Miracle-dz/UniFAR-FTUs huggingface dataset:
Male Reproduction: One of the Primary Targets of Bisphenol

Infertility is a major health issue affecting human life. The most notable factors caus - ing male infertility is exposure to environmental contaminants. Bisphenol A (BPA) is a common toxic environmental contaminant. Human population is exposed to bisphe - nol A through air, water, food and a variety of industrial products. Growing evidence from research on laboratory animals supports the hypothesis that bisphenol A is able to adversely affect male reproductive function. The specific mechanisms of action of bisphe nol A are wide but not definite. Bisphenol A interferes with the hormonal metabolism and regulation, binding affinity or enzymatic activity, resulting in a deviation from a normal reproductive behaviour. Binding ability to androgen and oestrogen receptors, as well as other properties, is currently investigated. A decreased sperm count, inhibition of sperm motility and reduction of organ weights were observed and linked with oxidative stress after bisphenol A treatment. In addition, prenatal exposure to bisphenol A may lead to adverse effects in the offspring. In this review, we address the topic of BPA effects on male reproductive function and emphasize its effects on testicular steroidogenesis and spermatogenesis. A considerably more detailed and systematic research focusing on bisphenol A toxicology is required for a better understanding of risks associated with exposure to this endocrine disruptor.
Polymer-based variable focal length microlens system

A novel polymer-based fluid-actuated variable focal length microlens system with a wide field-of-view (FOV) and large numerical aperture is designed and fabricated using standard photolithographic and silicon micromachining techniques. A flexible polydimethylsiloxane (PDMS) membrane is used to form the lens surface and is actuated by fluidic pressure applied by an external syringe pump. This lens system is capable of working in dual mode, forming either a double convex (DCX) or a double concave (DCV) lens. The relationship between the focal length (f) and FOV of the fabricated dynamic lens system as a function of the volume of the fluid pumped into or out of the lens chamber is investigated. The focal length of the dynamic lens system demonstrated in this paper could be tuned in the range of 75.9 to 3.1 mm and −75.9 to −3.3 mm for the DCX and DCV lens configurations, respectively. The FOV for this lens system was found to be in the range of 0.12 to 61° for DCX lens and 7 to 69° for DCV lens. The smallest F-number (f/#) that could be achieved using this dynamic lens is 0.61, which corresponds to the numerical aperture value of 0.64.
Low b‐value diffusion‐weighted imaging: Emerging applications in the body

Thanks to recent advances in magnetic resonance imaging technology, it has become possible to perform intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI) in any part of the body. Extracranial applications of DWI are currently under active investigation, especially for oncological imaging. However, the use of non‐quantitative low b‐value (10–100 s/mm2) DWI in the body is still a relatively unexplored field, and its potential is not fully recognized. Non‐quantitative low b‐value DWI may especially be useful for the evaluation of structures that have an inherently low signal at high b‐value DWI, including (but not limited to) the liver, heart, and small bowel. This article will review and discuss the basic principles and potential applications of nonquantitative low b‐value DWI in the body. J. Magn. Reson. Imaging 2012;35:1266–1273. © 2012 Wiley Periodicals, Inc.
Reduction of lipid peroxidation products and advanced glycation end‐product precursors by cyanobacterial aldo‐keto reductase AKR3G1—a founding member of the AKR3G subfamily

