Miracle-dz/UniFAR-FTUs huggingface dataset:
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation

Dynamic tuning of the poly(A) tail is a crucial mechanism for controlling translation and stability of eukaryotic mRNA. Achieving a comprehensive understanding of how this regulation occurs requires unbiased abundance quantification of poly(A)-tail transcripts and simple poly(A)-length measurement using high-throughput sequencing platforms. Current methods have limitations due to complicated setups and elaborate library preparation plans. To address this, we introduce Central Limit Theorem (CLT)-managed RNA-seq (CLT-seq), a simple and straightforward homopolymer-sequencing method. In CLT-seq, an anchor-free oligo(dT) primer rapidly binds to and unbinds from anywhere along the poly(A) tail string, leading to position-directed reverse transcription with equal probability. The CLT mechanism enables the synthesized poly(T) lengths, which correspond to the templated segment of the poly(A) tail, to distribute normally. Based on a well-fitted pseudogaussian-derived poly(A)-poly(T) conversion model, the actual poly(A)-tail profile is reconstructed from the acquired poly(T)-length profile through matrix operations. CLT-seq follows a simple procedure without requiring RNA-related pre-treatment, enrichment, or selection, and the CLT-shortened poly(T) stretches are more compatible with existing sequencing platforms. This proof-of-concept approach facilitates direct homopolymer base-calling and features unbiased RNA-seq. Therefore, CLT-seq provides unbiased, robust, and cost-efficient transcriptome-wide poly(A)-tail profiling. We demonstrate that CLT-seq on the most common Illumina platform delivers reliable poly(A)-tail profiling at a transcriptome-wide scale in human cellular contexts. We find that the poly(A)-tail-tuned ncRNA regulation undergoes a dynamic, complex process similar to mRNA regulation. Overall, CLT-seq offers a simplified, effective, and economical approach to investigate poly(A)-tail regulation, with potential implications for understanding gene expression and identifying therapeutic targets.
Socially transmitted innovations in dynamic predator-prey systems

Individual behavioral variation is common, yet often we do not know how it is maintained. A potential explanation is that some behaviors must be acquired rather than genetically inherited. We investigate the social transmission of behavioral innovations, which can be key for the success of predator species, especially in contexts where environmental changes take place. We examine innovation in two classic predator-prey models. We assume that innovations increase predator attack rates or conversion efficiencies, or that innovations reduce predator mortality or prey handling time. We find that a common outcome of innovations is the destabilization of the system. Destabilizing effects include increasing oscillations or limit cycles. If either of these outcomes increases the risk of extinction, innovations that benefit individual predators may not have positive long-term effects on predator populations. Furthermore, as populations cycle, innovative individuals can be nearly eliminated, maintaining temporal behavioral variability. The destabilizing effects of behavioral innovations on predator-prey dynamics could have implications for biological invasions, urban populations, endangered species, and, more broadly, the maintenance of behavioral polymorphisms.
Correlated Somatosensory Input in Parvalbumin/Pyramidal Cells in Mouse Motor Cortex

Abstract In mammalian cortex, feedforward excitatory connections recruit feedforward inhibition. This is often carried by parvalbumin (PV+) interneurons, which may densely connect to local pyramidal (Pyr) neurons. Whether this inhibition affects all local excitatory cells indiscriminately or is targeted to specific subnetworks is unknown. Here, we test how feedforward inhibition is recruited by using two-channel circuit mapping to excite cortical and thalamic inputs to PV+ interneurons and Pyr neurons to mouse primary vibrissal motor cortex (M1). Single Pyr and PV+ neurons receive input from both cortex and thalamus. Connected pairs of PV+ interneurons and excitatory Pyr neurons receive correlated cortical and thalamic inputs. While PV+ interneurons are more likely to form local connections to Pyr neurons, Pyr neurons are much more likely to form reciprocal connections with PV+ interneurons that inhibit them. This suggests that Pyr and PV ensembles may be organized based on their local and long-range connections, an organization that supports the idea of local subnetworks for signal transduction and processing. Excitatory inputs to M1 can thus target inhibitory networks in a specific pattern which permits recruitment of feedforward inhibition to specific subnetworks within the cortical column.
Mapping the cellular and molecular organization of mouse cerebral aging by single-cell transcriptome imaging

