Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated decision support in melanocytic lesion management

An automated melanocytic lesion image-analysis algorithm is described that aims to reproduce the decision-making of a dermatologist. The utility of the algorithm lies in its ability to identify lesions requiring excision from lesions not requiring excision. Using only wavelet coefficients as features, and testing three different machine learning algorithms, a cohort of 250 images of pigmented lesions is classified based on expert dermatologists’ recommendations of either excision (165 images) or no excision (85 images). It is shown that the best algorithm utilises the Shannon4 wavelet coupled to the support vector machine, where the latter is used as the classifier. In this case the algorithm, utilising only 22 othogonal features, achieves a 10-fold cross validation sensitivity and specificity of 0.96 and 0.87, resulting in a diagnostic-odds ratio of 261. The advantages of this method over diagnostic algorithms–which make a melanoma/no melanoma decision–are twofold: first, by reproducing the decision-making of a dermatologist, the average number of lesions excised per melanoma among practioners in general can be reduced without compromising the detection of melanoma; and second, the intractable problem of clinically differentiating between many atypical dysplastic naevi and melanoma is avoided. Since many atypical naevi that require excision on clinical grounds will not be melanoma, the algorithm–in contrast to diagnostic algorithms–can aim for perfect specificities without clinical concerns, thus lowering the excision rate of non-melanoma. Finally, the algorithm has been implemented as a smart phone application to investigate its utility in clinical practice and to streamline the assimilation of hitherto unseen tested images into the training set.
Understanding Learners' Opinion about Participation Certificates in Online Courses using Topic Modeling

This study proposes a formal multi-step methodology for qualitative assessment of topic modeling results in the context of online learner motivation to purchase Statements of Participation (SoP). We developed Latent Dirichlet Allocation (LDA) based topic models on open-ended responses of three post-course survey questions from 280 open courses offered on the FutureLearn learning platform. For qualitative assessment, we first determined the theme of the topic based on the words that constituted the topic and responses that were most strongly associated with the topic. Then, we verified the theme by comparing the topics assigned by LDA model on a test set with manual annotation. We also performed sentiment analysis to check for alignment with human judgment. Learner motivations in each theme were interpreted with the Expectancy-Value-Cost framework. Our analyses indicated that, primarily, learners were motivated to purchase the SoP based on perceptions of the utility value and financial cost of the certificate. We found that human judgment agreed with the topic model more frequently when LDA topic weights were larger.
Pull-down Assay on Streptavidin Beads and Surface Plasmon Resonance Chips for SWATH-MS-based Interactomics

Background/Aim: Pul-down assay is a popular in vitro method for identification of physical interactors of selected proteins. Here, for the first time, we compared three conventional variants of pull-down assay with the streptavidin-modified surface plasmon resonance (SPR) chips for the detection of PDZ and LIM domain protein 2 (PDLIM2) interaction partners. Materials and Methods: PDLIM2 protein–protein interactions were analysed by three variants of pull-down assay on streptavidin beads using LC-MS/MS in “Sequential Window Acquisition of all Theoretical fragment ion spectra (SWATH)” mode and compared with LC-SWATH-MS/MS data from SPR chips. Results: The results showed that (i) the use of SPR chip led to comparable data compared to on-column streptavidin beads, (ii) gravity flow and microflow in wash and elution steps provided better results than centrifugation, and (iii) type and concentration of detergent did not significantly affect the interactome data of cancer-associated PDLIM2. Conclusion: Our study supports further application of SPR-based affinity purification with SWATH mass spectrometry for reproducible and controlled characterization of cancer-associated interactomes.
Fibroblast growth factor23 is associated with axonal integrity and neural network architecture in the human frontal lobes