The purpose of this study was to investigate the origin and function of the aldo‐keto reductase (AKR) superfamily as enzymes involved in the detoxification of xenobiotics. We used the cyanobacterium Synechocystis sp. PCC 6803 as a model organism and sequence alignments to find bacterial AKRs with highest identity to human enzymes. Disappearance of NADPH was monitored spectrophotometrically to calculate enzymatic activity. The molecular weight of the native protein was determined by size exclusion chromatography. Substrate docking was performed by SwissDock. Sequence alignments identified the NADPH‐dependent AKR3G1 having 41.5 and 40% identity with the human enzymes AKR1B1 and AKR1B10, respectively. Highest enzymatic efficiency was observed with 4‐oxonon‐2‐enal (4‐ONE; kcat/Km, 561 s‐1 mM‐1) and 4‐hydroxynonenal (kcat/Km, 26.5 s‐1 mM‐1), respectively. P74308 is the most efficient enzyme for 4‐ONE discovered until now. Cooperativity of this monomeric enzyme was observed with some substrates. Enzyme inactivation or oligomerization as possible explanations for nonhyperbolic enzyme kinetics were ruled out by Selwyn's test and gel filtration. The role of the little investigated carbonyl‐reducing enzymes in detoxification seems to be in fact a very old process with rarely observed nonhyperbolic enzyme kinetics as an adaptation mechanism to higher concentrations of reactive oxygen species—Hintzpeter, J., Martin, H. ‐J., Maser, E. Reduction of lipid peroxidation products and advanced glycation end‐product precursors by cyanobacterial aldo‐keto reductase AKR3G1—a founding member of the AKR3G subfamily. FASEB J. 29, 263–273 (2015). www.fasebj. org
Cytoplasmic membrane protonmotive force energizes periplasmic interactions between ExbD and TonB

The TonB system of Escherichia coli (TonB/ExbB/ExbD) transduces the protonmotive force (pmf) of the cytoplasmic membrane to drive active transport by high‐affinity outer membrane transporters. In this study, chromosomally encoded ExbD formed formaldehyde‐linked complexes with TonB, ExbB and itself (homodimers) in vivo. Pmf was required for detectable cross‐linking between TonB–ExbD periplasmic domains. Consistent with that observation, the presence of inactivating transmembrane domain mutations ExbD(D25N) or TonB(H20A) also prevented efficient formaldehyde cross‐linking between ExbD and TonB. A specific site of periplasmic interaction occurred between ExbD(A92C) and TonB(A150C) and required functional transmembrane domains in both proteins. Conversely, neither TonB, ExbB nor pmf were required for ExbD dimer formation. These data suggest two possible models where either dynamic complex formation occurred through transmembrane domains or the transmembrane domains of ExbD and TonB configure their respective periplasmic domains. Analysis of T7‐tagged ExbD with anti‐ExbD antibodies revealed that a T7 tag was responsible both for our previous failure to detect T7–ExbD–ExbB and T7–ExbD–TonB formaldehyde‐linked complexes and for the concomitant artefactual appearance of T7–ExbD trimers.
Gene-delivery systems for iPS cell generation

Importance of the field: Induced pluripotent stem (iPS) cells offer extraordinary promise for regenerative medicine applications, and provide new opportunities for use in disease modeling, drug screening and drug toxicology. Areas coved in this review: iPS cell technology is still in its infancy. In this review article, we present a comprehensive survey of reprogramming approaches focusing on gene-delivery systems used for generation of iPS cells from somatic cells, categorize gene-delivery vectors, and discuss their advantages and limitations for somatic cell reprogramming. We include pertinent literature published between 2006 and the present. What the reader will gain: Although iPS cell technology has been improved via the use of various gene-delivery vectors, it still suffers from either low reprogramming efficiency or too many genomic modification steps. Extensive work is still required to improve current vectors or explore new vectors for effectively reprogramming human somatic cells into iPS cells, with or without minimal genomic modification steps. Take home message: A single non-integrating reprogramming vector system with high reprogramming efficiency is probably essential for generation of clinically translatable human iPS cells.
Semantic White Balance: Semantic Color Constancy Using Convolutional Neural Network

The goal of computational color constancy is to preserve the perceptive colors of objects under different lighting conditions by removing the effect of color casts caused by the scene's illumination. With the rapid development of deep learning based techniques, significant progress has been made in image semantic segmentation. In this work, we exploit the semantic information together with the color and spatial information of the input image in order to remove color casts. We train a convolutional neural network (CNN) model that learns to estimate the illuminant color and gamma correction parameters based on the semantic information of the given image. Experimental results show that feeding the CNN with the semantic information leads to a significant improvement in the results by reducing the error by more than 40%.
Heterogeneous vancomycin-intermediate susceptibility phenotype in bloodstream methicillin-resistant Staphylococcus aureus isolates from an international cohort of patients with infective endocarditis: prevalence, genotype, and clinical significance.

