Effects of dietary supplementation with L-arginine on the endogenous losses of amino acids in growing pigs exposed to heat stress.

Exposing pigs to heat stress (HS) provokes higher death of intestinal cells, resulting in elevated endogenous intestinal losses (EIL) of amino acids (AA) and damage to intestinal epithelia. Arginine (Arg) is precursor for the synthesis of polyamines, which are involved in proliferation of intestinal cells and restoration of the intestinal epithelia. Thus the effect of adding L-Arg to diets for HS pigs on the EIL of AA was analyzed. Twelve pigs (23.1 ± 1.1 kg body weight) implanted with T-type cannulas at the end of ileum were individually housed and allowed 15-days for surgery recovery under thermoneutral (TN) conditions (22 ± 2 °C). Following, the pigs were randomly assigned to one of three treatments: TN pigs fed a semi-purified, corn starch-3% casein basal diet (TN-B); HS pigs with the basal diet (HS-B); HS pigs consuming the basal diet supplemented with 0.20% L-Arg (HS-Arg). The experiment consisted of two 9-day periods; each period included 7-days of adaptation to their respective diet, followed by a 2-day ileal digesta collection period. Digesta was collected during 12 consecutive hours each day. The pigs were fed twice a-day. Ambient temperature (AT) inside the TN and HS rooms ranged from 18.6 to 27.6 °C and from 29.5 to 40.7 °C, respectively. Body temperature followed a pattern similar to that of AT. The daily EIL of indispensable AA increased (P < 0.01) in the HS-B pigs compared to both the TN-B and the HS-Arg pigs, however, there was no EIL difference between the TN-B and the HS-Arg pigs (P > 0.05). Likewise, with the exception of serine, daily losses of endogenous dispensable AA in the HS-B pigs were higher (P < 0.01) in comparison with those of TN-B and HS-Arg pigs. In summary, HS exposure compared to TN conditions increases the loss of endogenous AA, but dietary supplementation with L-Arg helped to counteract the negative HS effect.

Superficial white matter bundle atlas based on hierarchical fiber clustering over probabilistic tractography data.

The study of short association fibers is still an incomplete task due to their higher inter-subject variability and the smaller size of this kind of fibers in comparison to known long association bundles. However, their description is essential to understand human brain dysfunction and better characterize the human brain connectome. In this work, we present a multi-subject atlas of short association fibers, which was computed using a superficial white matter bundle identification method based on fiber clustering. To create the atlas, we used probabilistic tractography from one hundred subjects from the HCP database, aligned with non-linear registration. The method starts with an intra-subject clustering of short fibers (30-85 mm). Based on a cortical atlas, the intra-subject cluster centroids from all subjects are segmented to identify the centroids connecting each region of interest (ROI) of the atlas. To reduce computational load, the centroids from each ROI group are randomly separated into ten subgroups. Then, an inter-subject hierarchical clustering is applied to each centroid subgroup, followed by a second level of clustering to select the most-reproducible clusters across subjects for each ROI group. Finally, the clusters are labeled according to the regions that they connect, and clustered to create the final bundle atlas. The resulting atlas is composed of 525 bundles of superficial short association fibers along the whole brain, with 384 bundles connecting pairs of different ROIs and 141 bundles connecting portions of the same ROI. The reproducibility of the bundles was verified using automatic segmentation on three different tractogram databases. Results for deterministic and probabilistic tractography data show high reproducibility, especially for probabilistic tractography in HCP data. In comparison to previous work, our atlas features a higher number of bundles and greater cortical surface coverage.

ABrainVis: an android brain image visualization tool.

