Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNA-Detargeted Mengovirus for Oncolytic Virotherapy

ABSTRACT Mengovirus, a member of the Picornaviridae family, has a broad cell tropism and can cause encephalitis and myocarditis in multiple mammalian species. Attenuation has been achieved by shortening the polycytidine tract in the 5′ noncoding region (NCR). A poly(C)-truncated strain of mengovirus, vMC24, resulted in significant tumor regression in immunocompetent BALB/c mice bearing syngeneic MPC-11 plasmacytomas, but the associated toxicities were unacceptable. To enhance its safety profile, microRNA target sequences complementary to miR-124 or miR-125 (enriched in nervous tissue), miR-133 and miR-208 (enriched in cardiac tissue), or miR-142 (control; enriched in hematopoietic tissues) were inserted into the vMC24 NCRs. The microRNA-detargeted viruses showed reduced replication and cell killing specifically in cells expressing the cognate microRNAs, but certain insertions additionally were associated with nonspecific suppression of viral fitness in vivo. In vivo toxicity testing confirmed that miR-124 targets within the 5′ NCR suppressed virus replication in the central nervous system while miR-133 and miR-208 targets in the 3′ NCR suppressed viral replication in cardiac tissue. A dual-detargeted virus named vMC24-NC, with miR-124 targets in the 5′ NCR and miR-133 plus miR-208 targets in the 3′ NCR, showed the suppression of replication in both nervous and cardiac tissues but retained full oncolytic potency when administered by intratumoral (106 50% tissue culture infectious doses [TCID50]) or intravenous (107 to 108 TCID50) injection into BALB/c mice bearing MPC-11 plasmacytomas. Overall survival of vMC24-NC-treated tumor-bearing mice was significantly improved compared to that of nontreated mice. MicroRNA-detargeted mengoviruses offer a promising oncolytic virotherapy platform that merits further development for clinical translation. IMPORTANCE The clinical potential of oncolytic virotherapy for cancer treatment has been well demonstrated, justifying the continued development of novel oncolytic viruses with enhanced potency. Here, we introduce mengovirus as a novel oncolytic agent. Mengovirus is appealing as an oncolytic virotherapy platform because of its small size, simple genome structure, rapid replication cycle, and broad cell/species tropism. However, mengovirus can cause encephalomyelitis and myocarditis. It can be partially attenuated by shortening the poly(C) tract in the 5′ NCR but remains capable of damaging cardiac and nervous tissue. Here, we further enhanced the safety profile of a poly(C)-truncated mengovirus by incorporating muscle- and neuron-specific microRNA target sequences into the viral genome. This dual-detargeted virus has reduced pathogenesis but retained potent oncolytic activity. Our data show that microRNA targeting can be used to further increase the safety of an attenuated mengovirus, providing a basis for its development as an oncolytic platform.
Sparse Factorization Layers for Neural Networks with Limited Supervision

Whereas CNNs have demonstrated immense progress in many vision problems, they suffer from a dependence on monumental amounts of labeled training data. On the other hand, dictionary learning does not scale to the size of problems that CNNs can handle, despite being very effective at low-level vision tasks such as denoising and inpainting. Recently, interest has grown in adapting dictionary learning methods for supervised tasks such as classification and inverse problems. We propose two new network layers that are based on dictionary learning: a sparse factorization layer and a convolutional sparse factorization layer, analogous to fully-connected and convolutional layers, respectively. Using our derivations, these layers can be dropped in to existing CNNs, trained together in an end-to-end fashion with back-propagation, and leverage semisupervision in ways classical CNNs cannot. We experimentally compare networks with these two new layers against a baseline CNN. Our results demonstrate that networks with either of the sparse factorization layers are able to outperform classical CNNs when supervised data are few. They also show performance improvements in certain tasks when compared to the CNN with no sparse factorization layers with the same exact number of parameters.
Being Called to Safety: Occupational Callings and Safety Climate in the Emergency Medical Services

