Miracle-dz/UniFAR-FTUs huggingface dataset:
The dynamic transition between neural states is associated with the flexible use of memory

Flexible behavior requires switching between different task demands. It is known that such task-switching is associated with costs in terms of slowed reaction time, reduced accuracy, or both. The neural correlates of task-switching have usually been studied by requiring participants to switch between distinct tasks that recruit different brain networks. Here, we investigated the transition of neural states underlying switching between two memory-related processes with opposite task demands (i.e., memory retrieval and memory suppression). We investigated 26 healthy participants who performed a Think/No-Think task while being in the fMRI scanner. Behaviorally, we show that it was more difficult for participants to suppress unwanted memories when a No-Think was preceded by a Think trial instead of another No-Think trial. Neurally, we demonstrate that Think-to-No-Think switches were associated with an increase in control-related and a decrease in memory-related brain activity. Neural representations of task demand, assessed by decoding accuracy, were lower immediately after task switching compared to the non-switch transitions, suggesting a switch-induced delay in the neural transition towards the required task demand. This suggestion is corroborated by an association between demand-specific representational strength and demand-specific performance in switch trials. Taken together, we propose that the brain’s delayed transition of neural states towards the task demand at hand is associated with a switch cost leading to less successful memory suppression. Significance statement Our brain can switch between multiple tasks but at the cost of less optimal performance during transition. One possible neuroscientific explanation is that the representation of task demand is not easy to be updated immediately after switching. Thus, weak representations for the task at hand explain performance costs. To test this, we applied brain decoding approaches to human fMRI data when participants switched between successive trials of memory retrieval and suppression. We found that switching leads to a weaker representation of the current task. The remaining representation of the previous, opposite task is associated with inferior performance in the current task. Therefore, timely updating of task representations is critical for the task switching in the service of flexible behaviors.
Wide-Field Calcium Imaging of Dynamic Cortical Networks during Locomotion

Behavior results in widespread activation of the cerebral cortex. To fully understanding the cerebral cortex’s role in behavior therefore requires a mesoscopic level description of the cortical regions engaged and their functional interactions. Mesoscopic imaging of Ca2+ fluorescence through transparent polymer skulls implanted on transgenic Thy1-GCaMP6f mice reveals widespread activation of the cerebral cortex during locomotion, including not just primary motor and somatosensory regions but also premotor, auditory, retrosplenial, and visual cortices. To understand these patterns of activation, we used spatial Independent Component Analysis (sICA) that segmented the dorsal cortex of individual mice into 20-22 Independent Components (ICs). The resulting ICs are highly consistent across imaging sessions and animals. Using the time series of Ca2+ fluorescence in each IC, we examined the changes in functional connectivity from rest to locomotion. Compared to rest, functional connectivity increases prior to and at the onset of locomotion. During continued walking, a global decrease in functional connectivity develops compared to rest that uncovers a distinct, sparser network in which ICs in secondary motor areas increase their correlations with more posterior ICs in somatosensory, motor, visual, and retrosplenial cortices. Eigenvector centrality analysis demonstrates that ICs located in premotor areas increase their influence on the network during locomotion while ICs in other regions, including somatosensory and primary motor, decrease in importance. We observed sequential changes in functional connectivity across transitions between rest and locomotion, with premotor areas playing an important role in coordination of computations across cortical brain regions. SIGNIFICANCE Behavior such as locomotion requires the coordination of multiple cerebral cortical regions to accurately navigate the external environment. However, it is unclear how computations from various regions are integrated to produce a single, coherent behavioral output. Here, wide-field, epifluorescence Ca2+ imaging across the dorsal cerebral cortex reveals the changing functional interactions among cortical regions during the transition from rest to locomotion. While functional connectivity among most cortical nodes primarily decreases from rest to locomotion, a well-defined network of increased correlations emerges between premotor and other cortical regions with an increase in the importance of the premotor cortex to the network. The results suggest that the role of the premotor areas in locomotion involves coordinating interactions among different cortical regions.
A High-efficacy CRISPRi System for Gene Function Discovery in Zymomonas mobilis

