Miracle-dz/UniFAR-FTUs huggingface dataset:
No evidence for genetic sex determination in Daphnia magna

Mechanisms of sex determination (SD) differ widely across the tree of life. In genotypic sex determination (GSD), genetic elements determine whether individuals are male or female, while in environmental sex determination (ESD), external cues control the sex of the offspring. In cyclical parthenogens, females produce mostly asexual daughters, but environmental stimuli such as crowding, temperature or photoperiod may cause them to produce sons. In aphids, sons are induced by ESD, even though GSD is present, with females carrying two X chromosomes and males only one (X0 SD system). By contrast, although ESD exists in Daphnia, the two sexes were suggested to be genetically identical, based on a 1972 study on Daphnia magna (2n=20) that used three allozyme markers. This study cannot, however, rule out an X0 system, as all three markers may be located on autosomes. Motivated by the life cycle similarities of Daphnia and aphids, and the absence of karyotype information for Daphnia males, we tested for GSD (homomorphic sex chromosomes and X0) systems in D. magna using a whole-genome approach by comparing males and females of three genotypes. Our results confirm the absence of haploid chromosomes or haploid genomic regions in D. magna males as well as the absence of sex-linked genomic regions and sex-specific single-nucleotide polymorphisms. Within the limitations of the three studied populations here and the methods used, we suggest that our results make the possibility of genetic differences among sexes in the widely used Daphnia model system very unlikely.
The transmembrane serine protease hepsin suppresses type I interferon induction by cleaving STING

The transmembrane protease hepsin reduces antiviral innate immunity in hepatocytes. Viral vulnerability in hepatocytes Chronic viral infections of the liver can lead to organ dysfunction and hepatocellular carcinoma. Hsin et al. found that the transmembrane serine protease hepsin, which is abundant in the liver, suppressed the STING-mediated induction of type I IFNs in response to viral infection in mouse embryonic fibroblasts (MEFs) and human hepatocytes. Hepsin colocalized with STING at the endoplasmic reticulum and cleaved STING. This mechanism also appeared to account for the failure of prostate cancer cells, which also produce hepsin, to mount a STING-dependent type I IFN response to viral infection. Thus, hepsin makes hepatocytes vulnerable to viral infection and may contribute to the poor response of prostate cancer cells to immunotherapies that rely on STING activation. Many viral proteases mediate the evasion of antiviral innate immunity by cleaving adapter proteins in the interferon (IFN) induction pathway. Host proteases are also involved in innate immunity and inflammation. Here, we report that the transmembrane protease hepsin (also known as TMPRSS1), which is predominantly present in hepatocytes, inhibited the induction of type I IFN during viral infections. Knocking out hepsin in mouse embryonic fibroblasts (MEFs) increased the viral infection–induced expression of Ifnb1, an Ifnb1 promoter reporter, and an IFN-sensitive response element promoter reporter. Ectopic expression of hepsin in cultured human hepatocytes and HEK293T cells suppressed the induction of IFNβ during viral infections by reducing the abundance of STING. These effects depended on the protease activity of hepsin. We identified a putative hepsin target site in STING and showed that mutating this site protected STING from hepsin-mediated cleavage. In addition to hepatocytes, several hepsin-producing prostate cancer cell lines showed reduced STING-mediated type I IFN induction and responses. These results reveal a role for hepsin in suppressing STING-mediated type I IFN induction, which may contribute to the vulnerability of hepatocytes to chronic viral infections.
The social positions of taste between and within music genres: From omnivore to snob

Are higher status cultural tastes in the modern United States better described as being inclusive and broad or exclusive and narrow? We construct an original dataset in response to conflicting answers to this question. We fill a major gap in the literature on cultural tastes by simultaneously considering taste for both musical genres and artists within genres. By examining the compositional balance of respondents’ taste portfolios, we reconcile seemingly incommensurate theoretical frameworks of class homology and omnivorousness. The results indicate that an omnivorous disposition to music is a relatively middle-status position in the social structure. In contrast, positions characterized by higher levels of cultural capital map onto exclusive and narrower tastes for consecrated culture.
Scalable analytics of air quality batches with Apache Spark and Apache Sedona