Objective: The aim of this study was to investigate the importance of safety climate in the Emergency Medical Services (EMS) and to assess occupational callings as a boundary condition for the effect of safety climate on safety behaviors. Methods: EMS professionals (n = 132) participated in a three-wave survey study. Hierarchical linear regressions were conducted to test the moderating effects of occupational callings. Results: Safety climate was significantly related to safety behavior, and occupational callings moderated this direct relationship (&Dgr;R2 = 0.02 to 0.03, P < 0.05). Specifically, when occupational callings were high, the relationship between safety climate and safety behaviors was stronger, and when occupational callings were low, the relationship was weaker. Conclusion: In this EMS sample, safety climate was an important predictor of safety behavior. Further, occupational callings moderated this relationship, suggesting that callings may serve as a boundary condition.
An Evaluation of Deep Learning in Loop Closure Detection for Visual SLAM

Loop closure detection is a crucial module in simultaneous localization and mapping (SLAM), which reduces the accumulative error in building the environment map. Traditional appearance-based methods mostly utilize hand-crafted features, which are designed based on human expertise. Recent advances in deep learning inspire us to investigate its application in loop closure detection. Different from traditional approaches, deep learning methods automatically learn features from raw data and has better adaptability to complex environment changes. In this paper, we perform a comparison and analysis of several popular deep neural networks and traditional methods for loop closure detection. We evaluate their performance on two open datasets in terms of accuracy and processing time. According to the experimental results, we conclude that deep neural network is suitable for loop closure detection.
Position Based Nucleotide Analysis of miR168 Family in Higher Plants and its Targets in Mammalian Transcripts.

BACKGROUND miRNA are the post transcriptional regulator of the genes. The conserved miR168 family is evaluated for position based nucleotide preference in higher plants. Low density lipoprotein receptor adaptor protein 1 (LDLRAP1) target validated for miR168a obtained from rice origin is reported. METHODS The mature miRNA sequences include miR168-5p and miR168-3p, were obtained from miRBase (v21, June 2014) for 15 families (28 plants). The preferred position based nucleotide sequences were obtained using Data Analysis in Molecular Biology and Evolution software. The miR168-5p was subjected to cross kingdom analysis using psRNATarget. Target expression and functional annotation was analyzed by using Human Protein Atlas database WEB-based Gene SeTAnaLysis Toolkit. RESULTS miR168-5p shows same nucleotides at positions 1-6, 8-9, 11-12, 15-17 and 19. Also, miR168-3p is present in 3 families (10 plants) shows the same nucleotide at position 1-11, 13-15 and 17-21. The 123 targets in human transcriptome were identified showing 58% cleavage and 41% translation repression. Low density lipoprotein receptor adaptor protein 1 (LDLRAP1) target validated for miR168a obtained from rice origin, could also be targeted from miR168 from any other plant sources. The randomly selected 10 targets include some important genes likeRPL34, ATXN1, AKAPI3 and ALS2 and is involved in transcription, cell trafficking, cell metabolism and neurodegenerative disorder. CONCLUSION Our work suggests that miR168 family has conserved sequence in higher plants. The seed region position 2-8 shows 70-95% pairing with human targets. Cleavage site at position 10-14 and these were analysed for the base preference with the targets showed 80-96% Watson Crick pairing.
Interval Temporal Logics: a Journey

We discuss a family of modal logics for reasoning about relational structures of intervals over (usually) linear orders, with modal operators associated with the various binary relations between such intervals, known as Allen’s interval relations. The formulae of these logics are evaluated at intervals rather than points and the main effect of that semantic feature is substantially higher expressiveness and computational complexity of the interval logics as compared to point-based ones. Without purporting to provide a comprehensive survey of the field, we take the reader to a journey through the main developments in it over the past 10 years and outline some landmark results on expressiveness and (un)decidability of the satisfiability problem for the family of interval logics.
The Mechanisms for Within-Host Influenza Virus Control Affect Model-Based Assessment and Prediction of Antiviral Treatment