Zymomonas mobilis is a promising biofuel producer due to its high alcohol tolerance and streamlined metabolism that efficiently converts sugar to ethanol. Z. mobilis genes are poorly characterized relative to model bacteria, hampering our ability to rationally engineer the genome with pathways capable of converting sugars from plant hydrolysates into valuable biofuels and bioproducts. Many of the unique properties that make Z. mobilis an attractive biofuel producer are controlled by essential genes; however, these genes cannot be manipulated using traditional genetic approaches (e.g., deletion or transposon insertion) because they are required for viability. CRISPR interference (CRISPRi) is a programmable gene knockdown system that can precisely control the timing and extent of gene repression, thus enabling targeting of essential genes. Here, we establish a stable, high-efficacy CRISPRi system in Z. mobilis that is capable of perturbing all genes—including essentials. We show that Z. mobilis CRISPRi causes either strong knockdowns (>100-fold) using single guide RNA (sgRNA) spacers that perfectly match target genes, or partial knockdowns using spacers with mismatches. We demonstrate the efficacy of Z. mobilis CRISPRi by targeting essential genes that are universally conserved in bacteria, key to the efficient metabolism of Z. mobilis, or underlie alcohol tolerance. Our Z. mobilis CRISPRi system will enable comprehensive gene function discovery, opening a path to rational design of biofuel production strains with improved yields. IMPORTANCE Biofuels produced by microbial fermentation of plant feedstocks provide renewable and sustainable energy sources that have the potential to mitigate climate change and improve energy security. Engineered strains of the bacterium Z. mobilis can convert sugars extracted from plant feedstocks into next generation biofuels such as isobutanol; however, conversion by these strains remains inefficient due to key gaps in our knowledge about genes involved in metabolism and stress responses such as alcohol tolerance. Here, we develop CRISPRi as a tool to characterize gene function in Z. mobilis. We identify genes that are essential for growth, required to ferment sugar to ethanol, and involved in resistance to alcohol. Our Z. mobilis CRISPRi system makes it straightforward to define gene function and can be applied to improve strain engineering and increase biofuel yields.
Contributions to the knowledge of Norwegian Tachinidae (Diptera, Oestroidea) - Part 1, including an updated checklist

Records are given for 215 specimens representing 34 genera and 41 species of tachinid flies from western Norway. Gymnocheta magna Zimin, 1958, Prooppia nigripalpis (Robineau-Desvoidy, 1847) and Tachina ursina Meigen, 1824 are recorded in Norway for the first time, notes on their identification, biology and distribution are given. An updated checklist of Norwegian Tachinidae with references to sources of records succeeding Rognes (1986) is also given.
Global proteome and phosphoproteome alterations in third generation EGFR TKI resistance reveal drug targets to circumvent resistance

Lung cancer is the leading cause of cancer mortality worldwide. The treatment of lung cancer patients harboring mutant EGFR with orally administered EGFR TKIs has been a paradigm shift. Osimertinib and rociletinib are 3rd generation irreversible EGFR TKIs targeting the EGFR T790M mutation. Osimertinib is the current standard care for patients with EGFR mutations due to increased efficacy, lower side effects, and enhanced brain penetrance. Unfortunately, all patients develop resistance. Genomic approaches have primarily been used to interrogate resistance mechanisms. Here, we have characterized the proteome and phosphoproteome of a series of isogenic EGFR mutant lung adenocarcinoma cell lines that are either sensitive or resistant to these drugs. To our knowledge, this is the most comprehensive proteomic dataset resource to date to investigate 3rd generation EGFR TKI resistance in lung adenocarcinoma. We have interrogated this unbiased global quantitative mass spectrometry dataset to uncover alterations in signaling pathways, reveal a proteomic signature of epithelial mesenchymal transition (EMT) and identify kinases and phosphatases with altered expression and phosphorylation in TKI resistant cells. Decreased tyrosine phosphorylation of key sites in the phosphatase SHP2 suggests its inhibition resulting in inhibition of RAS/MAPK and activation of PI3K/AKT pathways. Furthermore, we performed anticorrelation analyses of this phosphoproteomic dataset with the published drug-induced P100 phosphoproteomic datasets from the Library of Integrated Network-Based Cellular Signatures (LINCS) program to predict drugs with the potential to overcome EGFR TKI resistance. We identified dactolisib, a PI3K/mTOR inhibitor, which in combination with osimertinib overcomes resistance both in vitro and in vivo. One Sentence Summary Global quantitative proteome and phosphoproteome analyses to examine altered signaling pathways in isogenic 3rd generation EGFR TKI sensitive and resistant cells.
Inhibitory and Toxic Effects of Blue‐green Algae on Daphnia

