Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional Silencing of HSD17B2 in Prostate Cancer Promotes Disease Progression

Purpose: Steroidogenic enzymes are essential for prostate cancer development. Enzymes inactivating potent androgens were not investigated thoroughly, which leads to limited interference strategies for prostate cancer therapy. Here we characterized the clinical relevance, significance, and regulation mechanism of enzyme HSD17B2 in prostate cancer development. Experimental Design: HSD17B2 expression was detected with patient specimens and prostate cancer cell lines. Function of HSD17B2 in steroidogenesis, androgen receptor (AR) signaling, and tumor growth was investigated with prostate cancer cell lines and a xenograft model. DNA methylation and mRNA alternative splicing were investigated to unveil the mechanisms of HSD17B2 regulation. Results: HSD17B2 expression was reduced as prostate cancer progressed. 17βHSD2 decreased potent androgen production by converting testosterone (T) or dihydrotestosterone (DHT) to each of their upstream precursors. HSD17B2 overexpression suppressed androgen-induced cell proliferation and xenograft growth. Multiple mechanisms were involved in HSD17B2 functional silencing including DNA methylation and mRNA alternative splicing. DNA methylation decreased the HSD17B2 mRNA level. Two new catalytic-deficient isoforms, generated by alternative splicing, bound to wild-type 17βHSD2 and promoted its degradation. Splicing factors SRSF1 and SRSF5 participated in the generation of new isoforms. Conclusions: Our findings provide evidence of the clinical relevance, significance, and regulation of HSD17B2 in prostate cancer progression, which might provide new strategies for clinical management by targeting the functional silencing mechanisms of HSD17B2. See related commentary by Mostaghel, p. 1139
Assessing the prevalence of Staphylococcus aureus in infertile male patients in Tabriz, northwest Iran

Background: Staphylococcus aureus is an infrequent, but one of the most successful bacteria that associated with infertility and are able to spermatozoa immobilization and agglutination. Objective: The aim of present study was to determine the frequency of S. aureus in semen obtained from infertile male patients in northwest Iran. Materials and Methods: Seminal fluids of 100 infertile men were evaluated. Standard semen examination was done according to World Health Organization guidelines. After isolation and identification of S. aureus isolates according to reference methods, determination of susceptibility against important antibiotics and polymerase chain reaction were performed to identify mecA and tst genes. Results: Data obtained from the present study shows that 16% of infertile male patients were colonized by S. aureus. Ten (62.5%) of the individuals had abnormal seminal fluid sperm motility and morphology and three (18.8%) of them had an abnormal seminal fluid density, whereas after washing with albumin-saline declined to 5 (31.3%), 4 (25%) and 1 (6.3%), respectively. The antibiogram results showed that, except penicillin, other antibiotics have high activity on isolates. Regarding polymerase chain reaction results, mecA sequences were detected in 3 (18.7%) strains, whilst the tst gene encoding TSST-1 was not detected in any of clinical strains. Conclusion: It would appear that the S. aureus may be an additional negative factor worsening sperm quality and affecting male fertility. Therefore, it demands that all the patients attending in infertility treatment facilities be investigated thoroughly.
Rhinolithiasis: A Misleading Entity

Introduction Rhinolithiasis is a rare entity; it entails a stone located in the nasal cavity. The entity presents with different signs and symptoms that can be easily confused with other more common clinical entities such as chronic rhinosinusitis. However, it can also mimic sinonasal tumors, making its proper diagnosis crucial. Materials and Methods In this article, we present a case series of 15 patients over the past 13 years between 2002 and 2015 who were seen in the clinics at the American University of Beirut Medical Center. We will shed light on the common presenting symptoms, physical examination findings, proper diagnostic modalities, and treatment options. Our data will be compared to the literature. Conclusion Rhinolithiasis could present with a wide spectrum of signs and symptoms and could be overlooked or mistaken for other diagnosis such as sinusitis or malignancy. It could be differentiated from other entities by rigid nasal endoscopy and computed tomography scan. The diagnosis of rhinolithiasis requires a high index of suspicion.
Active Anomaly Detection via Ensembles

In critical applications of anomaly detection including computer security and fraud prevention, the anomaly detector must be configurable by the analyst to minimize the effort on false positives. One important way to configure the anomaly detector is by providing true labels for a few instances. We study the problem of label-efficient active learning to automatically tune anomaly detection ensembles and make four main contributions. First, we present an important insight into how anomaly detector ensembles are naturally suited for active learning. This insight allows us to relate the greedy querying strategy to uncertainty sampling, with implications for label-efficiency. Second, we present a novel formalism called compact description to describe the discovered anomalies and show that it can also be employed to improve the diversity of the instances presented to the analyst without loss in the anomaly discovery rate. Third, we present a novel data drift detection algorithm that not only detects the drift robustly, but also allows us to take corrective actions to adapt the detector in a principled manner. Fourth, we present extensive experiments to evaluate our insights and algorithms in both batch and streaming settings. Our results show that in addition to discovering significantly more anomalies than state-of-the-art unsupervised baselines, our active learning algorithms under the streaming-data setup are competitive with the batch setup.
The Role of Talent Management Comparing Medium-Sized and Large Companies – Major Challenges in Attracting and Retaining Talented Employees

