Miracle-dz/UniFAR-FTUs huggingface dataset:
A metagenomic prospective cohort study on gut microbiome composition and clinical infection in small bowel transplantation

ABSTRACT Two-thirds of small-bowel transplantation (SBT) recipients develop bacteremia, with the majority of infections occurring within 3 months post-transplant. Sepsis-related mortality occurs in 31% of patients and is commonly caused by bacteria of gut origin, which are thought to translocate across the implanted organ. Serial post-transplant surveillance endoscopies provide an opportunity to study whether the composition of the ileal and colonic microbiota can predict the emergence as well as the pathogen of subsequent clinical infections in the SBT patient population. Five participants serially underwent aspiration of ileal and colonic bowel effluents at transplantation and during follow-up endoscopy either until death or for up to 3 months post-SBT. We performed whole-metagenome sequencing (WMS) of 40 bowel effluent samples and compared the results with clinical infection episodes. Microbiome composition was concordant between participants and timepoint-matched ileal and colonic samples. Four out of five (4/5) participants had clinically significant infections thought to be of gut origin. Bacterial translocation from the gut was observed in 3/5 patients with bacterial infectious etiologies. In all three cases, the pathogens had demonstrably colonized the gut between 1–10 days prior to invasive clinical infection. Recipients with better outcomes received donor grafts with higher alpha diversity. There was an increase in the number of antimicrobial resistance genes associated with longer hospital stay for all participants. This metagenomic study provides preliminary evidence to support the pathogen translocation hypothesis of gut-origin sepsis in the SBT cohort. Ileal and colonic microbiome compositions were concordant; therefore, fecal metagenomic analysis could be a useful surveillance tool for impeding infection with specific gut-residing pathogens.
Consensus-Agent Deep Reinforcement Learning for Face Aging

Face aging tasks aim to simulate changes in the appearance of faces over time. However, due to the lack of data on different ages under the same identity, existing models are commonly trained using mapping between age groups. This makes it difficult for most existing aging methods to accurately capture the correspondence between individual identities and aging features, leading to generating faces that do not match the real aging appearance. In this paper, we re-annotate the CACD2000 dataset and propose a consensus-agent deep reinforcement learning method to solve the aforementioned problem. Specifically, we define two agents, the aging process agent and the aging personalization agent, and model the task of matching aging features as a Markov decision process. The aging process agent simulates the aging process of an individual, while the aging personalization agent calculates the difference between the aging appearance of an individual and the average aging appearance. The two agents iteratively adjust the matching degree between the target aging feature and the current identity through a form of synergistic cooperation. Extensive experimental results on four face aging datasets show that our model achieves convincing performance compared to the current state-of-the-art methods.
RoBERTaLexPT: A Legal RoBERTa Model pretrained with deduplication for Portuguese

This work investigates the application of Natural Language Processing (NLP) in the legal context for the Portuguese language, emphasizing the importance of adapting pre-trained models, such as RoBERTa, from specialized corpora in the legal domain. We compiled and pre-processed a Portuguese Legal corpus, LegalPT corpus, addressing challenges of high document duplication in legal corpora, and measuring the impact of hyperparameters and embedding initialization. Experiments revealed that pre-training on legal and general data resulted in more effective models for legal tasks, with RoBERTaLexPT outperforming larger models trained on generic corpora, and other legal models from related works. We also aggregated a legal benchmark, PortuLex benchmark. This study contributes to improving NLP solutions in the Brazilian legal context, providing enhanced models, a specialized corpus, and a benchmark dataset. For reproducibility, we will make related code, data, and models available.
Impact of Climate Change on the Water Requirements of Oat in Northeast and North China

