Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel approach to the empirical characterization of learning in biological systems

Learning to execute precise, yet complex, motor actions through practice is a trait shared by most organisms. Here we develop a novel experimental approach for the comprehensive investigation and characterization of the learning dynamics of practiced motion. Following the dynamical systems framework, we consider a high-dimensional behavioral space in which a trial-by-trial sequence of motor outputs defines a trajectory that converges to a fixed point - the desired motor output. In this scenario, details of the internal dynamics and the trial-by-trial learning mechanism cannot be disentangled from behavioral noise for nonlinear systems or even well estimated for linear systems with many parameters. To overcome this problem, we introduce a novel approach: the sporadic application of systematic target perturbations that span the behavioral space and allow us to estimate the linearized dynamics in the vicinity of the fixed point. The steady-state Lyapunov equation then allows us to identify the noise covariance. We illustrate the method by analyzing sequence-generating neural networks with either intrinsic or extrinsic noise, at time resolutions that span from spike timing to spiking rates. We demonstrate the utility of our approach in experimentally plausible and realizable settings and show that this method can fully characterize the linearized between-trials learning dynamics as well as extract meaningful internal properties of the unknown mechanism that drives the motor output within each trial. We then illustrate how the approach can be extended to nonlinear learning dynamics through a flexible choice of the basis and magnitude of perturbations. Significance statement Movement control ties brain activity to measurable external actions in real time, providing a useful tool for both neuroscientists interested in the emergence of stable behavior and biomedical engineers interested in the design of neural prosthesis and brain-machine interfaces. We approach the question of motor skill learning by introducing artificial errors through a novel perturbative scheme amenable to analytic examination in the linearized regime close to the desired behavior. Numerical simulations then demonstrate how to probe the learning dynamics in both linear and nonlinear systems. These findings stress the usefulness of analyzing responses to deliberately induced errors and the importance of properly designing such perturbation experiments. Our approach provides a novel generic tool for monitoring the acquisition of motor skills.
Aurora kinase A is essential for meiosis in mouse oocytes

The Aurora protein kinases are well-established regulators of spindle building and chromosome segregation in mitotic and meiotic cells. In mouse oocytes, there is significant Aurora kinase A (AURKA) compensatory abilities when the other Aurora kinase homologs are deleted. Whether the other homologs, AURKB or AURKC can compensate for loss of AURKA is not known. Using a conditional mouse oocyte knockout model, we demonstrate that this compensation is not reciprocal because female oocyte-specific knockout mice are sterile and their oocytes fail to complete meiosis I. In determining the AURKA-specific functions, we demonstrate that its first meiotic requirement is to activate Polo-like kinase 1 at microtubule organizing centers (MTOCs; meiotic spindle poles). This activation induces fragmentation of the MTOCs, a step essential for building a bipolar spindle. The next step that requires AURKA is building the liquid-like spindle domain that involves TACC3. Finally, we find that AURKA is also required for anaphase I onset to trigger cohesin cleavage in an APC/C independent manner. We conclude that AURKA has multiple functions essential to completing MI that are distinct from AURKB and AURKC. Author Summary Female gametes, oocytes, are uniquely prone to chromosome segregation errors in meiosis I that are associated with early miscarriages. The Aurora protein kinases are essential to control chromosome segregation in all cell types. During mitosis, Aurora kinase A (AURKA) regulates the building of the spindle, the machinery responsible for pulling chromosomes apart. Here, we use a genetic approach to demonstrate that AURKA is essential for meiosis I in mouse oocytes. AURKA is required at multiple steps in meiosis I, first to trigger fragmentation of protein structures that make up the two ends of the meiotic spindle, later to regulate building of a specialized phase-separated spindle domain, and finally to trigger efficient cleavage of cohesin, the molecular glue that holds chromosomes together until anaphase onset. These findings are the first demonstration of distinct Aurora kinase function that cannot be compensated for by the other two homologs. Therefore, this mouse model is excellent tool for pinpointing specific Aurora kinase functions and identifying AURKA target proteins critical for chromosome segregation in meiosis I.
Role of T cells in intrauterine administration of activated peripheral blood mononuclear cells in recurrent implantation failure

