyses indicated that it may serve as a reservoir for the generation of VEC1 and VEC3 ECs in response to MI. Notably, only the VEC3 cluster was more populous in regenerating (i.e., ARP1MIP28) than non-regenerating (i.e., MIP28) hearts during the 1-week period after MI induction, which suggests that further investigation of the VEC3 cluster could identify new targets for improving myocardial recovery after MI. Histological analysis of KI67 and EndMT marker PDGFRA demonstrated that while the expression of proliferation of endothelial cells was not significantly different, expression of EndMT markers was significantly higher among endothelial cells of ARP1MIP28 hearts compared to MIP28 hearts, which were consistent with snRNAseq analysis of clusters VEC1 and VEC3. Furthermore, upregulated secrete genes by VEC3 may promote cardiomyocyte proliferation via the Pi3k-Akt and ERBB signaling pathways, which directly contribute to cardiac muscle regeneration. Conclusion: In regenerative heart, endothelial cells may express EndMT markers, and this process could contribute to regeneration via a endothelial-cardiomyocyte crosstalk that supports cardiomyocyte proliferation.

Implication of FOXD2 dysfunction in syndromic congenital anomalies of the kidney and urinary tract (CAKUT).

Background: Congenital anomalies of the kidney and urinary tract (CAKUT) are the predominant cause for chronic kidney disease below 30 years of age. Many monogenic forms have been discovered mainly due to comprehensive genetic testing like exome sequencing (ES). However, disease-causing variants in known disease-associated genes still only explain a proportion of cases. Aim of this study was to unravel the underlying molecular mechanism of syndromic CAKUT in two multiplex families with presumed autosomal recessive inheritance. Methods and Results: ES in the index individuals revealed two different rare homozygous variants in FOXD2, a transcription factor not previously implicated in CAKUT in humans: a frameshift in family 1 and a missense variant in family 2 with family segregation patterns consistent with autosomal-recessive inheritance. CRISPR/Cas9-derived Foxd2 knock-out (KO) mice presented with bilateral dilated renal pelvis accompanied by renal papilla atrophy while extrarenal features included mandibular, ophthalmologic, and behavioral anomalies, recapitulating the phenotype of humans with FOXD2 dysfunction. To study the pathomechanism of FOXD2-dysfunction-mediated developmental renal defects, in a complementary approach, we generated CRISPR/Cas9-mediated KO of Foxd2 in ureteric-bud-induced mouse metanephric mesenchyme cells. Transcriptomic analyses revealed enrichment of numerous differentially expressed genes important in renal/urogenital development, including Pax2 and Wnt4 as well as gene expression changes indicating a cell identity shift towards a stromal cell identity. Histology of Foxd2 KO mouse kidneys confirmed increased fibrosis. Further, GWAS data (genome-wide association studies) suggests that FOXD2 could play a role for maintenance of podocyte integrity during adulthood. Conclusions: In summary, our data implicate that FOXD2 dysfunction is a very rare cause of autosomal recessive syndromic CAKUT and suggest disturbances of the PAX2-WNT4 cell signaling axis contribute to this phenotype.

Investigating Stable and Dynamic Aspects of the Vietnamese Self-Compassion Scale using Generalisability Theory.

Objectives: Evaluating comprehensive reliability of the Vietnamese Self-Compassion Scale (VSCS) and its ability to distinguish between trait (stable) vs state (dynamic) aspects of self-compassion using Generalisability Theory (G-Theory) is necessary. This investigation contributes to both reliability and validity of research that uses the VSCS to measure self-compassion in Vietnamese adults. Methods: In a sample of 155 Vietnamese adults who completed the VSCS at three occasions that were each 2 weeks apart, a G-study was conducted to measure reliability and trait vs state aspects of each VSCS subscale and the short-form VSCS, and a D-study was conducted to examine the effects of removing subscales on overall scale reliability as well as evaluate trait vs state aspects of each item. Results: With G-coefficients of 0.93-0.98, both the complete and short-form VSCS (VSCS-SF) demonstrated excellent reliability in measuring trait self-compassion. Three of the six subscales-self-judgement, mindfulness, and kindness-also demonstrated excellent reliability, with G-coefficients of 0.82-0.85. Eighteen of the 26 items measured trait more than state. The remaining eight items reflected a mixture of trait and state, but this did not affect overall reliability. Conclusions: This study indicated that the VSCS, VSCS-SF, and three VSCS subscales reliably measured trait self-compassion, with scores generalisable across the Vietnamese population and occasions. Thus, overall self-compassion levels remained stable over time, which is useful for evaluating the effectiveness of an intervention because significant changes of self-compassion are likely to be long-lasting. Supplementary Information: The online version contains supplementary material available at 10.1007/s12671-022-01950-3.