Elevated levels of FGF23 in individuals with chronic kidney disease (CKD) are associated with adverse health outcomes, such as increased mortality, large vessel disease, and reduced white matter volume, cardiovascular and cerebrovascular events. Apart from the well-known link between cardiovascular (CV) risk factors, especially diabetes and hypertension, and cerebrovascular damage, elevated FGF23 is also postulated to be associated with cerebrovascular damage independently of CKD. Elevated FGF23 predisposes to vascular calcification and is associated with vascular stiffness and endothelial dysfunction in the general population with normal renal function. These factors may lead to microangiopathic changes in the brain, cumulative ischemia, and eventually to the loss of white matter fibers. The relationship between FGF23 and brain integrity in individuals without CKD has hitherto not been investigated. In this study, we aimed to determine the association between FGF23, and white matter integrity in a cohort of 50 participants with varying degrees of CV risk burden, using high resolution structural human brain connectomes constructed from MRI diffusion images. We observed that increased FGF23 was associated with axonal loss in the frontal lobe, leading to a fragmentation of white matter network organization. This study provides the first description of the relationship between elevated levels of FGF23, white matter integrity, and brain health. We suggest a synergistic interaction of CV risk factors and FGF23 as a potentially novel determinant of brain health.
ELBA: Exceptional Learning Behavior Analysis

Behavioral records collected through course assessments, peer assignments, and programming assignments in Massive Open Online Courses (MOOCs) provide multiple views about a student’s study style. Study behavior is correlated with whether or not the student can get a certificate or drop out from a course. It is of predominant importance to identify the particular behavioral patterns and establish an accurate predictive model for the learning results, so that tutors can give well-focused assistance and guidance on specific students. However, the behavioral records of individuals are usually very sparse; behavioral records between individuals are inconsistent in time and skewed in contents. These remain big challenges for the state-of-the-art methods. In this paper, we engage the concept of subgroup as a trade-off to overcome the sparsity of individual behavioral records and inconsistency between individuals. We employ the framework of Exceptional Model Mining (EMM) to discover exceptional student behavior. Various model classes of EMM are applied on dropout rate analysis, correlation analysis between length of learning behavior sequence and course grades, and passing state prediction analysis. Qualitative and quantitative experimental results on real MOOCs datasets show that our method can discover significantly interesting learning behavioral patterns of students.
Pax-5 Inhibits Breast Cancer Proliferation Through MiR-215 Up-regulation

Background/Aim: In breast cancer, Pax-5 promotes pro-epithelial features and suppresses malignant cancer processes. However, the molecular mechanism of this antitumor activity remains largely unknown. This study aimed to identify the cellular roles of Pax-5-regulated miRNAs in breast cancer progression. Materials and Methods: After transient transfection of Pax-5 in MDA-MB-231 breast cancer cells, Pax-5-regulated miRNA expression was examined by next-generation sequencing. The identified Pax-5-regulated miRNAs were then validated by qRT-PCR and examined for the roles they play in breast cancer cells. Results: Pax-5 was shown to be an effective modulator of miR-215-5p and its target genes. MiR-215 inhibited cell proliferation and migration of breast cancer cells, but not cell invasion. More importantly, Pax-5-induced suppression of cancer cell proliferation and migration was found to be miR-215-dependent. Interestingly, miR-215 profiling in clinical tumor samples showed that miR-215 expression was lower in cancer tissues in comparison to healthy controls. Conclusion: Pax-5 reduces breast cancer proliferation and migration through up-regulation of the tumor suppressor miR-215. This result supports the use of miR-215 as a prognostic marker for breast cancer.
Is There a Pathological Gait Associated With Common Soft Tissue Running Injuries?

