scholarly journals High-sensitivity pattern discovery in large, paired multi-omic datasets

2021 ◽  
Author(s):  
Andrew R Ghazi ◽  
Kathleen Sucipto ◽  
Gholamali Rahnavard ◽  
Eric A Franzosa ◽  
Lauren J McIver ◽  
...  
Keyword(s):  
Similarity Measures ◽  
High Sensitivity ◽  
New Associations ◽  
Association Testing ◽  
Metabolomic Profiling ◽  
Sensitivity Pattern ◽  
Association Discovery ◽  
Synthetic Datasets ◽  
Association Structure ◽  
High Dimensional Datasets

Modern biological screens yield enormous numbers of measurements, and identifying and interpreting statistically significant associations among features is essential. Here, we present a novel hierarchical framework, HAllA (Hierarchical All-against-All association testing), for structured association discovery between paired high-dimensional datasets. HAllA efficiently integrates hierarchical hypothesis testing with false discovery rate correction to reveal significant linear and non-linear block-wise relationships among continuous and/or categorical data. We optimized and evaluated HAllA using heterogeneous synthetic datasets of known association structure, where HAllA outperformed all-against-all and other block testing approaches across a range of common similarity measures. We then applied HAllA to a series of real-world multi-omics datasets, revealing new associations between gene expression and host immune activity, the microbiome and host transcriptome, metabolomic profiling, and human health phenotypes. An open-source implementation of HAllA is freely available at http://huttenhower.sph.harvard.edu/halla along with documentation, demo datasets, and a user group.

scholarly journals Bacteriophage-derived CHAP domain protein, P128, kills Staphylococcus cells by cleaving interpeptide cross-bridge of peptidoglycan

Microbiology ◽  
2014 ◽  
Vol 160 (10) ◽  
pp. 2157-2169 ◽  
Author(s):  
Sudarson Sundarrajan ◽  
Junjappa Raghupatil ◽  
Aradhana Vipra ◽  
Nagalakshmi Narasimhaswamy ◽  
Sanjeev Saravanan ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Mechanism Of Action ◽  
Catalytic Domain ◽  
Antibiotic Sensitivity ◽  
High Sensitivity ◽  
Common Mechanism ◽  
Cross Bridge ◽  
Sensitivity Pattern

P128 is an anti-staphylococcal protein consisting of the Staphylococcus aureus phage-K-derived tail-associated muralytic enzyme (TAME) catalytic domain (Lys16) fused with the cell-wall-binding SH3b domain of lysostaphin. In order to understand the mechanism of action and emergence of resistance to P128, we isolated mutants of Staphylococcus spp., including meticillin-resistant Staphylococcus aureus (MRSA), resistant to P128. In addition to P128, the mutants also showed resistance to Lys16, the catalytic domain of P128. The mutants showed loss of fitness as shown by reduced rate of growth in vitro. One of the mutants tested was found to show reduced virulence in animal models of S. aureus septicaemia suggesting loss of fitness in vivo as well. Analysis of the antibiotic sensitivity pattern showed that the mutants derived from MRSA strains had become sensitive to meticillin and other β-lactams. Interestingly, the mutant cells were resistant to the lytic action of phage K, although the phage was able to adsorb to these cells. Sequencing of the femA gene of three P128-resistant mutants showed either a truncation or deletion in femA, suggesting that improper cross-bridge formation in S. aureus could be causing resistance to P128. Using glutathione S-transferase (GST) fusion peptides as substrates it was found that both P128 and Lys16 were capable of cleaving a pentaglycine sequence, suggesting that P128 might be killing S. aureus by cleaving the pentaglycine cross-bridge of peptidoglycan. Moreover, peptides corresponding to the reported cross-bridge of Staphylococcus haemolyticus (GGSGG, AGSGG), which were not cleaved by lysostaphin, were cleaved efficiently by P128. This was also reflected in high sensitivity of S. haemolyticus to P128. This showed that in spite of sharing a common mechanism of action with lysostaphin, P128 has unique properties, which allow it to act on certain lysostaphin-resistant Staphylococcus strains.

