Bialystok15

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Visiting researcher at Dept of Theoretical Conputer Science Technical University of Bialystok, Poland, invited by Prof. Dr. Czeslaw Baginski, May 31-June 11 2015

Science

Retour d'expérience sur l'utilisation d'OMS Log Search pour constituer un Dashboard personnalisable et évolutif grâce aux informations collectées par les différentes solutions proposées dans OMS. L'objectif est de pouvoir monitorer simplement l'état de santé d'un SI hybride au sein d'une seule interface. Sécurité, performance, disponibilité...... Un Dashboard pour les gourverner tous où qu'ils soient!

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THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.

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The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.

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Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...

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Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.

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A brief information about the SCOP protein database used in bioinformatics. The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.

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Multi-source connectivity as the driver of solar wind variability in the heli...

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The ambient solar wind that flls the heliosphere originates from multiple sources in the solar corona and is highly structured. It is often described as high-speed, relatively homogeneous, plasma streams from coronal holes and slow-speed, highly variable, streams whose source regions are under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify solar wind sources and understand what drives the complexity seen in the heliosphere. By combining magnetic feld modelling and spectroscopic techniques with high-resolution observations and measurements, we show that the solar wind variability detected in situ by Solar Orbiter in March 2022 is driven by spatio-temporal changes in the magnetic connectivity to multiple sources in the solar atmosphere. The magnetic feld footpoints connected to the spacecraft moved from the boundaries of a coronal hole to one active region (12961) and then across to another region (12957). This is refected in the in situ measurements, which show the transition from fast to highly Alfvénic then to slow solar wind that is disrupted by the arrival of a coronal mass ejection. Our results describe solar wind variability at 0.5 au but are applicable to near-Earth observatories.

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Slide 1: Title Slide Extrachromosomal Inheritance Slide 2: Introduction to Extrachromosomal Inheritance Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus. Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids. Slide 3: Mitochondrial Inheritance Mitochondria: Organelles responsible for energy production. Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria. Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring. Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy. Slide 4: Chloroplast Inheritance Chloroplasts: Organelles responsible for photosynthesis in plants. Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts. Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species. Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA. Slide 5: Plasmid Inheritance Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes. Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation. Significance: Important in biotechnology for gene cloning and genetic engineering. Slide 6: Mechanisms of Extrachromosomal Inheritance Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance. Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells. Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression. Slide 7: Examples of Extrachromosomal Inheritance Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells. Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration. Slide 8: Importance of Extrachromosomal Inheritance Evolution: Provides insight into the evolution of eukaryotic cells. Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases. Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification. Slide 9: Recent Research and Advances Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA. Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases. Slide 10: Conclusion Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology. Future Directions: Continued research and technological advancements hold promise for new treatments and applications. Slide 11: Questions and Discussion Invite Audience: Open the floor for any questions or further discussion on the topic.

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Introduction: RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression. It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences. dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants. This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes. What are small ncRNAs? micro RNA (miRNA) short interfering RNA (siRNA) Properties of small non-coding RNA: Involved in silencing mRNA transcripts. Called “small” because they are usually only about 21-24 nucleotides long. Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered). Silence an mRNA by base pairing with some sequence on the mRNA. Discovery of siRNA? The first small RNA: In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the development of the worm C. elegans. Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14. Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions. Types of RNAi ( non coding RNA) MiRNA Length (23-25 nt) Trans acting Binds with target MRNA in mismatch Translation inhibition Si RNA Length 21 nt. Cis acting Bind with target Mrna in perfect complementary sequence Piwi-RNA Length ; 25 to 36 nt. Expressed in Germ Cells Regulates trnasposomes activity MECHANISM OF RNAI: First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces. Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands. The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it. THE RISC COMPLEX: RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA Unwinding of double stranded Si RNA by ATP independent Helicase Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA. DICER: endonuclease (RNase Family III) Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC) One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute ARGONAUTE PROTEIN : 1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA 2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity. MiRNA: The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .

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