Background: Previous research has demonstrated clear associations between specific running injuries and patterns of lower limb kinematics. However, there has been minimal research investigating whether the same kinematic patterns could underlie multiple different soft tissue running injuries. If they do, such kinematic patterns could be considered global contributors to running injuries. Hypothesis: Injured runners will demonstrate differences in running kinematics when compared with injury-free controls. These kinematic patterns will be consistent among injured subgroups. Study Design: Controlled laboratory study. Methods: The authors studied 72 injured runners and 36 healthy controls. The injured group contained 4 subgroups of runners with either patellofemoral pain, iliotibial band syndrome, medial tibial stress syndrome, or Achilles tendinopathy (n = 18 each). Three-dimensional running kinematics were compared between injured and healthy runners and then between the 4 injured subgroups. A logistic regression model was used to determine which parameters could be used to identify injured runners. Results: The injured runners demonstrated greater contralateral pelvic drop (CPD) and forward trunk lean at midstance and a more extended knee and dorsiflexed ankle at initial contact. The subgroup analysis of variance found that these kinematic patterns were consistent across each of the 4 injured subgroups. CPD was found to be the most important variable predicting the classification of participants as healthy or injured. Importantly, for every 1° increase in pelvic drop, there was an 80% increase in the odds of being classified as injured. Conclusion: This study identified a number of global kinematic contributors to common running injuries. In particular, we found injured runners to run with greater peak CPD and trunk forward lean as well as an extended knee and dorsiflexed ankle at initial contact. CPD appears to be the variable most strongly associated with common running-related injuries. Clinical Relevance: The identified kinematic patterns may prove beneficial for clinicians when assessing for biomechanical contributors to running injuries.
Social isolation alters ultrasonic vocalizations but not thyroarytenoid neuromuscular junctions in old rats

Age‐related muscle atrophy of the laryngeal muscles contributes to presbyphonia. Remodeling of the neuromuscular junction is one aspect underlying age‐related muscle atrophy. Although muscle disuse has been shown to exacerbate age‐related neuromuscular changes in the limb muscles, it is unknown if reduced vocal use has a similar effect in the laryngeal muscles. The objective of this study was to examine the use of social isolation as a novel method to reduce vocal use in old rats—and the impact of that reduced vocal use on ultrasonic vocalization acoustics and neuromuscular junction morphology in the thyroarytenoid muscle.
Cytomegalovirus infection and risk of preeclampsia: A meta-analysis of observational studies

Background: Cytomegalovirus (CMV) infection is one of the most common infectious diseases in pregnant women in terms of global impact and is related with many adverse health consequences during pregnancy. For the first time, we performed a systematic review and meta-analysis study to evaluate the possible association between CMV infection and preeclampsia (PE). Methods: A comprehensive literature search to identify the relevant papers published earlier than February 2018 was performed in PubMed, ISI (Web of Science), Google Scholar and SCOPUS databases. We followed the PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines for design, analysis and interpretation of results. Pooled odds ratio (OR) and 95% confidence intervals (CI) were estimated using a random-effects meta-analysis model. Heterogeneity was assessed with Q-test and I2 statistics. Results: A total of 13 studies including 6158 pregnant women (2734 women with PE and 3424 healthy controls) met the eligibility criteria. The results of meta-analyses based on PCR (OR: 3.09; 95% CI:0.72–13.24; I2=57.3%), IgG-ELISA (OR: 1.24; 95% CI:0.83–1.85; I2=71%) and IgM-ELISA (OR: 1.04; 95% CI:0.66–1.65; I2=0.0%) demonstrated that CMV infection could not be a potential risk factor for PE. Conclusions: In conclusion, results of the present study demonstrated that CMV infection could not be a potential risk for developing PE. More epidemiological and experimental studies are needed to investigate the impact of CMV infection on the development of PE.
Health effects in COPD smokers who switch to electronic cigarettes: a retrospective-prospective 3-year follow-up

Background Health effects of electronic cigarette (EC) use in patients with chronic obstructive pulmonary disease (COPD) are largely unexplored. Aim We present findings from a long-term prospective assessment of respiratory parameters in a cohort of COPD patients who ceased or substantially reduced conventional cigarette use with ECs. Methods We prospectively re-evaluated COPD exacerbations, spirometric indices, subjective assessments (using the COPD Assessment Tool [CAT] scores), physical activity (measured by the 6-minute walk distance [6MWD]), and conventional cigarette use in EC users with COPD who were retrospectively assessed previously. Baseline measurements prior to switching to EC use were compared to follow-up visits at 12, 24, and 36 months. Age- and sex-matched regularly smoking COPD patients who were not using ECs were included as reference (control) group. Results Complete data were available from 44 patients. Compared to baseline in the EC-user group, there was a marked decline in the use of conventional cigarettes. Although there was no change in lung function, significant improvements in COPD exacerbation rates, CAT scores, and 6MWD were observed consistently in the EC user group over the 3-year period (p<0.01). Similar findings were noted in COPD EC users who also smoked conventional cigarettes (“dual users”). Conclusion The present study suggests that EC use may ameliorate objective and subjective COPD outcomes and that the benefits gained may persist long-term. EC use may reverse some of the harm resulting from tobacco smoking in COPD patients.
Emerging approaches in literature-based discovery: techniques and performance review