The effects of the planktonic blue-green algae, Aphanizomenon gracile, Synechococcus elongatus, and Microcystis aeruginosa, on survival, growth, and food uptake of Daphnia pulicaria were determined. Synechococcus and Aphanizomenon were unsuitable food when offered alone, but did not affect the daphnids negatively when mixed with Scenedesmus. Microcystis was the only one found to be toxic. In pure suspensions of this blue-green, the daphnids did not survive more than 48 hours; they lived a little longer if Scenedesmus was supplied additionally. Growth was markedly reduced when only 50 μg carbon/l of Microcystis was added to the normal Scenedesmus food. It ceased at a concentration of 250 μg C/l. This can be explained by the reduction of food uptake. Very small quantities of Microcystis (10 μg C/l) present in the normal food caused a significant reduction of the filtering rate. Filtering inhibition was associated with the cells. Filtrate of Microcystis suspensions was not effective. Thus, the daphnids must ingest the blue-green cells in order to become toxified. Dual-labelling experiments showed that Microcystis cells are filtered from the medium by Daphnia with the same efficiency as Scendesmus and are not rejected. Toxicity of Microcystis is considered to be an effective defence mechanism against grazing pressure.
Cycling in degradation of organic polymers and uptake of nutrients by a litter-degrading fungus

Wood and litter degrading fungi are the main decomposers of lignocellulose and thus play a key role in carbon cycling in nature. Here we provide evidence for a novel lignocellulose degradation strategy employed by the litter degrading fungus Agaricus bisporus (known as the white button mushroom). Fusion of hyphae allows this fungus to synchronize the activity of its mycelium over large distances (50 cm). The synchronized activity has an 13-hour interval that increases to 20 h before becoming irregular and is associated with a 3.5-fold increase in respiration while compost temperature increases up to 2 °C. Transcriptomic analysis of this burst-like phenomenon supports a cyclic degradation of lignin, deconstruction of (hemi-) cellulose and microbial cell wall polymers, and uptake of degradation products during vegetative growth of A. bisporus. Cycling in expression of the ligninolytic system, enzymes involved in saccharification, and nutrient uptake is proposed to provide an efficient way for degradation of substrates such as litter.
CRISPR/Cas9-based silencing of the ATXN1 gene in Spinocerebellar ataxia type 1 (SCA1) fibroblasts

Spinocerebellar Ataxia type 1 (SCA1) is an autosomal dominant neurodegenerative disorder caused by a gain-of-function protein with toxic activities, containing an expanded polyQ tract in the coding region. Actually, there are no treatments available to delay the onset, stop or slow down the progression of this pathology. Many approaches developed over the years involve the use of siRNAs and antisense oligonucleotides (ASOs). Here we develop and validate a CRISPR/Cas9 therapeutic strategy in fibroblasts isolated from SCA1 patients. We started from the screening of 10 different sgRNAs able to recognize regions upstream and downstream the CAG repeats, in exon 8 of ATXN1 gene. The two most promising sgRNAs, G3 and G8, whose efficiency was evaluated with an in vitro system, significantly downregulated the ATXN 1 protein expression. This downregulation was due to the introduction of indels mutations into the ATXN1 gene. Notably, with an RNA-seq analysis, we demonstrated minimal off-target effects of our sgRNAs. These preliminary results support CRISPR/Cas9 as a promising approach for treated polyQ-expanded diseases.
SimText: a text mining framework for interactive analysis and visualization of similarities among biomedical entities

