Variation In Expression Research Articles

The expression of quantity in Oneida: a study in syntactic and semantic variation

Abstract One of the questions linguists try to answer is to what extent conceptual content is expressed similarly across languages. The null hypothesis is that languages express the same sorts of things but may differ in the particular morphological and syntactic constructions they use. This paper describes one semantic domain, quantification over objects in Oneida (Northern Iroquoian), where there is both variation in expression and variation in expressibility. Through a detailed and comprehensive description of quantificational expressions, we show that in Oneida quantification is pervasively and almost exclusively expressed by productive verb forms that are not number words; moreover, these verb forms head clauses (count clauses) adjoined to main clauses. We argue that to this morphosyntactic difference between Oneida and most languages corresponds a semantic difference, namely that in Oneida quantificational expressions denote properties of sets, whereas in most other languages they denote relations between sets (or between entities and sets), and this difference accounts for the systematic absence of proportional and partitive quantifiers in Oneida.

Genome-wide identification and expression analysis of watermelon (Citrullus lanatus) SSR2 gene during fruit development

BackgroundSterol side-chain reductase 2 (SSR2) is a key enzyme in the synthesis of plant cholesterol pathway. Despite the importance of watermelon as a horticultural cash crop, the SSR2 gene in watermelon has not been previously studied or reported.ResultsIn this study, 28 SSR2 genes were identified in the watermelon genome. The physicochemical properties of 28 ClaSSR proteins were predicted by bioinformatics methods, and the gene structure, conserved motif, chromosome localization, phylogenetic analysis, cis-acting elements, expression patterns, promoter activity analysis and subcellular localization of ClaSSRs were studied. The 28 ClaSSRs were unevenly distributed on 11 chromosomes, and phylogenetic analysis showed that they could be grouped into 4 groups with other related Cucurbitaceae homologous genes. Analysis of gene structure and motifs revealed similarities in exons/introns and motifs between members of the same group, further supporting phylogenetic results. The RT–qPCR results showed variations in ClaSSRs expression during watermelon fruit development. The analysis of promoter activity for ClaSSR25 showed strong activity. Subcellular localization studies confirmed that ClaSSR25 is mainly located in the cytoplasm, which aligns with the predicted outcomes. We additionally estimated the network of protein–protein interactions for ClaSSR25 and analyzed proteins that could potentially interact with ClaSSR25 in melon and Arabidopsis thaliana.ConclusionsWe conducted bioinformatics analysis and expression analysis of members of the watermelon SSR2 gene family in this work, and the outcomes set the stage for further investigations into the watermelon SSR2 gene.Graphical

Fine‐scale phenotypic variation of a large herbivore in a pulsed environment

AbstractThe resource rule hypothesis predicts that geographic differences in body size among populations of organisms are due to the amount, availability, and quality of food resources. For instance, the body size of large herbivores is often correlated with soil characteristics because better soils produce better forage. In semiarid environments, rainfall variation is an important driver of forage availability, especially highly nutritious annual forbs. Thus, in such pulsed‐resource environments, it is unclear whether the body size of large herbivores is influenced by fixed resources correlated with soil characteristics, irregular resource pulses correlated with rainfall, or both. Furthermore, it is not clear whether phenotypic expression is a function of forage quality or quantity. During the early autumns of 2011–2018, we captured 4554 white‐tailed deer (Odocoileus virginianus) on seven rangeland sites in the semiarid climate of South Texas, USA. The sites range from coastal to 140 km inland and represent gradients in both soil texture and annual rainfall. We recorded age‐ and sex‐specific indices of skeletal size, antler size, and body mass. Site‐specific soil characteristics explained most of the variation in skeletal size; percent sand was inversely related to skeletal size. For environmentally sensitive phenotypes (antler size and body mass), both soil characteristics and rainfall were influencers; increases in rainfall reduced the negative effect of sand. Percent sand and rainfall were positively correlated with annual biomass of preferred forbs, yet all phenotypic traits declined with increases in forb quantity. Increases in percent shrub cover increased all phenotype sizes. Our data suggest that the phenotypic expression of large herbivores in semiarid environments is driven by forage quality via edaphic characteristics rather than forage quantity via rainfall. Specifically, less sand in the soil allows for the development of shrub communities, which in turn provide a consistent source of forage in a variable, pulsed‐rainfall environment. Although forbs are of higher quality, they are highly ephemeral. The availability of a consistent source of forage may enable white‐tailed deer to extend time invested in body growth, which results in greater phenotype size. Our findings align with the resource rule hypothesis that identifies resource availability as a fundamental element explaining geographical variation in phenotypic expression.

