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BioRxiv : the Preprint Server For... Jun 2024Quantifying the kinetics with which memory T cell populations are generated and maintained is essential for identifying the determinants of the duration of immunity. The...
UNLABELLED
Quantifying the kinetics with which memory T cell populations are generated and maintained is essential for identifying the determinants of the duration of immunity. The quality and persistence of circulating CD4 effector memory (T ) and central memory (T ) T cells in mice appear to shift with age, but it is unclear whether these changes are driven by the aging host environment, by cell age effects, or both. Here we address these issues by combining DNA labelling methods, established fate-mapping systems, a novel reporter mouse strain, and mathematical models. Together, these allow us to quantify the dynamics of both young and established circulating memory CD4 T cell subsets, within both young and old mice. We show that that these cells and their descendents become more persistent the longer they reside within the T and T pools. This behaviour may limit memory CD4 T cell diversity by skewing TCR repertoires towards clones generated early in life, but may also compensate for functional defects in new memory cells generated in old age.
AUTHOR SUMMARY
Our long-term protection against infections depends in part on the maintenance of diverse populations of memory CD4 T cells, which are made in response to the initial exposure to the pathogen or a vaccine. These cells are not long-lived, but instead are maintained dynamically at a clonal level through loss and division. Understanding how immune memory persists therefore requires measuring these rates of these processes, and how they might change with age. Here we combine experiments in mice with mathematical models to show that memory CD4 T cells exhibit complex dynamics but increase their capacity to survive as they age. This dynamic implies that as individuals age, their memory CD4 T cell populations become enriched for older clones. This established memory may compensate for functional defects in new T cell responses generated later in life.
PubMed: 38948729
DOI: 10.1101/2023.10.16.562650 -
Biometrika Mar 2024Quantile regression has become a widely used tool for analysing competing risk data. However, quantile regression for competing risk data with a continuous mark is still...
Quantile regression has become a widely used tool for analysing competing risk data. However, quantile regression for competing risk data with a continuous mark is still scarce. The mark variable is an extension of cause of failure in a classical competing risk model where cause of failure is replaced by a continuous mark only observed at uncensored failure times. An example of the continuous mark variable is the genetic distance that measures dissimilarity between the infecting virus and the virus contained in the vaccine construct. In this article, we propose a novel mark-specific quantile regression model. The proposed estimation method borrows strength from data in a neighbourhood of a mark and is based on an induced smoothed estimation equation, which is very different from the existing methods for competing risk data with discrete causes. The asymptotic properties of the resulting estimators are established across mark and quantile continuums. In addition, a mark-specific quantile-type vaccine efficacy is proposed and its statistical inference procedures are developed. Simulation studies are conducted to evaluate the finite sample performances of the proposed estimation and hypothesis testing procedures. An application to the first HIV vaccine efficacy trial is provided.
PubMed: 38948429
DOI: 10.1093/biomet/asad039 -
Lancet Regional Health. Americas Jul 2024During COVID-19 in the US, social determinants of health (SDH) have driven health disparities. However, the use of SDH in COVID-19 vaccine modeling is unclear. This... (Review)
Review
UNLABELLED
During COVID-19 in the US, social determinants of health (SDH) have driven health disparities. However, the use of SDH in COVID-19 vaccine modeling is unclear. This review aimed to summarize the current landscape of incorporating SDH into COVID-19 vaccine transmission modeling in the US. Medline and Embase were searched up to October 2022. We included studies that used transmission modeling to assess the effects of COVID-19 vaccine strategies in the US. Studies' characteristics, factors incorporated into models, and approaches to incorporate these factors were extracted. Ninety-two studies were included. Of these, 11 studies incorporated SDH factors (alone or combined with demographic factors). Various sets of SDH factors were integrated, with occupation being the most common (8 studies), followed by geographical location (5 studies). The results show that few studies incorporate SDHs into their models, highlighting the need for research on SDH impact and approaches to incorporating SDH into modeling.
FUNDING
This research was funded by the Centers for Disease Control and Prevention (CDC).
PubMed: 38948323
DOI: 10.1016/j.lana.2024.100806 -
Npj Imaging 2024Label-free autofluorescence lifetime is a unique feature of the inherent fluorescence signals emitted by natural fluorophores in biological samples. Fluorescence...
Label-free autofluorescence lifetime is a unique feature of the inherent fluorescence signals emitted by natural fluorophores in biological samples. Fluorescence lifetime imaging microscopy (FLIM) can capture these signals enabling comprehensive analyses of biological samples. Despite the fundamental importance and wide application of FLIM in biomedical and clinical sciences, existing methods for analysing FLIM images often struggle to provide rapid and precise interpretations without reliable references, such as histology images, which are usually unavailable alongside FLIM images. To address this issue, we propose a deep learning (DL)-based approach for generating virtual Hematoxylin and Eosin (H&E) staining. By combining an advanced DL model with a contemporary image quality metric, we can generate clinical-grade virtual H&E-stained images from label-free FLIM images acquired on unstained tissue samples. Our experiments also show that the inclusion of lifetime information, an extra dimension beyond intensity, results in more accurate reconstructions of virtual staining when compared to using intensity-only images. This advancement allows for the instant and accurate interpretation of FLIM images at the cellular level without the complexities associated with co-registering FLIM and histology images. Consequently, we are able to identify distinct lifetime signatures of seven different cell types commonly found in the tumour microenvironment, opening up new opportunities towards biomarker-free tissue histology using FLIM across multiple cancer types.
