Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Resolution Ecological Niche Modeling of Ixodes scapularis Ticks Based on Passive Surveillance Data at the Northern Frontier of Lyme Disease Emergence in North America

Abstract Background: Lyme disease (LD) is a bacterial infection transmitted by the black-legged tick (Ixodes scapularis) in eastern North America. It is an emerging disease in Canada due to the expanding range of its tick vector. Environmental risk maps for LD, based on the distribution of the black-legged tick, have focused on coarse determinants such as climate. However, climatic factors vary little within individual health units, the level at which local public health decision-making takes place. We hypothesize that high-resolution environmental data and routinely collected passive surveillance data can be used to develop valid models for tick occurrence and provide insight into ecological processes affecting tick presence at fine scales. Methods: We used a maximum entropy algorithm (MaxEnt) to build a habitat suitability model for I. scapularis in Ottawa, Ontario, Canada using georeferenced occurrence points from passive surveillance data collected between 2013 and 2016 and high-resolution land cover and elevation data. We evaluated our model using an independent tick presence/absence dataset collected through active surveillance at 17 field sites during the summer of 2017. Results: Our model showed a good ability to discriminate positive sites from negative sites for tick presence (AUC = 0.878 ± 0.019, classification accuracy = 0.835 ± 0.020). Heavily forested suburban and rural areas in the west and southwest of Ottawa had higher predicted suitability than the more agricultural eastern areas. Conclusions: This study demonstrates the value of passive surveillance data to model local-scale environmental risk for the tick vector of LD at sites of interest to public health. Given the rising incidence of LD and other emerging vector-borne diseases in Canada, our findings support the ongoing collection of these data and collaboration with researchers to provide a timely and accurate portrait of evolving public health risk.
Dilated U-Net based Segmentation of Organs at Risk in Thoracic CT Images

Cancer is one of the leading cause of death across the globe and projection of radiation towards tumor is the standard treatment of cancer. The first step of irradiation is to delineate tumor from organs near to the tumor. Unlike previous methods of CT segmentation, this paper proposed a procedure for segmentation of organs individually in CT images of the thoracic region such as Heart, Aorta, Trachea and Esophagus and merging them to form multi organ Segmented image. The aim of this method is to avoid coarse output from dilated UNets. The overlapping issues has addressed by calculating the mode of eight neighborhood of pixels. The performance of the proposed technique tested on 60 CT scans collected from SegTHOR Challenge. Dice ratio and Hausdorff distance have used in evaluation paradigm.
The genetic landscape of a physical interaction

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions.
Neurocysticercosis and Hippocampal Atrophy: MRI Findings and the Evolution of Viable or Calcified Cysts in Patients With Neurocysticercosis

Neurocysticercosis (NC) is the most common parasitic infection of the central nervous system (CNS). Several studies have reported an association between NC and mesial temporal lobe epilepsy (MTLE). We intended to evaluate the frequency of hippocampal atrophy (HA), clinical evolution and imaging findings in patients with calcified neurocysticercotic lesions (CNLs). Methods: One hundred and eighty-one subjects (70 cases and 111 controls) were evaluated for the presence or absence of HA. We assessed the imaging findings, and the evolution of patients with NC treated or not with anthelmintics for NC. Results: Hippocampal volumes were different between cases and controls (p < 0.001). Seventy percent of the cases presented HA. 52.2% of the patients without a history of anthelmintic treatment for NC had reports of epileptic seizures. There was an association between non-treatment and the later occurrence of epileptic seizures (p = 0.006). There was an association between perilesional edema on MRI and the presence of uncontrolled epileptic seizures (p = 0.004). Conclusions: Hippocampal atrophy is frequent in patients with NCC. There was an association between no anthelmintic treatment in the acute phase of NC, perilesional edema, more pronounced hippocampal atrophy, and the occurrence of refractory seizures.
Dendritic Cells From the Cervical Mucosa Capture and Transfer HIV-1 via Siglec-1