Exploring the role of RNASET2 in the immune response of black soldier fly larvae.

T2 RNases are transferase-type enzymes distributed across phyla, crucial for breaking down single-stranded RNA molecules. In addition to their canonical function, several T2 enzymes exhibit pleiotropic roles, contributing to various biological processes, such as the immune response in invertebrates and vertebrates. This study aims at characterizing RNASET2 in the larvae of black soldier fly (BSF), Hermetia illucens, which are used for organic waste reduction and the production of valuable insect biomolecules for feed formulation and other applications. Given the exposure of BSF larvae to pathogens present in the feeding substrate, it is likely that the mechanisms of their immune response have undergone significant evolution and increased complexity. After in silico characterization of HiRNASET2, demonstrating the high conservation of this T2 homolog, we investigated the expression pattern of the enzyme in the fat body and hemocytes, two districts mainly involved in the insect immune response, in larvae challenged with bacterial infection. While no variation in HiRNASET2 expression was observed in the fat body following infection, a significant upregulation of HiRNASET2 synthesis occurred in hemocytes shortly after the injection of bacteria in the larva. The intracellular localization of HiRNASET2 in lysosomes of plasmatocytes, its extracellular association with bacteria, and the presence of a putative antimicrobial domain in the molecule, suggest its potential role in RNA clean-up and as an alarm molecule promoting phagocytosis activation by hemocytes. These insights contribute to the characterization of the immune response ofHermetia illucens larvae and may facilitate the development of animal feedstuff enriched with highly valuable BSF bioactive compounds.

Pervasive tissue-, genetic background-, and allele-specific gene expression effects in Drosophila melanogaster.

The pervasiveness of gene expression variation and its contribution to phenotypic variation and evolution is well known. This gene expression variation is context dependent, with differences in regulatory architecture often associated with intrinsic and environmental factors, and is modulated by regulatory elements that can act in cis (linked) or in trans (unlinked) relative to the genes they affect. So far, little is known about how this genetic variation affects the evolution of regulatory architecture among closely related tissues during population divergence. To address this question, we analyzed gene expression in the midgut, hindgut, and Malpighian tubule as well as microbiome composition in the two gut tissues in four Drosophila melanogaster strains and their F1 hybrids from two divergent populations: one from the derived, European range and one from the ancestral, African range. In both the transcriptome and microbiome data, we detected extensive tissue- and genetic background-specific effects, including effects of genetic background on overall tissue specificity. Tissue-specific effects were typically stronger than genetic background-specific effects, although the two gut tissues were not more similar to each other than to the Malpighian tubules. An examination of allele specific expression revealed that, while both cis and trans effects were more tissue-specific in genes expressed differentially between populations than genes with conserved expression, trans effects were more tissue-specific than cis effects. Despite there being highly variable regulatory architecture, this observation was robust across tissues and genetic backgrounds, suggesting that the expression of trans variation can be spatially fine-tuned as well as or better than cis variation during population divergence and yielding new insights into cis and trans regulatory evolution.

