Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural and functional conservation of the programmed −1 ribosomal frameshift signal of SARS-CoV-2

17 years after the SARS-CoV epidemic, the world is facing the COVID-19 pandemic. COVID-19 is caused by a coronavirus named SARS-CoV-2. Given the most optimistic projections estimating that it will take over a year to develop a vaccine, the best short-term strategy may lie in identifying virus-specific targets for small molecule interventions. All coronaviruses utilize a molecular mechanism called −1 PRF to control the relative expression of their proteins. Prior analyses of SARS-CoV revealed that it employs a structurally unique three-stemmed mRNA pseudoknot to stimulate high rates of −1 PRF, and that it also harbors a −1 PRF attenuation element. Altering −1 PRF activity negatively impacts virus replication, suggesting that this molecular mechanism may be therapeutically targeted. Here we present a comparative analysis of the original SARS-CoV and SARS-CoV-2 frameshift signals. Structural and functional analyses revealed that both elements promote similar rates of −1 PRF and that silent coding mutations in the slippery sites and in all three stems of the pseudoknot strongly ablated −1 PRF activity. The upstream attenuator hairpin activity has also been functionally retained. Small-angle x-ray scattering indicated that the pseudoknots in SARS-CoV and SARS-CoV-2 had the same conformation. Finally, a small molecule previously shown to bind the SARS-CoV pseudoknot and inhibit −1 PRF was similarly effective against −1 PRF in SARS-CoV-2, suggesting that such frameshift inhibitors may provide promising lead compounds to counter the current pandemic.
Unsupervised Learning and Clustered Connectivity Enhance Reinforcement Learning in Spiking Neural Networks

Reinforcement learning is a learning paradigm that can account for how organisms learn to adapt their behavior in complex environments with sparse rewards. However, implementations in spiking neuronal networks typically rely on input architectures involving place cells or receptive fields. This is problematic, as such approaches either scale badly as the environment grows in size or complexity, or presuppose knowledge on how the environment should be partitioned. Here, we propose a learning architecture that combines unsupervised learning on the input projections with clustered connectivity within the representation layer. This combination allows input features to be mapped to clusters; thus the network self-organizes to produce task-relevant activity patterns that can serve as the basis for reinforcement learning on the output projections. On the basis of the MNIST and Mountain Car tasks, we show that our proposed model performs better than either a comparable unclustered network or a clustered network with static input projections. We conclude that the combination of unsupervised learning and clustered connectivity provides a generic representational substrate suitable for further computation.
MeRIP-seq and RNA-seq data of mycelium and spore of Ascosphaera apis, a widespread bee fungal pathogen

Ascosphaera apis is widespread fungal pathogen of honeybee larvae, causing chalkbrood, a chronic disease that weakens bee health and colony productivity. In this article, mecylia and spores of A. apis were respectively purified followed by RNA isolation, cDNA library construction, MeRIP-seq and RNA-seq. A total of 62,551,172, 41,773,158, 49,535,092 and 61,569,610 raw reads were produced from Aam_IP, Aas_IP, Aam_input and Aas_input groups, respectively. After quality control, 58,484,368, 37,381,432, 44,655,434 and 58,739,742 clean reads were obtained. Furthermore, 47,706,205, 31,356,690, 35,259,810 and 44,319,061 clean reads were mapped to the reference genome of A. apis, including 39,337,036, 26,731,957, 31,987,396 and 40,017,855 unique mapped reads, and 8,369,169, 4,624,733, 3,272,414 and 4,301,206 multiple mapped reads. Among them, 96.31%, 96.51%, 96.82% and 97.11% of clean reads were mapped to exons; 2.09%, 2.31%,1.83% and 1.81% to introns; 1.60%, 1.18%, 1.35% and 1.08% to intergenic regions. Value of the data The data can be used to investigate the relationship between the m6A modification extent and the transcript level in the A. apis transcriptome. This dataset contributes to transcriptome-wide characterization of the m6A distributing patterns in mRNAs and non-coding RNAs in A. apis mycelium and spore. Current data benefits new functions of m6A modification in the transcripts extensively modified by m6A in A. apis mycelium and spore. Our data could be used to characterize differential patterns of the m6A methylation between mycelium and spore of A. apis.
The birth of a bacterial tRNA gene by large-scale, tandem duplication events