BACKGROUND The significance of heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) is unknown. Using a multinational collection of isolates from methicillin-resistant S. aureus (MRSA) infective endocarditis (IE), we characterized patients with IE with and without hVISA, and we genotyped the infecting strains. METHODS MRSA bloodstream isolates from 65 patients with definite IE from 8 countries underwent polymerase chain reaction (PCR) for 31 virulence genes, pulsed-field gel electrophoresis, and multilocus sequence typing. hVISA was defined using population analysis profiling. RESULTS Nineteen (29.2%) of 65 MRSA IE isolates exhibited the hVISA phenotype by population analysis profiling. Isolates from Oceania and Europe were more likely to exhibit the hVISA phenotype than isolates from the United States (77.8% and 35.0% vs 13.9%; P < .001). The prevalence of hVISA was higher among isolates with a vancomycin minimum inhibitory concentration of 2 mg/L (P = .026). hVISA-infected patients were more likely to have persistent bacteremia (68.4% vs 37.0%; P = .029) and heart failure (47.4% vs 19.6%; P = .033). Mortality did not differ between hVISA- and non-hVISA-infected patients (42.1% vs 34.8%, P = .586). hVISA and non-hVISA isolates were genotypically similar. CONCLUSIONS In these analyses, the hVISA phenotype occurred in more than one-quarter of MRSA IE isolates, was associated with certain IE complications, and varied in frequency by geographic region.
Relaxing the Tropics to an ‘observed’ state: analysis using a simple baroclinic model

The technique of relaxation of the tropical atmosphere towards an analysis in a month‐season forecast model has previously been successfully exploited in a number of contexts. Here it is shown that when tropical relaxation is used to investigate the possible origin of the observed anomalies in June–July 2007, a simple dynamical model is able to reproduce the observed component of the pattern of anomalies given by an ensemble of ECMWF forecast runs. Following this result, the simple model is used for a range of experiments on time‐scales of relaxation, variables and regions relaxed based on a control model run with equatorial heating in a zonal flow.
Screening vs. non-screening detected colorectal cancer: Differences in pre-therapeutic work up and treatment

Objectives To compare preoperative staging, multidisciplinary team-assessment, and treatment in patients with screening detected and non-screening detected colorectal cancer. Methods Data on patient and tumour characteristics, staging, multidisciplinary team-assessment and treatment in patients with screening and non-screening detected colorectal cancer from 2008 to 2012 were collected from the Stockholm–Gotland screening register and the Swedish Colorectal Cancer Registry. Results The screening group had a higher proportion of stage I disease (41 vs. 15%; p < 0.001), a more complete staging of primary tumour and metastases and were more frequently multidisciplinary team-assessed than the non-screening group (p < 0.001). In both groups, patients with endoscopically resected cancers were less completely staged and multidisciplinary team-assessed than patients with surgically resected cancers (p < 0.001). No statistically significant differences were observed between the screening and non-screening groups in the use of neoadjuvant treatment in rectal cancer (68 vs.76%), surgical treatment with local excision techniques in stage I rectal cancer (6 vs. 9%) or adjuvant chemotherapy in stages II and III disease (46 vs. 52%). Emergency interventions for colorectal cancer occurred in 4% of screening participants vs. 11% of non-compliers. Conclusions Screening detected cancer patients were staged and multidisciplinary team assessed more extensively than patients with non-screening detected cancers. Staging and multidisciplinary team assessment prior to endoscopic resection was less complete compared with surgical resection. Extensive surgical and (neo)adjuvant treatment was given in stage I disease. Participation in screening reduced the risk of emergency surgery for colorectal cancer.
Depth Map Reconstruction for Underwater Kinect Camera Using Inpainting and Local Image Mode Filtering