The values of schools: an analysis of vision statements

School vision statements articulate an aspired future state for the school, highlighting its ideals, purpose, and unique aspects to direct behavior and promote motivation and commitment among stakeholders. This paper investigates vision statements of schools as artifacts expressing the values emphasized by schools, drawing on organizational literature that shows the role of central organizational artifacts in conveying the values important to the organization. Using a comprehensive sample of elementary schools across all districts in Israel (N = 99), we built on Schwartz’s values theory to identify values and analyze expressed values. We employed a mixed methods approach, combining qualitative and quantitative methods to analyze these values. First, we analyzed the content of vision statements to investigate how values were manifested. Then, we investigated the values hierarchy reflected in the vision statements, and compared sectors to identify the impact of the broader social context. Our analysis revealed variation in values expression: as expected, self-direction and benevolence emerged as the most prevalent values in school vision statements; power and hedonism were less salient. Comparison of vision statements from public and public-religious schools, as well as across schools with varying socioeconomic status (SES), revealed differences in universalism values. Public schools and those with higher SES placed greater importance on universalism values compared to public-religious schools. Additionally, tradition values were less prominent in public schools but were the second most significant values in public-religious schools. We discuss the results within the framework of values theory and educational policy.

Comparative Transcriptomic and Lipidomic Analysis of Fatty Acid Accumulation in Three Camellia oleifera Varieties During Seed Maturing.

Camellia oleifera, a major woody oil crop in China, produces tea oil rich in unsaturated fatty acids, earning it names like liquid gold and eastern olive oil. This study provides an integrated investigation of the transcriptome and lipidome within seeds at the maturing process across three C. oleifera varieties, revealing a significant relationship between fatty acid production and genes involved in lipid synthesis. Through transcriptomic analysis, 26,344 genes with varied expression were found. Functional enrichment analysis highlighted that pathways related to starch and sucrose metabolism, plant hormone signal transduction, and lipid accumulation were highly enriched among the differentially expressed genes. Coordinated high expression of key genes (ACCase, KAS I, KAS II, KAS III, KAR, HAD, EAR, SAD, LPAAT, LACS, DGAT, PDAT) during the late maturation stage contributes largely to high oil content. Additionally, expression variations of SAD and FADs among different varieties were explored. The analysis suggests that high expression of genes such as FAD3, FAD7, and FAD8 notably increased linolenic acid content. This research provides new insights into the molecular mechanisms of oil biosynthesis in C. oleifera, offering valuable references for improving yield and quality.

Response signatures of intestinal microbiota and gene transcription of yellow catfish (Pelteobagrus fulvidraco) to Aeromonas hydrophila infection

Bacterial intestinal inflammation is a common disease of yellow catfish (Pelteobagrus fulvidraco) in high-density aquaculture. Understanding the interactions between host and intestinal bacteria is helpful to intestinal inflammatory disease control. Here, we constructed a model of intestinal inflammation after Aeromonas hydrophila infection in yellow catfish, and characterized variations in gene expression and microbiome in the gut through high-throughput sequencing. Furthermore, host gene-microbiome interactions were identified. Histology observation showed disordered distribution of columnar epithelial cells and decrease of goblet cells in intestine. A total of 4741 genes showed differentially expression, mostly in comparisons between 12 hpi group with each other groups respectively, including control, 24 hpi and 48 hpi groups. These genes were enriched in immune-related pathways including the IL-17 signaling pathway, triggering strong inflammatory response at the invading stage within 12 h. Subsequently, the host strengthened energy consumption by activating carbohydrate and lipid metabolism pathways to repair the intestinal mucosal immune defense line. In addition, fish with A. hydrophila infection show decreased richness of gut microbial, reduced relative abundance of probiotics including Akkermansia, and elevated pathogenic bacteria such as Plesimonas. An integrative analysis identified A. hydrophila-related genes, such as il22 and stat3, for which expression level is close associated with the shift of A. hydrophila-related bacteria relative abundance, such as Akkermansia and Cetobacterium. Aside from picturing the variations of intestine gene expression and mucosal microbiome of yellow catfish coping with A. hydrophila infection, our study probed the underlying host-microbe interactions in A. hydrophila infection induced intestinal inflammatory, providing new insights for disease control in aquaculture.

