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The genetic traits that underlie vulnerability to neuronal damage across specific brain circuits in Parkinson's disease (PD) remain to be elucidated. In this study, we characterized the brain topological intersection between propagating connectivity networks in controls and PD participants and gene expression patterns across the human cortex - such as the SNCA gene. We observed that brain connectivity originated from PD-related pathology epicenters in the brainstem recapitulated the anatomical distribution of alpha-synuclein histopathology in postmortem data. We also discovered that the gene set most related to cortical propagation patterns of PD-related pathology was primarily involved in microtubule cellular components. Thus, this study sheds light on new avenues for enhancing detection of PD neuronal vulnerability via an evaluation of in vivo connectivity trajectories across the human brain and successful integration of neuroimaging-genetic strategies. ; Acknowledgment: The authors thank the patients and their families for the time and effort they dedicated to the research. Funding This research was supported by grants from the National Institutes of Health (NIH; R01AG061811, and R01AG061445 to J.S.), the Ministry of Education, Science, and Technological Development of the Republic of Serbia (grant number 175090), the Italian Ministry of Health (grant number RF-2018-12366746), the Carlos III Institute of Health (PI11/02109) Spain, the Basque Government through the BERC 2018-2021 program and the Spanish State Research Agency through BCBL Severo Ochoa excellence accreditation SEV-2015-0490.

Ciguatoxins are polyether marine toxins that act as sodium channel activators. These toxins cause ciguatera, one of the most widespread nonbacterial forms of food poisoning, which presents several symptoms in humans including long-term neurological alterations. Earlier work has shown that both acute and chronic exposure of primary cortical neurons to synthetic ciguatoxin CTX3C have profound impacts on neuronal function. Thus, the present work aimed to identify relevant neuronal genes and metabolic pathways that could be altered by ciguatoxin exposure. To study the effect of ciguatoxins in primary neurons in culture, we performed a transcriptomic analysis using whole mouse genome microarrays, for primary cortical neurons exposed during 6, 24, or 72 h in culture to CTX3C. Here, we have shown that the effects of the toxin on gene expression differ with the exposure time. The results presented here have identified several relevant genes and pathways related to the effect of ciguatoxins on neurons and may assist in future research or even treatment of ciguatera. Moreover, we demonstrated that the effects of the toxin on gene expression were exclusively consequential of its action as a voltage-gated sodium channel activator, since all the effects of CTX3C were avoided by preincubation of the neurons with the sodium channel blocker tetrodotoxin ; The research leading to these results has received funding from the following FEDER cofounded-grants. From CDTI and Technological Funds, supported by Ministerio de Economía, Industria y Competitividad, AGL2014-58210-R, AGL2016-78728-R (AEI/FEDER, UE), ISCIII/PI16/01830 and RTC-2016-5507-2. From CDTI under ISIP Programme, Spain, IDI-20130304 APTAFOOD and ITC-20161072. From European Union POCTEP 0161-Nanoeaters -1-E-1, and Interreg AlertoxNet EAPA-317-2016. ABJ is recipient of a predoctoral fellowship from the Spanish Ministry of Education ; SI

Conventional diagnostics could benefit greatly from the high-throughput genomics technologies that have arisen over the past 10 years in basic research. Whether it is for DNA analysis (CGH arrays, SNP analysis) or RNA analysis (gene-expression arrays), information at the molecular level would undoubtedly improve the accuracy of diagnoses and prognoses. In the past 3 years, several efforts have been made to standardize assays, experimental procedures, and data processing, and governmental institutions such as the FDA, microarray manufacturers, and the scientific community have worked diligently to bring genomics into daily medicine. This talk will review the recent developments in molecular classification, prognostication, and treatments.

