The recent discovery of two independently evolved XX/XY sex determination systems in the snake genera Python and Boa sparked a new drive to study the evolution of sex chromosomes in poorly studied lineages of snakes, where female heterogamety was previously assumed. Therefore, we examined seven species from the genera Eryx, Cylindrophis, Python, and Tropidophis by conventional and molecular cytogenetic methods. Despite the fact that these species have similar karyotypes in terms of chromosome number and morphology, we detected variability in the distribution of heterochromatin, telomeric repeats, and rDNA loci. Heterochromatic blocks were mainly detected in the centromeric regions in all species, although accumulations were detected in pericentromeric and telomeric regions in a few macrochromosomes in several of the studied species. All species show the expected topology of telomeric repeats at the edge of all chromosomes, with the exception of Eryx muelleri, where additional accumulations were detected in the centromeres of three pairs of macrochromosomes. The rDNA loci accumulate in one pair of microchromosomes in all Eryx species and in Cylindrophis ruffus, in one macrochromosome pair in Tropidophis melanurus and in two pairs of microchromosomes in Python regius. Sex-specific differences were not detected, suggesting that these species likely have homomorphic, poorly differentiated sex chromosomes.

• Keywords
• C-banding, CGH, FISH, boa, evolution, heterochromatin, karyotype, python, rDNA, sex chromosomes, telomeres,
• MeSH
• Boidae * genetics   MeSH
• Cytogenetic Analysis MeSH
• Evolution, Molecular MeSH
• Sex Chromosomes MeSH
• DNA, Ribosomal genetics   MeSH
• Animals MeSH
• Check Tag
• Male MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA, Ribosomal MeSH

Two experimental trials were performed to elucidate the role of rodents in the life cycle of Hepatozoon species using snakes as intermediate hosts. In one trial, two ball pythons, Python regius Shaw, 1802 were force fed livers of laboratory mice previously inoculated with sporocysts of Hepatozoon ayorgbor Sloboda, Kamler, Bulantová, Votýpka et Modrý, 2007. Transmission was successful in these experimentally infected snakes as evidenced by the appearance of intraerythrocytic gamonts, which persisted until the end of trial, 12 months after inoculation. Developmental stages of haemogregarines were not observed in histological sections from mice. In another experimental trial, a presence of haemogregarine DNA in mice inoculated with H. ayorgbor was demonstrated by PCR in the liver, lungs and spleen.

• MeSH
• Apicomplexa isolation & purification   MeSH
• Boidae parasitology   MeSH
• Erythrocytes parasitology   MeSH
• Rodentia parasitology   MeSH
• Disease Vectors * MeSH
• Liver parasitology   MeSH
• Mice MeSH
• Lung parasitology   MeSH
• Polymerase Chain Reaction methods   MeSH
• DNA, Protozoan isolation & purification   MeSH
• Protozoan Infections, Animal transmission   MeSH
• Spleen parasitology   MeSH
• Animals MeSH
• Check Tag
• Mice MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA, Protozoan MeSH

The genome-wide association study (GWAS) is a popular genomic approach that identifies genomic regions associated with a phenotype and, thus, aims to discover causative mutations (CM) in the genes underlying the phenotype. However, GWAS discoveries are limited by many factors and typically identify associated genomic regions without the further ability to compare the viability of candidate genes and actual CMs. Therefore, the current methodology is limited to CM identification. In our recent work, we presented a novel approach to an empowered "GWAS to Genes" strategy that we named Synthetic phenotype to causative mutation (SP2CM). We established this strategy to identify CMs in soybean genes and developed a web-based tool for accuracy calculation (AccuTool) for a reference panel of soybean accessions. Here, we describe our further development of the tool that extends its utilization for other species and named it AccuCalc. We enhanced the tool for the analysis of datasets with a low-frequency distribution of a rare phenotype by automated formatting of a synthetic phenotype and added another accuracy-based GWAS evaluation criterion to the accuracy calculation. We designed AccuCalc as a Python package for GWAS data analysis for any user-defined species-independent variant calling format (vcf) or HapMap format (hmp) as input data. AccuCalc saves analysis outputs in user-friendly tab-delimited formats and also offers visualization of the GWAS results as Manhattan plots accentuated by accuracy. Under the hood of Python, AccuCalc is publicly available and, thus, can be used conveniently for the SP2CM strategy utilization for every species.