BACKGROUND: The visualization and analysis of brain data such as white matter diffusion tractography and magnetic resonance imaging (MRI) volumes is commonly used by neuro-specialist and researchers to help the understanding of brain structure, functionality and connectivity. As mobile devices are widely used among users and their technology shows a continuous improvement in performance, different types of applications have been designed to help users in different work areas. RESULTS: We present, ABrainVis, an Android mobile tool that allows users to visualize different types of brain images, such as white matter diffusion tractographies, represented as fibers in 3D, segmented fiber bundles, MRI 3D images as rendered volumes and slices, and meshes. The tool enables users to choose and combine different types of brain imaging data to provide visual anatomical context for specific visualization needs. ABrainVis provides high performance over a wide range of Android devices, including tablets and cell phones using medium and large tractography datasets. Interesting visualizations including brain tumors and arteries, along with fiber, are given as examples of case studies using ABrainVis. CONCLUSIONS: The functionality, flexibility and performance of ABrainVis tool introduce an improvement in user experience enabling neurophysicians and neuroscientists fast visualization of large tractography datasets, as well as the ability to incorporate other brain imaging data such as MRI volumes and meshes, adding anatomical contextual information.

FFClust: Fast fiber clustering for large tractography datasets for a detailed study of brain connectivity.

Automated methods that can identify white matter bundles from large tractography datasets have several applications in neuroscience research. In these applications, clustering algorithms have shown to play an important role in the analysis and visualization of white matter structure, generating useful data which can be the basis for further studies. This work proposes FFClust, an efficient fiber clustering method for large tractography datasets containing millions of fibers. Resulting clusters describe the whole set of main white matter fascicles present on an individual brain. The method aims to identify compact and homogeneous clusters, which enables several applications. In individuals, the clusters can be used to study the local connectivity in pathological brains, while at population level, the processing and analysis of reproducible bundles, and other post-processing algorithms can be carried out to study the brain connectivity and create new white matter bundle atlases. The proposed method was evaluated in terms of quality and execution time performance versus the state-of-the-art clustering techniques used in the area. Results show that FFClust is effective in the creation of compact clusters, with a low intra-cluster distance, while keeping a good quality Davies-Bouldin index, which is a metric that quantifies the quality of clustering approaches. Furthermore, it is about 8.6 times faster than the most efficient state-of-the-art method for one million fibers dataset. In addition, we show that FFClust is able to correctly identify atlas bundles connecting different brain regions, as an example of application and the utility of compact clusters.

Adaptive and maladaptive genetic diversity in small populations: Insights from the Brook Charr (Salvelinus fontinalis) case study.

Investigating the relative importance of neutral versus selective processes governing the accumulation of genetic variants is a key goal in both evolutionary and conservation biology. This is particularly true in the context of small populations, where genetic drift can counteract the effect of selection. Using Brook Charr (Salvelinus fontinalis) from Québec, Canada, as a case study, we investigated the importance of demographic versus selective processes governing the accumulation of both adaptive and maladaptive mutations in closed versus open and connected populations to assess gene flow effect. This was achieved by using 14,779 high-quality filtered SNPs genotyped among 1,416 fish representing 50 populations from three life history types: lacustrine (closed populations), riverine and anadromous (connected populations). Using the PROVEAN algorithm, we observed a considerable accumulation of putative deleterious mutations across populations. The absence of correlation between the occurrence of putatively beneficial or deleterious mutations and local recombination rate supports the hypothesis that genetic drift might be the main driver of the accumulation of such variants. However, despite a lower genetic diversity observed in lacustrine than in riverine or anadromous populations, lacustrine populations do not exhibit more deleterious mutations than the two other history types, suggesting that the negative effect of genetic drift in lacustrine populations may be mitigated by that of relaxed purifying selection. Moreover, we also identified genomic regions associated with anadromy, as well as an overrepresentation of transposable elements associated with variation in environmental variables, thus supporting the importance of transposable elements in adaptation.

Changes in D-dimer after initiation of antiretroviral therapy in adults living with HIV in Kenya.