Crop water requirements are directly affected by climatic variability, especially for crops grown in the areas which are sensitive to climatic change. Based on the SIMETAW model and a long-term meteorological dataset, we evaluated the spatiotemporal variations of climatic change impacts on water requirement of oat in North and Northeast China. The results indicated that effective rainfall showed an increasing trend, while the crop water requirement and irrigation demand presented decreasing trends over the past decades. The water requirement of oat showed significant longitudinal and latitudinal spatial variations, with a downtrend from north to south and uptrend from east to west. Climatic factors have obviously changed in the growth season of oat, with upward trends in the average temperature and precipitation, and downward trends in the average wind speed, sunshine hours, relative humidity, and solar radiation. Declines in solar radiation and wind speed, accompanied with the increase in effective rainfall, have contributed to the reduced crop water requirement over these decades. Given the complex dynamic of climate change, when studying the impact of climate change on crop water requirements, we should not only consider single factors such as temperature or rainfall, we need to analyze the comprehensive effects of various climatic factors.
A Galician Corpus for Misogyny Detection Online

Social networks are virtual spaces where millions of people share ideas, opinions, and experiences. However, this broad social interaction also exposes negative and harmful behaviors, such as harassment and misogyny. Misog-yny, particularly, is a worrying phenomenon that perpetuates gender inequality and under-mines the dignity and rights of women. In this context, Natural Language Processing (NLP) emerges as a promising tool to analyze and understand the discourse of social networks. However, most of NLP research, sentiment analysis, and hate speech, focuses on languages such as English and, to a lesser extent, Spanish. This implies that other languages in general, and minority languages, such as Gali-cian, in particular, are beyond the scope of this research, and that extrapolation of results and techniques is not explored. This work describes the development process of a Galician corpus for the detection of misog-yny online. The results are made available to the research community to facilitate further analysis by third-parties interested in studying this same subject.
CLSJUR.BR - A Model for Abstractive Summarization of Legal Documents in Portuguese Language based on Contrastive Learning

In the legal domain, there has been a growing interest among Natural Language Processing (NLP) researchers in the Automatic Legal Document Summarization. However, legal documents differ from the general texts, as the former involves technical texts of a legal nature, which are generally longer and contain more sophisticated vocabulary than the general domain texts. In this article, we propose the CLSJUR.BR, a Contrastive Learning model for automatic and abstractive summarization of legal documents in Portuguese language, that applies the reference-free evaluation technique. CLSJUR.BR was trained and evaluated using the Ruling.BR corpus, composed of judicial decisions from the Supreme Federal Court of Brazil. The results indicating their good applicability to the task of summarizing legal documents.
Exploring Computational Discernibility of Discourse Domains in Brazilian Portuguese within the Carolina Corpus

In this study, we explore the computational discernibility of Portuguese language discourse domains using a balanced sample from the Carolina corpus, including its five largest domains: Juridical , Entertainment , Journalistic , Virtual and Instructional . We analyze discernibility across three levels: degree of duplication, linguistic features distribution, and separability within semantic embedding spaces. We found clear quantitative differences between domains at all levels, compatible with expected qualitative properties. Our analysis shows that these domains can be distinguished based on various computable text properties, and suggests a consistent complexity scale between them. We identify the distinguishing properties and their potential benefits for NLP tasks. Additionally, we provide domain-balanced and deduplicated versions of Carolina for future research.
Time Cells in the Retrosplenial Cortex

The retrosplenial cortex (RSC) is a key component of the brain’s memory systems, with anatomical connections to the hippocampus, anterior thalamus, and entorhinal cortex. This circuit has been implicated in episodic memory and many of these structures have been shown to encode temporal information, which is critical for episodic memory. For example, hippocampal time cells reliably fire during specific segments of time during a delay period. Although RSC lesions are known to disrupt temporal memory, time cells have not been observed there. In the present study, we examined the firing patterns of RSC neurons during the intertrial delay period of two behavioral tasks, a blocked alternation task and a cued T-maze task. For the blocked alternation task, rats were required to approach the east or west arm of a plus maze for reward during different blocks of trials. Because the reward locations were not cued, the rat had to remember the goal location for each trial. In the cued T-maze task, the reward location was explicitly cued with a light and the rats simply had to approach the light for reward, so there was no requirement to hold a memory during the intertrial delay. Time cells were prevalent in the blocked alternation task, and most time cells clearly differentiated the east and west trials. We also found that RSC neurons could exhibit off-response time fields, periods of reliably inhibited firing. Time cells were also observed in the cued T-maze, but they were less prevalent and they did not differentiate left and right trials as well as in the blocked alternation task, suggesting that RSC time cells are sensitive to the memory demands of the task. These results suggest that temporal coding is a prominent feature of RSC firing patterns, consistent with an RSC role in episodic memory.
Cold stress induces a rapid redistribution of the antagonistic marks H3K4me3 and H3K27me3 in Arabidopsis thaliana

