Miracle-dz/UniFAR-FTUs huggingface dataset:
TMPRSS2-ERG fusions unexpectedly identified in men initially diagnosed with nonprostatic malignancies.

Background TMPRSS2-ERG gene fusions are frequently found in prostate cancer and are pathognomomic for prostatic origin. In a series of cancer cases assayed with comprehensive genomic profiling (CGP) in the course of clinical care, we reviewed the frequency of TMPRSS2-ERG fusions in patient tumors of various histologic subtypes. Methods Frequency of TMPRSS2-ERG fusions was determined in comprehensive genomic profiles from 64,263 cancer cases submitted to Foundation Medicine to assess genomic alterations suggesting benefit from targeted therapy. Genomic results from an index case of prostate cancer that underwent evolution from adenocarcinoma to pure squamous cell carcinoma are presented. Results TMPRSS2-ERG fusions were identified for 0.86% (250/29030) of male patients and not found for female patients (0/35233). TMPRSS2-ERG fusions were detected in six tumors that were classified as squamous carcinoma, five of which were of unknown primary site. The index case is a patient with a large left retrovesical mass diagnosed as squamous carcinoma by morphologic examination and a history of Gleason 9 prostate cancer with prior prostatectomy and salvage radiation therapy. TMPRSS2-ERG was detected by genomic profiling in the squamous cell tumor, the primary adenocarcinoma of the prostate, and in a metachronous prostatic adenocarcinoma metastasis. Based on these results, the patient received androgen deprivation therapy. A phylogenetic tree demonstrating clonal and histopathologic evolution of prostate cancer in the index patient was constructed. Conclusions In this large CGP dataset, TMPRSS2-ERG fusion was seen in ~30% of prostate cancers regardless of histologic type; the fusion was on occasion detected in advanced cancers not initially carrying a diagnosis of prostate carcinoma. CGP of advanced cancers in men may reveal prostatic origin by detection of the pathognomomic TMPRSS2-ERG fusion gene.
Feature Selection for Natural Language Call Routing Based on Self-Adaptive Genetic Algorithm

The text classification problem for natural language call routing was considered in the paper. Seven different term weighting methods were applied. As dimensionality reduction methods, the feature selection based on self-adaptive GA is considered. k-NN, linear SVM and ANN were used as classification algorithms. The tasks of the research are the following: perform research of text classification for natural language call routing with different term weighting methods and classification algorithms and investigate the feature selection method based on self-adaptive GA. The numerical results showed that the most effective term weighting is TRR. The most effective classification algorithm is ANN. Feature selection with self-adaptive GA provides improvement of classification effectiveness and significant dimensionality reduction with all term weighting methods and with all classification algorithms.
Determination of the bilinear stress‐crack opening curve for normal‐ and high‐strength concrete

An improved version of the method proposed to ACI committee 446 and to RILEM TC 187-SOC to determine the fracture parameters of concrete is applied in this study to several mixtures of normal and high-strength concretes. The results are processed with a C++ program developed by the authors to automatise the mathematical operations required to obtain the bilinear softening curve of concrete from the experimental results. Numerical simulations of the tests are also carried out using finite elements with an embedded cohesive crack. The comparison between numerical and experimental results confirms that the experimental and numerical procedures are appropiate for normal-strength concretes and high-strength concretes.
Scatter measurements for optical cone-beam computed tomography

Both x-ray and optical cone-beam CT (CBCT) scanners are limited by scattered photons that contaminate the primary images. Transparent radiochromic gels and plastics are anticipated to produce less scattering than polymerization gels and hence result in reconstructed dose distributions with greater contrast and dynamic range. Four methods of scatter measurement were investigated to quantify scatter fractions using an in-house optical CBCT scanner. The methods consisted of generating either "coin" shadows or primary beamlets in transmission images. The four methods generated similar results of 10% scatter fractions in gel transmission images for this particular scanner configuration with both leuco crystal violet and carbon black micelle gels. The scatter contributions were distributed as 5% from micelle gel, 2% from Teflon wall, 2% from refractive index matching liquid and 1% other sources. Applying a uniform background subtraction of 2% of open field intensity resulted in 0.2% difference between laser CT and cone-beam CT reconstructed attenuation coefficients for a black micelle gel finger phantom.
Survival gain in glioblastoma patients treated with dendritic cell immunotherapy is associated with increased NK but not CD8+ T cell activation in the presence of adjuvant temozolomide