According to the American National Institute of Environmental Health Sciences (NIEHS), air pollutants are harmful to the health of humans and other living beings, and cause damage to the climate and to the ecosystem by polluting lakes, streams, and soils. Recent developments in sensor technology, and Internet of Things (IoT) technologies provide an opportunity to use sensor networks to measure air quality, in real time, at a large number of locations. The adoption and deployment of IoT technologies for sensing air quality raises a challenging research agenda related to big data processing, such as, data analysis, scalable architectures, and algorithms for best managing and processing IoT data at different edges in the IoT ecosystem. In response to the DEBS'2021 contest, we design and implement a scalable solution for comparing previous year and current year air quality indexes for German Cities, as well as the calculus of cities' longest streaks of good air quality. Our solution is designed to be scalable. It's based on primo Apache Spark - an open-source unified analytics engine for large-scale data processing, and secundo Apache Sedona for creating spatial indexes, and performing spatial operations over large-scale spatial data.
Evaluations of Network Performance Enhancement on Cloud-native Network Function

Cloud-native network function (CNF) has progressively become a considerable solution adopted by telecom operators to provide network services. The deployment architecture of CNF can support a massive scale with low operational overhead compared to virtual network function (VNF). However, the network performance in CNF encounters severe challenges. One of the hurdles is Packet processing delay, whether in the user space or kernel space. In CNF, both spaces have solutions intend to accelerate the efficiency of processing. However, CNF is an emerging architecture with a lack of evaluation of which technology we should adopt. In this research, we experiment with the different processing acceleration technologies along with different CNF deployment methods. In our experiments, we believe that the kernel space has more opportunity for network acceleration in CNF, especially when CNFs deploy in virtual machines (VM).
Thinking in events: from databases to distributed collaboration software

In this keynote I give a subjective but systematic overview of the landscape of distributed event-based systems, with an emphasis on two areas I have worked on over the last decade: large-scale stream processing with Apache Kafka and associated tools, and real-time collaboration software in the style of Google Docs. While these may seem at first glance to be very different topics, there are also important points of overlap. This paper lays out a taxonomy of event-based systems that shows where their commonalities and differences lie. It also highlights some of the key trade-offs that arise in the implementation of event-based systems, drawing both from distributed systems theory and from experience of their practical deployment. Finally, the paper outlines a number of open research problems in this field.
Tutorial on graph stream analytics

In this short tutorial, we cover recent methods to analyze and model network data accessible as a stream of edges, such as interactions in a social network service, or any other graph database with real-time updates from a stream. First we introduce the data streaming computational model and give examples of the so-called temporal networks. We describe how traditional graph properties (sampling, subgraph counting, graph query evaluation, etc.), low-rank approximation, network embedding, link prediction, and centrality algorithms can be implemented and updated while the edge stream is processed. As an outlook, we discuss among others distributed data stream processing engines and concept drift detection in streams. For most part, we provide sample data and implementation as Python codes packaged in a Docker image.
Design of LSM-tree-based Key-value SSDs with Bounded Tails

Key-value store based on a log-structured merge-tree (LSM-tree) is preferable to hash-based key-value store, because an LSM-tree can support a wider variety of operations and show better performance, especially for writes. However, LSM-tree is difficult to implement in the resource constrained environment of a key-value SSD (KV-SSD), and, consequently, KV-SSDs typically use hash-based schemes. We present PinK, a design and implementation of an LSM-tree-based KV-SSD, which compared to a hash-based KV-SSD, reduces 99th percentile tail latency by 73%, improves average read latency by 42%, and shows 37% higher throughput. The key idea in improving the performance of an LSM-tree in a resource constrained environment is to avoid the use of Bloom filters and instead, use a small amount of DRAM to keep/pin the top levels of the LSM-tree. We also find that PinK is able to provide a flexible design space for a wide range of KV workloads by leveraging the read-write tradeoff in LSM-trees.
Distributed transactions on serverless stateful functions

Serverless computing is currently the fastest-growing cloud services segment. The most prominent serverless offering is Function-as-a-Service (FaaS), where users write functions and the cloud automates deployment, maintenance, and scalability. Although FaaS is a good fit for executing stateless functions, it does not adequately support stateful constructs like microservices and scalable, low-latency cloud applications, mainly because it lacks proper state management support and the ability to perform function-to-function calls. Most importantly, executing transactions across stateful functions remains an open problem. In this paper, we introduce a programming model and implementation for transaction orchestration of stateful serverless functions. Our programming model supports serializable distributed transactions with two-phase commit, as well as relaxed transactional guarantees with Sagas. We design and implement our programming model on Apache Flink StateFun. We choose to build our solution on top of StateFun in order to leverage Flink's exactly-once processing and state management guarantees. We base our evaluation on the YCSB benchmark, which we extended with transactional operations and adapted for the SFaaS programming model. Our experiments show that our transactional orchestration adds 10% overhead to the original system and that Sagas can achieve up to 34% more transactions per second than two-phase commit transactions at a sub-200ms latency.
Monoclonal Antibodies against Cell Wall Chitooligomers as Accessory Tools for the Control of Cryptococcosis