Organisms differ in the types and numbers of tRNA genes that they carry. While the evolutionary mechanisms behind tRNA gene set evolution have been investigated theoretically and computationally, direct observations of tRNA gene set evolution remain rare. Here, we report the evolution of a tRNA gene set in laboratory populations of the bacterium Pseudomonas fluorescens SBW25. The growth defect caused by deleting the single-copy tRNA gene, serCGA, is rapidly compensated by large-scale (45-290 kb) duplications in the chromosome. Each duplication encompasses a second, compensatory tRNA gene (serTGA) and is associated with a rise in tRNA-Ser(UGA) in the mature tRNA pool. We postulate that tRNA-Ser(CGA) elimination increases the translational demand for tRNA-Ser(UGA), a pressure relieved by increasing serTGA copy number. This work demonstrates that tRNA gene sets can evolve through duplication of existing tRNA genes, a phenomenon that may contribute to the presence of multiple, identical tRNA gene copies within genomes.
Evidence for face selectivity in early vision

The commonly accepted “simple-to-complex” model of visual processing in the brain posits that visual tasks on complex objects such as faces are based on representations in high-level visual areas. Yet, recent experimental data showing the visual system’s ability to localize faces in natural images within 100ms (Crouzet et al., 2010) challenge the prevalent hierarchical description of the visual system, and instead suggest the hypothesis of face-selectivity in early visual areas. In the present study, we tested this hypothesis with human participants in two eye tracking experiments, an fMRI experiment and an EEG experiment. We found converging evidence for neural representations selective for upright faces in V1/V2, with latencies starting around 40 ms post-stimulus onset. Our findings suggest a revision of the standard “simple-to-complex” model of hierarchical visual processing. Significance statement Visual processing in the brain is classically described as a series of stages with increasingly complex object representations: early visual areas encode simple visual features (such as oriented bars), and high-level visual areas encode representations for complex objects (such as faces). In the present study, we provide behavioral, fMRI, and EEG evidence for representations of complex objects – namely faces – in early visual areas. Our results challenge the standard “simple-to-complex” model of visual processing, suggesting that it needs to be revised to include neural representations for faces at the lowest levels of the visual hierarchy. Such early object representations would permit the rapid and precise localization of complex objects, as has previously been reported for the object class of faces.
Functional analysis of the chromosomal passenger complex in Arabidopsis

A key regulator of cell division in all eukaryotes is the kinase Aurora B, which is encoded by the Aurora 3 (AUR3) gene in Arabidopsis. Aurora B has at least two central functions during cell division. On the one hand, it is essential for the correct, i.e. balanced, segregation of chromosomes in mitosis and meiosis by controlling kinetochore function. On the other hand, Aurora B acts at the division plane, where it is necessary to complete cytokinesis. To accomplish these two spatially distinct functions, Aurora B in animals is guided to its sites of action by Borealin, INCENP, and Survivin that build together with Aurora B the chromosome passenger complex (CPC). However, besides Aurora homologs, only a candidate gene with restricted homology to INCENP has so far been described in Arabidopsis raising the question whether there exists a full complement of the CPC in plants and how Aurora homologs are targeted subcellularly. Here, we have identified and functionally characterized a Borealin homolog, BOREALIN RELATED (BORR), in Arabidopsis. This, together with detailed localization studies including the putative Arabidopsis INCENP homolog, supports the existence of a CPC in plants.
The Total and Active Bacterial Community of the Chlorolichen Cetraria islandica and Its Response to Long-Term Warming in Sub-Arctic Tundra