• Keywords
• GWAS, Manhattan plot, SP2CM, accuracy, causative mutation, python package,
• MeSH
• Genome-Wide Association Study * methods   MeSH
• Phenotype MeSH
• Genome MeSH
• Genomics * methods   MeSH
• Mutation MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Hepatozoon ayorgbor n. sp. is described from specimens of Python regius imported from Ghana. Gametocytes were found in the peripheral blood of 43 of 55 snakes examined. Localization of gametocytes was mainly inside the erythrocytes; free gametocytes were found in 15 (34.9%) positive specimens. Infections of laboratory-reared Culex quinquefasciatus feeding on infected snakes, as well as experimental infection of juvenile Python regius by ingestion of infected mosquitoes, were performed to complete the life cycle. Similarly, transmission to different snake species (Boa constrictor and Lamprophis fuliginosus) and lizards (Lepidodactylus lugubris) was performed to assess the host specificity. Isolates were compared with Hepatozoon species from sub-Saharan reptiles and described as a new species based on the morphology, phylogenetic analysis, and a complete life cycle.

• MeSH
• Boidae parasitology   MeSH
• Coccidia classification   growth & development   pathogenicity   MeSH
• Culex parasitology   MeSH
• Species Specificity MeSH
• Erythrocytes parasitology   MeSH
• Phylogeny MeSH
• Insect Vectors parasitology   MeSH
• Coccidiosis parasitology   transmission   veterinary   MeSH
• Molecular Sequence Data MeSH
• Polymerase Chain Reaction MeSH
• DNA, Protozoan analysis   isolation & purification   MeSH
• Sequence Analysis, DNA MeSH
• Life Cycle Stages MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA, Protozoan MeSH

Homologous and differentiated ZZ/ZW sex chromosomes (or derived multiple neo-sex chromosomes) were often described in caenophidian snakes, but sex chromosomes were unknown until recently in non-caenophidian snakes. Previous studies revealed that two species of boas (Boa imperator, B. constrictor) and one species of python (Python bivittatus) independently evolved XX/XY sex chromosomes. In addition, heteromorphic ZZ/ZW sex chromosomes were recently revealed in the Madagascar boa (Acrantophis sp. cf. dumerili) and putatively also in the blind snake Myriopholis macrorhyncha. Since the evolution of sex chromosomes in non-caenophidian snakes seems to be more complex than previously thought, we examined ten species of pythons and boas representing the families Boidae, Calabariidae, Candoiidae, Charinidae, Pythonidae, and Sanziniidae by conventional and molecular cytogenetic methods, aiming to reveal their sex chromosomes. Our results show that all examined species do not possess sex-specific differences in their genomes detectable by the applied cytogenetic methods, indicating the presence of poorly differentiated sex chromosomes or even the absence of sex chromosomes. Interestingly, fluorescence in situ hybridization with telomeric repeats revealed extensive distribution of interstitial telomeric repeats in eight species, which are likely a consequence of intra-chromosomal rearrangements.

• Keywords
• boa, comparative genomic hybridization, evolution, fluorescence in situ hybridization, karyotype, microsatellites, python, rDNA, sex chromosomes, sex determination, telomeres,
• MeSH
• Boidae genetics   MeSH
• Genome genetics   MeSH
• Gene Rearrangement MeSH
• In Situ Hybridization, Fluorescence MeSH
• Karyotyping MeSH
• Evolution, Molecular * MeSH
• Sex Chromosomes genetics   MeSH
• Sex Determination Processes genetics   MeSH
• Telomere genetics   MeSH
• Animals MeSH
• Check Tag
• Male MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

• MeSH
• Algorithms * MeSH
• Models, Biological MeSH
• History, 20th Century MeSH
• History, 21st Century MeSH
• Linear Models MeSH
• Nonlinear Dynamics MeSH
• Computer Simulation MeSH
• Signal Processing, Computer-Assisted MeSH
• Programming Languages * MeSH
• Software * MeSH
• Computational Biology history   methods   MeSH
• Check Tag
• History, 20th Century MeSH
• History, 21st Century MeSH
• Publication type
• Journal Article MeSH
• Historical Article MeSH
• Review MeSH