Polar Gini Curve: A Technique to Discover Gene Expression Spatial Patterns from Single-cell RNA-seq Data.

In this work, we describe the development of Polar Gini Curve, a method for characterizing cluster markers by analyzing single-cell RNA sequencing (scRNA-seq) data. Polar Gini Curve combines the gene expression and the 2D coordinates ("spatial") information to detect patterns of uniformity in any clustered cells from scRNA-seq data. We demonstrate that Polar Gini Curve can help users characterize the shape and density distribution of cells in a particular cluster, which can be generated during routine scRNA-seq data analysis. To quantify the extent to which a gene is uniformly distributed in a cell cluster space, we combine two polar Gini curves (PGCs)-one drawn upon the cell-points expressing the gene (the "foreground curve") and the other drawn upon all cell-points in the cluster (the "background curve"). We show that genes with highly dissimilar foreground and background curves tend not to uniformly distributed in the cell cluster-thus having spatially divergent gene expression patterns within the cluster. Genes with similar foreground and background curves tend to uniformly distributed in the cell cluster-thus having uniform gene expression patterns within the cluster. Such quantitative attributes of PGCs can be applied to sensitively discover biomarkers across clusters from scRNA-seq data. We demonstrate the performance of the Polar Gini Curve framework in several simulation case studies. Using this framework to analyze a real-world neonatal mouse heart cell dataset, the detected biomarkers may characterize novel subtypes of cardiac muscle cells. The source code and data for Polar Gini Curve could be found at http://discovery.informatics.uab.edu/PGC/ or https://figshare.com/projects/Polar_Gini_Curve/76749.

Giant lumbar spinal schwannoma: a case report and literature review.

We report a case of a 40-year-old female patient admitted to the hospital due to lumbar pain that spread to both legs and was associated with weakness of the lower extremities. Magnetic resonance imaging revealed an intradural - extramedullary tumor at the level of the T12 - L2 vertebra. The lesion was over 7 cm in greatest diameter and compressed the conus medullaris. The patient underwent surgery to remove the entire tumor. Postoperative pathology confirmed the diagnosis of schwannoma. The symptoms resolved almost completely without significant complications.

CiliaCarta: An integrated and validated compendium of ciliary genes.

The cilium is an essential organelle at the surface of mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We generated independent experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins using multiple cell and animal model systems (mouse, zebrafish and nematode) and techniques. For example, we show that OSCP1, which has previously been implicated in two distinct non-ciliary processes, causes ciliogenic and ciliopathy-associated tissue phenotypes when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 956 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/.

SPATA7 maintains a novel photoreceptor-specific zone in the distal connecting cilium.

Photoreceptor-specific ciliopathies often affect a structure that is considered functionally homologous to the ciliary transition zone (TZ) called the connecting cilium (CC). However, it is unclear how mutations in certain ciliary genes disrupt the photoreceptor CC without impacting the primary cilia systemically. By applying stochastic optical reconstruction microscopy technology in different genetic models, we show that the CC can be partitioned into two regions: the proximal CC (PCC), which is homologous to the TZ of primary cilia, and the distal CC (DCC), a photoreceptor-specific extension of the ciliary TZ. This specialized distal zone of the CC in photoreceptors is maintained by SPATA7, which interacts with other photoreceptor-specific ciliary proteins such as RPGR and RPGRIP1. The absence of Spata7 results in the mislocalization of DCC proteins without affecting the PCC protein complexes. This collapse results in destabilization of the axonemal microtubules, which consequently results in photoreceptor degeneration. These data provide a novel mechanism to explain how genetic disruption of ubiquitously present ciliary proteins exerts tissue-specific ciliopathy phenotypes.