Characterization of GPX Gene Family in Pepper (Capsicum annuum L.) under Abiotic Stress and ABA Treatment.

Plant glutathione peroxidases (GPXs) are important enzymes for removing reactive oxygen species in plant cells and are closely related to the stress resistance of plants. This study identified the GPX gene family members of pepper (Capsicum annuum L.), "CM333", at the whole-genome level to clarify their expression patterns and enzyme activity changes under abiotic stress and ABA treatment. The results showed that eight CaGPX genes were unevenly distributed across four chromosomes and one scaffold of the pepper genome, and their protein sequences had Cys residues typical of the plant GPX domains. The analysis of collinearity, phylogenetic tree, gene structure, and conserved motifs indicated that the CaGPX gene sequence is conserved, structurally similar, and more closely related to the sequence structure of Arabidopsis. Meanwhile, many cis elements involved in stress, hormones, development, and light response were found in the promoter region of the CaGPX gene. In addition, CaGPX1/4 and CaGPX6 were basically expressed in all tissues, and their expression levels were significantly upregulated under abiotic stress and ABA treatment. Subcellular localization showed that CaGPX1 and CaGPX4 are localized in chloroplasts. Additionally, the variations in glutathione peroxidase activity (GSH-Px) mostly agreed with the variations in gene expression. In summary, the CaGPXs gene may play an important role in the development of peppers and their response to abiotic stress and hormones.

Submandibular gland tissue RNAseq and spatial transcriptome analyses in IgG4-related disease.

To identify genes that could provide clues leading to the discovery of drugs to treat IgG4-related disease (IgG4-RD). Submandibular gland tissue bulk RNAseq analysis of 45 cases with a definite diagnosis of IgG4-RD was integrated with Visium spatial transcriptome analysis of 2 cases to identify pathogenic genes expressed in tertiary lymphoid tissues. Bulk RNAseq and pathway analyses showed upregulation of cell cycle and T cell-related signals in IgG4-RD. Spatial transcriptome analysis identified the cluster corresponding to germinal centers and the top 38 common genes that showed significant variations in expression compared with other clusters. The top 20 genes were extracted by comparing the bulk RNAseq data. Network analysis identified CDK1 as the ge most strongly associated of the top 20 genes. The CDK1 gene may be a regulator of the pathogenesis of IgG4-RD and provide clues for drug discovery.

Endocannabinoid and neuroplasticity-related changes as susceptibility factors in a rat model of posttraumatic stress disorder

Traumatic experiences result in the development of posttraumatic stress disorder (PTSD) in 10–25% of exposed individuals. While human clinical studies suggest that susceptibility is potentially linked to endocannabinoid (eCB) signaling, neurobiological PTSD susceptibility factors are poorly understood. Employing a rat model of contextual conditioned fear, we characterized distinct resilient and susceptible subpopulations based on lasting generalized fear, a core symptom of PTSD. In these groups, we assessed i.) eCB levels by mass spectrometry and ii.) expression variations of eCB system- and iii.) neuroplasticity-related genes by real-time quantitative PCR in the circuitry relevant in trauma-induced changes. Furthermore, employing unsupervised and semi-supervised machine learning based statistical analytical models, we assessed iv.) gene expression patterns with the most robust predictive power regarding PTSD susceptibility. According to our findings, in our model, generalized fear responses occurred with sufficient variability to characterize distinct resilient and susceptible subpopulations. Resilient subjects showed elevated prelimbic and lower ventral hippocampal levels of eCB 2-arachidonoyl-glycerol (2-AG) compared to resilient and non-shocked control subjects. Ventral hippocampal 2-AG content positively correlated with the strength of fear generalization. Furthermore, susceptibility was associated with i.) prefrontal, hippocampal and amygdalar neuronal hypoactivity, ii.) marked decrease in the expression of genes of transcription factors modulating neuroplasticity and iii.) an altered expression pattern of eCB-related genes, including enzymes involved in eCB metabolism. Unsupervised and semi-supervised statistical approaches highlighted that hippocampal gene expression patterns possess strong predictive power regarding susceptibility. Taken together, the marked eCB and neuroplasticity changes in susceptible individuals associated with abnormal activity patterns in the fear circuitry possibly contribute to context coding deficits, resulting in generalized fear.

