Miracle-dz/UniFAR-FTUs huggingface dataset:
TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors

The adaptive immune system in vertebrates has evolved to recognize non-self-antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared six metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR β-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.
Computable Early C. elegans Embryo with a Data-driven Phase Field Model

Morphogenesis is a precise and robust dynamic process during metazoan embryogenesis, consisting of both cell proliferation and cell migration. Despite the fact that much is known about specific regulations at the molecular level, how cell proliferation and migration together drive the morphogenesis at the cellular and organismic levels is not well understood. Here, using Caenorhabditis elegans as the model animal, we present a data-driven phase field model to compute the early embryonic morphogenesis within a confined eggshell. By using three-dimensional time-lapse cellular morphological information generated by imaging experiments to set the model parameters, we can not only reproduce the precise evolution of cell location, cell shape and cell-cell contact relationship in vivo, but also reveal the critical roles of cell division and cell-cell attraction in governing the early development of C. elegans embryo. In brief, we provide a generic approach to compute the embryonic morphogenesis and decipher the underlying mechanisms.
Comparative profiling of N-respirasomes predicts aberrant mitochondrial bioenergetics at single-cell resolution

Mitochondria sustain the energy demand of the cell. The composition and functional state of the mitochondrial oxidative phosphorylation system are informative indicators of organelle homeostasis and bioenergetic capacity. Here we describe a highly sensitive and reproducible method for single-cell visualization and quantification of mitochondrial respiratory supercomplexes as a novel means of measuring mitochondrial respiratory chain integrity. We apply a proximity ligation assay (PLA) and perform comparative studies of mitochondrial CI, CIII and CIV-containing supercomplexes (or N-respirasomes) in fixed human and mouse brain tissues, tumorigenic cells, iPSCs and iPSC-derived NPCs and neurons. Our optimized approach enables a quantitative in-situ assessment of even subtle mitochondrial lesions associated with aberrant respiration. By combining quantitative proteomics with single cell imaging analysis, we also report the mechanistic contribution of the MICOS complex subunit CHCHD3 in regulating N-respirasomes. Overall, our PLA-based profiling of N-respirasomes establishes a sensitive and complementary technique for detecting cell-type specific mitochondrial perturbations in fixed materials.
FLOW MECHANISMS THROUGH CONTINUOUS AND BURIED MACROPORES

Tillage destroys stable continuous macropores and at the same time creates unstable tillage pores within the tilled layer. The buried macropores below the tilled layer are not harmed. Flow through continuous pores is usually considered to be laminar. The objectives of this study were to determine the conditions under which water would flow into a buried macropore in a soil column, and to determine the flow regime inside a macropore. Packed columns (457 mm length, 76 mm diameter) were constructed with a sloping base to measure separately outflow from the artificial macropore (6 mm diameter) and the soil matrix. The columns were then tilled artificially by removing the top 12 cm and repacking. In addition, a study was conducted in a sloping box of soil with four macropores beneath a tilled layer. Dye was added to two 76-mm-diameter rings within the box, either immediately or 1 day before ponded infiltration into the rings. Ponded outflow rates from continuous 6-mm macropores ranged from 5 to 11 ml/s, which is equivalent to Reynolds numbers as high as 2370. Outflow also occurred from buried macropores, although the rate was reduced (0.01 to 0.3 ml/s) compared with continuous macropores. If dye was added immediately before infiltration, dye appeared in macropore outflow, but if dye was added 1 day before infiltration, no dye appeared in macropore outflow but only in matrix outflow. This indicated either preferential flow carrying the dye (if no time for binding to soil) or preferential flow of water around the dye. Even buried macropores can function as preferential flow pathways, and turbulent flow might occur through large, continuous macropores.
Role of Polylimonene as a Bio‐Based Additive in Thermal Oxidation of High Impact Polystyrene

Summary D-limonene, a naturally occurring product, was cationically polymerized in a reactor to form the bio-based polylimonene. The polymerization products were used for the preparation of blends with a food-contact polymer, High Impact Polystyrene (HIPS). Their thermal oxidation was further monitored by measuring the absorption of characteristic chemical groups using FTIR spectroscopy. The mechanism of polymer protection was investigated using generalized 2-Dimensional Correlation Analysis. It was found that polylimonene functions as a mild antioxidant for HIPS since it is oxidized first, leading to a short term protection of the polymer.
The importance of individual beliefs in assessing treatment efficacy