Over the last few years, intrauterine administration of autologous peripheral blood mononuclear cells (PBMC) has been proposed as new immunotherapy for patients with unexplained recurrent implantation failure (RIF). In these patients, administration of activated PBMC before embryo transfer results in a 2-fold increase in live birth rates(Yang et al., 2020). In this study we evaluated the role of T cells to promotes human endometrial receptivity. On the day of ovulation, PBMC were isolated from and activated with T cells mitogen, the phytohemagglutinin (PHA) and hCG for 48-h in a conditioned culture medium. Distributions of CD4+ T cells were characterized in 157 patients by flow cytometry before and after PHA/hCG activation. Cytokine production was analyzed by cytometric beads array. We observed in RIF patients a significant decrease in Th2 and natural Treg cells before activation with PHA/hCG and an increase of Th17 cells after activation compared to intrauterine sperm insemination (IUI) and in vitro fertilization (IVF) groups. Furthermore, the hCG/PHA treatment increases anti-inflammatory T cells (Th2 and Treg cells) compared to non-treated T cells. Principal component analysis (PCA) performed on CD4 T cell subtypes revealed a different cellular profile in the RIF compared to the IUI and IVF groups. This inflammatory state change could explain how endometrium immunomodulation by hCG-activated PBMC helps patients with unexplained RIF to reach implantation.
Divergent metabolism between Trypanosoma congolense and Trypanosoma brucei results in differential drug sensitivity

Animal African Trypanosomiasis (AAT) is a debilitating livestock disease prevalent across sub-Saharan Africa, a main cause of which is the protozoan parasite Trypanosoma congolense. In comparison to the well-studied T. brucei, there is a major paucity of knowledge regarding the biology of T. congolense. Here, we use a combination of omics technologies and novel genetic tools to characterise core metabolism in T. congolense mammalian-infective bloodstream-form parasites, and test whether metabolic differences compared to T. brucei impact upon drug sensitivity. Like T. brucei, glycolysis plays a major part in T. congolense energy metabolism. However, the rate of glucose uptake is significantly reduced in T. congolense, with cells remaining viable when cultured in concentrations as low as 2 mM. Instead of pyruvate, the primary glycolytic endpoints are succinate, malate and acetate. Comparative transcriptomics analysis showed higher levels of activity associated with the mitochondrial pyruvate dehydrogenase complex, acetate generation and the succinate shunt in T. congolense. However, based on omics analysis and chemical inhibition, there does not appear to be significant levels of oxidative phosphorylation. Stable-isotope labelling of glucose enabled the comparison of carbon usage between T. brucei and T. congolense, highlighting differences in nucleotide and fatty acid metabolism. To validate the metabolic similarities and differences, both species were treated with pharmacological inhibitors, confirming a lack of essential electron transport chain activity in T. congolense, but increased sensitivity to inhibition of mitochondrial pyruvate import. Strikingly, T. congolense exhibited significant resistance to inhibitors of fatty acid synthesis, including a 780-fold greater EC50 against the lipase and fatty acid synthase inhibitor Orlistat, compared to T. brucei. These data highlight that bloodstream form T. congolense diverges from T. brucei in key areas of metabolism, with several features that are intermediate between bloodstream- and insect-stage T. brucei. These results have implications for drug development, mechanisms of drug resistance and host-pathogen interactions.
An edge-centric model for harmonizing multi-relational network datasets

Functional and structural connections vary across conditions, measurements, and time. However, how to resolve multi-relational measures of connectivity remains an open challenge. Here, we propose an extension of structural covariance and morphometric similarity methods to integrate multiple estimates of connectivity into a single edge-centric network representation. We highlight the utility of this method through two applications: an analysis of multi-task functional connectivity data and multi-measure structural networks. In these analyses, we use data-driven clustering techniques to identify collections of edges that covary across tasks and measures, revealing overlapping mesoscale architecture. We also link these features to node-level properties such as modularity and canonical descriptors of brain systems. We further demonstrate that, in the case of multi-task functional networks, edge-level features are consistent across individuals yet exhibit subject-specificity. We conclude by highlighting other instances where the edge-centric model may be useful.
Description, taxonomy, and comparative genomics of a novel Thermoleptolyngbya strain isolated from hot springs of Ganzi, Sichuan China