One: Rearrangement of Prokaryotic Genetic Material and DNA Cloning Vectors -- 1 Genomic Structure and Evolution of Bacillus licheniformis ? and LP52 Phage Family -- 2 Expression of the Synthetic Proenkephalin Gene in E. coli -- 3 Cloning and Expression of Bacillus?-Glucanase Genes -- 4 Regulation of ?-Amylase Synthesis in Bacillus subtilis -- 5 New Variations on an Old Theme: Type I Restriction Enzymes and Their Recognition Sequences -- 6 The EcoDXX1 Restriction and Modification System of Escherichia coli ET7 -- 7 Biological Function of Type I Restriction Enzymes -- 8 The Fosfomycin Resistance Transposon Tn2921 -- 9 Transposition-like Events Mediated by Single-ended Derivatives of Transposon Tn21 -- 10 Cloning and Expression of Determinants Encoding Toxigenicity in Enterobacteria -- 11 Extrachromosomal Replicons in Streptomyces lavendulaegrasserius -- Two: DNA-Dependent RNA Polymerase in Prokaryotes: Structure and Function, Promoter Selection -- 1 Genetic Dissection of E. coli RNA Polymerase -- 2 Non-essential Sequences in the ? Subunit of E. coli RNA Polymerase -- 3 Sequence Analysis of the ? Gene of E. coli RNA Polymerase: Correlation with Structure-Function Studies -- 4 DNA-Dependent RNA Polymerase from Streptomyces granaticolor -- 5 Transcriptional and Translational Signals in Phages PZA and ø29 -- 6 Host-Vector System with the PR' Promoter of Phage Lambda -- 7 On the Difficulties of Defining and Measuring Promoter Strength1 The Case of the Promoters of Bacterial rRNA Genes -- Three: The Role of cAMP in Gene Expression -- 1 Cyclic AMP in Bacteria: Catabolite Repression and Related Effects -- 2 DNA Sequences Involved in Expression and Regulation of deoR-, cytR- and cAMP/CRP-Controlled Genes in Escherichia coli -- 3 Differential Cellular Distribution of Cyclic AMP-Dependent Protein Kinase during Development of Dictyostelium discoideum -- 4 Amplification of the Adenylate Cyclase Gene in Escherichia coli K12 -- 5 Factors Regulating the Activity of Escherichia coli Adenylate Cyclase -- 6 Regulation of Carbohydrate Metabolism by the Bacterial PEP:Sugar Phosphotransferase System -- 7 ATP-Dependent HPr Kinase Involved in Regulation of Carbohydrate Uptake in Gram-positive Bacteria: Inducer Exclusion and Inducer Expulsion -- 8 Regulation of cAMP Synthesis in Streptomyces granaticolor -- 9 Differences in Regulation of a Bacillus megaterium Metalloproteinase during Growth and Sporulation -- Four: Translational Control of Gene Expression -- 1 Ribosomal Protein Sl: "The Messenger RNA-Catching Arm" of Escherichia coli Ribosome -- 2 Initiation of Translation of Genetic Information in Streptomyces aureofaciens -- 3 Bacilli as Hosts for Protein Production -- 4 Structure and Expression of a Chloramphenicol Resistance Gene, cat-86, Cloned from Bacillus pumilus -- 5 An Approach to Controlled Removal of the 3? End of Ribosomal 16S RNA -- 6 Three Ribosomal tRNA-Binding Sites Involved in the Elongation Process -- 7 Structure, Function and Evolution of the 3? Ends of Small Ribosomal Subunit RNA -- 8 Amino Acid Residues In Elongation Factor Tu from Escherichia coli Near the Binding Site for the 3? Terminus of Aminoacyl-tRNA -- 9 Structural and Functional Alterations of Protein-Synthesis Elongation Factor Tu Purified from Streptomyces aureofaciens in an Aggregated State -- 10 Excessive Translational Accuracy Can Inhibit Growth -- 11 Particulate Protein-Synthesis Factors Associated with Translatable mRNA in Mammalian Cells.

Omics techniques have changed the way we depict the molecular features of a cell. The integrative and quantitative analysis of omics data raises unprecedented expectations for understanding biological systems on a global scale. However, its inherently noisy nature, together with limited knowledge of potential sources of variation impacting health and disease, require the use of proper mathematical and computational methods for its analysis and integration. Bayesian inference of probabilistic models allows propagation of the uncertainty from the experimental data to our beliefs of the model parameters, allowing us to appropriately answer complex biological questions. In this chapter, we build probabilistic models of gene expression from RNA-seq data and make inference about their parameters using Bayesian methods. We present models of increasing complexity, from the quantification of a single gene expression to differential gene expression for a whole transcriptome, comparing them to the available tools for analysis of gene expression data. We provide Stan scripts that introduce the reader into the implementation of Bayesian statistics for omics data. The rationale that we apply for transcriptomics data may be easily extended to model the particularities of other omics data and to integrate the different regulatory layers. ; FS-C received support from the Spanish Ministerio de Economía y Competitividad [grant no. RTI2018-102084-B-I00]; EL-P received support from the Spanish Ministerio de Economía y Competitividad (RTI2018-096961-B-I00), from the European Union (CardioNeT-ITN-289600 and CardioNext-ITN-608027) and the Spanish Carlos III Institute of Health (RD12/0042/066); M.A.d.P received support from the Spanish Ministerio de Economía y Competitividad (SAF2017-83130-R) and from the European Union Horizon 2020 research and innovation program under Marie Sklodowska-Curie grant agreement nº 641639 BIOPOL-ITN-641639; V.J-J. received an ESR contract from BIOPOL-ITN-641639). M.A.d.P is member of the Tec4Bio consortium (ref. S2018/NMT4443). The CNIC is supported by MCIU and the Pro-CNIC Foundation and is a Severo Ochoa Center of Excellence [MCIU award SEV-2015-0505]. ; Sí