In recent years, there has been debate about the effectiveness of treatments from different fields, such as neurostimulation, neurofeedback, brain training, and pharmacotherapy. This debate has been fuelled by contradictory and nuanced experimental findings. Notably, the effectiveness of a given treatment is commonly evaluated by comparing the effect of the active treatment versus the placebo on human health and/or behaviour. However, this approach neglects the individual’s subjective experience of the type of treatment s/he received in establishing treatment efficacy. Here, we show that individual differences in subjective treatment—the thought of receiving the active or placebo condition during an experiment—can explain variability in outcomes better than the actual treatment. We analysed four independent datasets (N=387 participants), including clinical patients and healthy adults from different age groups who were exposed to different neurostimulation treatments (transcranial magnetic stimulation: Study 1 & 2; transcranial direct current stimulation: Study 3 & 4). Our findings show that the inclusion of subjective treatment can provide a better model fit, either alone or in interaction with objective treatment (defined as the condition to which participants are assigned in the experiment). These results demonstrate the significant contribution of subjective experience in explaining the variability of clinical, cognitive and behavioural outcomes. We advocate for existing and future studies in clinical and non-clinical research to start accounting for participants’ subjective beliefs and their interplay with objective treatment when assessing the efficacy of treatments. This approach will be crucial in providing a more accurate estimation of the treatment effect and its source, allowing the development of effective and reproducible interventions. Significance statement We demonstrate that individual differences in subjective treatment—the belief of receiving the active or placebo condition during an experiment—can explain variability in research outcomes better than objective treatment, the actual treatment to which participants are assigned. Even though it is a standard practice for intervention studies to collect data on subjective treatment, its contribution to research outcomes has been overlooked. By demonstrating the explanatory power of subjective treatment beyond objective treatment in four independent datasets, we show its potential to provide further insights into the effectiveness of different interventions. We, therefore, encourage researchers to adopt our approach in existing and new studies, to improve experimental design and ultimately increase the rigour and robustness of clinical and non-clinical interventions.
Quantum Approximated Graph Cutting: A Rapid Replacement for T-REMD?

Determining an optimal protein configuration for the employment of protein binding analysis as completed by Temperature based Replica Exchange Molecular Dynamics (T-REMD) is an important process in the accurate depiction of a protein’s behavior in different solvent environments, especially when determining a protein’s top binding sites for use in protein-ligand and protein-protein docking studies. However, the completion of this analysis, which pushes out top binding sites through configurational changes, is an polynomial-state computational problem that can take multiple hours to compute, even on the fastest supercomputers. In this study, we aim to determine if graph cutting provide approximated solutions the MaxCut problem can be used as a method to provide similar results to T-REMD in the determination of top binding sites of Surfactant Protein A (SP-A) for binding analysis. Additionally, we utilize a quantum-hybrid algorithm within Iff Technology’s Polar+ package using an actual quantum processor unit (QPU), an implementation of Polar+ using an emulated QPU, or Quantum Abstract Machine (QAM), on a large scale classical computing device, and an implementation of a classical MaxCut algorithm on a supercomputer in order to determine the types of advantages that can be gained through using a quantum computing device for this problem, or even using quantum algorithms on a classical device. This study found that Polar+ provides a dramatic speedup over a classical implementation of a MaxCut approximation algorithm or the use of GROMACS T-REMD, and produces viable results, in both its QPU and QAM implementations. However, the lack of direct configurational changes carried out onto the structure of SP-A after the use of graph cutting methods produces different final binding results than those produced by GROMACS T-REMD. Thus, further work needs to be completed into translating quantum-based probabilities into configurational changes based on a variety of noise conditions to better determine the accuracy advantage that quantum algorithms and quantum devices can provide in the near future.
Remodeling of the maternal gut microbiome during pregnancy is shaped by parity

