Miracle-dz/UniFAR-FTUs huggingface dataset:
The first steps toward a global pandemic: Reconstructing the demographic history of parasite host switches in its native range

Background Host switching allows parasites to expand their niches. However, successful switching may require suites of adaptations and also may decrease performance on the old host. As a result, reductions in gene flow accompany many host switches, driving speciation. Because host switches tend to be rapid, it is difficult to study them in real-time and their demographic parameters remain poorly understood. As a result, fundamental factors that control subsequent parasite evolution, such as the size of the switching population or the extent of immigration from the original host, remain largely unknown. To shed light on the host switching process, we explored how host switches occur in independent host shifts by two ectoparasitic honey bee mites (Varroa destructor and V. jacobsoni). Results Both switched to the western honey bee (Apis mellifera) after it was brought into contact with their ancestral host (Apis cerana), ∼70 and ∼12 years ago, respectively. Varroa destructor subsequently caused worldwide collapses of honey bee populations. Using whole-genome sequencing on 63 mites collected in their native ranges from both the ancestral and novel hosts, we were able to reconstruct the known temporal dynamics of the switch. We further found multiple previously undiscovered mitochondrial lineages on the novel host, along with the genetic equivalent of tens of individuals that were involved in the initial host switch. Despite being greatly reduced, some gene flow remains between mites adapted to different hosts. Conclusion Our findings suggest that while reproductive isolation may facilitate the fixation of traits beneficial for exploitation of the new host, ongoing genetic exchange may allow genetic amelioration of inbreeding effects.
Selective predation of the pike Esox lucius: comparison of lateral plates and some metric features of the three‐spined stickleback Gasterosteus aculeatus

Selective predation of Esox lucius on Gasterosteus aculeatus in a natural assemblage of fish of a stream in Central Poland is described and analysed. The number of lateral plates, the standard length and four size‐dependent traits were significantly smaller for sticklebacks from stomach samples than for those from population samples. Thc remaining three metric traits were not significantly different among the samples. The regressions of five metric features (out of seven) on the standard length were significantly different between the sample of caten sticklebacks and that from the free‐living population. This supports the supposition that the selectivity of pikc predation with respect to metric traits is not attributable to selection on body size of the prey. Thus, it is reasonable to claim that the sample of caten sticklebacks is selectively taken from the natural population. It justifies the selective predation assumption of some hypotheses of the causes of the pattern of geographic variation in the three‐spined stickleback.
Working Memory as an Indicator for Comparative Cognition – Detecting Qualitative and Quantitative Differences

Working memory (WM), the representation of information held accessible for manipulation over time, is an essential component of all higher cognitive abilities. It allows for complex behaviors that go beyond simple stimulus-response associations and inflexible behavioral patterns. WM capacity determines how many different pieces of information (items) can be used for these cognitive processes, and in humans, it correlates with fluid intelligence. As such, WM might be a useful tool for comparison of cognition across species. WM can be tested using comparatively simple behavioral protocols, based on operant conditioning, in a multitude of different species. Species-specific contextual variables that influence an animal’s performance on a non-cognitive level are controlled by adapting the WM paradigm. The neuronal mechanisms by which WM emerges in the brain, as sustained neuronal activity, are comparable between the different species studied (mammals and birds), as are the areas of the brain in which WM activity can be measured. Thus WM is comparable between vastly different species within their respective niches, accounting for specific contextual variables and unique adaptations. By approaching the question of “general cognitive abilities” or “intelligence” within the animal kingdom from the perspective of WM, the complexity of the core question at hand is reduced to a fundamental memory system required to allow for complex cognitive abilities. This article argues that measuring WM can be a suitable addition to the toolkit of comparative cognition. By measuring WM on a behavioral level and going beyond behavior to the underlying physiological processes, qualitative and quantitative differences in cognition between different animal species can be identified, free of contextual restraints.
Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling

Motor imagery-based brain–computer interfaces (MI-BCIs) send commands to a computer using the brain activity registered when a subject imagines—but does not perform—a given movement. However, inconsistent MI-BCI performance occurs in variations of brain signals across subjects and experiments; this is considered to be a significant problem in practical BCI. Moreover, some subjects exhibit a phenomenon referred to as “BCI-inefficiency,” in which they are unable to generate brain signals for BCI control. These subjects have significant difficulties in using BCI. The primary goal of this study is to identify the connections of the resting-state network that affect MI performance and predict MI performance using these connections. We used a public database of MI, which includes the results of psychological questionnaires and pre-experimental resting-state taken over two sessions on different days. A dynamic causal model was used to calculate the coupling strengths between brain regions with directionality. Specifically, we investigated the motor network in resting-state, including the dorsolateral prefrontal cortex, which performs motor planning. As a result, we observed a significant difference in the connectivity strength from the supplementary motor area to the right dorsolateral prefrontal cortex between the low- and high-MI performance groups. This coupling, measured in the resting-state, is significantly stronger in the high-MI performance group than the low-MI performance group. The connection strength is positively correlated with MI-BCI performance (Session 1: r = 0.54; Session 2: r = 0.42). We also predicted MI performance using linear regression based on this connection (r-squared = 0.31). The proposed predictors, based on dynamic causal modeling, can develop new strategies for improving BCI performance. These findings can further our understanding of BCI-inefficiency and help BCI users to lower costs and save time.
A semi-automated design for high-throughput Lepidoptera larvae feeding bioassays

Lepidopteran pests cause considerable damage to all crops over the world. As larvae are directly responsible for these damages, many research efforts are devoted to find plant cultivars which are resistant or tolerant to pest attacks. However, such studies take time, efforts and are costly, especially when one wants to not only find resistance traits but also to evaluate their heritability. We present here a high throughput approach to screen plants for resistance or chemicals for their deterrence, using a leaf-disk consumption assay, which is both suitable for large scale tests and economically affordable. To monitor larvae feeding on leaf disks placed over a layer of agar, we designed 3D models of 50 cages plates. One webcam can sample simultaneously 3 of such plates at a rate of 1 image/min, and follow individual feeding activities on each leaf disk and the movements of 150 larvae. The resulting image stacks are first processed with a custom program running under an open-source image analysis package (Icy) to measure the surface of each leaf disk over time. We further developed statistical procedures running under the R software, to analyze the time course of the feeding activities of the larvae and to compare them between treatments. As a test case, we compared how European corn borer larvae respond to quinine, considered as a bitter alkaloid for many organisms, and to NeemAzal containing azadirachtin, which is a common antifeedant against pest insects. We found that increasing doses of azadirachtin reduce and delay feeding. However, contrary to our expectation, quinine was found poorly effective at the range of concentrations tested. The 3D printed model of the cage and the camera holder, the plugins running under Icy, and the R scripts are freely available, and can be modified according to the particular needs of the users.
Protein Interaction Patterns in Arabidopsis thaliana Leaf Mitochondria Change in Response to Illumination

Mitochondrial biology is underpinned by the presence and activity of large protein complexes participating in the organelle-located parts of cellular respiration, the TCA cycle and oxidative phosphorylation. While the enzymatic roles of these complexes are undisputed, little is known about the interactions of the subunits beyond their presence in the monomeric protein complexes and their functions in regulating mitochondria metabolism. By applying one of the most important regulatory cues for plant metabolism, the presence or absence of light, we here assess the changes in the composition and molecular mass of known mitochondrial protein complexes by employing a differential complexome profiling strategy. Covering a mass range up to 25 MDa, we demonstrate dynamic associations of TCA-cycle enzymes and of OXPHOS components. The data presented here form the basis for future studies aiming to advance our understanding of the role of protein:protein interactions in the regulation of plant mitochondrial functions.
FOX

Community detection is a hot topic for researchers in the fields of graph theory, social networks, and biological networks. Generally speaking, a community refers to a group of densely linked nodes in the network. Nodes usually have more than one community label, indicating their multiple roles or functions in the network. Unfortunately, existing solutions aiming at overlapping community detection are not capable of scaling to large-scale networks with millions of nodes and edges. In this article, we propose a fast-overlapping-community-detection algorithm—FOX. In the experiment on a network with 3.9 millions nodes and 20 millions edges, the detection finishes in 41 min and provides the most qualified results. The second-fastest algorithm, however, takes almost five times longer to run. As for another network with 22 millions nodes and 127 millions edges, our algorithm is the only one that can provide an overlapping community detection result and it only takes 533 min. Our algorithm is a typical heuristic algorithm, measuring the closeness of a node to a community by counting the number of triangles formed by the node and two other nodes in the community. We also extend the exploitation of triangle to open-triangle, which enlarges the scale of the detected communities.
Primary Immunodeficiencies in Russia: Data From the National Registry