When exposed to low temperatures, plants undergo a drastic reprogramming of their transcriptome in order to adapt to their new environmental conditions, which primes them for potential freezing temperatures. While the involvement of transcription factors in this process, termed cold acclimation, has been deeply investigated, the potential contribution of chromatin regulation remains largely unclear. A large proportion of cold-inducible genes carries the repressive mark histone 3 lysine 27 trimethylation (H3K27me3), which has been hypothesized as maintaining them in a silenced state in the absence of stress, but which would need to be removed or counteracted upon stress perception. However, the fate of H3K27me3 during cold exposure has not been studied genome-wide. In this study, we offer an epigenome profiling of H3K27me3 and its antagonistic active mark H3K4me3 during short-term cold exposure. Both chromatin marks undergo rapid redistribution upon cold exposure, however, the gene sets undergoing H3K4me3 or H3K27me3 differential methylation are distinct, refuting the simplistic idea that gene activation relies on a switch from an H3K27me3 repressed chromatin to an active form enriched in H3K4me3. Coupling the ChIP-seq experiments with transcriptome profiling reveals that differential histone methylation correlates with changes in expression. Interestingly, only a subset of cold-regulated genes lose H3K27me3 during their induction, indicating that H3K27me3 is not an obstacle to transcriptional activation. In the H3K27me3 methyltransferase curly leaf (clf) mutant, many cold regulated genes display reduced H3K27me3 levels but their transcriptional activity is not altered prior or during a cold exposure, suggesting that H3K27me3 may serve a more intricate role in the cold response than simply repressing the cold-inducible genes in naïve conditions.
Multi-condition and multi-modal temporal profile inference during mouse embryonic development

The emergence of single-cell time-series datasets enables modeling of changes in various types of cellular profiles over time. However, due to the disruptive nature of single-cell measurements, it is impossible to capture the full temporal trajectory of a particular cell. Furthermore, single-cell profiles can be collected at mismatched time points across different conditions (e.g., sex, batch, disease) and data modalities (e.g., scRNA-seq, scATAC-seq), which makes modeling challenging. Here we propose a joint modeling framework, Sunbear, for integrating multi-condition and multi-modal single-cell profiles across time. Sunbear can be used to impute single-cell temporal profile changes, align multi-dataset and multi-modal profiles across time, and extrapolate single-cell profiles in a missing modality. We applied Sunbear to reveal sex-biased transcription during mouse embryonic development and predict dynamic relationships between epigenetic priming and transcription for cells in which multi-modal profiles are unavailable. Sunbear thus enables the projection of single-cell time-series snapshots to multi-modal and multi-condition views of cellular trajectories.
Cell-type specific effects of Fusarium mycotoxins on primary neuronal and astroglial cells