Background The maternal microbiome has emerged as an important factor in gestational health and outcome and is associated with risk of preterm birth and offspring morbidity. Epidemiological evidence also points to successive pregnancies—referred to as maternal parity—as a risk factor for preterm birth, infant mortality, and impaired neonatal growth. Despite the fact that both the maternal microbiome and parity are linked to maternal-infant health, the impact of parity on the microbiome remains largely unexplored, in part due to the challenges of studying parity in humans. Results Using synchronized pregnancies and dense longitudinal monitoring of the microbiome in pigs, we describe a microbiome trajectory during pregnancy and determine the extent to which parity modulates this trajectory. We show that the microbiome changes reproducibly during gestation and that this remodeling occurs more rapidly as parity increases. At the time of parturition, parity was linked to the relative abundance of several bacterial species, including Treponema bryantii , Lactobacillus amylovorus , and Lactobacillus reuteri . Strain tracking carried out in 18 maternal-offspring “quadrads”—each consisting of one mother sow and three piglets—linked maternal parity to altered levels of Akkermansia muciniphila, Prevotella stercorea, and Campylobacter coli in the infant gut 10 days after birth. Conclusions Collectively, these results identify parity as an important environmental factor that modulates the gut microbiome during pregnancy and highlight the utility of a swine model for investigating the microbiome in maternal-infant health. In addition, our data show that the impact of parity extends beyond the mother and is associated with alterations in the community of bacteria that colonize the offspring gut early in life. The bacterial species we identified as parity-associated in the mother and offspring have been shown to influence host metabolism in other systems, raising the possibility that such changes may influence host nutrient acquisition or utilization. These findings, taken together with our observation that even subtle differences in parity are associated with microbiome changes, underscore the importance of considering parity in the design and analysis of human microbiome studies during pregnancy and in infants. Video abstract
Canonical and novel non-canonical activities of the Holliday junction resolvase Yen1

Yen1 and GEN1 are members of the Rad2/XPG family of nucleases that were identified as the first canonical nuclear Holliday junction (HJ) resolvases in budding yeast and humans due to their ability to introduce two symmetric, coordinated incisions on opposite strands of the HJ, yielding nicked DNA products that could be readily ligated. While GEN1 has been extensively characterized in vitro, much less is known about the biochemistry of Yen1. Here, we have performed the first in-depth characterization of purified Yen1. We confirmed that Yen1 resembles GEN1 in many aspects, including range of substrates targeted, position of most incisions they produce or monomeric state in solution. However, we have also observed unexpected alternative processing of substrates, such as nicked HJs and a different conformational preference on intact HJs. Moreover, we demonstrate that Yen1 is endowed with additional nuclease activities, like a nick-specific 5’-3’ exonuclease or HJ arm-chopping that could apparently blur its classification as a canonical HJ resolvase. Despite this, we show that Yen1 fulfills the requirements of a canonical HJ resolvase and hypothesize that its wider array of nuclease activities might contribute to its function in the removal of persistent recombination or replication intermediates.
Informative Neural Codes to Separate Object Categories

In order to develop object recognition algorithms, which can approach human-level recognition performance, researchers have been studying how the human brain performs recognition in the past five decades. This has already in-spired AI-based object recognition algorithms, such as convolutional neural networks, which are among the most successful object recognition platforms today and can approach human performance in specific tasks. However, it is not yet clearly known how recorded brain activations convey information about object category processing. One main obstacle has been the lack of large feature sets, to evaluate the information contents of multiple aspects of neural activations. Here, we compared the information contents of a large set of 25 features, extracted from time series of electroencephalography (EEG) recorded from human participants doing an object recognition task. We could characterize the most informative aspects of brain activations about object categories. Among the evaluated features, event-related potential (ERP) components of N1 and P2a were among the most informative features with the highest information in the Theta frequency bands. Upon limiting the analysis time window, we observed more information for features detecting temporally informative patterns in the signals. The results of this study can constrain previous theories about how the brain codes object category information.
Task dependence of neural representations of scene attributes but not scene categories in the prefrontal cortex

Natural scenes deliver rich sensory information about the world. Decades of research has shown that the scene-selective network in the visual cortex represents various aspects of scenes. However, less is known about how such complex scene information is processed beyond the visual cortex, such as in the prefrontal cortex. It is also unknown how task context impacts the process of scene perception, modulating which scene content is represented in the brain. In this study, we investigate these questions using scene images from four natural scene categories, which also depict two types of scene attributes, temperature (warm or cold), and sound level (noisy or quiet). A group of healthy human subjects from both sexes participated in the present study using fMRI. In the study, participants viewed scene images under two different task conditions; temperature judgment and sound-level judgment. We analyzed how these scene attributes and categories are represented across the brain under these task conditions. Our findings show that scene attributes (temperature and sound-level) are only represented in the brain when they are task-relevant. However, scene categories are represented in the brain, in both the parahippocampal place area and the prefrontal cortex, regardless of task context. These findings suggest that the prefrontal cortex selectively represents scene content according to task demands, but this task selectivity depends on the types of scene content; task modulates neural representations of scene attributes but not of scene categories. Significance statement Research has shown that visual scene information is processed in scene-selective regions in the occipital and temporal cortices. Here, we ask how scene content is processed and represented beyond the visual brain, in the prefrontal cortex (PFC). We show that both scene categories and scene attributes are represented in PFC, with interesting differences in task dependency: Scene attributes are only represented in PFC when they are task-relevant, but scene categories are represented in PFC regardless of the task context. Taken together, our work shows that scene information is processed beyond the visual cortex, and scene representation in PFC reflects how adaptively our minds extract relevant information from a scene.
Epilepsy kinase CDKL5 is a DNA damage sensor which controls transcriptional activity at DNA breaks