ABSTRACT In a two-stage phase II study, 24 patients with first diagnosis of glioblastoma (GBM) were treated with dendritic cell (DC) immunotherapy associated to standard radiochemotherapy with temozolomide (TMZ) followed by adjuvant TMZ. Three intradermal injections of mature DC loaded with autologous GBM lysate were administered before adjuvant TMZ, while 4 injections were performed during adjuvant TMZ. According to a two-stage Simon design, to proceed to the second stage progression-free survival (PFS) 12 months after surgery was expected in at least 8 cases enrolled in the first stage. Evidence of immune response and interaction with chemotherapy were investigated. After a median follow up of 17.4 months, 9 patients reached PFS12. In these patients (responders, 37.5%), DC vaccination induced a significant, persistent activation of NK cells, whose increased response was significantly associated with prolonged survival. CD8+ T cells underwent rapid expansion and priming but, after the first administration of adjuvant TMZ, failed to generate a memory status. Resistance to TMZ was associated with robust expression of the multidrug resistance protein ABCC3 in NK but not CD8+ T cells. The negative effect of TMZ on the formation of T cell-associated antitumor memory deserves consideration in future clinical trials including immunotherapy.
Real-world Noisy Image Denoising: A New Benchmark

Most of previous image denoising methods focus on additive white Gaussian noise (AWGN). However,the real-world noisy image denoising problem with the advancing of the computer vision techiniques. In order to promote the study on this problem while implementing the concurrent real-world image denoising datasets, we construct a new benchmark dataset which contains comprehensive real-world noisy images of different natural scenes. These images are captured by different cameras under different camera settings. We evaluate the different denoising methods on our new dataset as well as previous datasets. Extensive experimental results demonstrate that the recently proposed methods designed specifically for realistic noise removal based on sparse or low rank theories achieve better denoising performance and are more robust than other competing methods, and the newly proposed dataset is more challenging. The constructed dataset of real photographs is publicly available at \url{this https URL} for researchers to investigate new real-world image denoising methods. We will add more analysis on the noise statistics in the real photographs of our new dataset in the next version of this article.
Vibration control in thin slab hot strip mills

In a number of thin slab caster/hot strip mills, a serious vibration phenomenon can occur in F2–F4 stands during rolling thin gauge or high strength strip. In particular, the vibration of compact strip production (continuous) hot rolling mills is a more serious and difficult technical problem to resolve. When vibration occurs, chatter marks occur on the mill rolls and strip surface together with excessive noise. The problem not only reduces the life of the rolls but also poses a threat to the safety of the production equipment, having triggered a number of major accidents in the past. Following vibration theory study, computer simulation and field tests, measures were implemented to control the vibration, which achieved significant results and economic benefits.
Telomere dynamics in a lizard with morph‐specific reproductive investment and self‐maintenance

Abstract Telomeres in human fibroblasts shorten progressively during in vitro culturing and trigger replicative senescence. Furthermore, shortened telomeres can be used as biomarkers of disease. These observations have led to the suggestion that telomere dynamics may also be associated with viability and selection for life history variation in non‐human taxa. Model systems to examine this suggestion would particularly benefit from the coexistence of multiple phenotypes within the same species with different life history trade‐offs, since those could be compared in terms of telomere characteristics. This scenario also provokes the classic question of why one morph does not have marginally higher fitness and replaces the others. One explanation is that different morphs have different reproductive tactics with equal relative fitness. In Australian painted dragons (Ctenophorus pictus), males differ in head color, the presence or absence of a gular bib, and reproductive expenditure. Red males out‐compete yellow males in dominance contests, while yellow males copulate quickly and have higher success in sperm competition than red males. Males with bibs better defend partners against rival matings, at the cost of loss of body condition. We show that yellow‐headed and bib‐less males have longer telomeres than red, blue and bibbed males, suggesting that telomere length is positively associated with higher investment into self‐maintenance and less reproductive expenditure.
A Novel Multi-task Tensor Correlation Neural Network for Facial Attribute Prediction

Multi-task learning plays an important role in face multi-attribute prediction. At present, most researches excavate the shared information between attributes by sharing all convolutional layers. However, it is not appropriate to treat the low-level and high-level features of the face multi-attribute equally, because the high-level features are more biased toward the specific content of the category. In this article, a novel multi-attribute tensor correlation neural network (MTCN) is used to predict face attributes. MTCN shares all attribute features at the low-level layers, and then distinguishes each attribute feature at the high-level layers. To better excavate the correlations among high-level attribute features, each sub-network explores useful information from other networks to enhance its original information. Then a tensor canonical correlation analysis method is used to seek the correlations among the highest-level attributes, which enhances the original information of each attribute. After that, these features are mapped into a highly correlated space through the correlation matrix. Finally, we use sufficient experiments to verify the performance of MTCN on the CelebA and LFWA datasets and our MTCN achieves the best performance compared with the latest multi-attribute recognition algorithms under the same settings.
Next-generation sequencing technology in clinical virology.