Underwater optical cameras are widely used for security monitoring in ocean, such as earthquake prediction and tsunami alarming. Optical cameras recognize objects for autonomous underwater vehicles and provide security protection for sea-floor networks. However, there are many issues for underwater optical imaging, such as forward and backward scattering, light absorption, and sea snow. Many underwater image processing techniques have been proposed to overcome these issues. Among these techniques, the depth map gives important information for many applications of the post-processing. In this paper, we propose a Kinect-based underwater depth map estimation method that uses a captured coarse depth map by Kinect with the loss of depth information. To overcome the drawbacks of low accuracy of coarse depth maps, we propose a corresponding reconstruction architecture that uses the underwater dual channels prior dehazing model, weighted enhanced image mode filtering, and inpainting. Our proposed method considers the influence of mud sediments in water and performs better than the traditional methods. The experimental results demonstrated that, after inpainting, dehazing, and interpolation, our proposed method can create high-accuracy depth maps.
Pattern recognition receptor immunomodulation of innate immunity as a strategy to limit the impact of influenza virus

Influenza remains a major global health issue and the effectiveness of current vaccines and antiviral drugs is limited by the continual evolution of influenza viruses. Therefore, identifying novel prophylactic or therapeutic treatments that induce appropriate innate immune responses to protect against influenza infection would represent an important advance in efforts to limit the impact of influenza. Cellular pattern recognition receptors (PRRs) recognize conserved structures expressed by pathogens to trigger intracellular signaling cascades, promoting expression of proinflammatory molecules and innate immunity. Therefore, a number of approaches have been developed to target specific PRRs in an effort to stimulate innate immunity and reduce disease in a variety of settings, including during influenza infections. Herein, we discuss progress in immunomodulation strategies designed to target cell‐associated PRRs of the innate immune system, thereby, modifying innate responses to IAV infection and/or augmenting immune responses to influenza vaccines.
Trabodenoson, an Adenosine Mimetic With A1 Receptor Selectivity Lowers Intraocular Pressure by Increasing Conventional Outflow Facility in Mice

Purpose To evaluate the relationship between the IOP-lowering effect of trabodenoson and the associated structural and functional changes in the trabecular meshwork (TM). Methods Six independent cohorts of young and aged mice were exposed to three different topical once-a-day formulations of trabodenoson and eyes were compared to those treated with placebo drops. IOP was measured daily just before drug administration using rebound tonometry. Outflow facility was measured in enucleated eyes. Flow patterns and morphology of conventional outflow tissues were monitored using tracer beads and standard histology, respectively. In parallel, three-dimensional human TM tissue constructs (3D-HTM) were grown and used in experiments to test effect of trabodenoson on the expression of collagen IV, fibronectin, matrix metalloproteinase (MMP)-2 and MMP-14 plus MMP-2 activity. Results Topical administration of trabodenoson significantly lowered IOP on every day tested, up to 7 days. After 2 days of treatment, outflow facility increased by 26% in aged mice and 30% overall (young and aged mice), which was significantly different from vehicle (P < 0.05). Outflow facility was 15% higher than controls after 7 days of treatment (P = 0.07). While gross morphology was not affected by treatment, the intensity of tracer bead distribution increased by day 7 (P = 0.05). Parallel experiments in 3D-HTM showed that trabodenoson treatment significantly increased MMP-2 activity and MMP-14 abundance, while decreasing fibronectin and collagen IV expression. Conclusions Trabodenoson alters ECM turnover by TM cells and increases conventional outflow facility, which accounts for its ability to lower IOP in young and aged mice.
Cell Detection in Microscopy Images with Deep Convolutional Neural Network and Compressed Sensing