scholarly journals Normalisr: normalization and association testing for single-cell CRISPR screen and co-expression

2021 ◽  
Author(s):  
Lingfei Wang
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Large Scale ◽  
High Sensitivity ◽  
Statistical Hypothesis ◽  
P Value ◽  
Statistical Hypothesis Testing ◽  
Experimental Conditions ◽  
Library Size ◽  
Association Testing

AbstractSingle-cell RNA sequencing (scRNA-seq) provides unprecedented technical and statistical potential to study gene regulation but is subject to technical variations and sparsity. Here we present Normalisr, a linear-model-based normalization and statistical hypothesis testing framework that unifies single-cell differential expression, co-expression, and CRISPR scRNA-seq screen analyses. By systematically detecting and removing nonlinear confounding from library size, Normalisr achieves high sensitivity, specificity, speed, and generalizability across multiple scRNA-seq protocols and experimental conditions with unbiased P-value estimation. We use Normalisr to reconstruct robust gene regulatory networks from trans-effects of gRNAs in large-scale CRISPRi scRNA-seq screens and gene-level co-expression networks from conventional scRNA-seq.

Value of antifungal susceptibility testing in recurrent vulvovaginal Candidiasis by Non -Albicans Candida

2021 ◽  
Vol 30 (1) ◽  
pp. 161-167
Author(s):  
Ghada A. Mokhtar ◽  
Mohamed Sh. Ramadan ◽  
Shymaa Yahia
Keyword(s):  
Amphotericin B ◽  
Candida Species ◽  
Antifungal Susceptibility ◽  
High Sensitivity ◽  
Common Species ◽  
Vulvovaginal Candidiasis ◽  
Recurrent Vulvovaginal Candidiasis ◽  
Sensitivity Pattern ◽  
Vaginal Swabs ◽  
Vitek 2

Background: Vulvovaginal candidiasis (VVC) is regarded as a prevalent vaginal infection and mainly results from Candida albicans. Nevertheless, there has recently been a prominent shift in candidiasis etiology regarding non-albicans Candida (NAC) species with achieving importance. For women with more than three episodes annually are described as recurrent vulvovaginal candidiasis (RVVC). Objectives: To isolate, speciate, and determine the value of antifungal sensitivity pattern of candida species isolated from patients developed (RVVC). Methodology: High vaginal swabs (HVS) were taken from patients with RVVC and cultured on ordinary mycological media. Any significant candida growth was identified and speciated by VITEK 2 system. Their antifungal sensitivity was done by disc diffusion approach governed by CLSI guidelines. Results: A total of 110 Candida species from 250 high vaginal swabs were isolated. Among all candida species isolated from patients with RVCC, C.albicanis accounts for 44% while NAC accounts for 56% with C.glabrata most common species isolated. Voriconazole, amphotericin B, and nystatin showed high sensitivity rates (92 %, 89%, and 84% respectively) on all candida species (C.albicans and NAC) isolated from patients with RVVC. Conclusion: In RVCC there is increase in NAC (56%) with C.glabrata most common species isolated. Voriconazole, Nystatin, and amphotericin B have the best antifungal activity against all spp.

scholarly journals Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis

2020 ◽  
Vol 28 (4) ◽  
pp. 531-561 ◽  
Author(s):  
Andrew Lensen ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Genetic Programming ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Similarity Measures ◽  
Small Subset ◽  
Similarity Functions ◽  
New Approach ◽  
Performance Improvements ◽  
Consistent Performance ◽  
High Dimensional Datasets