Abstract Literature-based discovery systems aim at discovering valuable latent connections between previously disparate research areas. This is achieved by analyzing the contents of their respective literatures with the help of various intelligent computational techniques. In this paper, we review the progress of literature-based discovery research, focusing on understanding their technical features and evaluating their performance. The present literature-based discovery techniques can be divided into two general approaches: the traditional approach and the emerging approach. The traditional approach, which dominate the current research landscape, comprises mainly of techniques that rely on utilizing lexical statistics, knowledge-based and visualization methods in order to address literature-based discovery problems. On the other hand, we have also observed the births of new trends and unprecedented paradigm shifts among the recently emerging literature-based discovery approach. These trends are likely to shape the future trajectory of the next generation literature-based discovery systems.
Distributed cognition in aviation operations: a gate-to-gate study with implications for distributed crewing

Abstract The network analysis method, Event Analysis of Systemic Teamwork (EAST), was used to examine routine aviation operations from multiple perspectives from six key areas (i.e. Dispatch, ATC, ATM, Maintenance, Loading, and the Cockpit). Data was collected over a five-day observational field trial at an international air cargo operator. Researchers recorded the activities of agents operating within the six key areas over three outbound and two inbound flights. Three networks (i.e. social, information and task) were created for four key phases of flight: (i) pre-flight checks and engines start (ii) taxi, take-off and assent, (iii) descent, landing and taxi, and (iv) park and shut down. The networks represent a ‘work audit’ of short-haul cargo operations, which enabled a detailed understanding of the interactions and connections within the current system. Implications for the future of distributed crewing concepts are discussed. Practitioner Summary: An analysis of the aviation system was undertaken using the amalgamated data from three outbound and two inbound flights. These analyses show the social, information and task interactions for cargo operations. This has been used to specify requirements for future distributed crewing options.
ESSENCE-Q: Slavic language versions for developmental screening in young children

Purpose The Early Symptomatic Syndromes Eliciting Neurodevelopmental Clinical Examinations – Questionnaire (ESSENCE-Q) was developed as a brief screener to identify children with developmental concerns who might have neurodevelopmental disorders (NDDs). This study aimed to translate the ESSENCE-Q into south Slavic languages, namely, Bosnian, Bulgarian, Croatian, Macedonian, Montenegrin, Serbian, and Slovenian, and to evaluate its psychometric properties for screening purposes in clinical settings. Patients and methods In the study, the ESSENCE-Q was completed for 251 “typically developing” children and 200 children with 1 or more diagnosed NDDs, all aged 1–6 years. Internal consistency and construct validity were tested first, followed by generating receiver operating characteristic curves and the area under the curve. Optimal cutoff values were then explored. Results The Cronbach’s α coefficients were 0.91, 0.88, and 0.86 for ESSENCE-Q parent-completed form, and the telephone and direct interview forms administered by trained nurse or specialist, respectively. The 3 versions produced area under the curve values (95% confidence interval): 0.96 (0.93–0.99), 0.91 (0.86–0.95), and 0.91 (0.86–0.97), respectively. An optimal cutoff for ESSENCE-Q parent-completed form was found to be ≥3 points, while for the telephone and direct interviews, it was ≥5 points. Conclusion We found adequate measurement properties of the south Slavic languages versions of the ESSENCE-Q as a screener for NDDs in clinical settings. This study provided additional data supporting sound psychometric properties of the ESSENCE-Q.
Posterior Choroidal Stroma Reduces Accuracy of Automated Segmentation of Outer Choroidal Boundary in Swept Source Optical Coherence Tomography.