Fumonisin B1, deoxynivalenol (DON) and zearalenone (ZEA) are toxic secondary metabolites produced by Fusarium molds. These mycotoxins are common food and feed pollutants and represent a risk for human and animal health. Although the mycotoxins produced by this genus can cross the blood-brain-barrier (BBB) in many species, their effect on neuronal function remains unclear. We investigated cell viability effects of these toxins on specified neural cell types, including mouse primary neuronal, astroglial and mixed cell cultures 24 or 48 hours after mycotoxin administration. Cell viability assay revealed that DON decreased cell viability in a dose-dependent manner, independently from the culture’s type. Fumonisin B1 increased cell viability significantly on astroglial and mixed cell cultures in lower doses, while it exerted a highly toxic effect in 50 µM. ZEA had significant effects on all culture type in 10 nM by increasing the cell viability. Since ZEA is a mycoestrogen, we analyzed the effects of ZEA on the expression of estrogen receptor isotypes ERα and ERβ and mitochondrial voltage-dependent anion channel (VDAC1) by qRT-PCR. In neuronal and mixed cultures, ZEA administration decreased ERα expression, while in astroglial cultures, it induced the opposite effect. ERβ and VDAC1 expression was not altered by ZEA in either culture types. ZEA also affected the firing pattern of neurons by enhancing the burst frequency. Our results demonstrate that Fusarium mycotoxins are acting on a cell specific manner in the brain tissue.
Yellow Fever Emergence: Role of Heterologous Flavivirus Immunity in Preventing Urban Transmission

During major, recent yellow fever (YF) epidemics in Brazil, human cases were attributed only to spillover infections from sylvatic transmission with no evidence of human amplification. Furthermore, the historic absence of YF in Asia, despite abundant peridomestic Aedes aegypti and naive human populations, represents a longstanding enigma. We tested the hypothesis that immunity from dengue (DENV) and Zika (ZIKV) flaviviruses limits YF virus (YFV) viremia and transmission by Ae. aegypti. Prior DENV and ZIKV immunity consistently suppressed YFV viremia in experimentally infected macaques, leading to reductions in Ae. aegypti infection when mosquitoes were fed on infected animals. These results indicate that, in DENV- and ZIKV-endemic regions such as South America and Asia, flavivirus immunity suppresses YFV human amplification potential, reducing the risk of urban outbreaks. One-Sentence Summary Immunity from dengue and Zika viruses suppresses yellow fever viremia, preventing infection of mosquitoes and reducing the risk of epidemics.
Prioritizing replay when future goals are unknown

Although hippocampal place cells replay nonlocal trajectories, the computational function of these events remains controversial. One hypothesis, formalized in a prominent reinforcement learning account, holds that replay plans routes to current goals. However, recent puzzling data appear to contradict this perspective by showing that replayed destinations lag current goals. These results may support an alternative hypothesis that replay updates route information to build a “cognitive map. ” Yet no similar theory exists to formalize this view, and it is unclear how such a map is represented or what role replay plays in computing it. We address these gaps by introducing a theory of replay that learns a map of routes to candidate goals, before reward is available or when its location may change. Our work extends the planning account to capture a general map-building function for replay, reconciling it with data, and revealing an unexpected relationship between the seemingly distinct hypotheses.
Multi-view graph learning for deciphering the dominant cell communication assembly of downstream functional events from single-cell RNA-seq data

Cell-cell communications (CCCs) from multiple sender cells collaboratively affect downstream functional events in receiver cells, thus influencing cell phenotype and function. How to rank the importance of these CCCs and find the dominant ones in a specific downstream functional event has great significance for deciphering various physiological and pathogenic processes. To date, several computational methods have been developed to focus on the identification of cell types that communicate with enriched ligand-receptor interactions from single-cell RNA-seq (scRNA-seq) data, but to the best of our knowledge, all of them lack the ability to identify the communicating cell type pairs that play a major role in a specific downstream functional event, which we call it “dominant cell communication assembly (DCA)”. Here, we proposed scDCA, a multi-view graph learning method for deciphering DCA from scRNA-seq data. scDCA is based on a multi-view CCC network by constructing different cell type combinations at single-cell resolution. Multi-view graph convolution network was further employed to reconstruct the expression pattern of target genes or the functional states of receiver cells. The DCA was subsequently identified by interpreting the model with the attention mechanism. scDCA was verified in a real scRNA-seq cohort of advanced renal cell carcinoma, accurately deciphering the DCA that affect the expression patterns of the critical immune genes and functional states of malignant cells. Furthermore, scDCA also accurately explored the alteration in cell communication under clinical intervention by comparing the DCA for certain cytotoxic factors between patients with and without immunotherapy. scDCA is free available at: https://github.com/pengsl-lab/scDCA.git.
pTAC3 and pTAC14 are required for binding of plastid-encoded RNA polymerase to DNA