In order for companies to realize their organizational visions, they need staff who are high-potential and looking toward the future. Due to the demographic, social and economic situation in Europe, the labor market is already reflecting a lack of high-quality human resources (HR), which inspires research into and planned management of high-potential, i.e., talented, employees. Companies are aware that only those organizations that recognize this area as crucial and invest resources into it will be successful in the “war for talent. ” The purpose of the study was to research the field of talent management from the perspective of the definition of what the talent management process means for companies, how to attract and recognize talented employees, what development activities to provide them with and how to measure their performance and progress. We employed an exploratory approach, using the method of semi-structured interviews to gather information from 21 HR professionals who work at medium-sized and large Slovenian companies. We found that these organizations use various approaches and activities to attract and develop talented employees. At two thirds of the companies, performance is measured using annual evaluation interviews, by measuring the meeting of targets and evaluations by superiors. The biggest challenges in the field are attracting talented employees and positioning the organization as a desirable employer. The study is useful primarily as an overview of the field and of best practices, which companies can use to argument their existing processes.
Vulnerability or resilience of motopsin knockout mice to maternal separation stress depending on adulthood behaviors

Background Both environmental and genetic conditions contribute to the robust development of neuronal circuits and adulthood behaviors. Loss of motopsin gene function causes severe intellectual disability in humans and enhanced social behavior in mice. Furthermore, childhood maltreatment is a risk factor for some psychiatric disorders, and children with disabilities have a higher risk of abuse than healthy children. Materials and methods In this study, we investigated the effects of maternal separation (MS) on adulthood behaviors of motopsin knockout (KO) and wild-type (WT) mice. Results The MS paradigm decreased the duration that WT mice stayed in the center area of an open field, but not for motopsin KO mice; however, it decreased the novel object recognition index in both genotypes. In the marble burying test, motopsin KO mice buried fewer marbles than WT mice, regardless of the rearing conditions. The MS paradigm slightly increased and reduced open arm entry in the elevated plus maze by WT and motopsin KO mice, respectively. In the three-chamber test, the rate of sniffing the animal cage was increased by the MS paradigm only for motopsin KO mice. After the three-chamber test, motopsin KO mice had fewer cFos-positive cells in the prelimbic cortex, which is involved in emotional response, than WT mice. In the infralimbic cortex, the MS paradigm decreased the number of cFos-positive cells in motopsin KO mice. Conclusion Our results suggest that motopsin deficiency and childhood adversity independently affect some behaviors, but they may interfere with each other for other behaviors. Defective neuronal circuits in the prefrontal cortex may add to this complexity.
Asking Children to "Be Helpers" Can Backfire After Setbacks.

Describing behaviors as reflecting categories (e.g., asking children to "be helpers") has been found to increase pro-social behavior. The present studies (N = 139, ages 4-5) tested whether such effects backfire if children experience setbacks while performing category-relevant actions. In Study 1, children were asked either to "be helpers" or "to help," and then pretended to complete a series of successful scenarios (e.g., pouring milk) and unsuccessful scenarios (e.g., spilling milk while trying to pour). After the unsuccessful trials, children asked to "be helpers" had more negative attitudes. In Study 2, asking children to "be helpers" impeded children's helping behavior after they experienced difficulties while trying to help. Implications for how category labels shape beliefs and behavior are discussed.
Development of a Gesture-Based Game Applying Participatory Design to Reflect Values of Manual Wheelchair Users

