Miracle-dz/UniFAR-FTUs huggingface dataset:
Ancestral dietary change alters the development of Drosophila larvae through MAPK signalling

Increasing evidence in animal species ranging from mammals to insects has revealed phenotypes that are caused by ancestral life experiences including stress and diet. The descendent phenotypes themselves are wide ranging, and include changes to behaviour, disease risk, metabolism, and growth. Ancestral dietary macronutrient composition, and quantity (over- and under-nutrition) have been shown to alter descendent growth, metabolism and behaviour. Several studies have identified inherited molecules in gametes which are altered by ancestral diet and are required for the transgenerational effect. However, there is less understanding of the developmental pathways in the period between fertilisation and adulthood that are altered by the inherited molecules. Here we identify a key role of the MAPK signalling pathway in mediating changes to Drosophila larval developmental timing due to variation in ancestral diet. We exposed grand-parental and great grand-parental generations to defined protein to carbohydrate (P:C) dietary ratios and measured developmental timing. Descendent developmental timing was consistently faster in the period between the embryonic and pupal stages when the ancestor had a higher P:C ratio diet. Transcriptional analysis of embryos, larvae and adults revealed extensive and long-lasting changes to the MAPK signalling pathway which controlled growth rate through regulation of ribosomal RNA transcription. The importance of these processes was supported by pharmacological inhibition of MAPK and rRNA proteins which reproduced the ancestral diet-induced developmental changes. This work provides insight into the role of developmental growth signalling networks in mediating non-genetic inheritance in the period between fertilisation and adult. Summary statement Ancestral, diet-induced descendent developmental timing changes are caused by alteration of MAPK signalling pathways in the period between the embryo and pupal stages in Drosophila.
Smaller Hippocampal Volume among Black and Latinx Youth Living in High-Stigma Contexts

Are macro-level features of the social context associated with neurodevelopment in children? Answering this question is challenging, because most neuroimaging studies are conducted in one location, making it impossible to link contextual variation with neural outcomes. Here, we use one of the first national, multi-site neuroimaging studies with substantial variability in sociopolitical contexts: the Adolescent Brain and Cognitive Development study (N=11,534; M=9.9 years). We measured stigma surrounding gender, race, and Latinx ethnicity using objective state-level indicators of social policies and prejudicial attitudes and two neural markers consistently linked with stress exposure: hippocampal volume and amygdala reactivity to threat. In a pre-registered analysis, we find that African-American and Latinx youth in higher stigma environments have smaller hippocampal volume, controlling for demographics and family socioeconomic status. Stigmatizing environments were unrelated to hippocampal volume in non-stigmatized youth, providing evidence of specificity. We demonstrate that contextual approaches may yield new insights into neurodevelopment.
Unemployment, Employability and COVID19: How the Global Socioeconomic Shock Challenged Negative Perceptions Toward the Less Fortunate in the Australian Context

Unemployed benefit recipients are stigmatized and generally perceived negatively in terms of their personality characteristics and employability. The COVID19 economic shock led to rapid public policy responses across the globe to lessen the impact of mass unemployment, potentially shifting community perceptions of individuals who are out of work and rely on government income support. We used a repeated cross-sections design to study change in stigma tied to unemployment and benefit receipt in a pre-existing pre-COVID19 sample (n = 260) and a sample collected during COVID19 pandemic (n = 670) by using a vignette-based experiment. Participants rated attributes of characters who were described as being employed, working poor, unemployed or receiving unemployment benefits. The results show that compared to employed characters, unemployed characters were rated substantially less favorably at both time points on their employability and personality traits. The difference in perceptions of the employed and unemployed was, however, attenuated during COVID19 with benefit recipients perceived as more employable and more Conscientious than pre-pandemic. These results add to knowledge about the determinants of welfare stigma highlighting the impact of the global economic and health crisis on perception of others.
Calcium signaling through a transient receptor channel is important for Toxoplasma gondii growth

Transient Receptor Potential (TRP) channels participate in ion calcium (Ca2+) influx and intracellular Ca2+ release. TRP channels have not been studied in Toxoplasma gondii or any other Apicomplexan parasite. We characterized a protein predicted to possess a TRP domain (TgTRPPL-2) and determined its role in Ca2+ signaling in T. gondii, the causative agent of toxoplasmosis. TgTRPPL-2 localized to the plasma membrane and the endoplasmic reticulum of T. gondii. The ΔTgTRPPL-2 mutant was defective in growth and Ca2+ influx. Heterologous expression of TgTRPPL-2 in HEK-3KO cells allowed its functional characterization. Patching of ER-nuclear membranes demonstrated that TgTRPPL-2 is a non-selective cation channel that conducts Ca2+. Pharmacological blockers of TgTRPPL-2 inhibited Ca2+ influx and parasite growth. This is the first report of an Apicomplexan channel that conducts Ca2+ and initiates the Ca2+ signaling cascade that culminates in the stimulation of motility, invasion and egress. TgTRPPL-2 is a potential target for combating toxoplasmosis.
Graph-theoretical Analysis of EEG Functional Connectivity during Balance Perturbation in Traumatic Brain Injury