A real-world multi-center RNA-seq benchmarking study using the Quartet and MAQC reference materials

Translating RNA-seq into clinical diagnostics requires ensuring the reliability and cross-laboratory consistency of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. As part of the Quartet project, we present an RNA-seq benchmarking study across 45 laboratories using the Quartet and MAQC reference samples spiked with ERCC controls. Based on multiple types of ‘ground truth’, we systematically assess the real-world RNA-seq performance and investigate the influencing factors involved in 26 experimental processes and 140 bioinformatics pipelines. Here we show greater inter-laboratory variations in detecting subtle differential expressions among the Quartet samples. Experimental factors including mRNA enrichment and strandedness, and each bioinformatics step, emerge as primary sources of variations in gene expression. We underscore the profound influence of experimental execution, and provide best practice recommendations for experimental designs, strategies for filtering low-expression genes, and the optimal gene annotation and analysis pipelines. In summary, this study lays the foundation for developing and quality control of RNA-seq for clinical diagnostic purposes.

Sources of gene expression variation in a globally diverse human cohort.

Genetic variation that influences gene expression and splicing is a key source of phenotypic diversity1-5. Although invaluable, studies investigating these links in humans have been strongly biased towards participants of European ancestries, which constrains generalizability and hinders evolutionary research. Here to address these limitations, we developed MAGE, an open-access RNA sequencing dataset of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project6, spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, which mirrored the variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-expression quantitative trait loci (eQTLs) and cis-splicing QTLs (sQTLs), respectively). We identified more than 15,000 putatively causal eQTLs and more than 16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1,310 eQTLs and 1,657 sQTLs that are largely private to underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations. Moreover, the apparent 'population-specific' effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands our understanding of human gene expression diversity and provides an inclusive resource for studying the evolution and function of human genomes.

"Capable of much more": The effects of vocational training on caregiver expectations for neurodivergent dependents in Thailand.

Neurodivergence encompasses a spectrum of natural variations in neurological development, including autism, ADHD, and other expressions of cognitive diversity. Caregiver experiences while supporting their neurodivergent dependents critically influence the quality of life outcomes for neurodivergent dependents across life stages, including during the search for work. However, research on caregiver experiences during this stage remains scarce, especially within lesser studied developing contexts like Thailand. This study explored perspectives of Thai caregivers preparing neurodivergent dependents for employment through a focus group (n = 10) of pre-vocational training caregivers and interviews (n = 13) with post-training caregivers. Analysis revealed significant sociocultural factors introducing stigma that affected acceptance, diagnosis, interventions, and policy support. Both groups reported systemic barriers, doubts about future independence, and hopes to increase advocacy and inclusive attitudes. However, caregivers whose dependents had received the training showed marked shifts in their expectations for their dependents' success. Tailored vocational preparation helping dependents exhibit strengths may transform societal views on neurodiversity from deficiency to natural diversity and enable more meaningful, sustainable futures. These insights elucidate caregiver challenges and aspirations, which can better inform supportive research and interventions in Thailand and other non-Western locales.