Models of within-host influenza viral dynamics have contributed to an improved understanding of viral dynamics and antiviral effects over the past decade. Existing models can be classified into two broad types based on the mechanism of viral control: models utilising target cell depletion to limit the progress of infection and models which rely on timely activation of innate and adaptive immune responses to control the infection. In this paper, we compare how two exemplar models based on these different mechanisms behave and investigate how the mechanistic difference affects the assessment and prediction of antiviral treatment. We find that the assumed mechanism for viral control strongly influences the predicted outcomes of treatment. Furthermore, we observe that for the target cell-limited model the assumed drug efficacy strongly influences the predicted treatment outcomes. The area under the viral load curve is identified as the most reliable predictor of drug efficacy, and is robust to model selection. Moreover, with support from previous clinical studies, we suggest that the target cell-limited model is more suitable for modelling in vitro assays or infection in some immunocompromised/immunosuppressed patients while the immune response model is preferred for predicting the infection/antiviral effect in immunocompetent animals/patients.
A Combined One-Class SVM and Template-Matching Approach for User-Aided Human Fall Detection by Means of Floor Acoustic Features

The primary cause of injury-related death for the elders is represented by falls. The scientific community devoted them particular attention, since injuries can be limited by an early detection of the event. The solution proposed in this paper is based on a combined One-Class SVM (OCSVM) and template-matching classifier that discriminate human falls from nonfalls in a semisupervised framework. Acoustic signals are captured by means of a Floor Acoustic Sensor; then Mel-Frequency Cepstral Coefficients and Gaussian Mean Supervectors (GMSs) are extracted for the fall/nonfall discrimination. Here we propose a single-sensor two-stage user-aided approach: in the first stage, the OCSVM detects abnormal acoustic events. In the second, the template-matching classifier produces the final decision exploiting a set of template GMSs related to the events marked as false positives by the user. The performance of the algorithm has been evaluated on a corpus containing human falls and nonfall sounds. Compared to the OCSVM only approach, the proposed algorithm improves the performance by 10.14% in clean conditions and 4.84% in noisy conditions. Compared to Popescu and Mahnot (2009) the performance improvement is 19.96% in clean conditions and 8.08% in noisy conditions.
Tensile, charpy, creep and structural tests

EUROFER 97 - the European reference material for the first wall of a DEMO fusion reactor - was produced as 3.5 t batch of rods and plates. Following the history of the development activities from conventional martensitic 12 % Cr steel, MANET and OPTIFER up to the low or reduced activation (RAFM) EUROFER steel, results obtained from experiments on specimens from rods (O 100 mm) and plates (14 mm) are presented for a basic characterization. Physical and mechanical properties are compared with those of OPTIFER-1W and the F82H-mod 2% W steel. The transition behaviour was determined by plotting a continuous TTT (time temperature transition) diagram. In addition, extension coefficients were determined from room temperature up to 1000 °C. Hardening tests at temperatures from 850 °C to 1120 °C illustrated the range of maximum hardness as well as grain size development. Tempering tests and additional annealing experiments from 300 °C to 875 °C allowed characterizing tempering behaviour and stability. Charpy properties were examined for various heat treatments and specimen types between 60 °C and -100 °C. Further, ductility criteria like FATT, DBTT and 68 J were determined. Particular attention was paid to the influence of grain size and O 2 content. Tensile strength was measured for several heat treatments between room temperature and 700 °C. Long-term ageing was investigated by means of stabilization annealing experiments. These were carried out with various temperature/time combinations including tensile tests. In EUROFER tensile strength was hardly affected by the different heat treatments while the ductility criteria showed only a moderate increase in temperature. Therefore, it can be concluded that EUROFER is not susceptible to ageing. Creep and creep rupture properties were investigated in the temperature range of 450 °C to 650 °C. So far, creep times of up to 15000 h have been covered by the experiments. The status of the test program allows for an extrapolation of the 1 % yield limits and times to rupture to a period of 20000 h. Creep behaviour and stress exponents can be determined reliably for the experimental stress range. However, for the design relevant low stress range (= 100 MPa) up to 550 °C creep data are still lacking. Therefore, special creep tests at 500 °C and 550 °C were started in 2001. They are aimed at the experimental determination of design relevant yield limits (0.01-1%) and minimum creep rate behaviour.
Decoding the dynamic DNA methylation and hydroxymethylation landscapes in endodermal lineage intermediates during pancreatic differentiation of hESC