Lichens are traditionally defined as a symbiosis between a fungus and a green alga and or a cyanobacterium. This idea has been challenged by the discovery of bacterial communities inhabiting the lichen thalli. These bacteria are thought to contribute to the survival of lichens under extreme and changing environmental conditions. How these changing environmental conditions affect the lichen-associated bacterial community composition remains unclear. We describe the total (rDNA-based) and potentially metabolically active (rRNA-based) bacterial community of the lichen Cetaria islandica and its response to long-term warming using a 20-year warming experiment in an Icelandic sub-Arctic tundra. 16S rRNA and rDNA amplicon sequencing showed that the orders Acetobacterales (of the class Alphaproteobacteria) and Acidobacteriales (of the phylum Acidobacteria) dominated the bacterial community. Numerous ASVs (amplicon sequence variants) taxa could only be detected in the potentially active community but not in the total community. Long-term warming led to increases in relative abundance on class, order and ASV level. Warming altered the relative abundance of ASVs of the most common bacterial genera, such as Granulicella and Endobacter. The potentially metabolically active bacterial community was also more responsive to warming than the total community. Our results suggest that the bacterial community of the lichen C. islandica is dominated by acidophilic taxa and harbors disproportionally active rare taxa. We also show for the first time that climate warming can lead to shifts in lichen-associated bacterial community composition.
Calcium activates purified human TRPA1 with and without its N-terminal ankyrin repeat domain in the absence of calmodulin

Extracellular influx of calcium or release of calcium from intracellular stores have been shown to activate mammalian TRPA1 as well as to sensitize and desensitize TRPA1 electrophilic activation. Calcium binding sites on both intracellular N- and C-termini have been proposed. Here, we demonstrate based on fluorescence correlation spectroscopy (FCS), Förster resonance energy transfer (FRET) and bilayer patch-clamp studies, a direct calmodulin-independent action of calcium on the purified human TRPA1 (hTRPA1), causing structural changes and activation of hTRPA1 with and without its N-terminal ankyrin repeat domain (N-ARD). Thus, calcium can activate hTRPA1 by direct interaction with binding sites outside the N-ARD.
A tissue- and organ-based cell biological atlas of obesity-related human genes and cellular pathways

Over the last decades, several features of obesity have been identified at behavioral, physiological, endocrine and genomic levels, and they have revealed the complexity of the disease; obesity results from a combination of genetic predisposition, endocrine disorders, and dysregulation of both food intake and energy expenditure. This complexity makes the development of new therapeutic regimens challenging and bariatric surgery is still the treatment of choice for many obese patients. Given the need for noninvasive therapeutic intervention strategies, we sought to systematically study the biological manifestations of obesity in peripheral organs. We analyzed publicly available datasets of genes, genomic determinants, and levels of obesity-related hormones in the blood, using a combination of methodologies, including graph theory and dynamical modeling, that allow for the integration of different types of datasets. The analysis revealed tissue- and organ-specific metabolic impairments and potential new drug targets. All the data are organized into a tissue/organ-based subcellular-function atlas for human obesity. The data show that the complexity of the obesity arises due to the multiplicity of subcellular processes in different peripheral organs.
Spontaneous regression of micro-metastases following primary tumor excision: a critical role for primary tumor secretome

Background Numerous case studies have reported spontaneous regression of recognized metastases following primary tumor excision, but underlying mechanisms are elusive. Here, we present a model of regression and latency of metastases following primary tumor excision and identify potential underlying mechanisms. Results Using MDA-MB-231 HM human breast cancer cells that express highly sensitive luciferase, we monitored early development stages of spontaneous metastases in BALB/c nu/nu mice. Removal of the primary tumor caused marked regression of micro-metastases, but not of larger metastases, and in vivo supplementation of tumor secretome diminished this regression, suggesting that primary tumor-secreted factors promote early metastatic growth. Correspondingly, MDA-MB-231 HM -conditioned medium increased in vitro tumor proliferation and adhesion and reduced apoptosis . To identify specific mediating factors, cytokine array and proteomic analysis of MDA-MB-231 HM secretome were conducted. The results identified significant enrichment of angiogenesis, growth factor binding and activity, focal adhesion, and metalloprotease and apoptosis regulation processes. Neutralization of MDA-MB-231 HM -secreted key mediators of these processes, IL-8, PDGF-AA, Serpin E1 (PAI-1), and MIF, each antagonized secretome-induced proliferation. Moreover, their in vivo simultaneous blockade in the presence of the primary tumor arrested the development of micro-metastases. Interestingly, in the METABRIC cohort of breast cancer patients, elevated expression of Serpin E1, IL-8, or the four factors combined predicted poor survival. Conclusions These results demonstrate regression and latency of micro-metastases following primary tumor excision and a crucial role for primary tumor secretome in promoting early metastatic growth in MDA-MB-231 HM xenografts. If generalized, such findings can suggest novel approaches to control micro-metastases and minimal residual disease.
Changes in group size during resource shifts reveal drivers of sociality across the tree of life