Perbandingan Dataset Labelled Faces in the Wild (LFW) dan faces94 Menggunakan Algoritma Convolutional Neural Networks (CNN) untuk Pengenalan Wajah

This research compares the performance of two popular datasets, Labelled Faces in the Wild (LFW) and faces94, in the task of face recognition using Convolutional Neural Networks (CNN) algorithms. The LFW dataset is known for its high variation in pose, lighting, and expression, while faces94 is more structured with more uniform lighting and pose conditions. CNNs were chosen for their ability to extract important features from face images for classification. In this study, a CNN model was trained on both datasets and its performance was evaluated using accuracy, precision, and recall metrics. The experimental results showed that the model trained on the faces94 dataset achieved higher accuracy compared to the model trained on the LFW dataset. However, the model on the LFW dataset demonstrated better resilience to variations in lighting and pose conditions. These findings indicate that while a more structured dataset like faces94 can produce a model with high accuracy under testing conditions similar to the training data, a dataset with greater variation like LFW is more suitable for real-world applications involving diverse conditions. This study provides important insights into the selection of datasets for developing robust and accurate face recognition systems.

Evolution of the regulation of developmental gene expression in blind Mexican cavefish.

Developmental evolution and diversification of morphology can arise through changes in the regulation of gene expression or protein-coding sequence. To unravel mechanisms underlying early developmental evolution in cavefish of the species Astyanax mexicanus, we compared transcriptomes of surface-dwelling and blind cave-adapted morphs at the end of gastrulation. Twenty percent of the transcriptome was differentially expressed. Allelic expression ratios in cave X surface hybrids showed that cis-regulatory changes are the quasi-exclusive contributors to inter-morph variations in gene expression. Among a list of 108 genes with change at the cis-regulatory level, we explored the control of expression of rx3, which is a master eye gene. We discovered that cellular rx3 levels are cis-regulated in a cell-autonomous manner, whereas rx3 domain size depends on non-autonomous Wnt and Bmp signalling. These results highlight how uncoupled mechanisms and regulatory modules control developmental gene expression and shape morphological changes. Finally, a transcriptome-wide search for fixed coding mutations and differential exon use suggested that variations in coding sequence have a minor contribution. Thus, during early embryogenesis, changes in gene expression regulation are the main drivers of cavefish developmental evolution.

Endometrial senescence is mediated by interleukin 17 receptor B signaling

BackgroundWe previously identified Il17RB, a member of the IL17 superfamily, as a candidate marker gene for endometrial aging. While IL17RB has been linked to inflammation and malignancies in several organ systems, its function in the endometrium has not been investigated and is thus poorly understood. In the present study, we performed a functional analysis of this receptor with the aim of determining the effects of its age-associated overexpression on the uterine environment.MethodsWe analyzed IL17RB-related signaling pathways and downstream gene expression in an immortalized human endometrial glandular epithelial cell line (“hEM”) forced to express the receptor via lentiviral transduction (“IL17RB-hEM”). We also prepared endometrial organoids from human endometrial tissue sourced from hysterectomy patients (“patient-derived EOs”) and exposed them to cytokines that are upregulated by IL17RB expression to investigate changes in organoid-forming capacity and senescence markers. We analyzed RNA-seq data (GEO accession number GSE132886) from our previous study to identify the signaling pathways associated with altered IL17RB expression. We also analyzed the effects of the JNK pathway on organoid-forming capacity.ResultsStimulation with interleukin 17B enhanced the NF-κB pathway in IL17RB-hEM, resulting in significantly elevated expression of the genes encoding the senescence associated secretory phenotype (SASP) factors IL6, IL8, and IL1β. Of these cytokines, IL1β inhibited endometrial organoid growth. Bioinformatics analysis showed that the JNK signaling pathway was associated with age-related variation in IL17RB expression. When IL17RB-positive cells were cultured in the presence of IL17B, their organoid-forming capacity was slightly but non-significantly lower than in unexposed IL17RB-positive cells, but when IL17B was paired with a JNK inhibitor (SP600125), it was restored to control levels. Further, IL1β exposure significantly reduced organoid-forming capacity and increased p21 expression in endometrial organoids relative to non-exposure (control), but when IL1β was paired with SP600125, both indicators were restored to levels comparable to the control condition.ConclusionsWe have revealed an association between IL17RB, whose expression increases in the endometrial glandular epithelium with advancing age, and cellular senescence. Using human endometrial organoids as in vitro model, we found that IL1β inhibits cell proliferation and leads to endometrial senescence via the JNK pathway.