Traumatic Brain Injury (TBI) often results in balance impairment, increasing the risk for falls and further injuries. In this study, we investigated the postural instability in a group of 12 TBI patients vs 9 healthy controls (HC) by studying their brain’s response to an external perturbation of the computerized dynamic posturography platform. A 64-channel EEG was used to noninvasively record the brain’s anticipatory response while the participant was performing the dynamic posturography task. We used the global graph-theoretic network measures (global efficiency and modularity) derived from source-space EEG connectivity in different frequency bands as quantitative measures of the functional integration and segregation of the brain network during the task. The center of pressure (COP) displacement and the Berg Balance Scale (BBS) were used as balance outcomes. Furthermore, we used the Diffusion Tensor Imaging (DTI) data from all the participants to explore the association between the measures of the structural integrity of the white matter (Fractional Anisotropy, Mean Diffusivity, and Mode of Anisotropy) and the balance outcomes. Our findings revealed significant changes in functional segregation between the TBI group and controls during the task and also group-level differences in DTI measures. Also, we observed significant differences between theta-band modularity and global efficiency during rest vs. task within both the groups (TBI and HC). In terms of the neural correlates, we observed a distinct role played by different frequency bands; increase in theta-band modularity during the task was shown to be highly correlated with the poorer COP displacement and BBS in the TBI group; alpha-band and beta-band graph-theoretic measures were correlated with the measures of structural integrity. In terms of the regions of interest pertaining to the postural control, we noticed a significant cortical activity during the task in the paracentral lobule, post-central gyrus, cingulate gyrus, superior parietal gyrus, and other regions often reported to be involved in postural stability. Our study, although limited by small sample size, provides insights into the neural correlates of the balance deficits due to brain injury. Our future studies will focus on the larger sample size and also the effect of stabilometry platform training on the functional brain network modulation in TBI.
Efficient Similarity-Preserving Unsupervised Learning using Modular Sparse Distributed Codes and Novelty-Contingent Noise

There is increasing realization in neuroscience that information is represented in the brain, e.g., neocortex, hippocampus, in the form sparse distributed codes (SDCs), a kind of cell assembly. Two essential questions are: a) how are such codes formed on the basis of single trials, and how is similarity preserved during learning, i.e., how do more similar inputs get mapped to more similar SDCs. I describe a novel Modular Sparse Distributed Code (MSDC) that provides simple, neurally plausible answers to both questions. An MSDC coding field (CF) consists of Q WTA competitive modules (CMs), each comprised of K binary units (analogs of principal cells). The modular nature of the CF makes possible a single-trial, unsupervised learning algorithm that approximately preserves similarity and crucially, runs in fixed time, i.e., the number of steps needed to store an item remains constant as the number of stored items grows. Further, once items are stored as MSDCs in superposition and such that their intersection structure reflects input similarity, both fixed time best-match retrieval and fixed time belief update (updating the probabilities of all stored items) also become possible. The algorithm’s core principle is simply to add noise into the process of choosing a code, i.e., choosing a winner in each CM, which is proportional to the novelty of the input. This causes the expected intersection of the code for an input, X, with the code of each previously stored input, Y, to be proportional to the similarity of X and Y. Results demonstrating these capabilities for spatial patterns are given in the appendix.
Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield

Neural-Matrix style, high-density electrode arrays for brain-machine interfaces (BMIs) and neuroscientific research require the use of multiplexing: Each recording channel can be routed to one of several electrode sites on the array. This capability allows the user to flexibly distribute recording channels to the locations where the most desirable neural signals can be resolved. For example, in the Neuropixel probe, 960 electrodes can be addressed by 384 recording channels. However, currently no adaptive methods exist to use recorded neural data to optimize/customize the electrode selections per recording context. Here, we present an algorithm called classification-based selection (CBS) that optimizes the joint electrode selections for all recording channels so as to maximize isolation quality of detected neurons. We show, in experiments using Neuropixels in non-human primates, that this algorithm yields a similar number of isolated neurons as would be obtained if all electrodes were recorded simultaneously. Neuron counts were 41-85% improved over previously published electrode selection strategies. The neurons isolated from electrodes selected by CBS were a 73% match, by spike timing, to the complete set of recordable neurons around the probe. The electrodes selected by CBS exhibited higher average per-recording-channel signal-to-noise ratio. CBS, and selection optimization in general, could play an important role in development of neurotechnologies for BMI, as signal bandwidth becomes an increasingly limiting factor. Code and experimental data have been made available1.
Rapid Cortical Adaptation and the Role of Thalamic Synchrony during Wakefulness

Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of primarily in vitro and anesthetized studies have demonstrated the emergence of adaptation at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in perceptual adaptation, is underexplored, as are the mechanisms that underlie this phenomenon. To address these knowledge gaps, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of awake male and female mice, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation in the regime explored here results from changes in the timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex. SIGNIFICANCE STATEMENT Rapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical subpopulations of neurons.
Cellular birthdate predicts laminar and regional cholinergic projection topography in the forebrain

The basal forebrain cholinergic system projects broadly throughout the cortex and constitutes a critical source of neuromodulation for arousal and attention. Traditionally, this system was thought to function diffusely. However, recent studies have revealed a high degree of spatiotemporal specificity in cholinergic signaling. How the organization of cholinergic afferents confers this level of precision remains unknown. Here, using intersectional genetic fate mapping, we demonstrate that cholinergic fibers within the cortex exhibit remarkable laminar and regional specificity and that this is organized in accordance with cellular birthdate. Strikingly, birthdated cholinergic projections within the cortex follow an inside-out pattern of innervation. While early born cholinergic populations target deep layers, late born ones innervate superficial laminae. We also find that birthdate predicts cholinergic innervation patterns within the amygdala, hippocampus, and prefrontal cortex. Our work reveals previously unappreciated specificity within the cholinergic system and the developmental logic by which these circuits are assembled.
Viral mediated tethering to SEL1L facilitates ER-associated degradation of IRE1

The unfolded protein response (UPR) and endoplasmic reticulum (ER)-associated degradation (ERAD) are two essential components of the quality control system for proteins in the secretory pathway. When unfolded proteins accumulate in the ER, UPR sensors such as IRE1 induce the expression of ERAD genes, thereby increasing protein export from the ER to the cytosol and subsequent degradation by the proteasome. Conversely, IRE1 itself is an ERAD substrate, indicating that the UPR and ERAD regulate each other. Viruses are intracellular parasites that exploit the host cell for their own benefit. Cytomegaloviruses selectively modulate the UPR to take advantage of beneficial and inhibit detrimental effects on viral replication. We have previously shown that murine and human cytomegaloviruses express homologous proteins (M50 and UL50, respectively) that dampen the UPR at late times post infection by inducing IRE1 degradation. However, the degradation mechanism has remained uncertain. Here we show that the cytomegalovirus M50 protein mediates IRE1 degradation by the proteasome. M50-dependent IRE1 degradation can be blocked by pharmacological inhibition of p97/VCP or by genetic ablation of SEL1L, both of which are component of the ERAD machinery. SEL1L acts as a cofactor of the E3 ubiquitin ligase HRD1, while p97/VCP is responsible for the extraction of ubiquitylated proteins from the ER to the cytosol. We further show that M50 facilitates the IRE1-SEL1L interaction by binding to both, IRE1 and SEL1L. These results indicate that the viral M50 protein dampens the UPR by tethering IRE1 to SEL1L, thereby promoting its degradation by the ERAD machinery. Importance Viruses infect cells of their host and force them to produce virus progeny. This can impose stress on the host cell and activate counter-regulatory mechanisms. Protein overload in the endoplasmic reticulum (ER) leads to ER stress and triggers the unfolded protein response, which in turn upregulates protein folding and increases the degradation of proteins in the ER. Previous work has shown that cytomegaloviruses interfere with the unfolded protein response by degrading the sensor molecule IRE1. Herein we demonstrate how the viral M50 protein exploits the ER-associated degradation machinery to dispose of IRE1. Degradation of IRE1 curbs the unfolded protein response and helps the virus to increase the synthesis of its own proteins.
ATP regulates TDP-43 pathogenesis by specifically binding to an inhibitory component of a delicate network controlling LLPS