BACKGROUND: Increased coagulation biomarkers are associated with poor outcomes among people living with HIV (PLHIV). There are few data available from African cohorts demonstrating the effect of antiretroviral therapy (ART) on coagulation biomarkers. METHODS: From March 2014 to October 2014, ART-naïve PLHIV initiating non-nucleoside reverse transcriptase inhibitor-based ART were recruited from seven clinics in western Kenya and followed for up to 12 months. Demographics, clinical history and blood specimens were collected. Logistic regression models adjusted for intrasite clustering examined associations between HIV viral load and D-Dimer at baseline. Mixed linear effects models were used to estimate mean change from baseline to 6 months overall, and by baseline viral load, sex and TB status at enrollment. Mean change in D-dimer at 6 months is reported on the log10 scale and as percentage change from baseline. RESULTS: Among 611 PLHIV enrolled, 66% were female, median age was 34 years (interquartile range (IQR) 29-43 years), 31 (5%) participants had tuberculosis and median viral load was 113,500 copies/mL (IQR: 23,600-399,000). At baseline, 311 (50.9%) PLHIV had elevated D-dimer (> 500 ng/mL) and median D-dimer was 516.4 ng/mL (IQR: 302.7-926.6) (log baseline D-dimer: 2.7, IQR: 2.5-3.0). Higher baseline D-dimer was significantly associated with higher viral load (p < 0.0001), female sex (p = 0.02) and tuberculosis (p = 0.02). After 6 months on ART, 518 (84.8%) PLHIV had achieved viral load < 1000 copies/mL and median D-dimer was 390.0 (IQR: 236.6-656.9) (log D-dimer: 2.6, IQR: 2.4-2.8). Mean change in log D-dimer from baseline to 6 months was - 0.12 (95%CI -0.15, - 0.09) (p < 0.0001) indicating at 31.3% decline (95%CI -40.0, - 23.0) in D-dimer levels over the first 6 months on ART. D-dimer decline after ART initiation was significantly greater among PLHIV with tuberculosis at treatment initiation (- 172.1, 95%CI -259.0, - 106.3; p < 0.0001) and those with log viral load > 6.0 copies/mL (- 91.1, 95%CI -136.7, - 54.2; p < 0.01). CONCLUSIONS: In this large Kenyan cohort of PLHIV, women, those with tuberculosis and higher viral load had elevated baseline D-dimer. ART initiation and viral load suppression among ART-naïve PLHIV in Kenya were associated with significant decrease in D-dimer at 6 months in this large African cohort.

Fat, Cartilage, and Bone Metaplasia in Lungs of Cattle With Caudal Pleural Lesions and Subjacent Interstitial Fibrosis.

The changes associated with condemned lungs in cattle with chronic pleural lesions of the caudal lobes were characterized by histology and immunohistochemistry (IHC). Fibroproliferative pleural lesions were microscopically confirmed. Occasionally, the pleural lesions also included adipose, chondroid, and osseous metaplasia that were covered by mesothelial cells, mostly in the absence of inflammation. Other lungs also showed fibrosis in the subpleural interstitium and interlobular septa. In both condemned and noncondemned lungs, immunoreactivity to Wilms tumor 1 (WT1) was normally observed on surface mesothelial cells but not on the submesothelial fibroblasts and myofibroblasts. Conversely, the myofibroblasts beneath the pleura, but not the mesothelial cells, showed immunoreactivity to alpha smooth muscle actin and calponin. However, in the lungs with myofibroblastic foci in the pleura, the proliferated cells maintained WT1 immunoreactivity similar to those of some metaplastic cells. These findings may reflect the plasticity of mesothelial cells in vivo.

Coccidioidomycosis in Biopsies with Presumptive Diagnosis of Malignancy in Dogs: Report of Three Cases and Comparative Discussion of Published Reports.

Coccidioidomycosis is a respiratory fungal infection with occasional systemic dissemination. The disseminated coccidioidomycosis is considered a multifaceted disease. In medicine, disseminated coccidioidomycosis is included within a group of infectious diseases that have been referred as the great imitators. In many cases, malignancies are included in the presumptive diagnosis. In veterinary medicine, disseminated coccidioidomycosis is common in dogs. Nonetheless, despite of being a diagnostic dilemma, disseminated coccidioidomycosis is underestimated and frequently not included into differentials, even in endemic zones. Herein, we describe three cases of granulomatous inflammation caused by Coccidioides spp. which were masquerading malignancies in dogs (0.39 %). The presumptive diagnoses in these cases were osteosarcoma, lymphoma and neurofibroma, respectively. A PCR assay employing tissues in paraffin blocks resulted positive for C. posadasii in one of these cases. A comparative discussion on the ambiguous clinic-pathological presentation of disseminated coccidioidomycosis in dogs and humans is included.

Krüppel-like factor 5 as potential molecular marker in cervical cancer and the KLF family profile expression.

