Impact of predictive selection of LbCas12a CRISPR RNAs upon on- and off-target editing rates in soybean.

Clustered regularly interspaced short palindromic repeats (CRISPR) technology has revolutionized creating targeted genetic variation in crops. Although CRISPR enzymes have been reported to have high sequence-specificity, careful design of the editing reagents can also reduce unintended edits at highly homologous sites. This work details the first large-scale study of the heritability of on-target edits and the rate of edits at off-target sites in soybean (), assaying ~700 T1 plants each resulting from transformation with LbCas12a constructs containing CRISPR RNAs (crRNAs) predicted to be either "unique" with no off-target sites or "promiscuous" with >10 potential off-targets in the soybean genome.

Identification and validation of N-acetylputrescine in combination with non-canonical clinical features as a Parkinson's disease biomarker panel.

Parkinson's disease is a progressive neurodegenerative disorder in which loss of dopaminergic neurons in the substantia nigra results in a clinically heterogeneous group with variable motor and non-motor symptoms with a degree of misdiagnosis. Only 3-25% of sporadic Parkinson's patients present with genetic abnormalities that could represent a risk factor, thus environmental, metabolic, and other unknown causes contribute to the pathogenesis of Parkinson's disease, which highlights the critical need for biomarkers. In the present study, we prospectively collected and analyzed plasma samples from 194 Parkinson's disease patients and 197 age-matched non-diseased controls.

Elevated levels of mitochondrial CoQ induce ROS-mediated apoptosis in pancreatic cancer.

Reactive oxygen species (ROS) are implicated in triggering cell signalling events and pathways to promote and maintain tumorigenicity. Chemotherapy and radiation can induce ROS to elicit cell death allows for targeting ROS pathways for effective anti-cancer therapeutics. Coenzyme Q is a critical cofactor in the electron transport chain with complex biological functions that extend beyond mitochondrial respiration.

An Empirical Antigen Selection Method Identifies Neoantigens That Either Elicit Broad Antitumor T-cell Responses or Drive Tumor Growth.

Neoantigens are critical targets of antitumor T-cell responses. The ATLAS bioassay was developed to identify neoantigens empirically by expressing each unique patient-specific tumor mutation individually in , pulsing autologous dendritic cells in an ordered array, and testing the patient's T cells for recognition in an overnight assay. Profiling of T cells from patients with lung cancer revealed both stimulatory and inhibitory responses to individual neoantigens.

A Data-Driven Approach to Predicting Septic Shock in the Intensive Care Unit.

Early diagnosis of sepsis and septic shock has been unambiguously linked to lower mortality and better patient outcomes. Despite this, there is a strong unmet need for a reliable clinical tool that can be used for large-scale automated screening to identify high-risk patients. We addressed the following questions: Can a novel algorithm to identify patients at high risk of septic shock 24 hours before diagnosis be discovered using available clinical data? What are performance characteristics of this predictive algorithm? Can current metrics for evaluation of sepsis be improved using novel algorithm? Publicly available data from the intensive care unit setting was used to build septic shock and control patient cohorts.

Non-obvious correlations to disease management unraveled by Bayesian artificial intelligence analyses of CMS data.

Objective: Given the availability of extensive digitized healthcare data from medical records, claims and prescription information, it is now possible to use hypothesis-free, data-driven approaches to mine medical databases for novel insight. The goal of this analysis was to demonstrate the use of artificial intelligence based methods such as Bayesian networks to open up opportunities for creation of new knowledge in management of chronic conditions.

Materials And Methods: Hospital level Medicare claims data containing discharge numbers for most common diagnoses were analyzed in a hypothesis-free manner using Bayesian networks learning methodology.

Inference of transposable element ancestry.

Most common methods for inferring transposable element (TE) evolutionary relationships are based on dividing TEs into subfamilies using shared diagnostic nucleotides. Although originally justified based on the "master gene" model of TE evolution, computational and experimental work indicates that many of the subfamilies generated by these methods contain multiple source elements. This implies that subfamily-based methods give an incomplete picture of TE relationships.

Discovery of highly divergent repeat landscapes in snake genomes using high-throughput sequencing.

We conducted a comprehensive assessment of genomic repeat content in two snake genomes, the venomous copperhead (Agkistrodon contortrix) and the Burmese python (Python molurus bivittatus). These two genomes are both relatively small (∼1.4 Gb) but have surprisingly extensive differences in the abundance and expansion histories of their repeat elements.