The ability to automatically detect certain types of cells or cellular subunits in microscopy images is of significant interest to a wide range of biomedical research and clinical practices. Cell detection methods have evolved from employing hand-crafted features to deep learning-based techniques. The essential idea of these methods is that their cell classifiers or detectors are trained in the pixel space, where the locations of target cells are labeled. In this paper, we seek a different route and propose a convolutional neural network (CNN)-based cell detection method that uses encoding of the output pixel space. For the cell detection problem, the output space is the sparsely labeled pixel locations indicating cell centers. We employ random projections to encode the output space to a compressed vector of fixed dimension. Then, CNN regresses this compressed vector from the input pixels. Furthermore, it is possible to stably recover sparse cell locations on the output pixel space from the predicted compressed vector using $L_1$-norm optimization. In the past, output space encoding using compressed sensing (CS) has been used in conjunction with linear and non-linear predictors. To the best of our knowledge, this is the first successful use of CNN with CS-based output space encoding. We made substantial experiments on several benchmark datasets, where the proposed CNN + CS framework (referred to as CNNCS) achieved the highest or at least top-3 performance in terms of F1-score, compared with other state-of-the-art methods.
Application-layer denial of service attacks: taxonomy and survey

The recent escalation of application-layer denial of service DoS attacks has attracted a significant interest of the security research community. Since application-layer DoS attacks usually do not manifest themselves at the network level, they avoid traditional network-layer-based detection. Therefore, the security community has focused on specialised application-layer DoS attacks detection and mitigation mechanisms. However, the deployment of reliable and efficient defence mechanisms against these attacks requires the comprehensive understanding of the existing application-layer DoS attacks supported by a unified terminology. Thus, in this paper we address this issue and devise a taxonomy of application-layer DoS attacks. By devising the proposed taxonomy, we intend to give researchers a better understanding of these attacks and provide a foundation for organising research efforts within this specific field.
Interaction of Estrogen and Progesterone on Kisspeptin-10-Stimulated Luteinizing Hormone and Growth Hormone in Ovariectomized Cows

Background/Aims: Growth hormone (GH) is necessary for optimal reproductive efficiency and its secretion is influenced by sex steroids. This study was designed to determine whether kisspeptin-10 (Kp10) could stimulate GH and if gonadal steroids enhance the GH response to Kp10 in cows. Methods and Results: Intravenous injection of Kp10 at 100 or 200 pmol/kg body weight with or without treatment with estradiol cypionate and/or progesterone increased luteinizing hormone (p < 0.01) plasma concentrations. Plasma concentrations of GH were increased following Kp10 in cows treated with estradiol cypionate and/or progesterone (p < 0.05) but not in cows treated with Kp10 without gonadal steroids. Conclusions: These data suggest that reproductive steroids enhance the sensitivity of the somatotropic axis to physiologically relevant doses of Kp10, and support the possibility that Kp10 is an integrator of luteinizing hormone and GH release.
Adaptive Granulation-Based Prediction for Energy System of Steel Industry

The flow variation tendency of byproduct gas plays a crucial role for energy scheduling in steel industry. An accurate prediction of its future trends will be significantly beneficial for the economic profits of steel enterprise. In this paper, a long-term prediction model for the energy system is proposed by providing an adaptive granulation-based method that considers the production semantics involved in the fluctuation tendency of the energy data, and partitions them into a series of information granules. To fully reflect the corresponding data characteristics of the formed unequal-length temporal granules, a 3-D feature space consisting of the timespan, the amplitude and the linetype is designed as linguistic descriptors. In particular, a collaborative-conditional fuzzy clustering method is proposed to granularize the tendency-based feature descriptors and specifically measure the amplitude variation of industrial data which plays a dominant role in the feature space. To quantify the performance of the proposed method, a series of real-world industrial data coming from the energy data center of a steel plant is employed to conduct the comparative experiments. The experimental results demonstrate that the proposed method successively satisfies the requirements of the practically viable prediction.