Serum tumor markers: Can they clinically implicate in type 2 diabetes mellitus?

"Serum tumor markers expression (CA19-9, CA242, and CEA) and its clinical implications in type 2 diabetes mellitus" authored by Meng and Shi presents an observational case-control study investigating the correlation between tumor markers and type 2 diabetes mellitus (T2DM). The study explores the diagnostic accuracy of tumor markers, particularly cancer antigen 19-9 (CA19-9), CA242, and carcinoembryonic antigen, in poorly controlled T2DM patients with hemoglobin A1c levels exceeding 9%, employing receiver operating characteristic curve analysis. Though study offers valuable insights into the potential utility of tumor markers in clinical practice, caution is advised regarding routine tumor marker testing due to challenges such as limited availability and cost. Additionally, the study overlooks potential confounding factors like smoking and alcohol consumption. Variations in CA19-9 and CA242 expression underscore the complex interplay between tumor markers and systemic diseases, warranting further investigation into their diagnostic and prognostic implications. While Meng and Shi represent a significant contribution to the field, more extensive research is needed to fully elucidate the role of tumor markers in diabetes management and beyond.

DEEP LEARNING BASED EMOTION DETECTION SYSTEM

Emotion detection plays a crucial role in human-computer interaction, affective computing, and psychological research. Traditional methods of emotion detection often rely on manual annotations or subjective assessments, which can be time- consuming and prone to biases. In this paper, we propose a Deep Learning-Based Emotion Detection System that leverages advanced neural network architectures to automatically recognize emotions from facial expressions in real-time. The system utilizes convolutional neural networks (CNNs) for feature extraction from facial images and recurrent neural networks (RNNs) for sequence modeling of temporal dynamics in facial expressions. Our proposed system addresses key challenges in emotion detection, including variations in facial expressions, lighting conditions, and occlusions. By training on large-scale datasets of labeled facial images, the system learns to accurately classify emotions into predefined categories such as happiness, sadness, anger, fear, disgust, and surprise. We evaluate the performance of the system using standard metrics such as accuracy, precision, recall, and F1-score, demonstrating its effectiveness in real- world scenarios. The results indicate that the Deep Learning-Based Emotion Detection System achieves state-of-the-art performance in recognizing emotions from facial expressions, outperforming traditional methods. The system's ability to analyze facial dynamics in real-time opens up opportunities for applications in human-computer interaction, virtual reality, mental health monitoring, and personalized user experiences. Keywords: Deep Learning, Emotion Detection, Facial Expression Recognition, Convolutional Neural Networks, Recurrent Neural Networks, Affective Computing. Keywords: emotion Detection, Machine Learning, Classifier, Natural Language Processing

Single-cell level LasR-mediated quorum sensing response of Pseudomonas aeruginosa to pulses of signal molecules

Quorum sensing (QS) is a communication form between bacteria via small signal molecules that enables global gene regulation as a function of cell density. We applied a microfluidic mother machine to study the kinetics of the QS response of Pseudomonas aeruginosa bacteria to additions and withdrawals of signal molecules. We traced the fast buildup and the subsequent considerably slower decay of a population-level and single-cell-level QS response. We applied a mathematical model to explain the results quantitatively. We found significant heterogeneity in QS on the single-cell level, which may result from variations in quorum-controlled gene expression and protein degradation. Heterogeneity correlates with cell lineage history, too. We used single-cell data to define and quantitatively characterize the population-level quorum state. We found that the population-level QS response is well-defined. The buildup of the quorum is fast upon signal molecule addition. At the same time, its decay is much slower following signal withdrawal, and the quorum may be maintained for several hours in the absence of the signal. Furthermore, the quorum sensing response of the population was largely repeatable in subsequent pulses of signal molecules.