Introduction: Primary immunodeficiencies (PID) are a group of rare genetic disorders with a multitude of clinical symptoms. Characterization of epidemiological and clinical data via national registries has proven to be a valuable tool of studying these diseases. Materials and Methods: The Russian PID registry was set up in 2017, by the National Association of Experts in PID (NAEPID). It is a secure, internet-based database that includes detailed clinical, laboratory, and therapeutic data on PID patients of all ages. Results: The registry contained information on 2,728 patients (60% males, 40% females), from all Federal Districts of the Russian Federation. 1,851/2,728 (68%) were alive, 1,426/1,851 (77%) were children and 425/1,851 (23%) were adults. PID was diagnosed before the age of 18 in 2,192 patients (88%). Antibody defects (699; 26%) and syndromic PID (591; 22%) were the most common groups of PID. The minimum overall PID prevalence in the Russian population was 1.3:100,000 people; the estimated PID birth rate is 5.7 per 100,000 live births. The number of newly diagnosed patients per year increased dramatically, reaching the maximum of 331 patients in 2018. The overall mortality rate was 9.8%. Genetic testing has been performed in 1,740 patients and genetic defects were identified in 1,344 of them (77.2%). The median diagnostic delay was 2 years; this varied from 4 months to 11 years, depending on the PID category. The shortest time to diagnosis was noted in the combined PIDs—in WAS, DGS, and CGD. The longest delay was observed in AT, NBS, and in the most prevalent adult PID: HAE and CVID. Of the patients, 1,622 had symptomatic treatment information: 843 (52%) received IG treatment, mainly IVIG (96%), and 414 (25%) patients were treated with biological drugs. HSCT has been performed in 342/2,728 (16%) patients, of whom 67% are currently alive, 17% deceased, and 16% lost to follow-up. Three patients underwent gene therapy for WAS; all are currently alive. Conclusions: Here, we describe our first analysis of the epidemiological features of PID in Russia, allowing us to highlight the main challenges around PID diagnosis and treatment.
Weathering Products of a Dismantled Variscan Basement. Minero-Chemical Proxies to Insight on Cretaceous Palaeogeography and Late Neogene Palaeoclimate of Sardinia (Italy)

This study compares, for the first time, the mineralogy and geochemistry of two residual-clay deposits in NW Sardinia (Nurra district) that formed at different times in tropical and sub-tropical climates. Both deposits represent palaeosols with deep-weathered residual profiles and overlie Mesozoic carbonate rocks that were deposited on the south European palaeomargin. The older alterite is Cenomanian–Turonian in age and grades upward into a horizon of karstic bauxite, whereas the younger unit occurs within alluvial deposits of Late Neogene age. The Cretaceous palaeosol represents the precursor of the overlying bauxite and formed from unknown sedimentary parent rocks. In contrast, the Messinian weathering products formed by alluvium that was sourced from the Variscan metamorphic basement. Chemical Index of Alteration values, REE fractionation index values, and the results of R-mode factorial analysis suggest a common initial weathering path and a common precursor for the deposits. However, the latter stages of weathering of the Cretaceous palaeosols resulted in lateritic alteration and bauxite production, whereas weathering of the Late Neogene palaeosols produced 2:1 clay minerals under less extreme conditions. Comparison of these residual products constrains the parental material and weathering trends and allows insight into the relationship between palaeoclimate and regional/local palaeogeography of southern Europe during Upper Cretaceous and during Messinian.
A miR-137-related biological pathway of risk for Schizophrenia is associated with human brain emotion processing

Genome-Wide-Association studies have involved miR-137 in schizophrenia. However, the biology underlying this statistical evidence is unclear. Statistical polygenic risk for schizophrenia is associated with working memory, while other biological evidence involves miR-137 in emotion processing. We investigated the function of miR-137 target schizophrenia risk genes in humans. We identified a prefrontal co-expression pathway of schizophrenia-associated miR-137 targets and validated the association with miR-137 expression in neuroblastoma cells. Alleles predicting greater co-expression of this pathway were associated with greater prefrontal activation during emotion processing in two independent cohorts of healthy volunteers (N1=222; N2=136). Statistical polygenic risk for schizophrenia was instead associated with prefrontal activation during working memory. A co-expression pathway links miR-137 and its target genes to emotion processing and risk for schizophrenia. Low prefrontal miR-137 expression may be related with SCZ risk via increased expression of target risk genes, itself associated with increased prefrontal activation during emotion processing.
Learning in the eyes: specific changes in gaze patterns track explicit and implicit visual learning