Mutation of the CDKL5 kinase gene leads to the seizure-prone neurodevelopmental condition CDD (CDKL5 deficiency disorder) and is the most common genetic cause of childhood epilepsy. However, the phospho-targets and roles of CDKL5 are poorly understood, especially in the nucleus. We reveal CDKL5 as a sensor of DNA damage in actively transcribed regions of the nucleus, which phosphorylates transcriptional regulators such as Elongin A (ELOA) on a specific consensus motif. Recruitment of CDKL5 and ELOA to DNA damage sites, and subsequent ELOA phosphorylation, requires both active transcription and synthesis of poly–ADP ribose to which CDKL5 can bind. Critically, CDKL5 is essential for transcriptional control at DNA breaks. Therefore, CDKL5 is a DNA damage-sensing regulator of transcription, with implications for CDKL5-related human diseases. One sentence summary CDKL5 is a DNA damage-sensing kinase that modulates transcriptional activity near DNA breaks.
Distinct temporal expression of GW182 in neurons regulates dendritic arborization

Precise development of the dendritic architecture is a critical determinant of mature neuronal circuitry. MicroRNA-mediated regulation of protein synthesis plays a crucial role in dendritic morphogenesis but the role of miRISC protein components in this process is less studied. Here, we show an important role of a key miRISC protein GW182 in the regulation of dendritic growth. We have identified a distinct brain region specific Spatio-temporal expression pattern of GW182 during rat postnatal development. We found that the window of peak GW182 expression coincides with the period of extensive dendritic growth, both in the hippocampus and cerebellum. Perturbation of GW182 function during a specific temporal window resulted in reduced dendritic growth of cultured hippocampal neurons. Mechanistically, we show that GW182 modulates dendritic growth by regulating global somato-dendritic translation, and actin cytoskeletal dynamics of developing neurons. Furthermore, we found that GW182 affects dendritic architecture by regulating the expression of actin modulator LIMK1. Taken together, our data reveal a previously undescribed neurodevelopmental expression pattern of GW182 and its role in dendritic morphogenesis, through both translational control and actin cytoskeletal rearrangement. Summary GW182 is a key component of miRNA induced silencing complex (miRISC). Nawalpuri et al. show that GW182 has a unique temporal expression profile during neuronal development. The developmentally controlled expression of GW182 influences dendritic morphology by regulating the expression of actin modulator LIMK1.
Expanding the range of editable targets in the wheat genome using the variants of the Cas12a and Cas9 nucleases

The development of CRISPR-based editors having different protospacer adjacent motif (PAM) recognition specificities, or guide RNA length/structure requirements broadens the range of possible genome editing applications. Here, we evaluated the natural and engineered variants of Cas12a (FnCas12a from Francisella novicida and LbCas12a from Lachnospiraceae bacterium) and Cas9 for wheat genome editing efficiency and ability to induce heritable mutations in endogenous genes controlling important agronomic traits in wheat. Unlike FnCas12a, LbCas12a was able to induce mutations in the wheat genome in the current study, even though with a lower rate than that reported for SpCas9. The eight-fold improvement in the gene editing efficiency was achieved for LbCas12a by using the guide RNAs flanked by ribozymes and driven by the RNA polymerase II promoter from switchgrass. The efficiency of multiplexed genome editing (MGE) using LbCas12a was mostly similar to that obtained using the simplex RNA guides. A LbCas12a-MGE construct was successfully applied for generating heritable mutations in a gene controlling grain size and weight in wheat. We show that the range of editable loci in the wheat genome could be expanded by using the engineered variants of Cas12a (LbCas12a-RVR) and Cas9 (Cas9-NG and xCas9) that recognize the TATV and NG PAMs, respectively, with the Cas9-NG showing higher editing efficiency on the targets with atypical PAMs compared to xCas9. In conclusion, our study reports the set of validated natural and engineered variants of Cas12a and Cas9 editors for targeting loci in the wheat genome not amenable to Cas9-based modification.