Wheelchair users have been benefited from Natural User Interface (NUI) games because gesture-based applications can help motor disabled people. Previous work showed that considering values and the social context of these users improve game enjoyment. However, the literature lacks on studies that address games as a tool to approach personal values of people with physical disabilities. Participatory design encompasses techniques that allow absorbing and reflecting values of users into technologies. We developed a gesture-based game using participatory design addressing values of wheelchair users. To manage the development of our game, we permitted creativity and flexibility to the designers. Our design is aligned to the Game SCRUM and make use of concepts from the Creative Process. The products of each stage of the design that we applied are both a gesture-based game and its evaluation. We tested the enjoyment (immersion, difficult while playing, etc.) of users for the game that we developed thought game-based quantitative and qualitative analyses. Our results indicate that the game was able to provide a satisfactory entertaining experience to the users.
Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Immunotherapy can revolutionize anti-cancer therapy if specific targets are available. Recurrent somatic mutations in the exome can create highly specific neo-antigens. However, especially pediatric cancers are oligo-mutated and hardly exhibit recurrent neo-antigens. Yet, immunogenic peptides encoded by cancer-specific genes (CSGs), which are virtually not expressed in normal tissues, may enable a targeted immunotherapy of such cancers. Here, we describe an algorithm and provide a user-friendly software named RAVEN (Rich Analysis of Variable gene Expressions in Numerous tissues), which automatizes the systematic and fast identification of CSG-encoded peptides highly affine to Major Histocompatibility Complexes (MHC) starting from publicly available gene expression data. We applied RAVEN to a dataset assembled from more than 2,700 simultaneously normalized gene expression microarrays comprising 50 tumor entities, with a focus on sarcomas and pediatric cancers, and 71 normal tissue types. RAVEN performed a transcriptome-wide scan in each cancer entity for gender-specific CSGs. As a proof-of-concept we identified several established CSGs, but also many novel candidates potentially suitable for targeting multiple cancer types. The specific expression of the most promising CSGs was validated by qRT-PCR in cancer cell lines and by immunohistochemistry in a comprehensive tissue-microarray comprising 412 samples. Subsequently, RAVEN identified likely immunogenic peptides encoded by these CSGs by predicting the affinity to MHCs. Putative highly affine peptides were automatically crosschecked with the UniProt protein-database to exclude sequence identity with abundantly expressed proteins. The predicted affinity of selected peptides was validated in T2-cell peptide-binding assays in which many showed similar kinetics to a very immunogenic influenza control peptide. Collectively, we provide a comprehensive, exquisitely curated and validated catalogue of cancer-specific and highly MHC-affine peptides across 50 cancer entities. In addition, we developed an intuitive and freely available software to easily apply our algorithm to any gene expression dataset (https://github.com/JSGerke/RAVENsoftware). We anticipate that our peptide libraries and software constitute a rich resource to accelerate the development of novel immunotherapies.
Automatic Topic Segmentation for Video Lectures Using Low and High-Level Audio Features

Nowadays, video lectures are a very popular way to transmit knowledge, and because of that, there are many repositories with a large catalog of those videos on web. Despite all benefits that this high availability of video lectures brings, some problems also emerge from this scenario. One of these problems is that, it is very difficult find relevant content associate with those videos. Many times, students must to watch the entire video lecture to find the point of interest and, sometimes, these points are not found. For that reason, in this work we propose a novel method based on early fusion of low and high-level audio features for automatic topic segmentation in video lectures. We have performed experiments in two sets of video lectures where we obtained very satisfactory results that evidence the applicability of our method on improving content search in those videos.
3D motion capture system for assessing patient motion during Fugl-Meyer stroke rehabilitation testing

The authors introduce a novel marker-less multi-camera setup that allows easy synchronisation between 3D cameras as well as a novel pose estimation method that is calculated on the fly based on the human body being tracked, and thus requires no calibration session nor special calibration equipment. They show high accuracy in both calibration and data merging and is on par with equipment-based calibration. They deduce several insights and practical guidelines for the camera setup and for the preferred data merging methods. Finally, they present a test case that computerises the Fugl-Meyer stroke rehabilitation protocol using the authors’ multi-sensor capture system. They conducted a Helsinki-approved research in a hospital in which they collected data on stroke patients and healthy subjects using their multi-camera system. Spatio-temporal features were extracted from the acquired data and machine learning-based evaluations were applied. Results showed that patients and healthy subjects can be correctly classified at a rate of above 90%. Furthermore, they show that the most significant features in the classification are strongly correlated with the Fugl-Meyer guidelines. This demonstrates the feasibility of a low-cost, flexible and non-invasive motion capture system that can potentially be operated in a home setting.
Musculoskeletal Modeling and Analysis of Trikonasana

Context: Yoga has origins speculated to date back to pre-Vedic Indian period and is practiced as a common exercise, both in India as well as all around the world. Although the yoga practices are ages old, there is not much research literature available. Moreover, with the advancement in technology, the modern analysis tools are not used up to their full potential. Aims: This research focuses on developing a framework for analyzing trikonasana, using the optical motion capture system, and validating the noninvasive method for analyzing muscle activity in prominent muscles while performing trikonasana. Subjects and Methods: We have adopted the noninvasive analysis method using optical motion capture system OptiTrack™ for recording the human motion and musculoskeletal modeling software LifeMod™ to analyze the muscle activity while performing trikonasana. Surface electromyography (sEMG) studies were performed using Trigno™ (Delsys Inc.) wireless sEMG sensors to validate the LifeMod simulation results pertaining muscle activation. Results: It was observed that the characteristics of the sEMG match to that of the estimated muscle tension from the architecture used in this study. The muscle groups such as external right obliques muscles, rectus abdominis of the front leg, and gluteus maximus and gluteus medius of the rear leg were observed to undergo major activation during an isometric contraction while performing trikonasana. The magnitudes of the muscle tension during the left bend depict a close resemblance to the muscle tension magnitudes during the right bend. Conclusions: The optical motion capture system and musculoskeletal modeling software can be used to analyze muscle activity in any yoga exercise noninvasively. Since the yoga exercises majorly require the practitioner to maintain a certain posture for a considerable duration, our approach can be used to find the important muscles involved and their corresponding muscle tension when they undergo isometric contraction.
Human-level face verification with intra-personal factor analysis and deep face representation

