Miracle-dz/UniFAR-FTUs huggingface dataset:
DrugThatGene: integrative analysis to streamline the identification of druggable genes, pathways and protein complexes from CRISPR screens

MOTIVATION The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) nuclease system has allowed for high-throughput, large scale pooled screens for functional genomic studies. To aid in the translation of functional genomics to therapeutics, we developed DrugThatGene (DTG) as a web-based application that streamlines analysis of potential therapeutic targets identified from functional genetic screens. RESULTS Starting from a gene list as input, DTG offers automated identification of small molecules along with supporting information from human genetic and other relevant databases. Furthermore, DTG aids in the identification of common biological pathways and protein complexes in conjunction with associated small molecule inhibitors. Taken together, DTG aims to expedite the identification of small molecules from the abundance of functional genetic data generated from CRISPR screens. AVAILABILITY AND IMPLEMENTATION DTG is an open-source and free software available as a website at http://drugthatgene.pinellolab. org. Source code is available at: https://github.com/pinellolab/DrugThatGene, which can be downloaded in order to run DTG locally.
When Collective Knowledge Meets Crowd Knowledge in a Smart City: A Prediction Method Combining Open Data Keyword Analysis and Case-Based Reasoning

One of the significant issues in a smart city is maintaining a healthy environment. To improve the environment, huge amounts of data are gathered, manipulated, analyzed, and utilized, and these data might include noise, uncertainty, or unexpected mistreatment of the data. In some datasets, the class imbalance problem skews the learning performance of the classification algorithms. In this paper, we propose a case-based reasoning method that combines the use of crowd knowledge from open source data and collective knowledge. This method mitigates the class imbalance issues resulting from datasets, which diagnose wellness levels in patients suffering from stress or depression. We investigate effective ways to mitigate class imbalance issues in which the datasets have a higher proportion of one class over another. The results of this proposed hybrid reasoning method, using a combination of crowd knowledge extracted from open source data (i.e., a Google search, or other publicly accessible source) and collective knowledge (i.e., case-based reasoning), were that it performs better than other traditional methods (e.g., SMO, BayesNet, IBk, Logistic, C4.5, and crowd reasoning). We also demonstrate that the use of open source and big data improves the classification performance when used in addition to conventional classification algorithms.
Microvascular inflammation in renal allograft biopsies assessed by endothelial and leukocyte co‐immunostain: a retrospective study on reproducibility and clinical/prognostic correlates

The most prominent histologic lesion in antibody‐mediated rejection is microvascular inflammation (MVI); however, its recognition and scoring can be challenging and poorly reproducible between pathologists. We developed a dual immunohistochemical (IHC)‐stain (anti‐CD34/anti‐CD45 for endothelium/leukocytes) as ancillary tool to improve on the semi‐quantitative Banff scores and allow quantification of MVI. We examined the relationship between CD34–CD45 IHC‐based quantitative MVI score (the inflamed peritubular capillary ratio, iptcr) and renal‐graft failure or donor‐specific antibodies (DSA) strength at the time of biopsy. Quantitative iptcr score was significantly associated with renal graft failure (hazard ratio 1.81, per 1 SD‐unit [0.13 points] of iptcr‐increase; P = 0.026) and predicted the presence and strength of DSA (ordinal odds ratio: 2.42; P = 0.005; 75 biopsies/60 kidney transplant recipients; 30 HLA‐ and/or ABO‐incompatible). Next, we assessed inter‐pathologist agreement for ptc score and ptc extent (focal/diffuse) using CD34–CD45 IHC as compared to conventional stain. Compared to conventional stain, CD34–CD45 IHC significantly increased inter‐pathologist agreement on ptc score severity and extent (κ‐coefficient from 0.52–0.80 and 0.46–0.68, respectively, P < 0.001). Our findings show that CD34–CD45 IHC improves reproducibility of MVI scoring and facilitates MVI quantification and introduction of a dual anti‐CD34/CD45 has the potential to improve recognition of MVI ahead of DSA results.
Better with age? A comparison of geriatric and non-geriatric trauma patients’ psychological outcomes 6 months post-injury

