Thermoelectric generator powered timepiece circuit for rechargeable battery operation.

The advent of digital technology has revolutionized the way we keep track of time. Digital watches have become an essential part of our daily lives and provide us with accurate and reliable time measurement. However, battery reliability is a long-standing issue in the digital watch industry. Batteries require frequent replacement and are a major source of waste. To solve this problem, a digital watch that runs on a lithium-polymer battery that is recharged by a voltage generated by a thermoelectric generator (TEG) placed on the hand. The proposed model uses TEG1-19913 that generates power in the range of 11.5 W to 14.5 W with hot end basking at 250 °C and a cold end between 30 °C and 50 °C. The TEG voltage is used to charge the lithium polymer battery, eliminating the need for conventional charging methods. The watch is designed to be compact and lightweight, so it can be worn comfortably for extended periods of time. The TEG is integrated into the watch strap and ensures that it is constantly in contact with the skin. The lithium-polymer battery used in the watch is a high-performance rechargeable battery that has high energy density and long life. In summary, the proposed digital watch is an innovative ecological solution to the problems associated with traditional battery-powered watches. The compact and light design of the watch combined with the energy-efficient display makes it a convenient and efficient timekeeping device.

Deep neural architecture for natural language image synthesis for Tamil text using BASEGAN and hybrid super resolution GAN (HSRGAN).

Tamil is a language that has the most extended history and is a conventional language of India. It has antique origins and a distinct tradition. A study reveals that at the beginning of the twenty-first century, more than 66 million people spoke Tamil. In the present time, image synthesis from text emerged as a promising advancement in computer vision applications. The research work done so far in intelligent systems is trained in universal language but still has not achieved the desired development level in regional languages. Regional languages have a greater scope for developing applications and will enhance more research areas to be explored, ruling out the barrier. The current work using Auto Encoders failed at the point of providing vivid information along with essential descriptions of the synthesised images. The work aims to generate embedding vectors using a language model headed by image synthesis using GAN (Generative Adversarial Network) architecture. The proposed method is divided into two stages: designing a language model TBERTBASECASE model for generating embedding vectors. Synthesising images using Generative Adversarial Network called BASEGAN, the resolution has been improved through two-stage architecture named HYBRID SUPER RESOLUTION GAN. The work uses Oxford-102 and CUB-200 datasets. The framework efficiency has been measured using F1 Score, Fréchet inception distance (FID), and Inception Score (IS). Language and image synthesis architecture proposed can bridge the gap between the research ideas in regional languages.

FOXO1 constrains activation and regulates senescence in CD8 T cells.

Naive and memory T cells are maintained in a quiescent state, yet capable of rapid response and differentiation to antigen challenge via molecular mechanisms that are not fully understood. In naive cells, the deletion of Foxo1 following thymic development results in the increased expression of multiple AP-1 family members, rendering T cells less able to respond to antigenic challenge. Similarly, in the absence of FOXO1, post-infection memory T cells exhibit the characteristics of extended activation and senescence. Age-based analysis of human peripheral T cells reveals that levels of FOXO1 and its downstream target, TCF7, are inversely related to host age, whereas the opposite is found for AP-1 factors. These characteristics of aging also correlate with the formation of T cells manifesting features of cellular senescence. Our work illustrates a role for FOXO1 in the active maintenance of stem-like properties in T cells at the timescales of acute infection and organismal life span.

Affinity and dose of TCR engagement yield proportional enhancer and gene activity in CD4+ T cells.

Affinity and dose of T cell receptor (TCR) interaction with antigens govern the magnitude of CD4+ T cell responses, but questions remain regarding the quantitative translation of TCR engagement into downstream signals. We find that while the response of mouse CD4+ T cells to antigenic stimulation is bimodal, activated cells exhibit analog responses proportional to signal strength. Gene expression output reflects TCR signal strength, providing a signature of T cell activation. Expression changes rely on a pre-established enhancer landscape and quantitative acetylation at AP-1 binding sites. Finally, we show that graded expression of activation genes depends on ERK pathway activation, suggesting that an ERK-AP-1 axis plays an important role in translating TCR signal strength into proportional activation of enhancers and genes essential for T cell function.