Antigen presenting cells from the cervical mucosa are thought to amplify incoming HIV-1 and spread infection systemically without being productively infected. Yet, the molecular mechanism at the cervical mucosa underlying this viral transmission pathway remains unknown. Here we identified a subset of HLA-DR+ CD14+ CD11c+ cervical DCs at the lamina propria of the ectocervix and the endocervix that expressed the type-I interferon inducible lectin Siglec-1 (CD169), which promoted viral uptake. In the cervical biopsy of a viremic HIV-1+ patient, Siglec-1+ cells harbored HIV-1-containing compartments, demonstrating that in vivo, these cells trap viruses. Ex vivo, a type-I interferon antiviral environment enhanced viral capture and trans-infection via Siglec-1. Nonetheless, HIV-1 transfer via cervical DCs was effectively prevented with antibodies against Siglec-1. Our findings contribute to decipher how cervical DCs may boost HIV-1 replication and promote systemic viral spread from the cervical mucosa, and highlight the importance of including inhibitors against Siglec-1 in microbicidal strategies.
The Impact of Leadership and Psychosocial Work Environment on Recipient Satisfaction in Nursing Homes and Home Care

This study examines the association between nursing assistants’ assessment of leadership, their psychosocial work environment, and satisfaction among older people receiving care in nursing homes and home care. Cross-sectional surveys were conducted with nursing assistants (n = 1,132) and people receiving care (n = 1,535) in 45 nursing homes and 21 home care units. Direct leadership was associated with the psychosocial work environment in nursing homes and home care. Furthermore, better leadership was related to higher satisfaction among nursing assistants and older people in nursing homes. Thus, indirect leadership had no effect on recipients’ satisfaction in either nursing homes or home care. The path analysis showed an indirect effect between leadership factors and recipient satisfaction. The findings suggest that the psychosocial work environment of nursing assistants and recipient satisfaction in nursing homes can be increased by improving leadership.
rPredictorDB: a predictive database of individual secondary structures of RNAs and their formatted plots

Abstract Secondary data structure of RNA molecules provides insights into the identity and function of RNAs. With RNAs readily sequenced, the question of their structural characterization is increasingly important. However, RNA structure is difficult to acquire. Its experimental identification is extremely technically demanding, while computational prediction is not accurate enough, especially for large structures of long sequences. We address this difficult situation with rPredictorDB, a predictive database of RNA secondary structures that aims to form a middle ground between experimentally identified structures in PDB and predicted consensus secondary structures in Rfam. The database contains individual secondary structures predicted using a tool for template-based prediction of RNA secondary structure for the homologs of the RNA families with at least one homolog with experimentally solved structure. Experimentally identified structures are used as the structural templates and thus the prediction has higher reliability than de novo predictions in Rfam. The sequences are downloaded from public resources. So far rPredictorDB covers 7365 RNAs with their secondary structures. Plots of the secondary structures use the Traveler package for readable display of RNAs with long sequences and complex structures, such as ribosomal RNAs. The RNAs in the output of rPredictorDB are extensively annotated and can be viewed, browsed, searched and downloaded according to taxonomic, sequence and structure data. Additionally, structure of user-provided sequences can be predicted using the templates stored in rPredictorDB.
Maximizing Polyphenol Content to Uncork the Relationship Between Wine and Cancer

Studies have revealed conflicting results regarding the risk of cancer from alcohol consumption. Furthermore, some studies have suggested that wine may have benefits that separate it from other alcoholic beverages. As wine contains a significant amount of chemicals, specifically polyphenols like anthocyanins and proanthocyanidins (PA), that can affect cellular function and promote health, this hypothesis is reasonably supported by recent research. Polyphenols promote several anticancer cellular pathways, including xenobiotic metabolism, support of innate antioxidant production, and stimulation of phase I and II detoxification of carcinogens. However, the multitude of growing and production conditions of grapes, including temperature, water availability, soil type, maceration, and aging can result in a remarkably varying final product based on the available literature. Thus, we hypothesize that wines produced from grapes cultivated between steady daily temperatures at 15–25°C with moderate sun exposure from flowering to harvest, lower vine-water status, resulting either from lower precipitation, and irrigation practices or more permeable soil types, limitation of fertilizers, extended maceration, and aging in oak will impact the concentration of anthocyanins and PA in the finished wine and may have a differential impact on cancer. This higher concentration of polyphenols would, in theory, create a healthier wine, thus explaining the conflicting reports on the benefits or harms of wine.
Agonist c-Met Monoclonal Antibody Augments the Proliferation of hiPSC-derived Hepatocyte-Like Cells and Improves Cell Transplantation Therapy for Liver Failure in Mice