ABSTRACT This is the first study to compare both physical and psychological outcomes in geriatric and non-geriatric patients (n = 268) at baseline and 6 months post-trauma. Demographic, clinical, and psychological data, including screens for alcohol use, depressive symptoms, and post-traumatic stress symptoms (PTSS) were collected from 67 geriatric patients (70.7 ± 8.0 years) and 201 non-geriatric patients (40.2 ± 12.8 years) admitted to a Level I trauma center for ≥ 24 h. Geriatric patients were significantly less likely to screen positive for alcohol use at baseline, and depression, PTSS, and alcohol use at follow-up. When not controlling for discharge to rehabilitation or nursing facility, geriatric patients had significantly lower odds of alcohol use at follow-up. There was no significant difference in injury severity, resilience, or pre-trauma psychological status between the two groups. Results indicate that geriatric trauma patients fare better than their younger counterparts at 6 months post-trauma on measures of alcohol use, depression, and PTSS. Screenings and interventions for both age groups could improve psychological health post-trauma, but younger patients may require additional attention.
Heterogeneous Signaling at GABA and Glycine Co-releasing Terminals

The corelease of several neurotransmitters from a single synaptic vesicle has been observed at many central synapses. Nevertheless, the signaling synergy offered by cotransmission and the mechanisms that maintain the optimal release and detection of neurotransmitters at mixed synapses remain poorly understood, thus limiting our ability to interpret changes in synaptic signaling and identify molecules important for plasticity. In the brainstem and spinal cord, GABA and glycine cotransmission is facilitated by a shared vesicular transporter VIAAT (also named VGAT), and occurs at many immature inhibitory synapses. As sensory and motor networks mature, GABA/glycine cotransmission is generally replaced by either pure glycinergic or GABAergic transmission, and the functional role for the continued corelease of GABA and glycine is unclear. Whether or not, and how, the GABA/glycine content is balanced in VIAAT-expressing vesicles from the same terminal, and how loading variability effects the strength of inhibitory transmission is not known. Here, we use a combination of loose-patch (LP) and whole-cell (WC) electrophysiology in cultured spinal neurons of GlyT2:eGFP mice to sample miniature inhibitory post synaptic currents (mIPSCs) that originate from individual GABA/glycine co-releasing synapses and develop a modeling approach to illustrate the gradual change in mIPSC phenotypes as glycine replaces GABA in vesicles. As a consistent GABA/glycine balance is predicted if VIAAT has access to both amino-acids, we test whether vesicle exocytosis from a single terminal evokes a homogeneous population of mixed mIPSCs. We recorded mIPSCs from 18 individual synapses and detected glycine-only mIPSCs in 4/18 synapses sampled. The rest (14/18) were co-releasing synapses that had a significant proportion of mixed GABA/glycine mIPSCs with a characteristic biphasic decay. The majority (9/14) of co-releasing synapses did not have a homogenous phenotype, but instead signaled with a combination of mixed and pure mIPSCs, suggesting that there is variability in the loading and/or storage of GABA and glycine at the level of individual vesicles. Our modeling predicts that when glycine replaces GABA in synaptic vesicles, the redistribution between the peak amplitude and charge transfer of mIPSCs acts to maintain the strength of inhibition while increasing the temporal precision of signaling.
Structure and Content of the Visible Darknet

In this paper, we analyze the topology and the content found on the "darknet", the set of websites accessible via Tor. We created a darknet spider and crawled the darknet starting from a bootstrap list by recursively following links. We explored the whole connected component of more than 34,000 hidden services, of which we found 10,000 to be online. Contrary to folklore belief, the visible part of the darknet is surprisingly well-connected through hub websites such as wikis and forums. We performed a comprehensive categorization of the content using supervised machine learning. We observe that about half of the visible dark web content is related to apparently licit activities based on our classifier. A significant amount of content pertains to software repositories, blogs, and activism-related websites. Among unlawful hidden services, most pertain to fraudulent websites, services selling counterfeit goods, and drug markets.
MAPT (Tau) expression is a biomarker for an increased rate of survival in pediatric neuroblastoma