What is the link between eye movements and sensory learning? Although some theories have argued for a permanent and automatic interaction between what we know and where we look, which continuously modulates human information- gathering behavior during both implicit and explicit learning, there exist surprisingly little evidence supporting such an ongoing interaction. We used a pure form of implicit learning called visual statistical learning and manipulated the explicitness of the task to explore how learning and eye movements interact. During both implicit exploration and explicit visual learning of unknown composite visual scenes, eye movement patterns systematically changed in accordance with the underlying statistical structure of the scenes. Moreover, the degree of change was directly correlated with the amount of knowledge the observers acquired. Our results provide the first evidence for an ongoing and specific interaction between hitherto accumulated knowledge and eye movements during both implicit and explicit learning.
The SARS-CoV-2 Nucleocapsid phosphoprotein forms mutually exclusive condensates with RNA and the membrane-associated M protein

The multifunctional nucleocapsid (N) protein in SARS-CoV-2 binds the ~30 kb viral RNA genome to aid its packaging into the 80-90 nm membrane-enveloped virion. The N protein is composed of N-terminal RNA-binding and C-terminal dimerization domains that are flanked by three intrinsically disordered regions. Here we demonstrate that a centrally located 40 amino acid intrinsically disordered domain drives phase separation of N protein when bound to RNA, with the morphology of the resulting condensates affected by inclusion in the RNA of the putative SARS-CoV-2 packaging signal. The SARS-CoV-2 M protein, normally embedded in the virion membrane with its C-terminus extending into the virion core, independently induces N protein phase separation that is dependent on the N protein’s C-terminal dimerization domain and disordered region. Three-component mixtures of N+M+RNA form condensates with mutually exclusive compartments containing N+M or N+RNA, including spherical annular structures in which the M protein coats the outside of an N+RNA condensate. These findings support a model in which phase separation of the N protein with both the viral genomic RNA and the SARS-CoV-2 M protein facilitates RNA packaging and virion assembly.
Selection of Attachment Mutants during the Continuous Culture of Pseudomonas fluorescens and Relationship between Attachment Ability and Surface Composition

SUMMARY: A strain of Pseudomonas fluorescens that had been isolated from a freshwater source on a plastic substratum was grown in continuous culture in minimal medium. The ‘adsubble’ process (adsorptive bubble separation process) was found to foam-fractionate wild-type cells from the fermenter during flow conditions. This selection pressure favoured the enrichment of two major classes of mutant, both having cell surface characteristics fundamentally different from the wild-type. The wild-type produced very little extracellular polysaccharide, whereas a ‘mucoid’ mutant, found predominantly in the aqueous-phase, produced an alginate exopolymer. The second class of mutant was isolated from the walls of the fermenter and, like the wild-type, produced little exopolymer. This mutant, with crenated colony morphology, showed increased attachment to solid surfaces compared to the wild-type and mucoid cells when assayed for attachment to polystyrene surfaces for 2 h. Outer-membrane protein, lipopolysaccharides and exopolysaccharides of the wild-type and both mutants were analysed. The results demonstrate the role of cell surface characteristics in the adaptability of the organism to micro-environments such as a solid/liquid or air/liquid interface or the aqueous phase.
Combining SIMD and Many/Multi-core Parallelism for Finite-state Machines with Enumerative Speculation

Finite-state Machine (FSM) is the key kernel behind many popular applications, including regular expression matching, text tokenization, and Huffman decoding. Parallelizing FSMs is extremely difficult because of the strong dependencies and unpredictable memory accesses. Previous efforts have largely focused on multi-core parallelization and used different approaches, including speculative and enumerative execution, both of which have been effective but also have limitations. With increasing width and improving flexibility in SIMD instruction sets, this article focuses on combining SIMD and many/multi-core parallelism for FSMs. We have developed a novel strategy, called enumerative speculation. Instead of speculating on a single state as in speculative execution or enumerating all possible states as in enumerative execution, our strategy speculates transitions from several possible states, reducing the prediction overheads of speculation approach and the large amount of redundant work in the enumerative approach. A simple lookback approach produces a set of guessed states to achieve high speculation success rates in our enumerative speculation. In addition, to enable continued scalability of enumerative speculation with a large number of threads, we have developed a parallel merge method. We evaluate our method with four popular FSM applications: Huffman decoding, regular expression matching, HTML tokenization, and Div7. We obtain up to 2.5× speedup using SIMD on 1 core and up to 95× combining SIMD with 60 cores of an Intel Xeon Phi. On a single core, we outperform the best single-state speculative execution version by an average of 1.6×, and in combining SIMD and many-core parallelism, outperform enumerative execution by an average of 2×. Finally, when evaluate on a GPU, we show that our parallel merge implementations are 2.02--6.74× more efficient than corresponding sequential merge implementations and achieve better scalability on an Nvidia V100 GPU.