Rationale: Hepatocyte-like cells (HLCs) derived from human induced pluripotent stem cells (hiPSCs) have been developed to address the shortage of primary human hepatocytes (PHHs) for therapeutic applications. However, the in vivo repopulation capacity of HLCs remains limited. This study investigated the roles of agonist antibody activating the c-Met receptor in promoting the in vivo proliferation and repopulation of engrafted PHHs and/or HLCs in mice with liver injuries due to different causes. Methods: An agonist c-Met receptor antibody (5D5) was used to treat PHHs and hiPSC-HLCs in both cell culture and hepatocyte-engrafted immunodeficient mice mimicking various inherited and acquired liver diseases. The promoting roles and potential influence on the hepatic phenotype of the 5D5 regimen in cell transplantation-based therapeutic applications were systematically evaluated. Results: In hiPSC-HLC cell cultures, 5D5 treatment significantly stimulated c-Met receptor downstream signalling pathways and accelerated cell proliferation in dose-dependent and reversible manners. In contrast, only slight but nonsignificant promotion was observed in 5D5-treated PHHs. In vivo administration of 5D5 greatly promoted the expansion of implanted hiPSC-HLCs in fumarylacetoacetate hydrolase (Fah) deficient mice, resulting in significantly increased human albumin levels and high human liver chimerism (over 40%) in the transplanted mice at week 8 after transplantation. More importantly, transplantation of hiPSC-HLCs in combination with 5D5 significantly prolonged animal survival and ameliorated liver pathological changes in mice with acute and/or chronic liver injuries caused by Fas agonistic antibody treatment, carbon tetrachloride treatment and/or tyrosinemic stress. Conclusion: Our results demonstrated that the proliferation of hiPSC-HLCs can be enhanced by antibody-mediated modulation of c-Met signalling and facilitate hiPSC-HLC-based therapeutic applications for life-threatening liver diseases.
Transcriptomic definition of molecular subgroups of small round cell sarcomas

Sarcoma represents a highly heterogeneous group of tumours. We report here the first unbiased and systematic search for gene fusions combined with unsupervised expression analysis of a series of 184 small round cell sarcomas. Fusion genes were detected in 59% of samples, with half of them being observed recurrently. We identified biologically homogeneous groups of tumours such as the CIC‐fused (to DUX4, FOXO4 or NUTM1) and BCOR‐rearranged (BCOR–CCNB3, BCOR–MAML3, ZC3H7B–BCOR, and BCOR internal duplication) tumour groups. VGLL2‐fused tumours represented a more biologically and pathologically heterogeneous group. This study also refined the characteristics of some entities such as EWSR1–PATZ1 spindle cell sarcoma or FUS–NFATC2 bone tumours that are different from EWSR1–NFATC2 tumours and transcriptionally resemble CIC‐fused tumour entities. We also describe a completely novel group of epithelioid and spindle‐cell rhabdomyosarcomas characterized by EWSR1– or FUS–TFCP2 fusions. Finally, expression data identified some potentially new therapeutic targets or pathways. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Impaired inference in a case of developmental amnesia

Amnesia is associated with impairments in relational memory, which is critically supported by the hippocampus. By adapting the transitivity paradigm, we previously showed that age‐related impairments in inference were mitigated when judgments could be predicated on known pairwise relations, however, such advantages were not observed in the adult‐onset amnesic case D.A. Here, we replicate and extend this finding in a developmental amnesic case (N.C.), who also shows impaired relational learning and transitive expression. Unlike D.A. , N.C. 's damage affected the extended hippocampal system and diencephalic structures, and does not extend to neocortical areas that are affected in D.A. Critically, despite their differences in etiology and affected structures, N.C. and D.A. perform similarly on the task. N.C. showed intact pairwise knowledge, suggesting that he is able to use existing semantic information, but this semantic knowledge was insufficient to support transitive expression. The present results suggest a critical role for regions connected to the hippocampus and/or medial prefrontal cortex in inference beyond learning of pairwise relations. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.
Tetris: Optimizing cloud resource usage unbalance with elastic VM