ABSTRACT Although the impact of MAPT (Tau) expression has been well documented for neuronal cells in the context of tauopathies and neurodegenerative diseases, the impact and role of Tau expression in cancer, and specifically cancers of neuronal origin, is in its infancy. To determine the correlation between MAPT expression and survival in pediatric neuroblastoma, MAPT gene expression for samples from the TARGET pediatric neuroblastoma dataset was assessed. Initial analyses indicated that increased MAPT expression correlated with increased overall survival in neuroblastoma but not in ovarian cancer. Expression of apoptosis- and proliferation-effector genes in the neuroblastoma samples was consistent with the MAPT related survival result. Furthermore, we determined that higher neuroblastoma expression of APP also associated with neurodegeneration, correlated with better neuroblastoma survival rates. In sum, Gene expression associated with neuronal degenerative diseases was associated with a better neuroblastoma outcome. Abbreviations: ALS: Amyotrophic Lateral Sclerosis; APP: Amyloid Precursor Protein gene; CASP3: Caspase 3 gene; CASP9: Caspase 9 gene; H2AFX: H2A histone family, member X gene; HIST1H2AL: Histone H2A type 1 gene; HIST1H2BK: Histone H2B type 1-K gene; HIST1H3J: Histone H3J gene; HIST1H4B: Histone H4B gene; HIST2H2BE: Histone H2B type 2-E gene; HUGO: human genome organization; KM: Kaplan-Meier survival curve; MAPT: Tau gene; OV: Ovarian cancer; SNCA: alpha-syneculin gene; TARDBP: Transactive response DNA binding protein 43 kDa; TCGA: the cancer genome atlas
ReXCam: Resource-Efficient, Cross-Camera Video Analytics at Enterprise Scale

The deployment of large camera networks for video analytics is an established and accelerating trend. Many real video inference applications entail a common problem template: searching for an object or activity of interest (e.g. a person, a speeding vehicle) through a large camera network in live video. This capability, called cross-camera analytics, is compute and data intensive – requiring automated search across cameras and across frames, at the throughput of the live video stream. To address the cost challenge of processing every raw video frame from a large deployment, we present ReXCam, a new system for efficient cross-camera video analytics. ReXCam exploits spatial and temporal locality in the dynamics of real camera networks to guide its inferencetime search for a query identity. In an offline profiling phase, ReXCam builds a cross-camera correlation model that encodes the locality observed in historical traffic patterns. At inference time, ReXCam applies this model to filter frames that are not spatially and temporally correlated with the query identity’s current position. In the cases of occasional missed detections, ReXCam performs a fast-replay search on recently filtered video frames, enabling gracefully recovery. Together, these techniques allow ReXCam to reduce compute workload by 4.6× and improve inference precision by 27% on a well-known video dataset with footage from eight cameras, while maintaining within 1-2% of baseline recall.
On the structure of natural human movement

Understanding of human motor control is central to neuroscience with strong implications in the fields of medicine, robotics and evolution. It is thus surprising that the vast majority of motor control studies have focussed on humanmovement in the laboratory while neglecting behaviour in natural environments. We developed an experimental paradigm to quantify human behaviour in high resolution over extended periods of time in ecologically relevant environments. This allows us to discover novel insights and contradictory evidence to well-established findings obtained in controlled laboratory conditions. Using our data, wemap the statistics of natural humanmovement and their variability between people. The variability and complexity of the data recorded in these settings required us to develop new tools to extract meaningful information in an objective, data-driven fashion. Moving from descriptive statistics to structure, we identify stable structures of movement coordination, particularly within the arm-hand area. Combining our data with numerous published findings, we argue that current hypotheses that the brain simplifies motor control problems by dimensionality reduction are too reductionist. We propose an alternative hypothesis derived from sparse coding theory, a concept which has been successfully applied to the sensory system. To investigate this idea, we develop an algorithm for unsupervised identification of sparse structures in natural movement data. Our method outperforms state-of-the-art algorithms for accuracy and data-efficiency. Applying this method to hand data reveals a dictionary of sparse eigenmotions (SEMs) which are well preserved across multiple subjects. These are highly efficient and invariant representation of natural movement, and suggest a potential higher-order grammatical structure or “movement language”. Our findings make a number of testable predictions about neural coding of movement in the cortex. This has direct consequences for advancing research on dextrous prosthetics and robotics, and has profound implications for our understanding of how the brain controls our body.
Quantitative resistance to clubroot infection mediated by transgenerational epigenetic variation in Arabidopsis