The cellular diversity and complex organization of the brain have hindered systematic characterization of age-related changes in its cellular and molecular architecture, limiting our ability to understand the mechanisms underlying its functional decline during aging. Here we generated a high-resolution cell atlas of brain aging within the frontal cortex and striatum using spatially resolved single-cell transcriptomics and quantified the changes in gene expression and spatial organization of major cell types in these brain regions over the lifespan of mice. We observed substantially more pronounced changes in the composition, gene expression and spatial organization of non-neuronal cells over neurons. Our data revealed molecular and spatial signatures of glial and immune cell activation during aging, particularly enriched in subcortical white matter, and identified both similarities and notable differences in cell activation patterns induced by aging and systemic inflammatory challenge. These results provide critical insights into age-related decline and inflammation in the brain.
Designing DNA-based predictors of drug response using the signal joint with gene expression

Motivation: Anti-cancer drugs may elicit resistance or sensitivity through mechanisms which involve several genomic layers. Nevertheless, we have demonstrated that gene expression contains most of the predictive capacity compared to the remaining omic data types. Unfortunately, this comes at a price: gene expression biomarkers are often hard to interpret and show poor robustness. Results: To capture the best of both worlds, i.e. the accuracy of gene expression and the robustness of other genomic levels, such as mutations, copy-number or methylation, we developed Percolate, a computational approach which extracts the joint signal between gene expression and the other omic data types. We developed an out-of-sample extension of Percolate which allows predictions on unseen samples without the necessity to recompute the joint signal on all data. We employed Percolate to extract the joint signal between gene expression and either mutations, copy-number or methylation, and used the out-of sample extension to perform response prediction on unseen samples. We showed that the joint signal recapitulates, and sometimes exceeds, the predictive performance
No need for extensive artifact rejection for ICA - A multi-study evaluation on stationary and mobile EEG datasets

Objective Electroencephalography (EEG) studies increasingly make use of more ecologically valid experimental protocols involving mobile participants who actively engage with their environment (MoBI; Gramann et al., 2011). These mobile paradigms lead to increased artifacts in the recorded data that are often treated using Independent Component Analysis (ICA). When analyzing EEG data, especially in a mobile context, removing samples regarded as artifactual is a common approach before computing ICA. Automatic tools for this exist, such as the automatic sample rejection of the AMICA algorithm (Palmer et al., 2011), but the impact of the two factors movement intensity and the automatic sample rejection has not been systematically evaluated yet. Approach We computed AMICA decompositions on eight datasets from six open-access studies with varying degrees of movement intensities using increasingly conservative sample rejection criteria. We evaluated the subsequent decomposition quality in terms of the component mutual information, the amount of brain, muscle, and “other” components, the residual variance of the brain components, and an exemplary signal-to-noise ratio. Main results We found that increasing movements of participants led to decreasing decomposition quality for individual datasets but not as a general trend across all movement intensities. The cleaning strength had less impact on decomposition results than anticipated, and moderate cleaning of the data resulted in the best decompositions. Significance Our results indicate that the AMICA algorithm is very robust even with limited data cleaning. Moderate amounts of cleaning such as 5 to 10 iterations of the AMICA sample rejection with 3 standard deviations as the threshold will likely improve the decomposition of most datasets, irrespective of the movement intensity.
External Cues Improve Visual Working Memory Encoding in the Presence of Salient Distractors in Schizophrenia