Recently, the cloud systems face an increasing number of big data applications. It becomes an important issue for the cloud providers to allocate resources so as to accommodate as many of these big data applications as possible. In current cloud service, e.g., Amazon EMR, a job runs on a fixed cluster. This means that a fixed amount of resources (e.g. CPU, memory) is allocated to the life cycle of this job. We observe that the resources are inefficiently used in such services because of resources usage unbalance. Therefore, we propose a runtime elastic VM approach where the cloud system can increase or decrease the number of CPUs at different time periods for the jobs. There is little change to such services as Amazon EMR, yet the cloud system can accommodate many more jobs. In this paper, we first present a measurement study to show the feasibility and the quantitative impact of adjusting VM configurations dynamically. We then model the task and job completion time of big data applications, which are used for elastic VM adjustment decisions. We validate our models through experiments. We present Tetris, an elastic VM strategy based on cloud system that can better optimize resource utilization to support big data applications. We further implement a Tetris prototype and comprehensively evaluate Tetris on a real private cloud platform using Facebook trace and Wikipedia dataset. We observe that with Tetris, the cloud system can accommodate 31.3% more jobs.
Effect of group-based outpatient physiotherapy on function after total knee replacement: The ARENA randomised controlled trial. Arthritis Care and Research

Objective To evaluate the long-term clinical effectiveness of a novel group-based outpatient physiotherapy following total knee replacement (TKR). Methods In this two centre, unblinded, superiority, randomised controlled trial, 180 patients on a waiting list for primary TKR due to osteoarthritis were randomised to a 6 session group-based outpatient physiotherapy intervention and usual care (n=89) or usual care alone (n=91). The primary outcome was patient-reported functional ability measured by the Lower Extremity Functional Scale at 12 months post-operative. Secondary outcomes included knee symptoms, depression, anxiety and satisfaction. Questionnaires were completed pre-operatively and 3, 6 and 12 months post-operatively.
3D Enhanced Multi-scale Network for Thoracic Organs Segmentation

We focus on the segmentation of 4 OAR: heart, aorta, trachea, esophagus through Computed Tomography (CT) thoracic scans, where the esophagus is the most challenging to segment due to its volume imbalance and narrow shape. In this paper, a 3D Enhanced Multi-scale Network (EMSN) is proposed to improve the performance, which is a reﬁned variant of the 3D FCN network. Speciﬁcally, an extra stage is added to reﬁne the prediction map by concatenating a pre-liminary prediction map with the CT image to utilize auto-context. 3D dilated convolution is employed to enlarge the receptive ﬁeld of convolution kernel without loss of resolution. Besides, more residual connections are added in V-Net to avoid gradient degradation during back-propagation. For data preprocessing, a maximum bounding box is calculated and used to crop raw data to reduce calculation cost. And to achieve data augmentation, registration is performed by aligning each CT image and corresponding ground truth with the others in training set to generate non-linearly transformed new CT images along with annotations. The consensus is utilized by retaining models in the last few epochs to segment and vote for the ﬁnal prediction. Experiments demonstrate that our EMSN model achieves competitive performance on SegTHOR dataset.
PGE2/EP4 antagonism enhances tumor chemosensitivity by inducing extracellular vesicle‐mediated clearance of cancer stem cells

Cells expressing mesenchymal/basal phenotypes in tumors have been associated with stem cell properties. Cancer stem cells (CSCs) are often resistant to conventional chemotherapy. We explored overcoming mesenchymal CSC resistance to chemotherapeutic agents. Our goal was to reduce CSC numbers in vivo, in conjunction with chemotherapy, to reduce tumor burden. Analysis of clinical samples demonstrated that COX‐2/PGE2/EP4 signaling is elevated in basal‐like and chemoresistant breast carcinoma and is correlated with survival and relapse of breast cancer. EP4 antagonism elicts a striking shift of breast cancer cells from a mesenchymal/CSC state to a more epithelial non‐CSC state. The transition was mediated by EP4 antagonist‐induced extracellular vesicles [(EVs)/exosomes] which removed CSC markers, mesenchymal markers, integrins, and drug efflux transporters from the CSCs. In addition, EP4 antagonism‐induced CSC EVs/exosomes can convert tumor epithelial/non‐CSCs to mesenchymal/CSCs able to give rise to tumors and to promote tumor cell dissemination. Because of its ability to induce a CSC‐to‐non‐CSC transition, EP4 antagonist treatment in vivo reduced the numbers of CSCs within tumors and increased tumor chemosensitivity. EP4 antagonist treatment enhances tumor response to chemotherapy by reducing the numbers of chemotherapy‐resistant CSCs available to repopulate the tumor. EP4 antagonism can collaborate with conventional chemotherapy to reduce tumor burden.
Individual-Based Modeling of Amazon Forests Suggests That Climate Controls Productivity While Traits Control Demography

Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model - the Trait-based Forest Simulator (TFS) – to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal versus aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (‘fast’ versus ‘slow’ leaf traits, and high versus low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modelled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.