Summary Quantitative disease resistance, often influenced by environmental factors, is thought to be the result of DNA sequence variants segregating at multiple loci. However, heritable differences in DNA methylation, so‐called transgenerational epigenetic variants, also could contribute to quantitative traits. Here, we tested this possibility using the well‐characterized quantitative resistance of Arabidopsis to clubroot, a Brassica major disease caused by Plasmodiophora brassicae. For that, we used the epigenetic recombinant inbred lines (epiRIL) derived from the cross ddm1‐2 × Col‐0, which show extensive epigenetic variation but limited DNA sequence variation. Quantitative loci under epigenetic control (QTL epi) mapping was carried out on 123 epiRIL infected with P. brassicae and using various disease‐related traits. EpiRIL displayed a wide range of continuous phenotypic responses. Twenty QTL epi were detected across the five chromosomes, with a bona fide epigenetic origin for 16 of them. The effect of five QTL epi was dependent on temperature conditions. Six QTL epi co‐localized with previously identified clubroot resistance genes and QTL in Arabidopsis. Co‐localization of clubroot resistance QTL epi with previously detected DNA‐based QTL reveals a complex model in which a combination of allelic and epiallelic variations interacts with the environment to lead to variation in clubroot quantitative resistance.
Neural Machine Translation into Language Varieties

Both research and commercial machine translation have so far neglected the importance of properly handling the spelling, lexical and grammar divergences occurring among language varieties. Notable cases are standard national varieties such as Brazilian and European Portuguese, and Canadian and European French, which popular online machine translation services are not keeping distinct. We show that an evident side effect of modeling such varieties as unique classes is the generation of inconsistent translations. In this work, we investigate the problem of training neural machine translation from English to specific pairs of language varieties, assuming both labeled and unlabeled parallel texts, and low-resource conditions. We report experiments from English to two pairs of dialects, European-Brazilian Portuguese and European-Canadian French, and two pairs of standardized varieties, Croatian-Serbian and Indonesian-Malay. We show significant BLEU score improvements over baseline systems when translation into similar languages is learned as a multilingual task with shared representations.
Release of CXCL12 From Apoptotic Skeletal Cells Contributes to Bone Growth Defects Following Dexamethasone Therapy in Rats

Dexamethasone (Dex) is known to cause significant bone growth impairment in childhood. Although previous studies have suggested roles of osteocyte apoptosis in the enhanced osteoclastic recruitment and local bone loss, whether it is so in the growing bone following Dex treatment requires to be established. The current study addressed the potential roles of chemokine CXCL12 in chondroclast/osteoclast recruitment and bone defects following Dex treatment. Significant apoptosis was observed in cultured mature ATDC5 chondrocytes and IDG‐SW3 osteocytes after 48 hours of 10−6 M Dex treatment, and CXCL12 was identified to exhibit the most prominent induction in Dex‐treated cells. Conditioned medium from the treated chondrocytes/osteocytes enhanced migration of RAW264.7 osteoclast precursor cells, which was significantly inhibited by the presence of the anti‐CXCL12 neutralizing antibody. To investigate the roles of the induced CXCL12 in bone defects caused by Dex treatment, young rats were orally gavaged daily with saline or Dex at 1 mg/kg/day for 2 weeks, and received an intraperitoneal injection of anti‐CXCL12 antibody or control IgG (1 mg/kg, three times per week). Aside from oxidative stress induction systemically, Dex treatment caused reductions in growth plate thickness, primary spongiosa height, and metaphysis trabecular bone volume, which are associated with induced chondrocyte/osteocyte apoptosis and enhanced chondroclast/osteoclast recruitment and osteoclastogenic differentiation potential. CXCL12 was induced in apoptotic growth plate chondrocytes and metaphyseal bone osteocytes. Anti‐CXCL12 antibody supplementation considerably attenuated Dex‐induced chondroclast/osteoclast recruitment and loss of growth plate cartilage and trabecular bone. CXCL12 neutralization did not affect bone marrow osteogenic potential, adiposity, and microvasculature. Thus, CXCL12 was identified as a potential molecular linker between Dex‐induced skeletal cell apoptosis and chondroclastic/osteoclastic recruitment, as well as growth plate cartilage/bone loss, revealing a therapeutic potential of CXCL12 functional blockade in preventing bone growth defects during/after Dex treatment. © 2018 American Society for Bone and Mineral Research.
Designing a Tangible Interface for Manager Awareness in Wilderness Search and Rescue