Cervical cancer (CC) as other cancer types, presents molecular deregulations, such as the alterations of transcription factors. Krüppel-like factors (KLF) are a family of transcriptional regulators. They are involved in diverse cellular processes, such as proliferation, apoptosis, and angiogenesis among others. Here, we analyzed the expression of all 17 KLF members at messenger RNA (mRNA) level, and protein expression of the two most commonly altered KLF5 and KLF6 in cervical tissues. Fifty-nine cervical tissues ranging from normal tissue to CC were evaluated for KLF1-17 mRNA expression by end-point RT-PCR and KLF5 by qRT-PCR. For KLF5 and KLF6 protein analysis, a tissue microarray was constructed containing the 59 cases and subjected for immunohistochemistry assay and KLF6 IVS1-27G>A single nucleotide polymorphism by direct DNA sequencing. KLF2-16 expressions were present in normal tissue, whereas all 17 were present in Low-Grade Squamous Intraepithelial Lesion, High-Grade-SIL and CC, unrelated to presence of human papillomavirus (HPV). KLF5 mRNA expression gradually increased throughout the subgroups and overexpressed in CC (p=0.01). KLF5 and KLF6 proteins were immunodetected in all samples. For the KLF6 SNP analysis, 80% of the CC population analyzed presented GG genotype and the remaining 20% presented GA genotype (p=0.491). Our present data show that KLFs expression could not be related to HPV presence, at least at transcriptional level, and KLF5 mRNA overexpression could represent a potential molecular marker for CC; KLF6 SNP has no relation to increased risk of CC.

Bovine diseases causing neurological signs and death in Mexican feedlots.

The number of large feedlot operations, similar to that of USA and Canada, has notably increased in Mexico in the last three decades. Clinical and laboratory diagnoses of neurological diseases in feedlot cattle are crucial in Mexico and Central America because of the high incidence of bovine paralytic rabies (BPR). Because of its zoonotic potential, BPR must be promptly diagnosed and differentiated from other bovine neurological diseases such as thrombotic meningoencephalitis (TME), polioencephalomalacia (PEM) and botulism. More recently, BPR and botulism have been diagnosed with increasing frequency in Mexican feedlots. Neither BPR nor botulism has relevant gross lesions, thus post-mortem diagnosis without laboratory support is impossible. Herein, we describe five outbreaks of neurological diseases in Mexican feedlots in which BPR, botulism and PEM were diagnosed either independently or in combination. A diagram illustrating the most conspicuous pathologic findings and ancillary laboratory test required to confirm the diagnoses of these neurological diseases in feedlot cattle is proposed.

PhyberSIM: a tool for the generation of ground truth to evaluate brain fiber clustering algorithms.

Diffusion Magnetic Resonance Imaging tractography is a non-invasive technique that produces a collection of streamlines representing the main white matter bundle trajectories. Methods, such as fiber clustering algorithms, are important in computational neuroscience and have been the basis of several white matter analysis methods and studies. Nevertheless, these clustering methods face the challenge of the absence of ground truth of white matter fibers, making their evaluation difficult. As an alternative solution, we present an innovative brain fiber bundle simulator that uses spline curves for fiber representation. The methodology uses a tubular model for the bundle simulation based on a bundle centroid and five radii along the bundle. The algorithm was tested by simulating 28 Deep White Matter atlas bundles, leading to low inter-bundle distances and high intersection percentages between the original and simulated bundles. To prove the utility of the simulator, we created three whole-brain datasets containing different numbers of fiber bundles to assess the quality performance of QuickBundles and Fast Fiber Clustering algorithms using five clustering metrics. Our results indicate that QuickBundles tends to split less and Fast Fiber Clustering tends to merge less, which is consistent with their expected behavior. The performance of both algorithms decreases when the number of bundles is increased due to higher bundle crossings. Additionally, the two algorithms exhibit robust behavior with input data permutation. To our knowledge, this is the first whole-brain fiber bundle simulator capable of assessing fiber clustering algorithms with realistic data.

Short fiber bundle filtering and test-retest reproducibility of the Superficial White Matter.

