Isolasi Dan Identifikasi Bakteri Aerob Yang Berpotensi Menjadi Sumber Penularan Infeksi Nosokomial Di Irina a Rsup Prof. Dr. R. D. Kandou Manado

: Nosocomial infection or Hospital Acquired Infection (HAI) is an infection caused by bacteria, parasite, or virus in the hospital, infection occur at least 72 hours since hospitalized. This infection occurs due to lack of hygiene of the environment causing microorganism infection from environment to human, infection can also occur due to transmission of microorganism from one patient to other patients. Inpatients potentially have very high risk of nosocomial infection occur due to continuous requiring treatment for more than 24 hours. Purpose: To determine the existence of aerobic bacteria that could potentially be the source of transmission of nosocomial infection in Irina A RSUP Prof. Dr. R. D. Kandou Manado. Method: This research was descriptive with cross sectional approach. Fourteen samples were taken from the surface of medical equipment, bed, floor, and wall of the treatment room and eight samples were taken from the air. Identification of bacteria was performed by culture on agar medium, staining gram, and biochemical test. Result: Bacillus subtilis found in nine samples (41%), Serratia liquefaciens found in five samples (22,7%), Lactobacillus found in two samples (9,1%), Staphylococcus found in two samples (9,1%), Coccus Gram negative found in two samples (9,1%), Enterobacter aerogenes found in one sample (4,5%), and Enterobacter agglomerans found in one sample (4,5%). Conclusion: Bacillus subtilis is the most bacteria which had been found in this research

Using phenotypic similarity to improve rare disease identification in PhenomeCentral

<p>Presentation given by Orion Buske at Genome Informatics 2014 in Cambridge, UK. Covers the current performance of patient matching and gene prioritization algorithms in PhenomeCentral.</p

Additional file 2: Table S2. of Replicate exome-sequencing in a multiple-generation family: improved interpretation of next-generation sequencing data

Titration of percentage target exome sequenced as a function of depth of sequencing thresholds. (XLSX 59 kb

Additional file 1: Figure S1. of Replicate exome-sequencing in a multiple-generation family: improved interpretation of next-generation sequencing data

Systematic approach to study exome capture variability in exome-sequencing (A) Three-generation pedigree in which two individuals have an undiagnosed disease that segregated as an autosomal dominant disorder and a de novo variation arose in the second generation. (B) Model of individual subject sample blood DNA processing and sequencing. A sample of blood went through DNA isolation, and independent libraries (in triplicate) were sequenced to appropriate comparable depth and analyzed for various quality control parameters, target coverage, read depth and nucleotide variation detection. (C) Schematic illustration of sequencing read depth vs. targeted genomic region in relation to exome sequencing in replicate. Listed are also the main approaches taken in this study to analyzed exome replicate data. (D) Two main hypotheses tested using replicate exome data: (i) Biases in sequence capture resulting in poor coverage are addressable through repetition (ii) Library replication is beneficial to overall interpretation of sequence variation data. Figure S2. Titration of percentage targeted exome sequenced as a function of depth of sequencing thresholds in all three replicates per sample. Error bars show standard error for replicate sequencing. As expected, higher depth of sequencing thresholds (x-axis) result in higher-coverage (y-axis) variability in replicate exome data. Table S2.Titration of percentage target exome sequenced as a function of depth of sequencing thresholds (attached excel file). Table S3. Primers used for and results of Sanger sequencing analysis for resolution of replicate discordances in NGS data. Table S4. Primers used for and results of Sanger sequencing validation of de novo variants detected using NGS. (Concordant NGS and Sanger genotypes are highlighted in yellow). Figure S3. Box-plot of GC-content distribution in all first-exons (blue) and high-GC content (>70% GC; >=50 bp length). Table S5. Evaluation of coverage of targeted exons with high GC content (attached excel file). Table S6. Quote from Illumina for exome enrichment kits. Quotes in red indicate costs when the study was undertaken. Nextera prices, and other kit prices (in white) reflect current costs per sample (see last column). (DOC 1 mb

Additional file 1: of Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability

Supplementary Methods - Additional details on methods presented succinctly in main text. (DOCX 53 kb

Additional file 5: Supplementary Figures. of Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability

Figure S1. IGV image and Sanger verification trace files for indel in ARID1B and missense variation in UPF1. Figure S2. UK10K mutation load – counts as per variant annotation type on one patient. Figure S3. Histogram of mutation burden per patient in the UK10K cohort. Figure S4. Pathway interactions showing convergence onto UPP pathway. Figure S5. Plots for CNV distribution for two chromosomes as called by CNAseq. (DOCX 1972 kb

Additional file 4: Table S3. of Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability

UK10K study cohorts that comprise the positive control cohort – Table giving descriptions of the study cohorts from the UK10K project that comprised the positive control cohorts and conditions for use. (XLSX 13 kb

Selected segregation patterns of CNVs in LS-CHD pedigrees.

<p>See legend at the bottom of the figure for explanation of symbols. DNA numbers refer to Tables S1, S2, S3, S4, S5, S6, S7, S8, S9 for affected individuals in whom rare CNVs were identified. A.) In family 5, we identified a maternally inherited gain overlapping <i>PXDNL</i> and a paternally inherited insertion der(9)ins(X;9)(p11.22;q12) overlapping the Cornelia de Lange syndrome gene SMC1A in the severely affected propositus.(NB: Individual 2126 was not initially genotyped on the Affymetrix 6.0 panel and is therefore not described). B.) The severely affected propositus in family 54 showed three different rare CNVs: a paternally inherited gain overlapping SEMA5B, HSPBAP1, DIRC2 and PARP14, a paternally inherited loss of LIMS1, and a <i>de novo</i> partial duplication on chromosome1q21.1. C.) <i>De novo</i> occurrence and non-transmission of a large CNV gain (3817 kb) on chr4p16 overlapping the Ellis van Creveld region on chromosome 4. D.), E.) F.) Segregation of prioritized CNVs with disease in families 18, 21 and 39.</p

Karyotype der(9)ins(X;9)(p11.22;q12) in family 5.

<p>(a,b) FISH was performed on metaphase chromosomes obtained from peripheral blood with a labeled BAC clone that mapped within the detected copy gain (RP11-52N6, red) and a control probe mapped to the Xp/Yp pseudoautosomal region of the sex chromosomes (DXYS129 & DXYS153, green). Green dots show the control probe hybridized to the p arm of chromosomes X and Y. Red dots show the RP11-52N6 BAC clone hybridized on chromosome X (white arrow heads) and in the heterochromatin of chromosome 9 (white arrows). A star shows the normal chromosome 9. These results show that the copy gain is due to a der(9)ins(X;9)(p11.22;q12) in both the father (a) and his son (b). (c). Chromosomal region of the insertion (X;9)(p11.22;q12) in the father and the son of family 5. Four RefSeq genes are identified within this <i>region IQSEC2, RIBC2, HSD17B10</i> and the Cornelia de Lange gene <i>SMC1A</i>. One larger and one smaller CNV have been detected in the DGV database in this region.</p

Overview over lesions.

<p>Distribution of isolated and combined LS-CHD phenotypes. Percents are relative to the total of 174 individuals with cardiovascular malformation.</p>*<p>This number includes one case with hypoplastic left heart syndrome.</p