Biology subjects

Segal, J.

Publications and source records attributed to Segal, J..

4 recordsLinked to original sources

bioRxiv2025

Azurify integrates cancer genomics with machine learning to classify the clinical significance of somatic variants

Accurate classification of somatic variations from high-throughput sequencing data has become integral to diagnostics and prognostics across various cancers. However, the classification of these variations remains highly manual, inherently variable, and largely inaccessible outside specialized laboratories. Here, we introduce Azurify - a computational tool that integrates machine learning, public resources recommended by professional societies, and clinically annotated data to classify the pathogenicity of variations in precision cancer medicine. Trained on over 15,000 clinically classified variants from 8,202 patients across 138 cancer phenotypes, Azurify achieves 99.1% classification accuracy for concordant pathogenic variants in data from two external clinical laboratories. Additionally, Azurify reliably performs precise molecular profiling in leukemia cases. Azurifys unified, scalable, and modular framework can be easily deployed within bioinformatics pipelines and retrained as new data emerges. In addition to supporting clinical workflows, Azurify offers a high-throughput screening solution for research, enabling genomic studies to identify meaningful variant-disease associations with greater efficiency and consistency.

genomics↗

bioRxiv2021

Unified classification of mouse retinal ganglion cells using function, morphology, and gene expression

Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We used visually-evoked responses to classify 1859 mouse RGCs into 42 types. We also obtained morphological or transcriptomic data from subsets and used these measurements to align the functional classification to publicly available morphological and transcriptomic data sets. We created an online database that allows users to browse or download the data and to classify RGCs from their light responses using a machine learning algorithm. This work provides a resource for studies of RGCs, their upstream circuits in the retina, and their projections in the brain, and establishes a framework for future efforts in neuronal classification and open data distribution.

neuroscience↗

bioRxiv2018

Improving Children’s and Their Visitors’ Hand Hygiene Compliance

BackgroundNumerous interventions have tried to improve healthcare workers hand hygiene compliance, however little attention has been paid to childrens and their visitors compliance.\n\nAimTo increase childrens and visitors compliance using interactive educational interventions.\n\nMethodsThis was an observational study of hand hygiene compliance before and after the introduction of educational interventions. Qualitative data in the form of Questionnaires and interviews was obtained.\n\nFindingsHand hygiene compliance increased by 21.4% (P <0.001) following the educational interventions, with childrens compliance reaching 40.8% and visitors being 50.8%. Compliance varied depending on which of the [fi]ve moments of hygiene was observed (P<0.001), with the highest compliance after body [fl]uid exposure (96%). Responses from questionnaires showed educational interventions raised awareness of the importance of hand hygiene (69%, 57%) compared to those who had not experienced the educational intervention (50%).\n\nConclusionEducational interventions may result in a significant increase in childrens and visitors hand hygiene (P <0.001).

scientific communication and education↗

bioRxiv2018

A central component of the N1 event-related brain potential could index the early and automatic inhibition of the actions systematically activated by objects

Stimuli of the environment, like objects, systematically activate the actions they are associated to. These activations occur extremely fast. Nevertheless, behavioural data reveal that, in most cases, these activations are then automatically inhibited, around 100 ms after the occurrence of the stimulus. We thus tested whether this early inhibition could be indexed by a central component of the N1 event-related brain potential (ERP). To achieve that goal, we looked at whether this ERP component is greater in tasks that could increase the inhibition and in trials where reaction times happen to be long. The illumination of a real space bar of a keyboard out of the dark was used as a stimulus. To maximize the modulation of the inhibition, the task participants had to performed was manipulated across blocks. A look-only task and a count task were used to increase inhibition and an immediate press task was used to decrease it. ERPs of the two block-conditions where presses had to be prevented and where the largest central N1s were predicted were compared to those elicited in the press task, differentiating the ERPs to the third of the trials where presses were the slowest from the ERPs to the third of the trials with the fastest presses. Despite larger negativities due to motor potentials and despite greater attention likely in immediate press-trials, central N1s were found to be minimal for the fastest presses, intermediate for the slowest ones and maximal for the two no-press conditions. These results thus provide a strong support for the idea that the central N1 indexes an early and short lasting automatic inhibition of the actions systematically activated by objects. They also confirm that the strength of this automatic inhibition spontaneously fluctuates across trials and tasks. On the other hand, just before N1s, parietal P1s were found greater for fastest presses. They might thus index the initial activation of these actions. Finally, consistent with the idea that N300s index late inhibition processes, that occur preferentially when the task requires them, these ERPs were quasi absent for fast presses trials and much larger in the three other conditions.\n\nHighlightsEvent-related brain potentials (ERPs) elicited by a real object\n\nSmaller parietal P1s and greater central N1s for slowest than for fastest motor responses\n\nEven greater central N1s for tasks without such responses\n\nCentral N1s may index early inhibition of stimulus-activated actions\n\nN300s could index late inhibition of stimulus-activated actions

animal behavior and cognition↗