In recent years, there has been a growing interest in studying the Superficial White Matter (SWM). The SWM consists of short association fibers connecting near giry of the cortex, with a complex organization due to their close relationship with the cortical folding patterns. Therefore, their segmentation from dMRI tractography datasets requires dedicated methodologies to identify the main fiber bundle shape and deal with spurious fibers. This paper presents an enhanced short fiber bundle segmentation based on a SWM bundle atlas and the filtering of noisy fibers. The method was tuned and evaluated over HCP test-retest probabilistic tractography datasets (44 subjects). We propose four fiber bundle filters to remove spurious fibers. Furthermore, we include the identification of the main fiber fascicle to obtain well-defined fiber bundles. First, we identified four main bundle shapes in the SWM atlas, and performed a filter tuning in a subset of 28 subjects. The filter based on the Convex Hull provided the highest similarity between corresponding test-retest fiber bundles. Subsequently, we applied the best filter in the 16 remaining subjects for all atlas bundles, showing that filtered fiber bundles significantly improve test-retest reproducibility indices when removing between ten and twenty percent of the fibers. Additionally, we applied the bundle segmentation with and without filtering to the ABIDE-II database. The fiber bundle filtering allowed us to obtain a higher number of bundles with significant differences in fractional anisotropy, mean diffusivity, and radial diffusivity of Autism Spectrum Disorder patients relative to controls.

Phybers: a package for brain tractography analysis.

We present a Python library (Phybers) for analyzing brain tractography data. Tractography datasets contain streamlines (also called fibers) composed of 3D points representing the main white matter pathways. Several algorithms have been proposed to analyze this data, including clustering, segmentation, and visualization methods. The manipulation of tractography data is not straightforward due to the geometrical complexity of the streamlines, the file format, and the size of the datasets, which may contain millions of fibers. Hence, we collected and structured state-of-the-art methods for the analysis of tractography and packed them into a Python library, to integrate and share tools for tractography analysis. Due to the high computational requirements, the most demanding modules were implemented in C/C++. Available functions include brain Bundle Segmentation (FiberSeg), Hierarchical Fiber Clustering (HClust), Fast Fiber Clustering (FFClust), normalization to a reference coordinate system, fiber sampling, calculation of intersection between sets of brain fibers, tools for cluster filtering, calculation of measures from clusters, and fiber visualization. The library tools were structured into four principal modules: Segmentation, Clustering, Utils, and Visualization (Fibervis). Phybers is freely available on a GitHub repository under the GNU public license for non-commercial use and open-source development, which provides sample data and extensive documentation. In addition, the library can be easily installed on both Windows and Ubuntu operating systems through the pip library.

[Experiences of health professionals with biological accidents in an Intensive Care Unit.] / Experiencias de profesionales de la salud con accidentes biológicos en una Unidad de Cuidados Intensivos.

OBJECTIVE: Health personnel are at greater risk of contracting infections related to their work within the group of workers with biological risk, and these mishaps can affect their physical and mental health. therefore, the objective of this paper was to understand the experience of health professionals in an intensive care unit (ICU) in Cali (Colombia) who suffered biological accidents. METHODS: Explanatory sequential mixed design, it was developed in two phases, the first of a descriptive quantitative type and the second of a qualitative type with a phenomenological approach. Initially the knowledge about biosafety in 40 workers was characterized through a survey and a in the first contact, five participants were chosen who shared their experiences with biological accidents, through in-depth interviews. The statistical analysis was descriptive, the quantitative variables were presented through measures of central tendency and the qualitative variables through frequency and percentage. RESULTS: 39% of the professionals knew the biosafety barriers, 35% identified the pathogenic pathways, 34% were right about the protection measures, 51% answered correctly about hand washing, 70% answered adequately about biological waste, and only 38% recognized the procedure for reporting an accident. CONCLUSIONS: A low level of knowledge is identified on issues related to biosafety principles, transmission routes, hand sanitizing agents, and procedures to follow in the event of a biohazard accident. In addition, ICUs are identified as high-risk places. biological that cause feelings of fear, anguish, and stress that are added to the long working hours.