Abstract Dynamic changes in DNA methylation and demethylation reprogram transcriptional outputs to instruct lineage specification during development. Here, we applied an integrative epigenomic approach to unveil DNA (hydroxy)methylation dynamics representing major endodermal lineage intermediates during pancreatic differentiation of human embryonic stem cells (hESCs). We found that 5-hydroxymethylcytosine (5hmC) marks genomic regions to be demethylated in the descendent lineage, thus reshaping the DNA methylation landscapes during pancreatic lineage progression. DNA hydroxymethylation is positively correlated with enhancer activities and chromatin accessibility, as well as the selective binding of lineage-specific pioneer transcription factors, during pancreatic differentiation. We further discovered enrichment of hydroxymethylated regions (termed ‘5hmC-rim’) at the boundaries of large hypomethylated functional genomic regions, including super-enhancer, DNA methylation canyon and broad-H3K4me3 peaks. We speculate that ‘5hmC-rim’ might safeguard low levels of cytosine methylation at these regions. Our comprehensive analysis highlights the importance of dynamic changes of epigenetic landscapes in driving pancreatic differentiation of hESC.
Mindfulness-based stress reduction and cognitive behavioral therapy for chronic low back pain: similar effects on mindfulness, catastrophizing, self-efficacy, and acceptance in a randomized controlled trial

Abstract Cognitive behavioral therapy (CBT) is believed to improve chronic pain problems by decreasing patient catastrophizing and increasing patient self-efficacy for managing pain. Mindfulness-based stress reduction (MBSR) is believed to benefit patients with chronic pain by increasing mindfulness and pain acceptance. However, little is known about how these therapeutic mechanism variables relate to each other or whether they are differentially impacted by MBSR vs CBT. In a randomized controlled trial comparing MBSR, CBT, and usual care (UC) for adults aged 20 to 70 years with chronic low back pain (N = 342), we examined (1) baseline relationships among measures of catastrophizing, self-efficacy, acceptance, and mindfulness and (2) changes on these measures in the 3 treatment groups. At baseline, catastrophizing was associated negatively with self-efficacy, acceptance, and 3 aspects of mindfulness (nonreactivity, nonjudging, and acting with awareness; all P values <0.01). Acceptance was associated positively with self-efficacy (P < 0.01) and mindfulness (P values <0.05) measures. Catastrophizing decreased slightly more posttreatment with MBSR than with CBT or UC (omnibus P = 0.002). Both treatments were effective compared with UC in decreasing catastrophizing at 52 weeks (omnibus P = 0.001). In both the entire randomized sample and the subsample of participants who attended ≥6 of the 8 MBSR or CBT sessions, differences between MBSR and CBT at up to 52 weeks were few, small in size, and of questionable clinical meaningfulness. The results indicate overlap across measures of catastrophizing, self-efficacy, acceptance, and mindfulness and similar effects of MBSR and CBT on these measures among individuals with chronic low back pain.
Ancestral Variation in Orbital Rim Shape: A Three‐Dimensional Pilot Study

Traditional nonmetric methods of ancestry assessment posit orbital rim shape varies among ancestral groups. This pilot study uses morphometric analysis of 3D orbital variation to test discrimination among individuals of primarily European, African, and Asian ancestry. Although the size and nature of the sample analyzed limit inferences for other samples, principal components analysis suggests ancestry has a significant effect on rim shape (p = 2.93e‐04). European orbits display more marked folding of the orbit in the sagittal plane than either African or Asian orbits, while the lateral margin of African orbits lies further posterior relative to the medial margin when compared to Asian orbits. The findings suggest curviplanar relationships are the most ancestrally informative aspect of orbital rim shape; these relationships may be distorted by perspective based on orientation of the skull relative to the viewer in traditional nonmetric analyses. Additional studies on geometric morphometric approaches to ancestry assessment are therefore warranted.
Simultaneous targeted inhibition of Sox2‐Oct4 transcription factors using decoy oligodeoxynucleotides to repress stemness properties in mouse embryonic stem cells

