Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both our open protocol and a commercial solution, we show high concordance between bulk clonality metrics. This approach is an inexpensive and open-source alternative to commercial solutions.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291816PMC
http://dx.doi.org/10.1186/s12864-023-09424-zDOI Listing

Publication Analysis

Top Keywords

open protocol
8
protocol modeling
4
modeling cell
4
cell clonotype
4
clonotype repertoires
4
repertoires tcrβ
4
tcrβ cdr3
4
cdr3 sequences
4
sequences cell
4
cell receptor
4

Similar Publications

First responders are often exposed to many physically and mentally stressful events throughout their careers, and common complaints include poor sleep quality, chronic pain, post-traumatic stress symptoms, mood dysregulation, and cognitive impairments. We performed an open protocol, active treatment-only study with a small sample of male firefighters ( = 16) to examine the effects of transcranial photobiomodulation (PBM) on self-reported symptom measures and objective measures of cognitive function. The treatment consisted of 810 nm near-infrared light to the head using four transcranial LEDs and one intranasal LED.

View Article and Find Full Text PDF

eHealth Assistant AI Chatbot Using a Large Language Model to Provide Personalized Answers through Secure Decentralized Communication.

Sensors (Basel)

September 2024

Department of Electric, Electronic and Computer Engineering, Technical University of Cluj-Napoca, North University Center of Baia Mare, 430083 Baia Mare, Romania.

In this paper, we present the implementation of an artificial intelligence health assistant designed to complement a previously built eHealth data acquisition system for helping both patients and medical staff. The assistant allows users to query medical information in a smarter, more natural way, respecting patient privacy and using secure communications through a chat style interface based on the Matrix decentralized open protocol. Assistant responses are constructed locally by an interchangeable large language model (LLM) that can form rich and complete answers like most human medical staff would.

View Article and Find Full Text PDF

Motivated by the necessity of guiding and monitoring students when assembling electronic circuits during in-class activities, we propose , an augmented breadboard that enhances synchronous and remote physical computing classes. uses LEDs placed on each row of a breadboard to guide, via four distinct blinking patterns, how to place and connect components and wires. It also uses a set of Input/Output pins to sense voltage levels or to generate voltage output at user-specified rows.

View Article and Find Full Text PDF

T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing.

View Article and Find Full Text PDF

A novel blockchain-based architectural modal for healthcare data integrity: Covid19 screening laboratory use-case.

Procedia Comput Sci

March 2023

Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis (ISTMT), University of Tunis El Manar, Tunisia.

In this paper, we are proposing a blockchain-based architectural model to ensure the integrity of healthcare-sensitive data in an AI-based medical research context. In our approach, we will use the HL7 FHIR standardized data structure to ensure the interoperability of our approach with the existing hospital information systems (HIS). Indeed, structuring the data coming from several heterogeneous sources would enhance its quality.

View Article and Find Full Text PDF