Therapeutic strategies against systemic mycoses can involve antifungal resistance and significant toxicity. Thus, novel therapeutic approaches to fight fungal infections are urgent. ABSTRACT Therapeutic strategies against systemic mycoses can involve antifungal resistance and significant toxicity. Thus, novel therapeutic approaches to fight fungal infections are urgent. Monoclonal antibodies (MAbs) are promising tools to fight systemic mycoses. In this study, MAbs of the IgM isotype were developed against chitin oligomers. Chitooligomers derive from chitin, an essential component of the fungal cell wall and a promising therapeutic target, as it is not synthesized by humans or animals. Surface plasmon resonance (SPR) assays and cell-binding tests showed that the MAbs recognizing chitooligomers have high affinity and specificity for the chitin derivatives. In vitro tests showed that the chitooligomer MAbs increased the fungicidal capacity of amphotericin B against Cryptococcus neoformans. The chitooligomer-binding MAbs interfered with two essential properties related to cryptococcal pathogenesis: biofilm formation and melanin production. In a murine model of C. neoformans infection, the combined administration of the chitooligomer-binding MAb and subinhibitory doses of amphotericin B promoted disease control. The data obtained in this study support the hypothesis that chitooligomer antibodies have great potential as accessory tools in the control of cryptococcosis.
Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of more than 530 PKs have been targeted by FDA-approved medications and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on co-occurrence patterns in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. In historical data, associations between PKs and specific cancers could be predicted years in advance with good accuracy. Our model may be a tool to predict the relevance of inhibiting PKs with specific cancers.
TMEM120 is a coenzyme A-binding membrane protein with structural similarities to ELOVL fatty acid elongase

TMEM120A, also named as TACAN, is a novel membrane protein highly conserved in vertebrates and was recently proposed to be a mechanosensitive channel involved in sensing mechanical pain. Here we present the single particle cryo-EM structure of human TMEM120A which forms a tightly packed dimer with extensive interactions mediate by the N-terminal coiled coil domain (CCD), the C-terminal transmembrane domain (TMD), and the re-entrant loop between the two domains. The TMD of each TMEM120A subunit contains six transmembrane helices (TMs) and has no clear structural feature of a channel protein. Instead, the six TMs form an α-barrel with a deep pocket where a coenzyme A (CoA) molecule is bound. Intriguingly, some structural features of TMEM120A resemble those of elongase for very long-chain fatty acid (ELOVL) despite low sequence homology between them, pointing to the possibility that TEME120A may function as an enzyme for fatty acid metabolism, rather than a mechanosensitive channel.
Interpretable modeling of genotype–phenotype landscapes with state-of-the-art predictive power

Large-scale measurements linking genetic background to biological function have driven a need for models that can incorporate these data for reliable predictions and insight into the underlying biochemical system. Recent modeling efforts, however, prioritize predictive accuracy at the expense of model interpretability. Here, we present LANTERN (https://github.com/usnistgov/lantern), a hierarchical Bayesian model that distills genotype-phenotype landscape (GPL) measurements into a low-dimensional feature-space that represents the fundamental biological mechanisms of the system while also enabling straightforward, explainable predictions. Across a benchmark of large-scale datasets, LANTERN equals or outperforms all alternative approaches, including deep neural networks. LANTERN furthermore extracts useful insights into the landscape including its inherent dimensionality, a latent space of additive mutational effects, and novel metrics of landscape structure. LANTERN facilitates straightforward discovery of fundamental mechanisms in GPLs, while also reliably extrapolating to unexplored regions of genotypic-space.
Patterns of physical activity among the students of an Indian university and their perceptions about the curricular content concerned with health