Background People with schizophrenia (PSZ) are impaired in attentional prioritization of non-salient but relevant stimuli over salient distractors during visual working memory (VWM) encoding. Conversely, guidance of top-down attention by external predictive cues is intact. Yet, it is unknown whether this preserved ability can help PSZ encode more information in the presence of salient distractors. Methods We employed a visuospatial change-detection task using four Gabor patches with differing orientations in 66 PSZ and 74 healthy controls (HCS). Two Gabor patches flickered which were designated either as targets or distractors and either a predictive or a non-predictive cue was displayed to manipulate top-down attention, resulting in four conditions. Results We observed significant effects of group, salience and cue as well as significant interactions of salience by cue, group by salience and group by cue. Across all conditions, PSZ stored significantly less information in VWM than HCS. PSZ stored significantly less non-flickering than flickering information with a non-predictive cue. However, PSZ stored significantly more flickering and non-flickering information with a predictive cue. Conclusions Our findings indicate that control of attentional selection is impaired in schizophrenia. We demonstrate that additional top-down information significantly improves performance in PSZ. The observed deficit in attentional control suggests a disturbance of GABAergic inhibition in early visual areas. Moreover, our findings are indicative of a mechanism for enhancing attentional control in PSZ, which could be utilized by pro-cognitive interventions. Thus, the current paradigm is suitable to reveal both preserved and compromised cognitive component processes in schizophrenia.
Convergent Community Assembly among Globally Separated Acidic Cave Biofilms

Microorganisms that are adapted to extremely acidic conditions, known as extreme acidophiles, are catalysts for rock weathering, metal cycling, and mineral formation in naturally acidic environments. They are also important drivers of large-scale industrial processes such as biomining and contaminant remediation. ABSTRACT Acidophilic bacteria and archaea inhabit extreme geochemical “islands” that can tell us when and how geographic barriers affect the biogeography of microorganisms. Here, we describe microbial communities from extremely acidic (pH 0 to 1) biofilms, known as snottites, from hydrogen sulfide-rich caves. Given the extreme acidity and subsurface location of these biofilms, and in light of earlier work showing strong geographic patterns among snottite Acidithiobacillus populations, we investigated their structure and diversity in order to understand how geography might impact community assembly. We used 16S rRNA gene cloning and fluorescence in situ hybridization (FISH) to investigate 26 snottite samples from four sulfidic caves in Italy and Mexico. All samples had very low biodiversity and were dominated by sulfur-oxidizing bacteria in the genus Acidithiobacillus. Ferroplasma and other archaea in the Thermoplasmatales ranged from 0 to 50% of total cells, and relatives of the bacterial genera Acidimicrobium and Ferrimicrobium were up to 15% of total cells. Rare phylotypes included Sulfobacillus spp. and members of the phyla “Candidatus Dependentiae” and “Candidatus Saccharibacteria” (formerly TM6 and TM7). Although the same genera of acidophiles occurred in snottites on separate continents, most members of those genera represent substantially divergent populations, with 16S rRNA genes that are only 95 to 98% similar. Our findings are consistent with a model of community assembly where sulfidic caves are stochastically colonized by microorganisms from local sources, which are strongly filtered through environmental selection for extreme acid tolerance, and these different colonization histories are maintained by dispersal restrictions within and among caves. IMPORTANCE Microorganisms that are adapted to extremely acidic conditions, known as extreme acidophiles, are catalysts for rock weathering, metal cycling, and mineral formation in naturally acidic environments. They are also important drivers of large-scale industrial processes such as biomining and contaminant remediation. Understanding the factors that govern their ecology and distribution can help us better predict and utilize their activities in natural and engineered systems. However, extremely acidic habitats are unusual in that they are almost always isolated within circumneutral landscapes. So where did their acid-adapted inhabitants come from, and how do new colonists arrive and become established? In this study, we took advantage of a unique natural experiment in Earth’s subsurface to show how isolation may have played a role in the colonization history, community assembly, and diversity of highly acidic microbial biofilms.
Leishmania amazonensis controls macrophage-regulated cell death to establish chronic infection in vitro and in vivo