Recent advances in nucleic acid sequencing technologies, referred to as 'next-generation' sequencing (NGS), have produced a true revolution and opened new perspectives for research and diagnostic applications, owing to the high speed and throughput of data generation. So far, NGS has been applied to metagenomics-based strategies for the discovery of novel viruses and the characterization of viral communities. Additional applications include whole viral genome sequencing, detection of viral genome variability, and the study of viral dynamics. These applications are particularly suitable for viruses such as human immunodeficiency virus, hepatitis B virus, and hepatitis C virus, whose error-prone replication machinery, combined with the high replication rate, results, in each infected individual, in the formation of many genetically related viral variants referred to as quasi-species. The viral quasi-species, in turn, represents the substrate for the selective pressure exerted by the immune system or by antiviral drugs. With traditional approaches, it is difficult to detect and quantify minority genomes present in viral quasi-species that, in fact, may have biological and clinical relevance. NGS provides, for each patient, a dataset of clonal sequences that is some order of magnitude higher than those obtained with conventional approaches. Hence, NGS is an extremely powerful tool with which to investigate previously inaccessible aspects of viral dynamics, such as the contribution of different viral reservoirs to replicating virus in the course of the natural history of the infection, co-receptor usage in minority viral populations harboured by different cell lineages, the dynamics of development of drug resistance, and the re-emergence of hidden genomes after treatment interruptions. The diagnostic application of NGS is just around the corner.
Type 1 diabetes induction in humanized mice

Significance Type 1 diabetes (T1D) is known to be caused by immune destruction of insulin-producing β cells, but the disease pathogenesis remains poorly understood largely because of limitations in animal models to study the immunopathology. Here we established a humanized mouse T1D model, in which diabetes is driven by human T cells recognizing the HLA-DQ8–restricted insulin B chain peptide consisting of amino acids 9–23 (InsB:9–23). This study not only demonstrates the capacity of InsB:9–23-specific human CD4 T cells to initiate diabetes but also provides a preclinical humanized mouse model that has the potential to be used in studies of the immunopathogenesis and immunotherapy of T1D. There is an urgent and unmet need for humanized in vivo models of type 1 diabetes to study immunopathogenesis and immunotherapy, and in particular antigen-specific therapy. Transfer of patient blood lymphocytes to immunodeficient mice is associated with xenogeneic graft-versus-host reactivity that complicates assessment of autoimmunity. Improved models could identify which human T cells initiate and participate in beta-cell destruction and help define critical target islet autoantigens. We used humanized mice (hu-mice) containing robust human immune repertoires lacking xenogeneic graft-versus-host reactivity to address this question. Hu-mice constructed by transplantation of HLA-DQ8+ human fetal thymus and CD34+ cells into HLA-DQ8–transgenic immunodeficient mice developed hyperglycemia and diabetes after transfer of autologous HLA-DQ8/insulin-B:9–23 (InsB:9–23)-specific T-cell receptor (TCR)-expressing human CD4+ T cells and immunization with InsB:9–23. Survival of the infused human T cells depended on the preexisting autologous human immune system, and pancreatic infiltration by human CD3+ T cells and insulitis were observed in the diabetic hu-mice, provided their islets were stressed by streptozotocin. This study fits Koch’s postulate for pathogenicity, demonstrating a pathogenic role of islet autoreactive CD4+ T-cell responses in type 1 diabetes induction in humans, underscores the role of the target beta-cells in their immunological fate, and demonstrates the capacity to initiate disease with T cells, recognizing the InsB:9–23 epitope in the presence of islet inflammation. This preclinical model has the potential to be used in studies of the pathogenesis of type 1 diabetes and for testing of clinically relevant therapeutic interventions.
Feature-Based Efficient Moving Object Detection for Low-Altitude Aerial Platforms

Moving Object Detection is one of the integral tasks for aerial reconnaissance and surveillance applications. Despite the problem's rising potential due to increasing availability of unmanned aerial vehicles, moving object detection suffers from a lack of widely-accepted, correctly labelled dataset that would facilitate a robust evaluation of the techniques published by the community. Towards this end, we compile a new dataset by manually annotating several sequences from VIVID and UAV123 datasets for moving object detection. We also propose a feature-based, efficient pipeline that is optimized for near real-time performance on GPU-based embedded SoMs (system on module). We evaluate our pipeline on this extended dataset for low altitude moving object detection. Ground-truth annotations are made publicly available to the community to foster further research in moving object detection field.
Ultrasonic Force Microscopy