Multiple Kernel Point Set Registration.

The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue arising from these studies concerns the mapping of data with nonlinear relationships and the ability to select a suitable kernel. Kernel selection is crucial for effective point set registration. We focus here on multiple kernel point set registration. We make several contributions in this paper. First, each observation is modeled using the Student's t-distribution, which is heavily tailed and more robust than the Gaussian distribution. Second, by automatically adjusting the kernel weights, the proposed method allows us to prune the ineffective kernels. This makes the choice of kernels less crucial. After parameter learning, the kernel saliencies of the irrelevant kernels go to zero. Thus, the choice of kernels is less crucial and it is easy to include other kinds of kernels. Finally, we show empirically that our model outperforms state-of-the-art methods recently proposed in the literature.

Evaluation of potential candidate genes involved in salinity tolerance in striped catfish (Pangasianodon hypophthalmus) using an RNA-Seq approach.

Increasing salinity levels in freshwater and coastal environments caused by sea level rise linked to climate change is now recognized to be a major factor that can impact fish growth negatively, especially for freshwater teleost species. Striped catfish (Pangasianodon hypophthalmus) is an important freshwater teleost that is now widely farmed across the Mekong River Delta in Vietnam. Understanding the basis for tolerance and adaptation to raised environmental salinity conditions can assist the regional culture industry to mitigate predicted impacts of climate change across this region. Attempt of next generation sequencing using the ion proton platform results in more than 174 million raw reads from three tissue libraries (gill, kidney and intestine). Reads were filtered and de novo assembled using a variety of assemblers and then clustered together to generate a combined reference transcriptome. Downstream analysis resulted in a final reference transcriptome that contained 60,585 transcripts with an N50 of 683 bp. This resource was further annotated using a variety of bioinformatics databases, followed by differential gene expression analysis that resulted in 3062 transcripts that were differentially expressed in catfish samples raised under two experimental conditions (0 and 15 ppt). A number of transcripts with a potential role in salinity tolerance were then classified into six different functional gene categories based on their gene ontology assignments. These included; energy metabolism, ion transportation, detoxification, signal transduction, structural organization and detoxification. Finally, we combined the data on functional salinity tolerance genes into a hypothetical schematic model that attempted to describe potential relationships and interactions among target genes to explain the molecular pathways that control adaptive salinity responses in P. hypophthalmus. Our results indicate that P. hypophthalmus exhibit predictable plastic regulatory responses to elevated salinity by means of characteristic gene expression patterns, providing numerous candidate genes for future investigations.

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms.

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine.

Asymmetric mixture model with simultaneous feature selection and model detection.

A mixture model based on the symmetric Gaussian distribution that simultaneously treats the feature selection, and the model detection has recently received great attention for pattern recognition problems. However, in many applications, the distribution of the data has a non-Gaussian and nonsymmetric form. This brief presents a new asymmetric mixture model for model detection and model selection. In this brief, the proposed asymmetric distribution is modeled with multiple student's- t distributions, which are heavily tailed and more robust than Gaussian distributions. Our method has the flexibility to fit different shapes of observed data, such as non-Gaussian and nonsymmetric. Another advantage is that the proposed algorithm, which is based on the variational Bayesian learning, can simultaneously optimize over the number of the student's- t distribution that is used to model each asymmetric distribution, the number of components, and the saliency of the features. Numerical experiments on both synthetic and real-world datasets are conducted. The performance of the proposed model is compared with other mixture models, demonstrating the robustness, accuracy, and effectiveness of our method.