Pathogenic protists of the genus Leishmania have evolved various strategies to exploit macrophages as host cells and subvert their immuno-metabolic functions to favour intracellular parasite survival. Surprisingly little is known on how Leishmania affects regulated cell death (RCD) pathways of its host cell, even though increased survival of in vitro infected macrophages has been reported, and chronic macrophage infection in vivo causes the devastating immunopathologies of leishmaniasis. To overcome this limitation and gain first systems-level insight into the interaction between intracellular Leishmania and the host cell RCD pathways, including apoptosis, pyroptosis and necroptosis, we applied transcriptomic analyses on L. amazonensis-infected, primary macrophages (termed LIMs) and used YO-PRO-1 to monitor cell death by fluorescent microscopy. RNAseq analyses at day 3 post-infection (PI) revealed dichotomic dysregulation of more than 60% of RCD-related genes in LIMs, characterized by up-regulation of anti-RCD and down-regulation of pro-RCD markers, including key regulators common to the three forms of cell death such as casp8, fadd, tradd, tnfaip3, tax1bp1, birc3, and itch. This profile correlated with expression changes of transcription factors known to regulate RCD, including AP1 and NF-κB family members, pparγ and cebpβ. Consequently, LIMs showed remarkable longevity in culture for at least 50 days, despite a constant increase of parasite burden to about 100 parasites per cell, while non-infected cells were cleared from the culture in just a few days. Longitudinal expression analysis of LIMs at days 0, 3, 15, and 30 PI by RT-qPCR confirmed stable maintenance of this high longevity profile with the dichotomic decrease and increase of RCD-activators and -inhibitors, respectively. LIMs further showed significant resistance to RCD-inducing signals compared to non-infected cells, including CSF-1 deprivation (intrinsic apoptosis), actinomycin D treatment (extrinsic apoptosis), LPS/ATP stimulation (pyroptosis). Significantly, we extended the anti-RCD expression pattern and RCD resistance phenotype to L. amazonensis-infected macrophages recovered from lesions, thus validating our long-term in vitro infection system as an easily accessible model to study chronic macrophage infection. In conclusion, our analyses firmly document the pan-anti RCD effect of L. amazonensis on its macrophage host cell in vitro and in vivo and shed important new light on mechanisms underlying Leishmania chronic infection.
Molecular determinants of Karyopherin-β2 chaperone and disaggregation activity

Karyopherin-β2 (Kapβ2) is a nuclear-import receptor that recognizes proline-tyrosine nuclear localization signals (PY-NLSs) of diverse cytoplasmic cargo for transport to the nucleus. Kapβ2 cargo include several disease-linked RNA-binding proteins (RBPs) with prion-like domains (PrLDs), such as FUS, TAF15, EWSR1, hnRNPA1, and hnRNPA2. These RBPs with PrLDs are linked via pathology and genetics to debilitating degenerative disorders, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and multisystem proteinopathy (MSP). Remarkably, Kapβ2 prevents and reverses aberrant phase transitions of these cargo, which is cytoprotective. However, the molecular determinants of Kapβ2 that enable these activities remain poorly understood, particularly from the standpoint of nuclear-import receptor architecture. Kapβ2 is a superhelical protein comprised of 20 HEAT repeats. Here, we design truncated variants of Kapβ2 and assess their ability to antagonize FUS aggregation and toxicity in yeast and FUS condensation at the pure protein level and in human cells. We find that HEAT repeats 8-20 of Kapβ2 recapitulate all salient features of Kapβ2 activity. By contrast, Kapβ2 truncations lacking even a single cargo-binding HEAT repeat display reduced activity. Thus, we define a minimal Kapβ2 construct for delivery in adeno-associated viruses as a potential therapeutic for ALS/FTD, MSP, and related disorders.
Measuring Engagement Effects of Educational Games and Virtual Manipulatives on Mathematics

ii Acknowledgments v List of Figures xii List of Tables xiii Chapter 1: Introduction 1 Engagement 2 Behavioral engagement. 4 Cognitive engagement. 4 Emotional engagement 6 Summary. 6 Traditional Technologies for Mathematics Learning 8 Virtual manipulatives. 8 Educational (Digital) Games 10 Main Attributes of Virtual Manipulatives and Educational Games 12 Significance of the Study 15 Purpose Statement 19 Organization of the Proposed Study 21 Glossary of Terms 22 Chapter 2: Review of the Literature 26
UNDERST ANDING THE ROLE PERFORMANCE THROUGH THE LENSES OF TALENT MANAGEMENT AND ITS FACETS