Clustering is a difficult and widely studied data mining task, with many varieties of clustering algorithms proposed in the literature. Nearly all algorithms use a similarity measure such as a distance metric (e.g., Euclidean distance) to decide which instances to assign to the same cluster. These similarity measures are generally predefined and cannot be easily tailored to the properties of a particular dataset, which leads to limitations in the quality and the interpretability of the clusters produced. In this article, we propose a new approach to automatically evolving similarity functions for a given clustering algorithm by using genetic programming. We introduce a new genetic programming-based method which automatically selects a small subset of features (feature selection) and then combines them using a variety of functions (feature construction) to produce dynamic and flexible similarity functions that are specifically designed for a given dataset. We demonstrate how the evolved similarity functions can be used to perform clustering using a graph-based representation. The results of a variety of experiments across a range of large, high-dimensional datasets show that the proposed approach can achieve higher and more consistent performance than the benchmark methods. We further extend the proposed approach to automatically produce multiple complementary similarity functions by using a multi-tree approach, which gives further performance improvements. We also analyse the interpretability and structure of the automatically evolved similarity functions to provide insight into how and why they are superior to standard distance metrics.

scholarly journals Isolation Of Extended-Spectrum B-Lactamase (ESBL) Producing Escherichia coli and Klebsiella pneumiae From Dr. Zainoel Abidin General Hospital, Aceh

2019 ◽  
Vol 4 (1) ◽  
pp. 16-22 ◽  
Author(s):  
Zinatul Hayati ◽  
Syamsul Rizal ◽  
Ridhia Putri
Keyword(s):  
Escherichia Coli ◽  
General Hospital ◽  
Clinical Specimen ◽  
Antibiotic Sensitivity ◽  
High Sensitivity ◽  
Clinical Microbiology Laboratory ◽  
Isolation And Identification ◽  
E Coli ◽  
Extended Spectrum ◽  
Sensitivity Pattern

Infection that occurs in Indonesia has increased more significantly than before, compared to the increasing bacterial multidrug resistance (MDR) as the cause of infection. A study conducted in 5 hospitals in Indonesia in 2013 showed that the prevalence rate of extended-spectrum β-lactamase (ESBL)-producing bacteria reached 32-68%. The objective of this study is to detect the prevalence and resistence pattern of ESBL-producing Escherichia coli and Klebsiella pneumoniae in Dr. Zainoel Abidin General Hospital, Banda Aceh. This study was conducted from 1 September 2016 to 31 December 2016. Specimen types included in this study were blood, sputum, urine, pus, mucosal swab, and another body fluids sample. The sampling method in this study was total sampling that is all clinical specimen examined in Clinical Microbiology Laboratory. Isolation and identification ESBL-producing bacteria was performed by VITEK-2 machine (Biomerieux). The result of this study is that a total 122 E. coli and K. pneumoniae were isolated. That consisted of 48 (39%) E. coli isolates and 74 (61%) K. pneumoniae isolates. From 48 E. coli isolates it was found out that 41 (85%) had ESBL phenotypes and from 74 K. pneumoniae isolates it was found out that 59 (80%) had ESBL phenotypes. In total, 100 (82%) isolates from 122 isolates had ESBL phenotypes. Distribution of ESBL-producing E. coli and K. pneumoniae based on sample was 24 (89%) isolates from the total of 27 urine isolates, 18 (95%) isolates from the total of 19 blood isolates, 28 (78%) isolates from the total of 36 sputum isolates, and 30 (75%) isolates from the total of 40 pus isolates. Antibiotic sensitivity pattern of the E. coli and K. pneumoniae isolates had high sensitivity to amycasin dan meropenem which was above 89%. Meanwhile, it also had sensitivity to Fosfomycin and Piperacyclin-Tazobactam by 80% and 77% respectively. Another antibiotic was less effective

scholarly journals EVALUATION OF ANTIBIOTIC SENSITIVITY PATTERN IN ACUTE TONSILLITIS

