T cell cytolytic capacity is independent of initial stimulation strength.

How cells respond to myriad stimuli with finite signaling machinery is central to immunology. In naive T cells, the inherent effect of ligand strength on activation pathways and endpoints has remained controversial, confounded by environmental fluctuations and intercellular variability within populations. Here we studied how ligand potency affected the activation of CD8+ T cells in vitro, through the use of genome-wide RNA, multi-dimensional protein and functional measurements in single cells. Our data revealed that strong ligands drove more efficient and uniform activation than did weak ligands, but all activated cells were fully cytolytic. Notably, activation followed the same transcriptional pathways regardless of ligand potency. Thus, stimulation strength did not intrinsically dictate the T cell-activation route or phenotype; instead, it controlled how rapidly and simultaneously the cells initiated activation, allowing limited machinery to elicit wide-ranging responses

Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity

Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR

Non-linear feedback control of robust bi-color LED lighting

Light-emitting diode (LED) technology involves highly complex interactions of heat, light, power and color. Dimming a bi-color LED system with color mixing feature will alter the power and junction temperatures, which in turn shift the color spectra of the LEDs. In this paper, a closed-loop control method based on the nonlinear empirical LED model is proposed for decoupling the dimming control and color control of a bi-color system comprising warm-white and cool-white LEDs. The proposed control scheme has been successfully implemented to provide highly precise and independent control of dimming and correlated color temperature (CCT). Even considering significant changes in ambient temperature, the maximum errors in luminous flux and CCT employing the proposed method are around 3% and 1.78% respectively while the corresponding errors using an existing linear duty-cycle control method are 20% and 27.5% respectively.link_to_OA_fulltex

Precise Dimming and Color Control of LED Systems Based on Color Mixing

This paper proposes a closed-loop nonlinear scheme for precisely controlling the luminosity and correlated color temperature (CCT) of a bicolor adjustable light-emitting diode (LED) lamp. The main objective is to achieve a precise and fully independent dimming and CCT control of the light mixture emitted from a two-string LED lamp comprising warm-white and cool-white color LEDs, regardless of the operating conditions and throughout the long operating lifetime of the LED lamp. The proposed control method is formulated using the nonlinear empirical LED model of the bicolor white LED system. Experimental results show that with the proposed closed-loop nonlinear approach, both CCT and dimming control of the bicolor lamp is significantly more accurate and robust to ambient temperature variations, ambient light interference, and LED aging than the conventional linear approach used in existing products. The maximum error in luminous flux employing the proposed closed-loop nonlinear approach is 3%, compared with 20% using the closed-loop linear approach. The maximum deviation in CCT is only 1.78%, compared with 27.5% with its linear counterpart

Modulation of Resting State Networks After Slow and Periodic Visual Stimulation in Humans

Electronic Poster Session: fMRI: Physiology - abstract no. 5313Periodicity is inherent in numerous external sensory stimuli. However, its effect on large-scale resting state brain networks has not been fully understood. This study investigated brain networks before and after periodic visual stimulation in low frequency (1Hz) using resting state functional MRI. Enhanced connectivity in visual, temporal, salience and ventral attention networks were detected after 1Hz visual stimulation. Furthermore, power spectrum analysis showed increase in infra-slow (<0.1Hz) rsfMRI activity. These findings suggest that slow and periodic visual stimulation initiates and/or facilitates certain neuromodulatory mechanisms such as neural oscillations, leading to increased rsfMRI connectivity

Harnessing CURATE.AI for N-of-1 Optimization Analysis of Combination Therapy in Hypertension Patients: A Retrospective Case Series

10.1002/adtp.202100091Advanced Therapeutics4102100091-210009

Pharmacological Inactivation of Dorsal Hippocampus Enhances Responses and Induces Adaptation to Sound in Midbrain.

Electronic Poster Session: fMRI - Physiology - abstract no. 5310The hippocampus is associated with the memory and learning, meanwhile, receives signal from all sensory system indirectly. However, whether and how the hippocampus influences sound processing in the auditory system remains unclear. Our recent study showed that optogenetic stimulation of hippocampus enhances the brain bilateral auditory cortex connectivity. This fMRI study investigated the influence of hippocampus on auditory processing in the inferior colliculus (IC) by using tetrodotoxin (TTX) to pharmacologically deactivate the dorsal hippocampus. For the first time, our results revealed that the dorsal hippocampus plays a dynamic role in shaping the IC auditory response