Literature exploration in PubMed on a large number of biomedical entities (e.g., genes, diseases, experiments) can be time consuming and challenging comparing many entities to one other. Here, we describe SimText, a user-friendly toolset that provides customizable and systematic workflows for the analysis of similarities among a set of entities based on words from abstracts and/or other text. SimText can be used for (i) data generation: text collection from PubMed and extraction of words with different text mining approaches, and (ii) interactive analysis of data using unsupervised learning techniques and visualization in a Shiny web application. Availability and Implementation We developed SimText as an open-source R software and integrated it into Galaxy, an online data analysis platform. A command line version of the toolset is available for download from GitHub at https://github.com/mgramm1/simtext.
Early defects in lysosomal storage diseases disrupt excitatory synaptic transmission

At least two thirds of patients affected with lysosomal storage disorders (LSD) exhibit neurological symptoms. For mucopolysaccharidosis type IIIC (MPS IIIC, Sanfilippo disease type C) caused by mutations in the HGSNAT gene and lysosomal storage of heparan sulfate the major burden is progressive and severe neuropsychiatric problems, mental retardation, and dementia though to be mainly mediated by neurodegeneration. HGSNAT knockout mice match human clinical phenotype and develop hyperactivity followed by memory impairment and death. In order to understand whether early clinical symptoms in MPS IIIC mice occurring before the onset of massive neurodegeneration are caused by neuronal dysfunction we studied synaptic transmission and morphology in cultured hippocampal and CA1 pyramidal neurons of MPSIIIC mice. Synaptic spines were also studied in other mouse LSD models and postsynaptic densities in post-mortem cortices of human neurological MPS patients. Cultured hippocampal and CA1 pyramidal neurons of MPS IIIC mice showed a drastic decrease or abnormal distribution of multiple pre- and postsynaptic proteins that could be rescued in vitro and in vivo by virus-mediated gene correction. Dendritic spine densities were immature in cultured hippocampal MPS IIIC mouse neurons and reduced in pyramidal neurons of mouse models of MPS IIIC and other (Tay-Sachs, sialidosis) LSD starting from postnatal day 10. MPS IIIC neurons presented alterations in frequency and amplitude of miniature excitatory and inhibitory postsynaptic currents, sparse synaptic vesicles, reduced postsynaptic densities, disorganised microtubule network and partially impaired axonal transport of synaptic proteins. Postsynaptic densities were also reduced in post-mortem cotrees of human MPS I, II, IIIA, C and D patients suggesting that the pathology is common for these neurological LSD. Together, our results demonstrate that lysosomal storage causes alterations in synaptic structure and abnormalities in neurotransmission originating from disrupted vesicular transport and preceding the first cognitive symptoms and suggest drugs known to affect synaptic transmission can be potentially applied to treat behavioral and cognitive defects in neurological LSD patients.
Diversity Analysis of Tomato Genotypes Using RAPD Markers and High-Performance Liquid Chromatography In Relation To β - Carotene Content