Very recently, liquid-liquid phase separation (LLPS) of cytoplasmic TDP-43 independent of forming stress granule (SG) has been decoded to initiate the neuron death for ALS. Mysteriously neurons maintain ATP concentrations of ∼3 mM, but whether ATP modulates TDP-43 LLPS remains completely unknown. Here we characterized the effects of ATP on LLPS of TDP-43 PLD and its six mutants by DIC and NMR. For the first time, the results revealed: 1) ATP does induce and subsequently dissolve LLPS of TDP-43 PLD. 2) ATP achieves the modulation all by specifically binding Arg mostly saturated at 1:100. 3) LLPS of TDP-43 PLD and its exaggeration into aggregation are controlled by a delicate network composed of both attractive and inhibitory interactions, thus rationalizing the susceptibility of TDP-43 PLD to various ALS-causing mutations. Our studies together establish that ATP specifically binds Arg in intrinsically-disordered domains even not RGG-/R-rich, implying that ATP might be a universal regulator for most, if not all, R-containing intrinsically-disordered domains by altering their physicochemical features, conformations, dynamics, LLPS and assembly. Under physiological conditions, TDP-43 even in neuronal cytoplasm is highly bound with ATP and thus inhibited for its toxic LLPS, highlighting a central role of ATP in TDP-43 pathogenesis and aging.
Cloning,Expression and Characterization of a Non-Specific Lipid Transfer Protein Gene from Potato

Plant non-specific lipid transfer proteins(nsLTPs) are abundantlipid binding proteins with small molecules that play several biological roles including antimicrobial defense,signaling,cell wall loosening,proteinase inhibiting and so on. A new cDNA clone,named StLTPa1,corresponding to potato nsLTP gene was isolated from a cultivated potato(Solanum tuberosum) infected with Ralstonia solanacearum. The sequence analysis showed that the cloned cDNA contained 636 bp nucleotide which encoded a type I nsLTP of 91 amino acids. The StLTPa1 gene is well conserved in the coding region with 60–92% identity at the amino acid level,and 75–85% identity at the nucleotide sequence level compared with other Solanaceae nsLTPs. The transcripts of the gene accumulated in potato leaf and stem tissues induced by R. solanacearum and showed dominant differential expression between resistant and susceptible genotypes. In situ hybridization results showed that the StLTPa1 mRNA was localized in phloem cells of vascular tissues in potato leaf and stem tissues after pathogen infection. Salicylic acid,methyl jasmonate and abscisic acid induced StLTPa1 gene expression in different manners. These three signal molecules could produce a long-term effect on the StLTPa1 gene expression during the early stages of potato—R. solanacearum interaction. These results thus showed that the StLTPa1 may be pathogen-responsive gene in plant defenses and involve in a complex gene regulation network.
Experimental Study On Performance And Emissions Of A Diesel Engine Using Ethanol And Biodiesel Blended Diesel Fuels

Using biofuels is a general trend in transportation sector in many countries including Vietnam that aims to reduce both dependence on fossil fuel and environmental pollution. This paper presents the comparative experimental results of engine performance and emissions of a 4-cylinder, naturally aspirated diesel engine fueled by ethanol and biodiesel blended diesel fuels. The blends included DE5 (95% diesel-5% ethanol), DE10 (90% diesel-10% ethanol), DE5B5 (90% diesel-5% ethanol-5% biodiesel), DE10B5 (85% diesel-10% ethanol-5% biodiesel). The engine was tested at 100% of load while the engine speed varied from 1000 rpm to 3500 rpm, and at 75%, 50%, 25% of loads while keeped the engine speed constant at 3500 rpm. Results showed that the DE5 and DE10 blends caused a minor change in engine torque and fuel consumption whereas reduced quite clearly HC, CO and smoke emissions but increased NOx emissions as compared to the conventional diesel. However, blending 5% biodiesel in the DE5B5 and DE10B5 blends could help reduce a bit NOx emissions whereas the engine torque and fuel consumption nearly did not change and the other emissions in exhaust gas still significantly reduced.
An Improved Graph based Rules Mining Technique from Text

: An improved graph based association rules mining (ARM) approach to extract association rules from text databases is proposed in this paper. To improve the accuracy of mining association rules from textual database, we represent the documents as graphs to allow for a much more expressive document representation than the traditional text representation approaches. Document sets are represented as graph sets to which the proposed graph mining algorithm is applied to extract frequent subgraphs, which are then further processed to produce feature vectors (one per document). Weighted subgraph mining is used to ensure the efficiency and throughput of the proposed technique; only the most frequent subgraphs are extracted. The proposed technique is validated and evaluated using real world textual data sets. The results determine that the proposed approach is better than existing text mining algorithms on almost all textual datasets