We present a tangible interface for supporting wilderness search-and-rescue (SAR) managers in maintaining awareness of a large SAR incident, where there are numerous field teams searching for a lost person in a wilderness area. This interface consists of physical and digital representations of the search area and elements of the search activity (e.g., the locations of search teams, weather information, and clues from the field). It is intended to allow SAR managers to inspect information about the response and search area from different perspectives and aid them in planning by allowing them to physically manipulate the representations and explore the data through touch.
Implantable cardioverter–defibrillator in hypertrophic cardiomyopathy

Sudden cardiac death (SCD) is the most devastating complication in hypertrophic cardiomyopathy (HCM). The implantable cardioverter–defibrillator (ICD) has proven to be effective in SCD prevention in several clinical scenarios. In HCM population, it has demonstrated to successfully abort life-threatening ventricular arrhythmias despite the extreme morphology characteristic of HCM, often with massive degrees of left ventricular hypertrophy and/or LV outflow tract obstruction. Studies showed a high rate of appropriate intervention in secondary prevention and in primary prevention of patients considered at high risk. This appropriate intervention rate is even more significant considering the young and otherwise healthy patients that compose HCM population. Since SCD incidence in HCM is relatively low, optimal identification of patients at high risk is crucial. Classical strategy of risk stratification based on clinical risk factors has several limitations and has proven to overestimate risk. A new risk prediction model that provides individual 5-year estimated risk appears to be superior to traditional models based on bivariate risk factors. Perioperative complications seem to be similar to those related to the implant of other cardiac devices, while long-term complications have been traditionally in the spotlight. HCM patients are considered more vulnerable to ICD-related complications and inappropriate ICD therapy because of their young age at implant and increased prevalence of atrial fibrillation, but long-term follow-up data on ICD-related complications in general practice is limited. The subcutaneous implantable cardioverter defibrillator seems to be a safe and effective alternative in HCM, although long-term data are scarce.
Improving GAN with neighbors embedding and gradient matching

We propose two new techniques for training Generative Adversarial Networks (GANs) in the unsupervised setting. Our objectives are to alleviate mode collapse in GAN and improve the quality of the generated samples. First, we propose neighbor embedding, a manifold learning-based regularization to explicitly retain local structures of latent samples in the generated samples. This prevents generator from producing nearly identical data samples from different latent samples, and reduces mode collapse. We propose an inverse t-SNE regularizer to achieve this. Second, we propose a new technique, gradient matching, to align the distributions of the generated samples and the real samples. As it is challenging to work with high-dimensional sample distributions, we propose to align these distributions through the scalar discriminator scores. We constrain the difference between the discriminator scores of the real samples and generated ones. We further constrain the difference between the gradients of these discriminator scores. We derive these constraints from Taylor approximations of the discriminator function. We perform experiments to demonstrate that our proposed techniques are computationally simple and easy to be incorporated in existing systems. When Gradient matching and Neighbour embedding are applied together, our GN-GAN achieves outstanding results on 1D/2D synthetic, CIFAR-10 and STL-10 datasets, e.g. FID score of 30.80 for the STL-10 dataset. Our code is available at: https://github.com/tntrung/gan