The last two decades have seen an escalating interest in methods for large-scale unconstrained face recognition. While the promise of computer vision systems to efficiently and accurately verify and identify faces in naturally occurring circumstances still remains elusive, recent advances in deep learning are taking us closer to human-level recognition. In this study, the authors propose a new paradigm which employs deep features in a feature extractor and intra-personal factor analysis as a recogniser. The proposed new strategy represents the face changes of a person using identity specific components and the intra-personal variation through reinterpretation of a Bayesian generative factor analysis model. The authors employ the expectation-maximisation algorithm to calculate model parameters which cannot be observed directly. Recognition outcomes achieved through benchmarking on large-scale wild databases, Labeled Faces in the Wild (LFW) and Youtube Face (YTF), clearly prove that the proposed approach provides remarkable face verification performance improvement over state-of-the-art approaches.
Association between age at onset of independent walking and objectively measured sedentary behavior is mediated by moderate-to-vigorous physical activity in primary school children

Objective Age at onset of walking has been shown as an early predictor of physical activity in infants and children. However, little is known about whether age at onset of walking may predict sedentary behavior (SB). The aim of the present study was to examine the association between the timing of onset of walking and objectively measured SB, and whether this association is mediated by moderate-to-vigorous physical activity (MVPA) in children. Methods The subjects were 388 elementary school children aged 6–12 years. Current weight and height data were collected. Birth weight and the age in months the child first walked independently were reported based on the parents’ recall. Children’s SB and physical activity were objectively measured using a triaxial accelerometer (Active style Pro HJA-350IT, OMRON). The following summary outcome variables were derived from accelerometer data: Time (min/day) spent in SB (≤1.5 metabolic equivalents [METs]) and MVPA (≥3.0 METs). Results The mean ± SD time (min/day) spent in sedentary was 376 ± 62 and MVPA was 67.6 ± 20.8. Multiple linear regression analyses revealed that a later age at independent walking was associated with increased time spent in SB (β = 0.15, P < 0.001) and decreased time spent in MVPA (β = -0. 18, P < 0.001) after adjusting for gender, birth weight, current age, body weight, schools, and time spent wearing the accelerometer. When MVPA was introduced as a covariate in the model predicting SB, the association between the age at independent walking and time spent in SB was completely attenuated (β = 0.04, P = 0.215), while MVPA was significantly associated with SB (β = -0.61, P < 0.001). Conclusions Our results indicate that infants who walked at a later age spent more time in SB in childhood, and this association is mediated by MVPA. Appropriate interventions which focus on increasing MVPA and thereby reducing SB may be beneficial in infants who demonstrate a later age at onset of independent walking.
Analysis of User Activity in Wireless Local Area Network of Petrozavodsk State University

Wireless networks are widely used for Internet access in public places, trading centers and educational institutions. The study of users' activity in these places can help solve problems of marketing, security, location, and monitoring of public transport. The article describes an experiment to measure the activity of users in wireless networks of Petrozavodsk State University because some educational and administrative processes are slowed because of a strict speed limit for all users. The authors developed a method to determine users' activity without the access to the service equipment and personal data, as well as a software complex to implement this method. Then they collected and analyzed data on the hours of the highest and lowliest activity, class schedule effect, and the dynamics of users' returns to the network. The information obtained was used to determine the allowed constraints of the Internet access speed for network users. A number of equations take into account the typical behavior of wireless network users, their activity and the capacity of external network channels. Computed rates for speed limits significantly exceed the established indicators in the network of Petrozavodsk University during hours of average and minimum network load. The results obtained can be used in corporate networks to dynamically calculate the permissible speed limit and to improve the quality of user service.
Privacy Preserving Shortest Path Queries on Directed Graph

Ahstract- Trust relation in this work refers to permission that is given to a user at source-host to access another user at target-host through an authentication key with a unique fingerprint. We form a directed graph out of these trust relations, such that user-host pairs are considered as nodes and fingerprints as arrows. We present a novel protocol to query the shortest path from node A to node B, in a privacy preserving manner. We would like to use a cloud to perform such queries, but we do not allow the cloud to learn any information about the graph, nor the query. Also the database owner is prevented from learning any information about the query, except that it happened.