57 research outputs found
“Where’s the I-O?” Artificial Intelligence and Machine Learning in Talent Management Systems
Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; and in addressing the issue of fairness, we present experimental evidence regarding the potential for AI/ML to evoke adverse reactions from job applicants during selection procedures. We close by emphasizing increased collaboration among I-O psychologists, computer scientists, legal scholars, and members of other professional disciplines in developing, implementing, and evaluating AI/ML applications in organizational contexts
Metal ion-dependent, reversible, protein filament formation by designed beta-roll polypeptides
<p>Abstract</p> <p>Background</p> <p>A right-handed, calcium-dependent β-roll structure found in secreted proteases and repeat-in-toxin proteins was used as a template for the design of minimal, soluble, monomeric polypeptides that would fold in the presence of Ca<sup>2+</sup>. Two polypeptides were synthesised to contain two and four metal-binding sites, respectively, and exploit stacked tryptophan pairs to stabilise the fold and report on the conformational state of the polypeptide.</p> <p>Results</p> <p>Initial analysis of the two polypeptides in the presence of calcium suggested the polypeptides were disordered. The addition of lanthanum to these peptides caused aggregation. Upon further study by right angle light scattering and electron microscopy, the aggregates were identified as ordered protein filaments that required lanthanum to polymerize. These filaments could be disassembled by the addition of a chelating agent. A simple head-to-tail model is proposed for filament formation that explains the metal ion-dependency. The model is supported by the capping of one of the polypeptides with biotin, which disrupts filament formation and provides the ability to control the average length of the filaments.</p> <p>Conclusion</p> <p>Metal ion-dependent, reversible protein filament formation is demonstrated for two designed polypeptides. The polypeptides form filaments that are approximately 3 nm in diameter and several hundred nm in length. They are not amyloid-like in nature as demonstrated by their behaviour in the presence of congo red and thioflavin T. A capping strategy allows for the control of filament length and for potential applications including the "decoration" of a protein filament with various functional moieties.</p
Radiographic Response to Neoadjuvant Therapy in Pleural Mesothelioma Should Serve as a Guide for Patient Selection for Cytoreductive Operations
BACKGROUND: Malignant pleural mesothelioma (MPM) is associated with poor prognosis despite advances in multimodal therapeutic strategies. While patients with resectable disease may benefit from added survival with oncologic resection, patient selection for mesothelioma operations often relies on both objective and subjective evaluation metrics. We sought to evaluate factors associated with improved overall survival (OS) in patients with mesothelioma who underwent macroscopic complete resection (MCR).
METHODS: Patients with MPM who received neoadjuvant therapy and underwent MCR were identified in a prospectively maintained departmental database. Clinicopathologic, blood-based, and radiographic variables were collected and included in a Cox regression analysis (CRA). Response to neoadjuvant therapy was characterized by a change in tumor thickness from pretherapy to preoperative scans using the modified RECIST criteria.
RESULTS: In this study, 99 patients met the inclusion criteria. The median age of the included patients was 64.7 years, who were predominantly men, had smoking and asbestos exposure, and who received neoadjuvant therapy. The median change in tumor thickness following neoadjuvant therapy was -16.5% (interquartile range of -49.7% to +14.2%). CRA demonstrated reduced OS associated with non-epithelioid histology [hazard ratio (HR): 3.06, 95% confidence interval (CI): 1.62-5.78, p \u3c 0.001] and a response to neoadjuvant therapy inferior to the median (HR: 2.70, CI: 1.55-4.72, p \u3c 0.001). Patients who responded poorly (below median) to neoadjuvant therapy had lower median survival (15.8 months compared to 38.2 months, p \u3c 0.001).
CONCLUSION: Poor response to neoadjuvant therapy in patients with MPM is associated with poor outcomes even following maximum surgical cytoreduction and should warrant a patient-centered discussion regarding goals of care and may therefore help guide further therapeutic decisions
oPOSSUM: integrated tools for analysis of regulatory motif over-representation
The identification of over-represented transcription factor binding sites from sets of co-expressed genes provides insights into the mechanisms of regulation for diverse biological contexts. oPOSSUM, an internet-based system for such studies of regulation, has been improved and expanded in this new release. New features include a worm-specific version for investigating binding sites conserved between Caenorhabditis elegans and C. briggsae, as well as a yeast-specific version for the analysis of co-expressed sets of Saccharomyces cerevisiae genes. The human and mouse applications feature improvements in ortholog mapping, sequence alignments and the delineation of multiple alternative promoters. oPOSSUM2, introduced for the analysis of over-represented combinations of motifs in human and mouse genes, has been integrated with the original oPOSSUM system. Analysis using user-defined background gene sets is now supported. The transcription factor binding site models have been updated to include new profiles from the JASPAR database. oPOSSUM is available at http://www.cisreg.ca/oPOSSUM
Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers
We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions
Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework
The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods
Ramucirumab plus docetaxel versus placebo plus docetaxel in patients with locally advanced or metastatic urothelial carcinoma after platinum-based therapy (RANGE): a randomised, double-blind, phase 3 trial
Few treatments with a distinct mechanism of action are available for patients with platinum-refractory advanced or metastatic urothelial carcinoma. We assessed the efficacy and safety of treatment with docetaxel plus either ramucirumab-a human IgG1 VEGFR-2 antagonist-or placebo in this patient population
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