Plastid-encoded RNA polymerase (PEP) is a bacterial-type multisubunit RNA polymerase responsible for the majority of transcription in chloroplasts. PEP consists of four core subunits, which are orthologs of their cyanobacterial counterparts. In Arabidopsis thaliana, PEP associates with 12 PEP-associated proteins (PAPs), which serve as peripheral subunits of the RNA polymerase. The exact contributions of PAPs to PEP function are still poorly understood. We use ptChIP-seq to show that PAP1/pTAC3, a peripheral subunit of PEP, binds to the same genomic loci as RpoB, a core subunit of PEP. The pap1/ptac3 mutant shows a complete loss of RpoB binding to DNA throughout the genome, indicating that PAP1/pTAC3 is necessary for RpoB binding to DNA. A similar loss of RpoB binding to DNA is observed in the pap7/ptac14 mutant, which is defective in another peripheral PEP subunit. We propose that the peripheral subunits of PEP are required for the recruitment of core PEP subunits to DNA. KEY MESSAGE The peripheral subunits of plastid-encoded RNA polymerase play a crucial role in recruiting the core PEP subunits to DNA in Arabidopsis chloroplasts.
Computational Modeling of Solar Energy Storage in Rock Beds

Over the last 60 years, technology for harvesting solar energy has been extensively developed and used. Examples of applications incorporating this technology include the following: heating and cooling of residential and commercial buildings; solar water heaters; photo-voltaic conversion to electricity; solar-thermal-electric power generation; and solar desalination of seawater. In parallel, thermal energy storage (TES) systems have also been extensively developed and employed for enhancing the efficiency of energy conversion systems, typically by matching thermal energy supply and demand during summer-winter, day-night, and peak-off-peak periods. In this work, the focus is on computational modeling of flat-plate solar-thermal collectors and sensible diurnal TES systems consisting of rock beds, both with air as the working fluid. Such collectors and TES systems are inexpensive, relatively simple, easy to construct, and quite effective for many solar energy and building engineering applications. Numerous publications on flat-plate solar-thermal collectors and rock-bed TES systems are available, but there is a need for efficient computational methods for designing and optimizing them. The contributions of this work are the following: proposal of cost-effective mathematical models of fluid (air) flow and heat transfer through flat-plate solar-thermal collectors and rock-bed TES systems; adaptation of a finite volume method (FVM) for the solution of the aforementioned mathematical model of rock-bed TES systems; testing of the proposed computational methods; and applications of the proposed models and methods to two demonstration problems. In one of these problems, a sample rock-bed TES system is simulated and assessed. In the other one, actual meteorological data from three different geographical locations are used to estimate the performance of a system that couples a flat-plate solar-thermal collector with a rock-bed TES system. %%%%Au cours des soixante dernieres annees, les technologies de recuperation d'energie solaire ont ete developpees et utilisees de maniere considerable. Les exemples d'applications incorporant ces technologies sont, entre autres : chauffage et refrigeration de bâtiments residentiels et commerciaux ; chauffe-eau solaire ; conversion photovoltaique d'electricite; generation de puissance solaire-thermique ; et desalinisation de l'eau de mer. Parallelement, les systemes de stockage d'energie thermique (TES) ont egalement ete largement developpes et utilises afin d'ameliorer l'efficacite des systemes de conversion d'energie, notamment en faisant coincider l'offre et la demande en energie thermique durant les periodes estivales et hivernales, nocturnes et diurnes, heures creuses et heures pleines. Lors de ces travaux, une attention toute particuliere a ete portee a la modelisation numerique des collecteurs solaires-thermiques et des systemes TES diurnes composes de lits de pierre, tous ayant l'air pour fluide caloporteur. De tels collecteurs et systemes TES sont peu chers, relativement simples,…