As an imaging method of elastic properties and subsurface features on the microscopic scale, the scanning acoustic microscope (SAM) provides spatial resolution comparable or superior to that of optical microscopes. Nondestructive evaluation methods of defects and elastic properties on the microscopic scale were developed by using the SAM, and they have been widely applied to various fields in science and technology. One major problem in acoustic microscopy is resolution. The best resolution of SAM with water as the coupling fluid has been 240 nm at a frequency of 4.4 GHz. At a more conventional frequency of 1 GHz, the resolution is about 1 μm. Therefore the resolution of SAM is not always sufficient for examining nanoscale defects and advanced micro/nanodevices. For materials characterization on the nanometer scale, atomic force microscopy (AFM) was developed and extended in order to observe elastic properties in force-modulation mode. In the force-modulation mode, the sample is vibrated, and the resultant cantilever-deflection vibration is measured and used to produce elasticity images of objects. The lateral force-modulation AFM can evaluate the friction force or the shear elasticity in real time. However in the force-modulation mode, it is difficult to analyze stiff objects such as metals and ceramics. When the sample is vertically vibrated at ultrasonic frequencies much higher than the cantilever resonance frequency, the tip cannot vibrate due to the inertia of the cantilever. However by modulating the amplitude of the ultrasonic vibration, deflection vibration of the cantilever at the modulation frequency is excited due to the rectifier effect of the nonlinear force curves. Based on the tip-sample indentation during ultrasonic vibration, we developed ultrasonic force microscopy (UFM) for contact elasticity and subsurface imaging of rigid objects using a soft cantilever with a stiffness of the order of 0.1 N/m.
Activating Intrinsic Carbohydrate-Active Enzymes of the Smut Fungus Ustilago maydis for the Degradation of Plant Cell Wall Components

ABSTRACT The microbial conversion of plant biomass to valuable products in a consolidated bioprocess could greatly increase the ecologic and economic impact of a biorefinery. Current strategies for hydrolyzing plant material mostly rely on the external application of carbohydrate-active enzymes (CAZymes). Alternatively, production organisms can be engineered to secrete CAZymes to reduce the reliance on externally added enzymes. Plant-pathogenic fungi have a vast repertoire of hydrolytic enzymes to sustain their lifestyle, but expression of the corresponding genes is usually highly regulated and restricted to the pathogenic phase. Here, we present a new strategy in using the biotrophic smut fungus Ustilago maydis for the degradation of plant cell wall components by activating its intrinsic enzyme potential during axenic growth. This fungal model organism is fully equipped with hydrolytic enzymes, and moreover, it naturally produces value-added substances, such as organic acids and biosurfactants. To achieve the deregulated expression of hydrolytic enzymes during the industrially relevant yeast-like growth in axenic culture, the native promoters of the respective genes were replaced by constitutively active synthetic promoters. This led to an enhanced conversion of xylan, cellobiose, and carboxymethyl cellulose to fermentable sugars. Moreover, a combination of strains with activated endoglucanase and β-glucanase increased the release of glucose from carboxymethyl cellulose and regenerated amorphous cellulose, suggesting that mixed cultivations could be a means for degrading more complex substrates in the future. In summary, this proof of principle demonstrates the potential applicability of activating the expression of native CAZymes from phytopathogens in a biocatalytic process. IMPORTANCE This study describes basic experiments that aim at the degradation of plant cell wall components by the smut fungus Ustilago maydis. As a plant pathogen, this fungus contains a set of lignocellulose-degrading enzymes that may be suited for biomass degradation. However, its hydrolytic enzymes are specifically expressed only during plant infection. Here, we provide the proof of principle that these intrinsic enzymes can be synthetically activated during the industrially relevant yeast-like growth. The fungus is known to naturally synthesize valuable compounds, such as itaconate or glycolipids. Therefore, it could be suited for use in a consolidated bioprocess in which more complex and natural substrates are simultaneously converted to fermentable sugars and to value-added compounds in the future.
Topological knots and links in proteins

Significance Twenty years after a discovery of knotted proteins, we found that some single-protein chains can form links, which have even more complex structures than knots. We derive conditions that proteins need to meet to form links. We search through the entire Protein Data Bank and identify several chains that form a Hopf link and a Solomon link. The link motif has not been recognized before; however, it is clearly of important functional significance in proteins. In this article, we relate topological properties of proteins with links to their function and stability and show that the link topology is characteristic of eukaryotes only. Twenty years after their discovery, knots in proteins are now quite well understood. They are believed to be functionally advantageous and provide extra stability to protein chains. In this work, we go one step further and search for links—entangled structures, more complex than knots, which consist of several components. We derive conditions that proteins need to meet to be able to form links. We search through the entire Protein Data Bank and identify several sequentially nonhomologous chains that form a Hopf link and a Solomon link. We relate topological properties of these proteins to their function and stability and show that the link topology is characteristic of eukaryotes only. We also explain how the presence of links affects the folding pathways of proteins. Finally, we define necessary conditions to form Borromean rings in proteins and show that no structure in the Protein Data Bank forms a link of this type.