Purpose To determine the influence of choroidal boundary morphology on the accuracy of automated measurements of subfoveal choroidal thickness (SFCT) in swept source optical coherence tomography (SSOCT). Methods A retrospective image analysis of foveal-centered horizontal line scans from normal and diseased eyes using the Topcon DRI OCT-1 Atlantis SSOCT was conducted. Subfoveal choroid-scleral junction (CSJ) and retina-choroidal junction (RCJ) morphologies were graded by two observers. Automated SFCT (A-SFCT) was compared with manual SFCT (M-SFCT) measurements from Bruch's membrane to the posterior limits of choroidal vessel, hyperreflective stroma, and hyporeflective lamina fusca. Agreement in boundary grading was assessed by Cohen's kappa. A-SFCT and M-SFCT were compared using Bland-Altman analysis and paired t-tests. Results A total of 200 eyes of 100 patients with a mean (SD) age of 62 (18) years were included. The choroidal vessel, stromal, and lamina fusca boundaries were visible in 100%, 58%, and 38% of the eyes, respectively. Interobserver agreement in RCJ and CSJ grading was high (kappa = 0.974 and 0.851). Mean A-SFCT differed from M-SFCT by only 2 μm at posterior choroidal vessel boundary (P = 0.801). A-SFCT overestimated SFCT at the posterior vessel wall boundary by 17 μm (P = 0.026) and 23 μm (P = 0.001) in the presence of a visible posterior choroidal stroma and lamina fusca, respectively. Conclusions Automated outer choroidal boundary segmentation tends to identify the posterior limit of the choroidal vessel. Agreement between A-SFCT and M-SFCT is reduced by the presence of posterior stromal layer and lamina fusca. A-SFCT should be interpreted with RCJ and CSJ boundary grading.
Understanding Student Procrastination via Mixture Models

Time management is crucial to success in online courses in which students can schedule their learning on a ﬂexible basis. Procrastination is largely viewed as a failure of time management and has been linked to poorer outcomes for students. Past research has quantiﬁed the extent of students’ procras-tination by deﬁning single measures directly from raw logs of student activity. In this work, we use a probabilistic mixture model to allow diﬀerent types of behavioral patterns to naturally emerge from clickstream data and analyze the resulting patterns in the context of procrastination. More-over, we extend our analysis to include measures of student regularity–how consistent the procrastinating behaviors are– and construct a composite Time Management Score ( TM ). Our results show that mixture modeling is able to unveil latent types of behavior, each of which is associated with a level of procrastination and its regularity. Overall, students identiﬁed as non-procrastinators tend to perform sig-niﬁcantly better. Within non-procrastinators, higher levels of regularity signify better performance, while this may be the opposite for procrastinators.
The impact of phosphoinositide 5-phosphatases on phosphoinositides in cell function and human disease

Phosphoinositides (PIs) are recognized as major signaling molecules in many different functions of eukaryotic cells. PIs can be dephosphorylated by multiple phosphatase activities at the 5-, 4-, and 3- positions. Human PI 5-phosphatases belong to a family of 10 members. Except for inositol polyphosphate 5-phosphatase A, they all catalyze the dephosphorylation of PI(4,5)P2 and/or PI(3,4,5)P3 at the 5- position. PI 5-phosphatases thus directly control the levels of PI(3,4,5)P3 and participate in the fine-tuning regulatory mechanisms of PI(3,4)P2 and PI(4,5)P2. Second messenger functions have been demonstrated for PI(3,4)P2 in invadopodium maturation and lamellipodia formation. PI 5-phosphatases can use several substrates on isolated enzymes, and it has been challenging to establish their real substrate in vivo. PI(4,5)P2 has multiple functions in signaling, including interacting with scaffold proteins, ion channels, and cytoskeleton proteins. PI 5-phosphatase isoenzymes have been individually implicated in human diseases, such as the oculocerebrorenal syndrome of Lowe, through mechanisms that include lipid control. Oncogenic and tumor-suppressive functions of PI 5-phosphatases have also been reported in different cell contexts. The mechanisms responsible for genetic diseases and for oncogenic or tumor-suppressive functions are not fully understood. The regulation of PI 5-phosphatases is thus crucial in understanding cell functions.