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
Sadhana Joshi ◽  
Gaurav Parashar
Keyword(s):  
Prospective Observational Study ◽  
Antibiotic Sensitivity ◽  
High Sensitivity ◽  
Acute Tonsillitis ◽  
Sensitivity Pattern ◽  
History Of ◽  
Amoxicillin Clavulanic Acid ◽  
Antibiotics Sensitivity ◽  
Low Sensitivity ◽  
Body Ache

Background: Tonsillitis is a frequent condition noticed in the ENT department of every hospital. One out of every 10 children visiting the ENT OPD, suffer from acute tonsillitis. Methods: This was a prospective observational study conducted on patients coming with a history of throat pain, pain on swallowing, fever, body ache and other constitutional symptoms. Results: Antibiotic resistance was seen in case of the commonly used antibiotics like ampicillin, amoxicillin, Amoxicillin+Clavulanic acid. Cephalosporins were less commonly used antibiotics and showed resistance in 78.00% cases. Cotrimoxazole showed about 16.00% resistant cases. The less commonly used antibiotic was vancomycin however, showed high sensitivity (100%) followed by Linezolid (92.00%) and Clindamycin (82.00%). Erythromycin showed 76% sensitivity while ciprofloxacin showed a low sensitivity of 40.00% followed by Cephalosporins (22.0%). Conclusion: The antibiotic sensitivity pattern could revolutionize the management of chronic tonsillitis. Keywords: Acute tonsillitis, Antibiotics, Sensitivity

scholarly journals Susceptibility Pattern of ESBL Urine Specimens in Non-Intensive Care Room at Ulin General Hospital

2021 ◽  
Vol 27 (3) ◽  
pp. 254
Author(s):  
Alicia Fitri Wulandhany ◽  
Dewi Indah Noviana Pratiwi ◽  
Noor Muthmainah ◽  
Agung Biworo
Keyword(s):  
Intensive Care ◽  
General Hospital ◽  
High Sensitivity ◽  
Density Level ◽  
Beta Lactam ◽  
Cross Sectional ◽  
Intensive Care Patients ◽  
Sensitivity Pattern ◽  
Low Sensitivity ◽  
Urine Specimens

Beta-lactam antibiotic resistance can occur in ESBL-producing bacteria such as E.coli and K.pneumoniae, which can cause UTI. One of the risk factors for infection is the non-intensive care space density level. The objective of this study was to determine the sensitivity pattern of ESBL-producing bacteria in urine specimens of patients in the non-intensive care of Ulin General Hospital, Banjarmasin, in the period of 2016-2018. A descriptive study with a cross-sectional design using data results of urine culture and antibiotic susceptibility patterns data in non-intensive care patients at Ulin General Hospital from 2016 to 2018. The urine test results showed 96 positive isolates of ESBL-producing bacteria, consisting of ESBL-E.coli (69.8%) and ESBL-K.pneumonia (30.2%). Antibiotics with low sensitivity tests were Penicillin, Cephalosporin, Monobactam, and Penicillin/beta-lactam inhibitor combinations. Contrastingly, antibiotics with high sensitivity were Aminoglycoside, Carbapenem, and Glycylcycline. It was concluded from this study that the ESBL-producing bacteria in urine specimens for non-intensive care patients of Banjarmasin Ulin General Hospital in the period of 2016-2018 showed varying sensitivity to antibiotics

scholarly journals Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis

2020 ◽  
Author(s):  
Andrew Lensen ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Genetic Programming ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Similarity Measures ◽  
Small Subset ◽  
Similarity Functions ◽  
New Approach ◽  
Performance Improvements ◽  
Consistent Performance ◽  
High Dimensional Datasets

Clustering is a difficult and widely studied data mining task, with many varieties of clustering algorithms proposed in the literature. Nearly all algorithms use a similarity measure such as a distance metric (e.g., Euclidean distance) to decide which instances to assign to the same cluster. These similarity measures are generally predefined and cannot be easily tailored to the properties of a particular dataset, which leads to limitations in the quality and the interpretability of the clusters produced. In this article, we propose a new approach to automatically evolving similarity functions for a given clustering algorithm by using genetic programming. We introduce a new genetic programming-based method which automatically selects a small subset of features (feature selection) and then combines them using a variety of functions (feature construction) to produce dynamic and flexible similarity functions that are specifically designed for a given dataset. We demonstrate how the evolved similarity functions can be used to perform clustering using a graph-based representation. The results of a variety of experiments across a range of large, high-dimensional datasets show that the proposed approach can achieve higher and more consistent performance than the benchmark methods. We further extend the proposed approach to automatically produce multiple complementary similarity functions by using a multi-tree approach, which gives further performance improvements. We also analyse the interpretability and structure of the automatically evolved similarity functions to provide insight into how and why they are superior to standard distance metrics.

Exploring Similarities Across High-Dimensional Datasets

2007 ◽  
pp. 53-84 ◽  
Author(s):  
Karlton Sequeira ◽  
Mohammed J. Zaki
Keyword(s):  
Breast Cancer ◽  
National Basketball Association ◽  
High Dimensional ◽  
Basketball Player ◽  
Related Data ◽  
Independent Analysis ◽  
Dataset Size ◽  
Synthetic Datasets ◽  
High Dimensional Datasets ◽  
Different Sources

Very often, related data may be collected by a number of sources, which may be unable to share their entire datasets for reasons like confidentiality agreements, dataset size, and so forth. However, these sources may be willing to share a condensed model of their datasets. If some substructures of the condensed models of such datasets, from different sources, are found to be unusually similar, policies successfully applied to one may be successfully applied to the others. In this chapter, we propose a framework for constructing condensed models of datasets and algorithms to find similar substructure in pairs of such models. The algorithms are based on the tensor product. We test our framework on pairs of synthetic datasets and compare our algorithms with an existing one. Finally, we apply it to basketball player statistics for two National Basketball Association (NBA) seasons, and to breast cancer datasets. The results are statistically more interesting than results obtained from independent analysis of the datasets.

scholarly journals Urinary Tract Infections Caused by Staphylococcus saprophyticus and their antimicrobial sensitivity pattern in Young Adult Women

2011 ◽  
Vol 5 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Sanya Tahmina Jhora ◽  
Shikha Paul
Keyword(s):  
Antibiotic Sensitivity ◽  
High Sensitivity ◽  
Adult Women ◽  
Age Group ◽  
Medical College ◽  
Continuous Evaluation ◽  
Antimicrobial Sensitivity ◽  
Sensitivity Pattern ◽  
Group Rate ◽  
Tract Infections

The present study was conducted to observe the antibiotic sensitivity pattern of isolated S. saprophyticus from urine samples of patients admitted in inpatient department or visited the out patient department of Sir Salimullah Medical College & Mitford Hospital (SSMC& MH) Dhaka from October 2002 to September 2003. Among the isolates, Esch.coli was the most predominant (82.61%) urinary pathogens followed by S. saprophyticus (7.01%). 93.10% S.saprophyticus was isolated from females of which highest (44.82%) rate of isolation was among female of 18- 45 years age group. Rate of isolation was also high (41.38%) among female of <18 years age group. All strains of S.saprophyticus (100%) were sensitive to Imipenem. High sensitivity was also observed to gentamicin (86.20%) andceftriaxone (72.41%). Ciprofloxacin was found to be sensitive against 68.96% isolates. Sensitivity of ceftazidime, cephalexin and cloxacillin were 65.51%, 55.17% and 55.17% respectively. However, most of the S. saprophyticus are resistant to ampicillin, nalidixic acid and cotrimoxazole. So, the present study illustrates that physicians and microbiologists must be aware that S. saprophyticus is an important cause of UTIs in young women and there is a need for continuous evaluation of common antibiotics used in the therapy of uropathogens.DOI: http://dx.doi.org/10.3329/bjmm.v5i1.15817 Bangladesh J Med Microbiol 2011; 05 (01): 21-25

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