From biofilms to whale pods, organisms have repeatedly converged on sociality as a strategy to improve individual fitness. Yet, it remains challenging to identify the most important drivers—and by extension, the evolutionary mechanisms—of sociality for particular species. Here, we present a conceptual framework, literature review, and model demonstrating that the direction and magnitude of the response of group size to sudden resource shifts provides a strong indication of the underlying drivers of sociality. We catalog six functionally distinct mechanisms related to the acquisition of resources, and we model these mechanisms’ effects on the survival of individuals foraging in groups. We find that whether, and to what degree, optimal group size increases, decreases, or remains constant when resource abundance declines depends strongly on the dominant mechanism. Existing empirical data support our model predictions, and we demonstrate how our framework can be used to predict the dominant social benefit for particular species. Together, our framework and results show that a single easily measurable characteristic, namely, group size under different resource abundances, can illuminate the potential drivers of sociality across the tree of life.
OsNLP4 is required for nitrate assimilation gene expressions and nitrate-dependent growth in rice

In plants, nitrate is important nutrient and signaling molecule that modulates the expression of many genes and regulates growth. In paddy grown rice, nitrogen is mostly supplied in the form of ammonium, but nitrate also shares substantial portion of available nitrogen. A number of nitrogen transporters and nitrate assimilation enzymes have been identified and functionally characterized. However, little is known about the nitrate sensor system and regulatory mechanisms of these nitrate related genes. In recent years, NIN-like proteins (NLPs) have been described as key transcription factors of nitrogen responses in Arabidopsis thaliana. But the functions of OsNLPs in rice are still elusive. Here we report the characterization of OsNLP4 to reveal its function in rice. Growths of OsNLP4 knockout mutants were reduced under the nitrate supply, but not under ammonium supply. The mRNA accumulation of genes involved in nitrate assimilation were declined significantly and nitrate uptake rate and nitrate reductase activity were also impaired in the mutants. Using rice protoplast transient expression system, OsNLP4-GFP fusion was localized to nucleus irrespective of nitrate conditions. OsNLP4 was also required for normal yield under paddy field conditions. We propose the OsNLP4 is essential for regulation of genes involved in nitrate assimilation and nitrate-dependent growth in rice. One sentence summary The osnlp4 mutants exhibit abnormal nitrate response and poor growth under nitrate supply and in paddy field conditions.
T-bet+ CD11c+ B cells are critical for anti-chromatin IgG production in the development of lupus

A hallmark of systemic lupus erythematosus is high titers of circulating autoantibody. A novel CD11c+ B cell subset has been identified that is critical for the development of autoimmunity. However, the role of CD11c+ B cells in the development of lupus is unclear. Chronic graft-versus-host disease (cGVHD) is a lupus-like syndrome with great autoantibody production. In the present study we investigated the role of CD11c+ B cells in the pathogenesis of lupus in the cGVHD model. Here, we found the percentage and absolute number of CD11c+ B cells and titer of sera anti-chromatin IgG and IgG2a antibody were increased in cGVHD mice. CD11c+ plasma cells from cGVHD mice produced large amounts of anti-chromatin IgG2a upon stimulation. Depletion of CD11c+ B cells reduced anti-chromatin IgG and IgG2a production. T-bet expression was further shown to be upregulated in CD11c+ B cells. Knockout of T-bet in B cells alleviated cGVHD. The percentage of T-bet+ CD11c+ B cells was elevated in lupus patients and positively correlated with serum anti-chromatin levels. Our findings suggest T-bet+ CD11c+ B cells contribute to the pathogenesis of lupus and provides potential target for therapeutic intervention.
A Framework for Adversarially Robust Streaming Algorithms

