Miracle-dz/UniFAR-FTUs huggingface dataset:
Redifferentiation of radioiodine-refractory thyroid cancers.

The management of radioiodine refractory thyroid cancers (RAIR TC) is challenging for the clinician. Tyrosine kinase inhibitors classically prescribed in this setting can fail due to primary or acquired resistance or the necessity of drug withdrawal because of serious or moderate but chronic and deleterious adverse effects. Thus, the concept of redifferentiation strategy, which involves treating patients with one or more drugs capable of restoring radioiodine sensitivity for RAIR TC, has emerged. The area of redifferentiation strategy leads to the creation of new definitions of RAIR TC including persistent non radioiodine-avid patients and 'true' RAIR TC patients. The latter group presents a restored or increased radioiodine uptake in metastatic lesions but with no radiological response on conventional imaging i.e. progression of a metastatic disease thus proving that they are 'truly' resistant to the radiation delivered by radioiodine. Unlike these patients, metastatic TC patients with restored radioiodine uptake offer the hope of prolonged remission or even cure of the disease as for radioiodine-avid metastatic TC. We review here the different redifferentiation strategies based on the underlying molecular mechanism leading to the sodium iodide symporter (NIS) and radioiodine uptake reinduction, i.e. by modulating signaling pathways, NIS transcription, NIS trafficking to the plasma membrane, NIS post-transcriptional regulation, by gene therapy and other potential strategies. We discuss clinical trials and promising preclinical data of potential future targets.
Is Adolescents’ Food Intake Associated with Exposure to the Food Intake of Their Mothers and Best Friends?

Both mothers’ and best friends’ food intake are associated with adolescents’ food intake, but they are rarely investigated simultaneously. In this study, we tested the associations of mothers’ and best friends’ food intake with adolescents’ intake of unhealthy and healthy food, obtained from home and from outside the home, and the moderating role of adolescents’ exposure to their food intake. Participants included 667 adolescents (53% female, Mage = 12.9) and 396 of their mothers. Within this adolescent sample, 378 best friend dyads were identified. All participants completed food frequency questionnaires. Mothers separately reported on their food intake in the presence and absence of their child, and adolescents indicated how often they ate and drank together with their best friend during school breaks. Mothers’, but not best friends’, food intake was positively related to adolescents’ intake of unhealthy and healthy food obtained from home and healthy food obtained from outside the home. Exposure to mothers’ healthy food intake magnified mother-child similarities in healthy food intake. Exposure to best friends’ intake of unhealthy food moderated adolescent-friend similarities in unhealthy food intake. Future work should assess the mechanisms that underlie these similarities, and should investigate these associations over time and in later developmental periods.
Identifying and Monitoring Deficiencies in Physical Examination of the Foot and Ankle With Diagnostic Ultrasound

Abstract Despite the high incidence of foot and ankle injuries and their biomechanical importance to more proximal joints, the foot and ankle are some of the most daunting and underemphasized musculoskeletal structures in medical training. This study used musculoskeletal ultrasound to identify a knowledge gap in physical medicine and rehabilitation residents in foot and ankle surface anatomy palpation and to determine whether senior residents had higher examination performance compared with more junior residents. Physical medicine and rehabilitation residents at different levels of training were tested cross-sectionally, and palpation accuracy was compared by class year. There was a trend of improvement across class years, with significant class differences in accuracy for the talonavicular joint, calcaneocuboidal joint, and posterior tibialis and peroneal tendons (P < 0.05). Despite this trend, the accuracy was not consistently higher among the senior residents considering the training they received. For all 30 residents assessed, accuracy within 1 cm was highest for the tibiotalar joint (93.3%), peroneal tendons (83.3%), posterior tibialis tendon (63.3%), and talonavicular joint (50%). It was lower for the calcaneocuboidal joint (26.7%) and the second (13.3%) and fourth for the tarsometatarsal joints (20%). Anatomical knowledge and palpation skills of the foot and ankle, particularly at the midfoot and forefoot, may be an area of improvement for physical medicine and rehabilitation resident training.
Extension of the Theory of Planned Behavior (TPB) to Predict Patterns of Marijuana Use among Young Iranian Adults

Background: Marijuana use is increasing among adolescents and young adults. Long-term marijuana use magnifies the risk of a wide variety of behavioral, cognitive-emotional, and neurological problems, and can be a gateway to use of other drugs. In the present study, we investigated the cognitive-emotional and behavioral predictors of marijuana use. To this end, young Iranian adults answered questions based on an extended Theory of Planned Behavior (TPB) and related it to marijuana use. We hypothesized that cognitive-emotional and behavioral factors would predict intention to use marijuana, and that this, in turn, would predict actual consumption. Methods: A total of 166 young Iranian adults (mean age: 20.51 years; 15.7% females) attending a walk-in center for drug use took part in this cross-sectional study. Participants completed questionnaires covering sociodemographic information, frequency of marijuana use per week, along with questionnaires assessing the following dimensions of the TPB: attitude towards marijuana use, subjective norms, self-efficacy to resist marijuana use, environmental constraints, problem-solving skills, and behavioral intention for marijuana use. Results: Mean marijuana use was found to be 4.6 times/week. Attitude towards marijuana use, subjective norms, environmental constraints, and behavioral intention to use marijuana were positively correlated to each other and with marijuana use/week. In contrast, higher self-efficacy and problem-solving skills were associated with lower marijuana use/week. The multiple regression analysis showed that a positive attitude to marijuana use, lower self-efficacy in resisting its use, higher behavioral intention, and poorer problem-solving skills predicted actual use. Conclusion: The pattern of results suggests that dimensions of TPB can explain marijuana use among young Iranian adults self-admitted to a walk-in center for drug use. Specifically, poor problem-solving skills, low self-efficacy in resisting marijuana use, and positive labelling of its use appeared to be the best predictors of actual use. It follows that prevention programs aimed at improving problem-solving skills and raising self-efficacy, along with educational interventions aimed at highlighting the negative effects of marijuana might decrease the risk of its use among young adults in Iran.
Remodeling i wsteczny remodeling lewego przedsionka u chorych z niewydolnością nerek