Transcriptional master regulators like Sox2 and Oct4, which are expressed in various human tumors, have been shown to cause tumor growth promotion as well as epithelial dysplasia by means of interfering with progenitor cell differentiation. In order to investigate the potential of Sox2‐Oct4 transcription factor decoy (TFD) strategy for differentiation therapy, mouse embryonic stem cells (mESCs) were used in this study as a model of cancer stem cells (CSCs). Sox2‐Oct4 complex decoy ODNs (cd‐ODNs) were designed according to their elements in the promoter region of Sox2 gene. DNA–protein interactions between decoy ODNs and their corresponding proteins were examined by electrophoretic mobility shift assay (EMSA). Then, decoy and scrambled ODNs were transfected into mESCs with lipofectamine under 2 inhibitors (2i) conditions. Fluorescence and confocal microscopy, cell viability, cell cycle and apoptosis analysis, alkaline phosphatase, embryoid body formation assay, and real‐time PCR were used to conduct further investigations. EMSA data showed that Sox2‐Oct4 decoy ODNs bound specifically to their recombinant proteins. The results revealed that the synthesized complex decoy can concomitantly target Sox2 and Oct4, which subsequently represses the stemness properties of mESCs compared to controls through decreasing cell viability, arresting cell cycle in G0/G1 phases, inducing apoptosis, and modulating differentiation in mESCs despite the presence of 2i/LIF in cell culture. While cd‐ODN strategy seems to offer great promise for cancer therapy, further studies are still required to put this powerful investigative tool in practice for a wide range of human cancers.
Molecular characterization of circulating tumor cells from patients with metastatic breast cancer reflects evolutionary changes in gene expression under the pressure of systemic therapy

Resistance to systemic therapy is a major problem in metastatic breast cancer (MBC) that can be explained by initial tumor heterogeneity as well as by evolutionary changes during therapy and tumor progression. Circulating tumor cells (CTCs) detected in a liquid biopsy can be sampled and characterized repeatedly during therapy in order to monitor treatment response and disease progression. Our aim was to investigate how CTC derived gene expression of treatment predictive markers (ESR1/HER2) and other cancer associated markers changed in patient blood samples during six months of first-line systemic treatment for MBC. CTCs from 36 patients were enriched using CellSearch (Janssen Diagnostics) and AdnaTest (QIAGEN) before gene expression analysis was performed with a customized gene panel (TATAA Biocenter). Our results show that antibodies against HER2 and EGFR were valuable to isolate CTCs unidentified by CellSearch and possibly lacking EpCAM expression. Evaluation of patients with clinically different breast cancer subgroups demonstrated that gene expression of treatment predictive markers changed over time. This change was especially prominent for HER2 expression. In conclusion, we found that changed gene expression during first-line systemic therapy for MBC could be a possible explanation for treatment resistance. Characterization of CTCs at several time-points during therapy could be informative for treatment selection.
Learning from high risk industries may not be straightforward: a qualitative study of the hierarchy of risk controls approach in healthcare

Abstract Objective Though healthcare is often exhorted to learn from ‘high-reliability’ industries, adopting tools and techniques from those sectors may not be straightforward. We sought to examine the hierarchies of risk controls approach, used in high-risk industries to rank interventions according to supposed effectiveness in reducing risk, and widely advocated as appropriate for healthcare. Design Classification of risk controls proposed by clinical teams following proactive detection of hazards in their clinical systems. Classification was based on a widely used hierarchy of controls developed by the US National Institute for Occupational Safety and Health (NIOSH). Setting and participants A range of clinical settings in four English NHS hospitals. Results The four clinical teams in our study planned a total of 42 risk controls aimed at addressing safety hazards. Most (n = 35) could be classed as administrative controls, thus qualifying among the weakest type of interventions according to the HoC approach. Six risk controls qualified as ‘engineering’ controls, i.e. the intermediate level of the hierarchy. Only risk control qualified as ‘substitution’, classified as the strongest type of intervention by the HoC. Conclusions Many risk controls introduced by clinical teams may cluster towards the apparently weaker end of an established hierarchy of controls. Less clear is whether the HoC approach as currently formulated is useful for the specifics of healthcare. Valuable opportunities for safety improvement may be lost if inappropriate hierarchical models are used to guide the selection of patient safety improvement interventions. Though learning from other industries may be useful, caution is needed.