We investigate the adversarial robustness of streaming algorithms. In this context, an algorithm is considered robust if its performance guarantees hold even if the stream is chosen adaptively by an adversary that observes the outputs of the algorithm along the stream and can react in an online manner. While deterministic streaming algorithms are inherently robust, many central problems in the streaming literature do not admit sublinear-space deterministic algorithms; on the other hand, classical space-efficient randomized algorithms for these problems are generally not adversarially robust. This raises the natural question of whether there exist efficient adversarially robust (randomized) streaming algorithms for these problems.
Procedural Reading Comprehension with Attribute-Aware Context Flow

Procedural texts often describe processes (e.g., photosynthesis and cooking) that happen over entities (e.g., light, food). In this paper, we introduce an algorithm for procedural reading comprehension by translating the text into a general formalism that represents processes as a sequence of transitions over entity attributes (e.g., location, temperature). Leveraging pre-trained language models, our model obtains entity-aware and attribute-aware representations of the text by joint prediction of entity attributes and their transitions. Our model dynamically obtains contextual encodings of the procedural text exploiting information that is encoded about previous and current states to predict the transition of a certain attribute which can be identified as a span of text or from a pre-defined set of classes. Moreover, our model achieves state of the art results on two procedural reading comprehension datasets, namely ProPara and npn-cooking
Span-based Discontinuous Constituency Parsing: A Family of Exact Chart-based Algorithms with Time Complexities from O(nˆ6) Down to O(nˆ3)

We introduce a novel chart-based algorithm for span-based parsing of discontinuous constituency trees of block degree two, including ill-nested structures. In particular, we show that we can build variants of our parser with smaller search spaces and time complexities ranging from $\mathcal O(n^6)$ down to $\mathcal O(n^3)$. The cubic time variant covers 98\% of constituents observed in linguistic treebanks while having the same complexity as continuous constituency parsers. We evaluate our approach on German and English treebanks (Negra, Tiger and Discontinuous PTB) and report state-of-the-art results in the fully supervised setting. We also experiment with pre-trained word embeddings and \bert{}-based neural networks.
Towards Productionizing Subjective Search Systems

Existing e-commerce search engines typically support search only over objective attributes, such as price and locations, leaving the more desirable subjective attributes, such as romantic vibe and worklife balance unsearchable. We found that this is also the case for Recruit Group, which operates a wide range of online booking and search services, including jobs, travel, housing, bridal, dining, beauty, and where each service is among the biggest in Japan, if not internationally. We present our progress towards productionizing a recent subjective search prototype (OpineDB) developed by Megagon Labs for Recruit Group. Several components within OpineDB are enhanced to satisfy production demands, including adding a BERT language model pre-trained on massive hospitality domain review corpora. We also found that the challenges of productionizing the system are beyond enhancing the components. In particular, an important requirement in production-quality systems is to instrument a proper way of measuring the search quality, which is extremely tricky when the search results are subjective. This led to the creation of a high-quality benchmark dataset from scratch, involving over 600 queries by user interviews and a collection of more than 120,000 query-entity relevancy labels. Also, we found that the existing search algorithms do not meet the search quality standard required by production systems. Consequently, we enhanced the ranking model by fine-tuning several search algorithms and combining them under a learning-to-rank framework. The model achieves 5%-10% overall precision improvement and 90+% precision on more than half of the benchmark testing queries making these queries ready for AB-testing. While some enhancements can be immediately applied to other verticals, our experience reveals that benchmarking and fine-tuning ranking algorithms are specific to each domain and cannot be avoided.