OBJETIVO: El personal sanitario tiene mayor riesgo de contraer infecciones relacionadas con su labor dentro del grupo de trabajadores con riesgo biológico, pudiendo afectar estos percances a su salud física y mental. Por lo tanto, se estableció como objetivo de la investigación comprender la experiencia de los profesionales sanitarios de una Unidad de cuidados intensivos (UCI) en Cali (Colombia) que sufrieron accidentes biológicos. METODOS: Se empleó un diseño fue mixto secuencial explicativo, que se desarrolló en dos fases: la primera, de tipo cuantitativo descriptivo; la segunda, de tipo cualitativo con enfoque fenomenológico. Inicialmente se caracterizaron los conocimientos sobre bioseguridad en cuarenta trabajadores a través de una encuesta y se estableció un primer contacto, se eligieron cinco participantes que compartieron sus experiencias con accidentes de tipo biológico, por medio de entrevistas a profundidad. El análisis estadístico fue descriptivo, las variables cuantitativas fueron presentadas a través de medidas de tendencia central y las variables cualitativas a través de frecuencia y porcentaje. RESULTADOS: El 39% de los profesionales conocían las barreras de bioseguridad, el 35% identificaron las vías patógenas, el 34% acertaron sobre las medidas de protección, el 51% respondieron correctamente sobre el lavado de manos, el 70% respondieron adecuadamente sobre los residuos biológicos y solo el 38% reconoció el procedimiento para reportar un accidente. CONCLUSIONES: Se aprecia un nivel bajo de conocimientos en temas relacionados con principios de bioseguridad, vías de transmisión, agentes de higienización de manos y procedimientos a seguir frente a un accidente de riesgo biológico. Sumado a ello, se identifican las UCI como un lugar de alto riesgo biológico que ocasionan sentimientos de temor, angustia y estrés, además de las altas jornadas laborales.

[Learning conditions in health team residences during the COVID-19 pandemic, Argentina 2020]. / Condiciones del aprendizaje en las residencias del equipo de salud durante la pandemia COVID-19, Argentina 2020.

COVID-19 pandemic modified learning conditions in health professions' residences. The objective of the research was to explore Argentinian residents' perceptions regarding training conditions during the first year of pandemic. A descriptive, quali-quantitative study was developed through an online, anonymous questionnaire, with 42 items: 17 closed options and 25 Likert scale from 1 to 5; and 2 open questions. Sampling was intentional and non-probabilistic. The questionnaire was answered by 1595 residents, 74% were physicians, 47.1% belonged to clinical specialties and 21.8% worked on the front line of care. A 77.2% worked in the public sector and 89.4% in hospital practice, 42.1% assumed tasks not typical of their specialty. They agreed on the availability of personal protection and supplies (mean 3.8 ± 1.3), reduction of lectures (mean 3.5 ± 1.6), procedures (mean 3.8 ± 1.4) and rotations (mean 3.7 ± 1.2). They concurred on the need to extend training to recover learning (mean 3 ± 1.6). The decrease in practices was associated with surgical specialties (p = 0.0001) and not practicing in the front line of care (p = 0.007). They perceived as positive aspects the chance to strengthen bonds between residents and closeness with relatives, and negative aspects the effects on health due to stress and social distancing. In conclusion, the general conditions of training were affected. This leads to rethink the teaching and assessment curricular alternatives, as well as interventions related to the well-being of the residents.

La pandemia COVID-19 afectó las condiciones de aprendizaje en las residencias del equipo de salud. El objetivo fue explorar las percepciones de residentes de Argentina sobre las condiciones generales de su formación en este contexto. Se realizó un estudio descriptivo, cuali-cuantitativo, a través de un cuestionario en línea, anónimo, con 17 ítems de opciones cerradas y 25 con escala de Likert de 1 a 5, con un muestreo no probabilístico e intencional. Respondieron 1595 residentes, 74% médicos, 47.1% pertenecía a una especialidad clínica y 21.8% a la primera línea de atención. El 77.2% se desempeñó en residencias públicas y el 89.4% en el ámbito hospitalario. El 42.1% asumió tareas no propias de su especialidad. Hubo acuerdo sobre la disponibilidad de insumos y protección personal (media 3.8 ± 1.3), la afectación de clases y conferencias (media 3.5 ± 1.6), procedimientos (media 3.8 ± 1.4) y rotaciones (media 3.7 ± 1.2). Asimismo, sobre prorrogar la formación para recuperar aprendizajes (media 3 ± 1.6). La disminución de prácticas se asoció a especialidades quirúrgicas (p = 0.0001) y no estar en la primera línea de atención (p = 0.007). Percibieron positivamente el fortalecimiento de vínculos entre residentes y con familiares, y negativos los efectos en la salud por estrés y distanciamiento social. En conclusión, las condiciones generales de la formación se vieron afectadas. Esto conduce a pensar tanto en la necesidad de alternativas curriculares de enseñanza y evaluación, como en intervenciones vinculadas al bienestar de los residentes.