PubMed: 38948152
DOI: 10.1038/s44303-024-00021-7 -
Frontiers in Physiology 2024Proximal tubule (PT) cells maintain a high-capacity apical endocytic pathway to recover essentially all proteins that escape the glomerular filtration barrier. The multi...
Proximal tubule (PT) cells maintain a high-capacity apical endocytic pathway to recover essentially all proteins that escape the glomerular filtration barrier. The multi ligand receptors megalin and cubilin play pivotal roles in the endocytic uptake of normally filtered proteins in PT cells but also contribute to the uptake of nephrotoxic drugs, including aminoglycosides. We previously demonstrated that opossum kidney (OK) cells cultured under continuous fluid shear stress (FSS) are superior to cells cultured under static conditions in recapitulating essential functional properties of PT cells . To identify drivers of the high-capacity, efficient endocytic pathway in the PT, we compared FSS-cultured OK cells with less endocytically active static-cultured OK cells. Megalin and cubilin expression are increased, and endocytic uptake of albumin in FSS-cultured cells is > 5-fold higher compared with cells cultured under static conditions. To understand how differences in receptor expression, distribution, and trafficking rates contribute to increased uptake, we used biochemical, morphological, and mathematical modeling approaches to compare megalin traffic in FSS- versus static-cultured OK cells. Our model predicts that culturing cells under FSS increases the rates of all steps in megalin trafficking. Importantly, the model explains why, despite seemingly counterintuitive observations (a reduced fraction of megalin at the cell surface, higher colocalization with lysosomes, and a shorter half-life of surface-tagged megalin in FSS-cultured cells), uptake of albumin is dramatically increased compared with static-grown cells. We also show that FSS-cultured OK cells more accurately exhibit the mechanisms that mediate uptake of nephrotoxic drugs compared with static-grown cells. This culture model thus provides a useful platform to understand drug uptake mechanisms, with implications for developing interventions in nephrotoxic injury prevention.
PubMed: 38948083
DOI: 10.3389/fphys.2024.1404248 -
Theranostics 2024Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with several RPTs already well established in the treatment of several different... (Review)
Review
Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with several RPTs already well established in the treatment of several different types of cancers. However, the current approaches to RPTs often follow a somewhat inflexible "one size fits all" paradigm, where patients are administered the same amount of radioactivity per cycle regardless of their individual characteristics and features. This approach fails to consider inter-patient variations in radiopharmacokinetics, radiation biology, and immunological factors, which can significantly impact treatment outcomes. To address this limitation, we propose the development of theranostic digital twins (TDTs) to personalize RPTs based on actual patient data. Our proposed roadmap outlines the steps needed to create and refine TDTs that can optimize radiation dose to tumors while minimizing toxicity to organs at risk. The TDT models incorporate physiologically-based radiopharmacokinetic (PBRPK) models, which are additionally linked to a radiobiological optimizer and an immunological modulator, taking into account factors that influence RPT response. By using TDT models, we envisage the ability to perform virtual clinical trials, selecting therapies towards improved treatment outcomes while minimizing risks associated with secondary effects. This framework could empower practitioners to ultimately develop tailored RPT solutions for subgroups and individual patients, thus improving the precision, accuracy, and efficacy of treatments while minimizing risks to patients. By incorporating TDT models into RPTs, we can pave the way for a new era of precision medicine in cancer treatment
PubMed: 38948052
DOI: 10.7150/thno.93973 -
Heliyon Jun 2024In recent decades, water scarcity has turned into a serious problem spanning many countries, now even capable of causing or inflaming ethnic and national conflicts....
In recent decades, water scarcity has turned into a serious problem spanning many countries, now even capable of causing or inflaming ethnic and national conflicts. While our planet has very limited freshwater resources, it has huge amounts of saltwater in seas and oceans. There is a very limited number of ways that can make saltwater drinkable, the most important of them is desalination. This study aimed to provide a method for the simultaneous optimization of desalination plant location and its water distribution network based on mathematical modeling. For this purpose, the authors formulated a non-linear mathematical model with the objective of minimizing the costs of water production and transmission. A genetic algorithm was also developed for solving the proposed nonlinear model. The method was used in a case study of Sistan and Baluchestan, which is one of Iran's most water stressed provinces. The proposed genetic algorithm managed to provide an acceptable solution for this problem in 3.74 s. The best solution was found to be constructing a desalination facility with a capacity of 394,052 cubic meters per day in a single location, that is, the city of Chabahar. The water transmission lines needed for transporting water to other parts of the province and their capacities were also determined.