We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software application to design custom coarse-grained (CG) models, as well as pre-defined models of polyelectrolytes, peptides, and globular proteins in the Extensible Simulation Package for Research on Soft Matter (ESPResSo). The Python interface of ESPResSo offers a flexible framework, capable of building custom CG models from scratch. As a downside, building CG models from scratch is prone to mistakes, especially for newcomers in the field of CG modeling, or for molecules with complex architectures. The pyMBE module builds CG models in ESPResSo using a hierarchical bottom-up approach, providing a robust tool to automate the setup of CG models and helping new users prevent common mistakes. ESPResSo features the constant pH (cpH) and grand-reaction (G-RxMC) methods, which have been designed to study chemical reaction equilibria in macromolecular systems with many reactive species. However, setting up these methods for systems, which contain several types of reactive groups, is an error-prone task, especially for beginners. The pyMBE module enables the automatic setup of cpH and G-RxMC simulations in ESPResSo, lowering the barrier for newcomers and opening the door to investigate complex systems not studied with these methods yet. To demonstrate some of the applications of pyMBE, we showcase several case studies where we successfully reproduce previously published simulations of charge-regulating peptides and globular proteins in bulk solution and weak polyelectrolytes in dialysis. The pyMBE module is publicly available as a GitHub repository (https://github.com/pyMBE-dev/pyMBE), which includes its source code and various sample and test scripts, including the ones that we used to generate the data presented in this article.

• Publication type
• Journal Article MeSH

This paper presents an implementation of the parallelization of genetic algorithms. Three models of parallelized genetic algorithms are presented, namely the Master-Slave genetic algorithm, the Coarse-Grained genetic algorithm, and the Fine-Grained genetic algorithm. Furthermore, these models are compared with the basic serial genetic algorithm model. Four modules, Multiprocessing, Celery, PyCSP, and Scalable Concurrent Operation in Python, were investigated among the many parallelization options in Python. The Scalable Concurrent Operation in Python was selected as the most favorable option, so the models were implemented using the Python programming language, RabbitMQ, and SCOOP. Based on the implementation results and testing performed, a comparison of the hardware utilization of each deployed model is provided. The results' implementation using SCOOP was investigated from three aspects. The first aspect was the parallelization and integration of the SCOOP module into the resulting Python module. The second was the communication within the genetic algorithm topology. The third aspect was the performance of the parallel genetic algorithm model depending on the hardware.

• Keywords
• Coarse-Grained, Fine-Grained, Master–Slave, SCOOP, parallelized genetic algorithms,
• MeSH
• Algorithms * MeSH
• Computers * MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: The cerebellum is one of the major central nervous structures consistently altered in obesity. Its role in higher cognitive function, parts of which are affected by obesity, is mediated through projections to and from the cerebral cortex. We therefore investigated the relationship between body mass index (BMI) and cerebellocerebral connectivity. METHODS: We utilized the Human Connectome Project's Young Adults dataset, including functional magnetic resonance imaging (fMRI) and behavioral data, to perform connectome-based predictive modeling (CPM) restricted to cerebellocerebral connectivity of resting-state fMRI and task-based fMRI. We developed a Python-based open-source framework to perform CPM, a data-driven technique with built-in cross-validation to establish brain-behavior relationships. Significance was assessed with permutation analysis. RESULTS: We found that (i) cerebellocerebral connectivity predicted BMI, (ii) task-general cerebellocerebral connectivity predicted BMI more reliably than resting-state fMRI and individual task-based fMRI separately, (iii) predictive networks derived this way overlapped with established functional brain networks (namely, frontoparietal networks, the somatomotor network, the salience network, and the default mode network), and (iv) we found there was an inverse overlap between networks predictive of BMI and networks predictive of cognitive measures adversely affected by overweight/obesity. CONCLUSIONS: Our results suggest obesity-specific alterations in cerebellocerebral connectivity, specifically with regard to task execution. With brain areas and brain networks relevant to task performance implicated, these alterations seem to reflect a neurobiological substrate for task performance adversely affected by obesity.

• Keywords
• BMI, Human Connectome Project (HCP), Python, cerebellum, connectome-based predictive modeling, functional magnetic resonance imaging (fMRI),
• MeSH
• Adult MeSH
• Body Mass Index * MeSH
• Connectome * methods   MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Young Adult MeSH
• Cerebellum * physiology   diagnostic imaging   MeSH
• Nerve Net MeSH
• Obesity physiopathology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

SUMMARY: AEON.py is a Python library for the analysis of the long-term behaviour in very large asynchronous Boolean networks. It provides significant computational improvements over the state-of-the-art methods for attractor detection. Furthermore, it admits the analysis of partially specified Boolean networks with uncertain update functions. It also includes techniques for identifying viable source-target control strategies and the assessment of their robustness with respect to parameter perturbations. AVAILABILITY AND IMPLEMENTATION: All relevant results are available in Supplementary Materials. The tool is accessible through https://github.com/sybila/biodivine-aeon-py. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

• MeSH
• Gene Library MeSH
• Software * MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH