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Hickey Saleh posted an update 6 months, 3 weeks ago
Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth.
Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with eithout alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches.
cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.
cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.
Nowadays there is a strong trend towards a circular economy using lignocellulosic biowaste for the production of biofuels and other bio-based products. The use of enzymes at several stages of the production process (e.g., saccharification) can offer a sustainable route due to avoidance of harsh chemicals and high temperatures. For novel enzyme discovery, physically linked gene clusters targeting carbohydrate degradation in bacteria, polysaccharide utilization loci (PULs), are recognized ‘treasure troves’ in the era of exponentially growing numbers of sequenced genomes.
We determined the biochemical properties and structure of a protein of unknown function (PUF) encoded within PULs of metagenomes from beaver droppings and moose rumen enriched on poplar hydrolysate. The corresponding novel bifunctional carbohydrate esterase (CE), now named BD-FAE, displayed feruloyl esterase (FAE) and acetyl esterase activity on simple, synthetic substrates. Whereas acetyl xylan esterase (AcXE) activity was detected on acetng given its capacity to remove ferulic acid and acetic acid from natural corn and birchwood xylan substrates, respectively. Its detailed biochemical characterization and solved crystal structure add to the toolbox of enzymes for biomass valorization as well as structural information to inform the classification of new CEs.
Cutaneous leishmaniasis is a vector-borne parasitic disease whose lasting scars can cause stigmatization and depressive symptoms. It is endemic in remote rural areas and its incidence is under-reported, while the effectiveness, as opposed to efficacy, of its treatments is largely unknown. Here we present the data management plan(DMP) of a project which includes mHealth tools to address these knowledge gaps in Colombia. Calcium folinate chemical structure The objectives of the DMP are to specify the tools and procedures for data collection, data transfer, data entry, creation of analysis dataset, monitoring and archiving.
The DMP includes data from two mobile apps one implements a clinical prediction rule, and the other is for follow-up and treatment of confirmed cases. A desktop interface integrates these data and facilitates their linkage with other sources which include routine surveillance as well as paper and electronic case report forms. Multiple user and programming interfaces are used, as well as multiple relational and non-relational database engines. This DMP describes the successful integration of heterogeneous data sources and technologies. However the complexity of the project meant that the DMP took longer to develop than expected. We describe lessons learned which could be useful for future mHealth projects.
The DMP includes data from two mobile apps one implements a clinical prediction rule, and the other is for follow-up and treatment of confirmed cases. A desktop interface integrates these data and facilitates their linkage with other sources which include routine surveillance as well as paper and electronic case report forms. Multiple user and programming interfaces are used, as well as multiple relational and non-relational database engines. This DMP describes the successful integration of heterogeneous data sources and technologies. However the complexity of the project meant that the DMP took longer to develop than expected. We describe lessons learned which could be useful for future mHealth projects.
To investigate machine-learning (ML) algorithms to differentiate corneal biomechanical properties between different topographical stages of keratoconus (KC) by dynamic Scheimpflug tonometry (CST, Corvis ST, Oculus, Wetzlar, Germany). In the following, ML models were used to predict the severity in a training and validation dataset.
Three hundred and eighteen keratoconic and one hundred sixteen healthy eyes were included in this monocentric and cross-sectional pilot study. Dynamic corneal response (DCR) and corneal thickness related (pachymetric) parameters from CST were chosen by appropriated selection techniques to develop a ML algorithm. The stage of KC was determined by the topographical keratoconus classification system (TKC, Pentacam, Oculus). Patients who were classified as TKC 1, TKC 2 and TKC 3 were assigned to subgroup mild, moderate, and advanced KC. If patients were classified as TKC 1-2, TKC 2-3 or TKC 3-4, they were assigned to subgroups according to the normative range of further corneal indices (index of surface variance, keratoconus index and minimum radius).