Primary Angiomatoid Melanomas in Dogs.

Melanocyte-derived tumours are common in humans and animals and their spontaneous occurrence in dogs and the clinicopathological progression in malignant presentations is comparable with humans. Melanomas are a heterogeneous group of malignant neoplasms and several subtypes have been classified, including angiomatoid melanoma, of which only five cases have been reported in humans but none in animals. We now document cases of primary angiomatoid melanoma in the skin and oral cavity of two dogs. Neoplastic cells resembling endothelial cells that lined large blood vessels in the tumours were immunonegative for CD34 but intensely positive for SOX10.

[Dermatoses in patients with acute myeloid and lymphoid leukemia. Cohort follow-up in a tertiary care hospital]. / Dermatosis en pacientes con leucemia aguda mieloide y linfoide. Seguimiento de una cohorte en un hospital de tercer nivel.

INTRODUCTION: Cutaneous manifestations in patients with acute leukemia (AL) cover a broad spectrum, including those due to leukemia per se, to chemotherapy and other drugs and those inherent to hospital care. MATERIAL AND METHODS: This is a cohort study in a tertiary hospital setting where the development of dermatoses was followed for 2 years in 22 patients with the diagnosis of AL. RESULTS: During the study, all patients developed some type of dermatosis, mostly due to chemotherapy.

Novel genotyping assay for the nt230 (del4) ABCB1 gene mutation and its allele frequency in Border Collie dogs in Mexico.

A 4-bp deletion in the ATP-binding cassette subfamily B member 1 (ABCB1) gene, also referred to as the multidrug resistance gene (MDR1), produces stop codons that cause premature termination of P-glycoprotein 1 (P-gp) synthesis. Dogs with the homozygous mutation do not express functional P-gp, which increases their sensitivity markedly to many common veterinary drugs. We detected the nt230 (del4) ABCB1 mutation in Border Collie dogs in western Mexico with a simple and affordable primer-introduced restriction analysis PCR (PIRA-PCR). PIRA-PCR clearly identified all genotypes in our sample of 104 dogs. Genotype frequencies were 0.952 (wild/wild), 0.029 (wild/mut) and 0.019 (mut/mut). Allele frequencies were 0.033 (mutant alleles) and 0.966 (wild-type alleles). In this small subset of the Mexican dog population, we found a higher prevalence of the nt230 (del4) MDR1/ABCB1 gene mutation than reported in other countries.

Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism.

Fiber clustering methods are typically used in brain research to study the organization of white matter bundles from large diffusion MRI tractography datasets. These methods enable exploratory bundle inspection using visualization and other methods that require identifying brain white matter structures in individuals or a population. Some applications, such as real-time visualization and inter-subject clustering, need fast and high-quality intra-subject clustering algorithms. This work proposes a parallel algorithm using a General Purpose Graphics Processing Unit (GPGPU) for fiber clustering based on the FFClust algorithm. The proposed GPGPU implementation exploits data parallelism using both multicore and GPU fine-grained parallelism present in commodity architectures, including current laptops and desktop computers. Our approach implements all FFClust steps in parallel, improving execution times in all of them. In addition, our parallel approach includes a parallel Kmeans++ algorithm implementation and defines a new variant of Kmeans++ to reduce the impact of choosing outliers as initial centroids. The results show that our approach provides clustering quality results very similar to FFClust, and it requires an execution time of 3.5 s for processing about a million fibers, achieving a speedup of 11.5 times compared to FFClust.