Drug repositioning using multiple gene expression profiles
Chuo University's Professor Y-h. Taguchi places focus on drug repositioning using multiple gene expression profiles. In my previous manuscripts (1-3), I introduced our studies of in silico drug repositioning using gene expression profiles. Nevertheless, in these studies, we could use the single gene expression profile to perform in silico drug repositioning. In this manuscript, the last one in this series, I introduce our recent study (4) in which we could use multiple gene expression profiles. Please see my previous article for more details about the in silico drug repositioning. (5)In the studies (1-3) introduced previously, I used tensor decomposition (TD) based unsupervised feature extraction (FE) (6,7), which was a mathematical/computational method for data processing and was recently implemented in Bioconductor packages. (8)

The current study was carried out to explore gene expression of the LTB4R gene with the development of chronic myeloid leukemia (CML) in Iraqi patients. The differences in the expression of this gene between patients and healthy controls were studied. The correlation of gender and age with CML patients compared with controls was included as well as the correlation of gene expression folding 2-ΔΔCt of LTB4R with clinical parameters (WBC, RBC, haemoglobin, platelets, and BCR-ABL gene). Results revealed significant increases in the mean of gene expression level (ΔCt) of patient groups compared to the corresponding ΔCt means in the healthy control group, the gene expression folding (2-∆∆Ct) of the LTB4R gene reflects significant differences in the expression showed the highest level in CML patients which reached to (9.12 ), no significant differences were exhibited according to age and gender between CML patients and control. The study revealed a non-significant positive correlation between LTB4R gene expression level with both the BCR-ABL gene and WBC. Our results concluded that the LTB4R gene expression level could act as a marker for the prognosis of CML.

Abstract
Over 60% of trained social workers provide mental health services in their practices, and in all these settings clients are likely to have experienced trauma influencing their current circumstances, including childhood maltreatment and neglect. The 1998 Adverse Childhood Experiences Study has heightened interest in the long-term effects of trauma, especially early in life. Research has shown that our experiences influence our genes' activity through biochemical changes in what is known as epigenetic marks. Yet social work practice has participated minimally in targeting the influences of genes on behavior for research or intervention, partially because of a lack of scientific knowledge. This systematic review examines published research that investigated the influences of early trauma experiences on changes in gene expression related to emotionality and stress response. Authors conducted a systematic literature review according to the steps outlined by Shuster in Google Scholar, PubMed, and PsycINFO. Collected literature was reduced to 76 peer-reviewed articles after applying exclusion criteria. A strong pattern of relationships emerged from the review. Trauma and early life stress were associated with epigenetic marks in offspring on genes linked to stress reactivity (22 studies) and emotionality (23 studies).

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License. ; [Motivation]: Systems biology demands the use of several point of views to get a more comprehensive understanding of biological problems. This usually leads to take into account different data regarding the problem at hand, but it also has to do with using different perspectives of the same data. This multifaceted aspect of systems biology often requires the use of several tools, and it is often hard to get a seamless integration of all of them, which would help the analyst to have an interactive discourse with the data. [Results]: Focusing on expression profiling, BicOverlapper 2.0 visualizes the most relevant aspects of the analysis, including expression data, profiling analysis results and functional annotation. It also integrates several state-of-the-art numerical methods, such as differential expression analysis, gene set enrichment or biclustering. © 2014 The Author. Published by Oxford University Press. All rights reserved. ; This work was supported by the Spanish Government, under the Ministerio de Economía y Competitividad-MINECO (projects BFU2011-28804 and Consolider-Ingenio CSD007-00015) and by the Ministerio de Ciencia e Innovación - MICINN (project FI2010-16234). ; Peer Reviewed