Thermoleptolyngbya is a newly proposed genus of thermophilic cyanobacteria that are often abundant in thermal environments. However, a vast majority of Thermoleptolyngbya strains were not systematically identified, and genomic features of this genus are also sparse. Here, polyphasic approaches were employed to identify a thermophilic Thermoleptolyngbya A183 (FACHB-2491) isolated from hot spring Erdaoqiao, Ganzi prefecture, China. Morphological characterization was investigated by microscopy. Whilst the results of 16S rRNA were inconclusive, the phylogenetic reconstruction and secondary structures of 16S-23S ITS strongly suggested that A183 strain is a novel species within Thermoleptolyngbya. Moreover, genome-scale average nucleotide identity (ANI) confirmed the genetic divergence of A183 from Thermoleptolyngbya O-77. Comparative genome analysis revealed inconsistent genome structures of Thermoleptolyngbya strains. Further GO analysis showed that the specific genes were distributed in a wide range of functional categories. In addition, analysis of genes related to thermotolerance, signal transduction, and carbon/nitrogen/sulfur assimilation revealed the ability of this strain to adapt to inhospitable niches in hot springs.
Neuroepithelial organoid patterning is mediated by Wnt-driven Turing mechanism

Cell patterning in epithelia is critical for the establishment of tissue function during development. The organization of patterns in these tissues is mediated by the interpretation of signals operating across multiple length scales. How epithelial tissues coordinate changes in cell identity across these length scales to orchestrate cellular rearrangements and fate specification remains poorly understood. Here, we use human neural tube organoids as model systems to interrogate epithelial patterning principles that guide domain specification. In silico modeling of the patterning process by cellular automata, validated by in vitro experiments, reveal that the initial positions of floor plate cells, coupled with activator-inhibitor signaling interactions, deterministically dictate the patterning outcome according to a discretized Turing reaction-diffusion mechanism. This model predicts an enhancement of organoid patterning by modulating inhibitor levels. Receptor-ligand interaction analysis of scRNAseq data from multiple organoid domains reveals WNT-pathway ligands as the specific inhibitory agents, thereby allowing for the experimental validation of model predictions. These results demonstrate that neuroepithelia employ reaction-diffusion-based mechanisms during early embryonic human development to organize cellular identities and morphogen sources to achieve patterning. The wider implementation of such in vitro organoid models in combination with in-silico agent-based modeling coupled to receptor-ligand analysis of scRNAseq data opens avenues for a broader understanding of dynamic tissue patterning processes.
Plasmodium falciparum K13 mutations in Africa and Asia present varying degrees of artemisinin resistance and an elevated fitness cost in African parasites

The emergence of artemisinin (ART) resistance in Plasmodium falciparum parasites has led to increasing rates of treatment failure with first-line ART-based combination therapies (ACTs) in Southeast Asia. In this region, select mutations in K13 can result in delayed parasite clearance rates in vivo and enhanced survival in the ring-stage survival assay (RSA) in vitro. Our genotyping of 3,299 P. falciparum isolates across 11 sub-Saharan countries reveals the continuing dominance of wild-type K13 and confirms the emergence of a K13 R561H variant in Rwanda. Using gene editing, we provide definitive evidence that this mutation, along with M579I and C580Y, can confer variable degrees of in vitro ART resistance in African P. falciparum strains. C580Y and M579I were both associated with substantial fitness costs in African parasites, which may counter-select against their dissemination in high-transmission settings. We also report the impact of multiple K13 mutations, including the predominant variant C580Y, on RSA survival rates and fitness in multiple Southeast Asian strains. No change in ART susceptibility was observed upon editing point mutations in ferrodoxin or mdr2, earlier associated with ART resistance in Southeast Asia. These data point to the lack of an evident biological barrier to mutant K13 mediating ART resistance in Africa, while identifying their detrimental impact on parasite growth.
Temporal order of mutations influences cancer initiation dynamics