This study was conducted to investigate the β-carotene content and genetic diversity of 18 red fruited and 12 orange fruited tomato genotypes, using high-performance liquid chromatographic and RAPD markers respectively. β-carotene content was significantly higher in orange fruited tomato genotypes as compared to red fruited tomato genotypes. The highest β-carotene content was found in orange fruited genotype 9A-1-1 (43.7) μg/g) whereas lowest β-carotene content was observed in Pusa Ruby (6.6) μg/g). Genetic diversity in thirty tomato genotypes was analyzed by RAPD markers generated by 23 random primers. The amplification profile consisted of 202 fragments of size ranging from 174 bp to 3650 bp of which 39 were monomorphic and 163 were polymorphic with 80.69% polymorphism. The number of bands generated by each primer varied from 4 (OPM-18) to 13 (OPK-04) with an average of 8.78 fragments per primer. The percentage ofpolymorphic bands with different primers ranged from 40 to 100%. The efficiency of RAPD marker for cultivar identification was found 2.97% as only six fragments are cultivar specific. Orange fruited genotype NBC showed three unique fragments, OPK 03–968 bp, OPL 17–322 bp and OPM 12–2349 bp. The similarity coefficients detected by RAPD ranged from 0.63 to 0.96 which revealed existence of limited genetic variation among tomato genotypes. The consensus tree constructed showed three major clusters. First cluster comprise of 16 genotypes, second cluster of 13 genotypes and the red fruited tomato genotype M-1-2B formed third independent cluster. The RAPD technology proved useful in describing genetic diversity among tomato genotypes.
Crowd-Steer: Realtime Smooth and Collision-Free Robot Navigation in Densely Crowded Scenarios Trained using High-Fidelity Simulation

We present a novel high fidelity 3-D simulator that significantly reduces the sim-to-real gap for collision avoidance in dense crowds using Deep Reinforcement Learning (DRL). Our simulator models realistic crowd and pedestrian behaviors, along with friction, sensor noise and delays in the simulated robot model. We also describe a technique to incrementally control the randomness and complexity of training scenarios to achieve better convergence and generalization capabilities. We demonstrate the effectiveness of our simulator by training a policy that fuses data from multiple perception sensors such as a 2-D lidar and a depth camera to detect pedestrians and computes smooth, collision-free velocities. Our novel reward function and multi-sensor formulation results in smooth and unobtrusive navigation. We have evaluated the learned policy on two differential drive robots and evaluate its performance in new dense crowd scenarios, narrow corridors, T and L-junctions, etc. We observe that our algorithm outperforms prior dynamic navigation techniques in terms of metrics such as success rate, trajectory length, mean time to goal, and smoothness.
Generosity among the Ik of Uganda

Abstract Abstract According to Turnbull's 1972 ethnography The Mountain People, the Ik of Uganda had a culture of selfishness that made them uncooperative. His claims contrast with two widely accepted principles in evolutionary biology, that humans cooperate on larger scales than other species and that culture is an important facilitator of such cooperation. We use recently collected data to examine Ik culture and its influence on Ik behaviour. Turnbull's observations of selfishness were not necessarily inaccurate but they occurred during a severe famine. Cooperation re-emerged when people once again had enough resources to share. Accordingly, Ik donations in unframed Dictator Games are on par with average donations in Dictator Games played by people around the world. Furthermore, Ik culture includes traits that encourage sharing with those in need and a belief in supernatural punishment of selfishness. When these traits are used to frame Dictator Games, the average amounts given by Ik players increase. Turnbull's claim that the Ik have a culture of selfishness can be rejected. Cooperative norms are resilient, and the consensus among scholars that humans are remarkably cooperative and that human cooperation is supported by culture can remain intact.
The Blind Men and the Elephant: Integrated Offline/Online Optimization Under Uncertainty

Optimization problems under uncertainty are traditionally solved either via offline or online methods. Offline approaches can obtain high-quality robust solutions, but have a considerable computational cost. Online algorithms can react to unexpected events once they are observed, but often run under strict time constraints, preventing the computation of optimal solutions. Many real world problems, however, have both offline and online elements: a substantial amount of time and information is frequently available (offline) before an online problem is solved (e.g. energy production forecasts, or historical travel times in routing problems); in other cases both offline (i.e. strategic) and online (i.e. operational) decisions need to be made. Surprisingly, the interplay of these offline and online phases has received little attention: like in the blind men and the elephant tale, we risk missing the whole picture, and the benefits that could come from integrated offline/online optimization. In this survey we highlight the potential shortcomings of pure methods when applied to mixed offline/online problems, we review the strategies that have been designed to take advantage of this integration, and we suggest directions for future research.