Background University students are at risk of losing their focus on maintaining healthy levels of physical activity because of their engagements with curricular and co-curricular activities. In India, the physical activity levels of adult population have been reported to be declining in the recent years. However, large studies focusing on university students pertaining to their physical activity are not there in Indian context. Do the curricula in higher education promote physical activity? - is another question that has not been addressed well. Objectives Our work aims at describing the physical activity levels of the students in a large public-funded central university located in northern India. The study also aims at capturing the student perceptions about the emphasis their curricular activities receive in connection with leading a physically active lifestyle. Methods This is a cross-sectional descriptive study and uses International Physical Activity Questionnaire (IPAQ-Long form) to record physical activity among 4586 students. Stratified sampling method was used to enroll the students from each stream (faculty). About 15% of all enrolled students from each faculty were included in the study. The study was conducted in between 2016 and 2019. To capture the student perceptions, we have used a 5-item newly developed scale. Results 2828 (61.7%) male and 1758 (38.3%) female students participated in the study. The mean age of our sample was 22.34 years. Our results indicate that about 14.5% of all students in the study fall under the Inactive category. Further, the perception about the curricular content pertaining to physical activity varied widely between the students of different streams. Discussion Our sample reported a better physical activity pattern in comparison to the reported overall physical activity levels of the adult population of India. Our results also suggest that health-related topics are inadequately represented in many of the streams of higher education in the university.
The Application of Transbronchial Lung Cryobiopsy and Uniportal and Tubeless Video-Assisted Thoracic Surgery in the Multidisciplinary Diagnosis of Interstitial Lung disease—A Real-World Prospective Study

The application of transbronchial lung cryobiopsy (TBLC) and uniportal and tubeless video-assisted thoracic surgery (UT-VATS) in the multidisciplinary diagnosis of interstitial lung disease (ILD) has not been demonstrated in real-world clinical practice. This prospective study included 137 patients with no definitive diagnosis who were the subject of two multidisciplinary discussion (MDD) sessions. As indicated in the first MDD, 67 patients underwent UT-VATS and 70 underwent TBLC. The specificity of biopsy information and its contribution to final MDD diagnosis were evaluated in the second MDD. The post-operative complications and hospitalization costs associated with the two biopsy methods were compared. UT-VATS was favored for patients initially diagnosed with idiopathic pulmonary fibrosis (IPF), bronchiolitis-associated interstitial lung disease (RB-ILD)/desquamative interstitial pneumonia (DIP) and undefined idiopathic interstitial pneumonia (UIIP), while TBLC was preferred for pulmonary lymphangioleiomyomatosis (PLAM) and pulmonary alveolar proteinosis (PAP). The spirometry parameters were better in patients who underwent UT-VATS than those who underwent TBLC. UT-VATS provided more specific pathological results than TBLC (85.7 vs 73.7%, p = 0.06). In patients initially diagnosed with UIIP, pathological information from UT-VATS was more clinically useful than that obtained from TBLC, although both tests contributed similarly to cases initially diagnosed as interstitial pneumonia with auto-immune features (IPAF)/connective tissue disease-related ILD (CTD-ILD). The safety of UT-VATS was comparable with TBLC although TBLC was cheaper during hospitalization (US$4,855.7 vs US$3,590.9, p < 0.001). multidisciplinary discussion decisions about biopsies were driven by current knowledge of sampling and diagnosis capacity as well as potential risks of different biopsy methods. The current MDD considered UT-VATS more informative than TBLC in cases initially diagnosed as UIIP although they were equally valuable in patients initially diagnosed with IPAF/CTD-ILD.
Directional Selection of Microbial Community Reduces Propionate Accumulation in Glycerol and Glucose Anaerobic Bioconversion Under Elevated pCO2

Volatile fatty acid accumulation is a sign of digester perturbation. Previous work showed the thermodynamic limitations of hydrogen and CO2 in syntrophic propionate oxidation under elevated partial pressure of CO2 (pCO2). Here we study the effect of directional selection under increasing substrate load as a strategy to restructure the microbial community and induce cross-protection mechanisms to improve glucose and glycerol conversion performance under elevated pCO2. After an adaptive laboratory evolution (ALE) process, viable cell density increased and predominant microbial groups were modified: an increase in Methanosaeta and syntrophic propionate oxidizing bacteria (SPOB) associated with the Smithella genus was found with glycerol as the substrate. A modest increase in SPOB along with a shift in the predominance of Methanobacterium toward Methanosaeta was observed with glucose as the substrate. The evolved inoculum showed affected diversity within archaeal spp. under 5 bar initial pCO2; however, higher CH4 yield resulted from enhanced propionate conversion linked to the community shifts and biomass adaptation during the ALE process. Moreover, the evolved inoculum attained increased cell viability with glucose and a marginal decrease with glycerol as the substrate. Results showed differences in terms of carbon flux distribution using the evolved inoculum under elevated pCO2: glucose conversion resulted in a higher cell density and viability, whereas glycerol conversion led to higher propionate production whose enabled conversion reflected in increased CH4 yield. Our results highlight that limited propionate conversion at elevated pCO2 resulted from decreased cell viability and low abundance of syntrophic partners. This limitation can be mitigated by promoting alternative and more resilient SPOB and building up biomass adaptation to environmental conditions via directional selection of microbial community.