PubMed: 38948037
DOI: 10.1016/j.heliyon.2024.e32758 -
Bioinformatics Advances 2024The data sharing of large comprehensive cancer research projects, such as The Cancer Genome Atlas (TCGA), has improved the availability of high-quality data to research...
MOTIVATION
The data sharing of large comprehensive cancer research projects, such as The Cancer Genome Atlas (TCGA), has improved the availability of high-quality data to research labs around the world. However, due to the volume and inherent complexity of high-throughput omics data, analysis of this is limited by the capacity for performing data processing through programming languages such as R or Python. Existing webtools lack functionality that supports large-scale analysis; typically, users can only input one gene, or a gene list condensed into a gene set, instead of individual gene-level analysis. Furthermore, analysis results are usually displayed without other sample-level molecular or clinical annotations. To address these gaps in the existing webtools, we have developed Evergene using R and Shiny.
RESULTS
Evergene is a user-friendly webtool that utilizes RNA-sequencing data, alongside other sample and clinical annotation, for large-scale gene-centric analysis, including principal component analysis (PCA), survival analysis (SA), and correlation analysis (CA). Moreover, Evergene achieves in-depth analysis of cancer transcriptomic data which can be explored through dimensional reduction methods, relating gene expression with clinical events or other sample information, such as ethnicity, histological classification, and molecular indices. Lastly, users can upload custom data to Evergene for analysis.
AVAILABILITY AND IMPLEMENTATION
Evergene webtool is available at https://bshihlab.shinyapps.io/evergene/. The source code and example user input dataset are available at https://github.com/bshihlab/evergene.
PubMed: 38948009
DOI: 10.1093/bioadv/vbae092 -
Chemistry of Materials : a Publication... Jun 2024Thermal annealing is the most common postdeposition technique used to crystallize antimony selenide (SbSe) thin films. However, due to slow processing speeds and a high...
Thermal annealing is the most common postdeposition technique used to crystallize antimony selenide (SbSe) thin films. However, due to slow processing speeds and a high energy cost, it is incompatible with the upscaling and commercialization of SbSe for future photovoltaics. Herein, for the first time, a fast-annealing technique that uses millisecond light pulses to deliver energy to the sample is adapted to cure thermally evaporated SbSe films. This study demonstrates how photonic curing (PC) conditions affect the outcome of SbSe phase conversion from amorphous to crystalline by evaluating the films' crystalline, morphological, and optical properties. We show that SbSe is readily converted under a variety of different conditions, but the zone where suitable films for optoelectronic applications are obtained is a small region of the parameter space. SbSe annealing with short pulses (<3 ms) shows significant damage to the sample, while using longer pulses (>5 ms) and a 4-5 J cm radiant energy produces (211)- and (221)-oriented crystalline SbSe with minimal to no damage to the sample. A proof-of-concept photonically cured SbSe photovoltaic device is demonstrated. PC is a promising annealing method for large-area, high-throughput annealing of SbSe with various potential applications in SbSe photovoltaics.
PubMed: 38947981
DOI: 10.1021/acs.chemmater.4c00540 -
Frontiers in Chemistry 2024The deterioration of mild steel in an acidic environment poses a significant challenge in various industries. The emergence of effective corrosion inhibitors has drawn...
Unraveling the corrosion inhibition behavior of prinivil drug on mild steel in 1M HCl corrosive solution: insights from density functional theory, molecular dynamics, and experimental approaches.
The deterioration of mild steel in an acidic environment poses a significant challenge in various industries. The emergence of effective corrosion inhibitors has drawn attention to studies aimed at reducing the harmful consequences of corrosion. In this study, the corrosion inhibition efficiency of Prinivil in a 1M HCl solution through various electrochemical and gravimetric techniques has been investigated for the first time. The results demonstrated that the inhibition efficiency of Prinivil expanded from 61.37% at 50 ppm to 97.35% at 500 ppm concentration at 298 K. With a regression coefficient ( ) of 0.987, K value of 0.935 and E value of 43.024 kJ/mol at 500 ppm concentration of inhibitor, a strong affinity of Prinivil for adsorption onto the metal surface has been significantly found. Scanning electron microscopy (SEM) and contact angle measurement analyses further support the inhibitory behavior of Prinivil, demonstrating the production of a defensive layer on the surface of mild steel. Additionally, molecular dynamics (MD) and Monte Carlo simulations were employed to investigate the stability and interactions between Prinivil and the metallic surface (Fe (1 1 0)) at the atomic level. The computed results reveal strong adsorption of Prinivil upon the steel surface, confirming its viability as a corrosion inhibitor.
PubMed: 38947959
DOI: 10.3389/fchem.2024.1403118