The research was conducted to understand the possible relationship of talent management and its four facets with role performance of the employees working in telecom sector of Pakistan. To test the hypotheses of the study, the data based on 262 respondents was collected through simple random sampling method. The primary data was collected by distributing print outs of the questionnaire for which scales were adapted from previous studies. The relationship of talent management and its facets with employee performance was tested through step wise multiple regression analysis. The relationship of talent retention with role performance was not supported by the data. Whereas, other facets of talent management viz. training and development, talent attraction and career development were having substantial relationship with role performance. In addition to this, the relationship between talent management and role performance was found positive and significant. Due to limited financial resources and paucity of time, the study has some limitations. The study is conducted based on cross sectional design and limited the sample to one major city of the country. Whereas, the longitudinal study with more geographical coverage can give more generalized results.
IMPACT OF JD-R MODEL ON ORGANIZATIONAL OUTCOMES: MEDIATING ROLE OF WORK ENGAGEMENT AND JOB BURNOUT

This study is an attempt to investigate the intervention of job burn-out and job engagement between JD-R model with organizational outcomes as turnover intention and job satisfaction in the nursing sector. For this purpose, three hundred questionnaires were distributed in nursing staff by using the quantitative approach. Convenient sampling technique has been used for the collection of data, and for data analysis SPSS and AMOS 21 has been used in this study. Findings of the study revealed the full mediation of job engagement between job resources, job satisfaction and turnover intention. There is a positive significant relation between job resources and job satisfaction however, negative relation with turnover intention. Moreover, results explain a positive and significant relation between job demands and job satisfaction and a positive but insignificant relation with turnover intention. Furthermore, there is no mediation of job burnout and job engagement between job demands and job satisfaction, turnover intention. It also revealed that there is no mediating relation of job burnout between job resources, job satisfaction and turnover intention. This study presents fresh evidences and literature support with supported theories of the discussed variables by looking the value in the context of health sector. In this field, it can assist many scholars for further studies as a ground.
ROLE OF CORRUPTION AND ITS IMPACT UNDER VARIOUS REGIMES: CROSS COUNTRY ANALYSIS

Many empirical studies investigate relationship between democracy and corruption by considering democratic and non-democratic regimes. There are many economies which are not fully democratic and autocratic, so there is a dire need to explore these relationships in case of other two categories of political regimes, such as flawed democracies and hybrid regime. Does this relationship equally hold in these political regimes? This study gauges out the linkages between corruption and economic growth for all plausible cases of political regimes. Empirical analysis includes sample of 159 countries based on different political regimes, consisting on 20 full democracies, 55 flawed democracies, 39 hybrid regime, and 53 authoritarian regimes. The data are taken from the period of 2006 to 2019. The sophisticated empirical Bayesian estimation procedure is employed to explore the association between growth and socio-economic variables. The results indicate that corruption in case of mature democracies has no significant effect on economic growth While in autocracies has significant positive effect on economic growth. However, corruption has negative effect on economic growth in flawed democracies and hybrid regime.
Diffeomorphism invariant gauge theories

A class of diffeomorphism invariant gauge theories is studied. The action for this class of theories can be formulated as a generalisation of the well known topological BF-theories with a potential for the B-field or in a pure connection formulation. When the gauge group is chosen to be SU(2) the theory describes gravity. For a larger gauge group G one gets a unified model of gravity and Yang-Mills fields. A background for the theory is chosen which breaks the gauge group G by selecting in it a preferred SU(2) subgroup which describes the gravitational sector. The Yang-Mills sector is described by the part of the gauge group that commutes with this SU(2). Thus, when the action is expanded around this background the spectrum of the linearised theory consists of the usual gravitons plus Yang-Mills fields. In addition, there is a set of massive scalar fields that are charged both under the gravitational and Yang-Mills subgroups. The latter sector is described by the part of the gauge group that does not commute with SU(2). A fermionic Lagrangian is also proposed which can be coupled to the BF plus potential formulation.