An siRNA-based functional genomics screen for the identification of regulators of ciliogenesis and ciliopathy genes.

Defects in primary cilium biogenesis underlie the ciliopathies, a growing group of genetic disorders. We describe a whole-genome siRNA-based reverse genetics screen for defects in biogenesis and/or maintenance of the primary cilium, obtaining a global resource. We identify 112 candidate ciliogenesis and ciliopathy genes, including 44 components of the ubiquitin-proteasome system, 12 G-protein-coupled receptors, and 3 pre-mRNA processing factors (PRPF6, PRPF8 and PRPF31) mutated in autosomal dominant retinitis pigmentosa. The PRPFs localize to the connecting cilium, and PRPF8- and PRPF31-mutated cells have ciliary defects. Combining the screen with exome sequencing data identified recessive mutations in PIBF1, also known as CEP90, and C21orf2, also known as LRRC76, as causes of the ciliopathies Joubert and Jeune syndromes. Biochemical approaches place C21orf2 within key ciliopathy-associated protein modules, offering an explanation for the skeletal and retinal involvement observed in individuals with C21orf2 variants. Our global, unbiased approaches provide insights into ciliogenesis complexity and identify roles for unanticipated pathways in human genetic disease.

Bounded asymmetrical Student's-t mixture model.

The finite mixture model based on the Student's-t distribution, which is heavily tailed and more robust than the Gaussian mixture model (GMM), is a flexible and powerful tool to address many computer vision and pattern recognition problems. However, the Student's-t distribution is unbounded and symmetrical around its mean. In many applications, the observed data are digitalized and have bounded support. The distribution of the observed data usually has an asymmetric form. A new finite bounded asymmetrical Student's-t mixture model (BASMM), which includes the GMM and the Student's-t mixture model (SMM) as special cases, is presented in this paper. We propose an extension of the Student's-t distribution in this paper. This new distribution is sufficiently flexible to fit different shapes of observed data, such as non-Gaussian, nonsymmetric, and bounded support data. Another advantage of the proposed model is that each of its components can model the observed data with different bounded support regions. In order to estimate the model parameters, previous models represent the Student's-t distributions as an infinite mixture of scaled Gaussians. We propose an alternate approach in order to minimize the higher bound on the data negative log-likelihood function, and directly deal with the Student's-t distribution. As an application, our method has been applied to image segmentation with promising results.

A Bayesian bounded asymmetric mixture model with segmentation application.

Segmentation of a medical image based on the modeling and estimation of the tissue intensity probability density functions via a Gaussian mixture model has recently received great attention. However, the Gaussian distribution is unbounded and symmetrical around its mean. This study presents a new bounded asymmetric mixture model for analyzing both univariate and multivariate data. The advantage of the proposed model is that it has the flexibility to fit different shapes of observed data such as non-Gaussian, nonsymmetric, and bounded support data. Another advantage is that each component of the proposed model has the ability to model the observed data with different bounded support regions, which is suitable for application on image segmentation. Our method is intuitively appealing, simple, and easy to implement. We also propose a new method to estimate the model parameters in order to minimize the higher bound on the data negative log-likelihood function. Numerical experiments are presented where the proposed model is tested in various images from simulated to real 3- D medical ones.

A Nonsymmetric Mixture Model for Unsupervised Image Segmentation.

Finite mixture models with symmetric distribution have been widely used for many computer vision and pattern recognition problems. However, in many applications, the distribution of the data has a non-Gaussian and nonsymmetric form. This paper presents a new nonsymmetric mixture model for image segmentation. The advantage of our method is that it is simple, easy to implement, and intuitively appealing. In this paper, each label is modeled with multiple D-dimensional Student's t-distribution, which is heavily tailed and more robust than Gaussian distribution. Expectation-maximization algorithm is adopted to estimate model parameters and to maximize the lower bound on the data log-likelihood from observations. Numerical experiments on various data types are conducted. The performance of the proposed model is compared with that of other mixture models, demonstrating the robustness, accuracy, and effectiveness of our method.