Musashi-2 (MSI2) supports TGF-ß signaling and inhibits claudins to promote non-small cell lung cancer (NSCLC) metastasis.

Non-small cell lung cancer (NSCLC) has a 5-y survival rate of ∼16%, with most deaths associated with uncontrolled metastasis. We screened for stem cell identity-related genes preferentially expressed in a panel of cell lines with high versus low metastatic potential, derived from NSCLC tumors of Kras(LA1/+);P53(R172HΔG/+) (KP) mice. The Musashi-2 (MSI2) protein, a regulator of mRNA translation, was consistently elevated in metastasis-competent cell lines. MSI2 was overexpressed in 123 human NSCLC tumor specimens versus normal lung, whereas higher expression was associated with disease progression in an independent set of matched normal/primary tumor/lymph node specimens. Depletion of MSI2 in multiple independent metastatic murine and human NSCLC cell lines reduced invasion and metastatic potential, independent of an effect on proliferation. MSI2 depletion significantly induced expression of proteins associated with epithelial identity, including tight junction proteins [claudin 3 (CLDN3), claudin 5 (CLDN5), and claudin 7 (CLDN7)] and down-regulated direct translational targets associated with epithelial-mesenchymal transition, including the TGF-ß receptor 1 (TGFßR1), the small mothers against decapentaplegic homolog 3 (SMAD3), and the zinc finger proteins SNAI1 (SNAIL) and SNAI2 (SLUG). Overexpression of TGFßRI reversed the loss of invasion associated with MSI2 depletion, whereas overexpression of CLDN7 inhibited MSI2-dependent invasion. Unexpectedly, MSI2 depletion reduced E-cadherin expression, reflecting a mixed epithelial-mesenchymal phenotype. Based on this work, we propose that MSI2 provides essential support for TGFßR1/SMAD3 signaling and contributes to invasive adenocarcinoma of the lung and may serve as a predictive biomarker of NSCLC aggressiveness.

Vespucci: a system for building annotated databases of nascent transcripts.

Global run-on sequencing (GRO-seq) is a recent addition to the series of high-throughput sequencing methods that enables new insights into transcriptional dynamics within a cell. However, GRO-sequencing presents new algorithmic challenges, as existing analysis platforms for ChIP-seq and RNA-seq do not address the unique problem of identifying transcriptional units de novo from short reads located all across the genome. Here, we present a novel algorithm for de novo transcript identification from GRO-sequencing data, along with a system that determines transcript regions, stores them in a relational database and associates them with known reference annotations. We use this method to analyze GRO-sequencing data from primary mouse macrophages and derive novel quantitative insights into the extent and characteristics of non-coding transcription in mammalian cells. In doing so, we demonstrate that Vespucci expands existing annotations for mRNAs and lincRNAs by defining the primary transcript beyond the polyadenylation site. In addition, Vespucci generates assemblies for un-annotated non-coding RNAs such as those transcribed from enhancer-like elements. Vespucci thereby provides a robust system for defining, storing and analyzing diverse classes of primary RNA transcripts that are of increasing biological interest.

Remodeling of the enhancer landscape during macrophage activation is coupled to enhancer transcription.

Recent studies suggest a hierarchical model in which lineage-determining factors act in a collaborative manner to select and prime cell-specific enhancers, thereby enabling signal-dependent transcription factors to bind and function in a cell-type-specific manner. Consistent with this model, TLR4 signaling primarily regulates macrophage gene expression through a pre-existing enhancer landscape. However, TLR4 signaling also induces priming of ∼3,000 enhancer-like regions de novo, enabling visualization of intermediates in enhancer selection and activation. Unexpectedly, we find that enhancer transcription precedes local mono- and dimethylation of histone H3 lysine 4 (H3K4me1/2). H3K4 methylation at de novo enhancers is primarily dependent on the histone methyltransferases Mll1, Mll2/4, and Mll3 and is significantly reduced by inhibition of RNA polymerase II elongation. Collectively, these findings suggest an essential role of enhancer transcription in H3K4me1/2 deposition at de novo enhancers that is independent of potential functions of the resulting eRNA transcripts.