Cancer is a set of genetic diseases that are driven by mutations. It was recently discovered that the temporal order of genetic mutations affects the cancer evolution and even the nature of the decease itself. The mechanistic origin of these observations, however, remain not well understood. Here we present a theoretical model for cancer initiation dynamics that allows us to quantify the impact of the temporal order of mutations. In our approach, the cancer initiation process is viewed as a set of stochastic transitions between discrete states defined by the different numbers of mutated cells. Using a first-passage analysis, probabilities and times before the cancer initiation are explicitly evaluated for two alternative sequences of two mutations. It is found that the probability of cancer initiation is determined only by the first mutation, while the dynamics depends on both mutations. In addition, it is shown that the acquisition of a mutation with higher fitness before mutation with lower fitness increases the probability of the tumor formation but delays the cancer initiation. Theoretical results are explained using effective free-energy landscapes.
Physical theory of biological noise buffering by multicomponent phase separation

Significance The stochastic nature of transcription/translation implies that the concentrations of cellular proteins are “noisy” and not constant in time or across cell populations. Liquid–liquid phase separation (LLPS) can reduce or “buffer” this noise by maintaining well-defined concentrations, even in the presence of concentration distributions. However, this idea was recently challenged experimentally in multicomponent systems. Our physical theory of LLPS in ternary systems (solutes ϕ and ψ in a solvent) predicts their LLPS properties as a function of the ϕ–ϕ (homotypic) and ϕ–ψ (heterotypic) interaction strengths. We show how buffering can be effective if the noise distribution aligns with the tie-lines of the phase diagram and suggest that evolution may optimize concentration buffering by selecting appropriate mutations. Maintaining homeostasis is a fundamental characteristic of living systems. In cells, this is contributed to by the assembly of biochemically distinct organelles, many of which are not membrane bound but form by the physical process of liquid–liquid phase separation (LLPS). By analogy with LLPS in binary solutions, cellular LLPS was hypothesized to contribute to homeostasis by facilitating “concentration buffering,” which renders the local protein concentration within the organelle robust to global variations in the average cellular concentration (e.g., due to expression noise). Interestingly, concentration buffering was experimentally measured in vivo in a simple organelle with a single solute, while it was observed not to be obeyed in one with several solutes. Here, we formulate theoretically and solve analytically a physical model of LLPS in a ternary solution of two solutes (ϕ and ψ) that interact both homotypically (ϕ–ϕ attractions) and heterotypically (ϕ–ψ attractions). Our physical theory predicts how the coexisting concentrations in LLPS are related to expression noise and thus, generalizes the concept of concentration buffering to multicomponent systems. This allows us to reconcile the seemingly contradictory experimental observations. Furthermore, we predict that incremental changes of the homotypic and heterotypic interactions among the molecules that undergo LLPS, such as those that are caused by mutations in the genes encoding the proteins, may increase the efficiency of concentration buffering of a given system. Thus, we hypothesize that evolution may optimize concentration buffering as an efficient mechanism to maintain LLPS homeostasis and suggest experimental approaches to test this in different systems.
High Performance Liquid Chromatography of Pheophorbide a and Pyropheophorbide a in Salted Vegetables and Chlorella

The photosensitizers pheophorbide a and pyropheophorbide a, derived from chlorophyll in salted green vegetables and chlorella, were determined by high performance liquid chromatography under the following operating conditioms: μ-Bondapak C-18 reverse-phase separation with methanol-2% phosphate solution (90: 10v/v) as the mobile phase, and UV detection at 415nm. A flow rate ot 1.0ml/min at room temperature gave a good base line separation of pheophorbide a and pyropheophorbide a (retention times of 12.1 and 14.8min, respectively). The method was applied to the rapid monitoring of poisonous chlorophyll derivatives in vegetables and chlorella. Pheophorbide a was detected in fresh vegetables, but pyropheophorbide a was not. In salted vegetables stored for a long time (more than 3 months), almost all the chlorophyll had been converted to pyropheophorbide a. In commercial chlorella, pheophorbide a was detected to a far greater extent than pyropheophorbide a.
Surveillance of Shiga toxin-producing Escherichia coli associated bloody diarrhea in Argentina

In Argentina, the hemolytic uremic syndrome associated with Shiga toxin-producing Escherichia coli (STEC-HUS) infection is endemic, and reliable data about prevalence and risk factors are available since 2000. However, information about STEC-associated bloody diarrhea (BD) cases is limited. A prospective study was carried out in seven tertiary-hospitals and 18 Referral Units from different regions, aiming to determine (i) STEC-positive BD cases frequency in 714 children aged 1 to 9 years old; and (ii) rate of progression to HUS. The number and regional distribution of STEC-HUS cases assisted in the same hospitals and period was also assessed. A total of 29 (4.1%) STEC-positive BD cases were confirmed by Shiga Toxin Quik Chek (STQC) and/or mPCR. The highest frequencies were found in the Southern region (Neuquén, 8.7%; Bahía Blanca, 7.9%), in children between 12 and 23 month of age (8.8%), during summertime. Four (13.8%) cases progressed to HUS, three to five days after BD onset. Twenty-seven STEC-HUS children mainly under 5 years old (77.8%) were enrolled, 51.9% were female; 44% were Stx-positive by STQC and all by mPCR. The most common serotypes were O157:H7 and O145:H28 and prevalent genotypes were stx2a-only or associated, both among BD and HUS cases. Considering the endemic behavior of HUS and its impact on public health, it is important to have updated information about the epidemiology of the diarrheal disease for early recognition of infected patients and initiation of supportive treatment. Finally, it also gives the opportunity to respond to outbreak situations effectively and in timely manner.
Sample-wise unsupervised deconvolution of complex tissues

We report a sample-wise fully unsupervised deconvolution method, namely sample-wise Convex Analysis of Mixtures (swCAM), that can estimate constituent proportions and subtype-specific expressions in individual samples using tissue-level bulk data (Chen 2019). The swCAM software tool enables statistically-principled subtype-level downstream analyses, such as detecting subtype-specific differentially expressed genes (sDEG) and differential dependency networks (DDN) (Zhang, Li et al. 2009, Chen, Lu et al. 2020). Significantly different from population-level deconvolution, individual-level deconvolution is mathematically an underdetermined problem because there are more variables than observations. We therefore extend the existing CAM framework by adding an extra term of between-sample variations and formulate swCAM as a nuclear-norm regularized low-rank matrix factorization problem (Wang, Hoffman et al. 2016). We determine hyperparameter value by random entry exclusion based cross-validation scheme and obtain swCAM solution using a modified efficient alternating direction method of multipliers (ADMM). Experimental results on realistic simulation data sets show that swCAM can accurately perform sample-wise unsupervised deconvolution of complex tissues and successfully recover subtype-specific correlation networks that are otherwise unobtainable using existing methods.
Rapid fabrication of hydrogel micropatterns by projection stereolithography for studying self-organized developmental patterning

Self-organized patterning of mammalian embryonic stem cells on micropatterned surfaces has previously been established as an in vitro platform for early mammalian developmental studies, complimentary to in vivo studies. Traditional micropatterning methods, such as micro-contact printing (μCP), involve relatively complicated fabrication procedures, which restricts widespread adoption by biologists. Here, we demonstrate a rapid method of micropatterning by printing hydrogel micro-features onto a glass-bottomed culture vessel. The micro-features are printed using a projection stereolithography bioprinter yielding hydrogel structures that geometrically restrict the attachment of cells or protein. Compared to traditional, physical photomasks, a digitally tunable virtual photomask is used in the projector to generate blue light patterns that enable rapid iteration with minimal cost and effort. We show that a protocol that makes use of this method together with LN521 coating creates a surface suitable for human embryonic stem cell (hESC) attachment and growth with minimal non-specific adhesion. We further demonstrate that self-patterning of hESCs following previously published gastrulation and ectodermal induction protocols achieves results comparable with those obtained with commercially available plates (CYTOO).