Cardiovascular diseases compose a kind of con­tinuum initiated by cardiovascular risk factors in consequence leading to the development of atherosclerosis, infarct and secondary heart failure. This sequel effecting in death has been proposed in 1991 by Dzau and Braunwald as a concept of lethal cardiac chain. In this process cardiovascular risk factors, such as elevated cholesterol, hypertension, diabetes mellitus, cigarette smoking and end-stage renal disease (ESRD) are now known to promote oxidative stress and to cause endothelial dysfunction, initiating a cascade of events, including alterations in vasoactive mediators, inflammatory responses, and cardiac and vascular remodeling, that culminates in target-organ pathology. However, research concerning reverse process, which can be present due to disappearing of causative factors is not numerous and but rather incomplete. Left atrium (AL) dilatation is a hallmark of LA structural remodeling in ESRD. Biomarker of these changes is left atrium volume index (LAVI). Left atrium remodeling refers to a time-dependent adaptive regulation of cardiac myocytes in order to maintain homeostasis against external stressors. LA enlargement is accompanied by impairment of the LA hemodynamic performance. Renal transplantation (RT) is a potentially allowing intervention reversal or at least the inhibition of adverse changes dependent to cardiac remodeling. Research has shown that observed after RT is to reduce the planimetric parameters and LA volume. Parameters showing LA hemodynamic activity as: LAEF, LAAE and LAIE improving already during the short observation while LAPE is reduced. LAFS behaves differently because although much greater at the end of follow-up, its growth is largely due to the relatively slow improvement in the long for perspective, while a shorter period after RT changes are not yet significant. LA remodeling as an effect of atrial uremic cardiomyopathy is in fact an exemplum of complex cardiomyopathy with elements characteristic for congestive and infiltrative cardiomyopathy, because early LAVI reduction after RT mainly depends on changed hemodynamic conditions, whereas the main reason for further late decreasing of LAVI value is related rather to resolution of uremic toxaemia. Improvement of LA structural and functional properties after RT is a continuous and prolonged process.
A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

Simple Summary Reproductive performance is an important factor, which determines productive life and drives culling decisions in dairy herds. There are strong motives for including reproductive performance in genetic selection programs of dairy cows; however, low heritability estimates reported for reproductive performance measures limit the genetic selection efficiency. More effective genetic selection could be achieved using genomic information. The aim of this study was to identify genomic region(s) associated with the length of the calving interval in Holstein cows. The accuracies of genomic estimated breeding values (GEBVs) with single-step genomic BLUP (ssGBLUP) and the pedigree-based BLUP were compared as well. The results showed that the accuracies of GEBVs using the single-step genomic BLUP were much higher than those estimated using the pedigree-based BLUP. We identified three genomic regions (BTA3, BTA6, and BTA7) associated with the length of the calving interval in Holstein dairy cows. Abstract The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi- and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological process terms including alanine transport, L-alanine transport, proline transport, and glycine transport were identified as the most important terms enriched by the genes inside the identified windows.
A toolbox for data processing in Radiomics analysis

In the current study, we aimed to develop an easy-to-use toolbox for data processing in Radiomics analysis. The toolbox was design to conduct data processing of classification (eg. classifying benign and malignant tumor) and prognosis (eg. prediction of 3 years survival rate) analysis in Radiomics researches. The toolbox was composed of data preprocessing, feature extraction, feature selection, Radiomics signature construction, clinical variables selection, combined model construction and performance evaluation. The Radiomics signature was obtained with the procedure of data preprocessing, features extraction, features selection, and signature construction. The valuable clinical variables were selected by Akaike information criterion (AIC) or Bayesian Information Criterion (BIC). The combined model was constructed by integrating Radiomics signature with the selected clinical variables. The toolbox provided an evaluation part to assess the performance of the combined model. For the classification analysis, the toolbox provided the classification evaluation metrics including area under receiver operating characteristic curve (AUC), classification accuracy (ACC), true and false positive rate (TPR and FPR), positive and negative predictive values (PPV and NPV), together with other evaluation approaches including receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA). For the overall survival analysis, the toolbox provided the evaluation approach of C-index and K-M (Kaplan -Meier) curve. For the survival analysis of certain time point, the toolbox provided the evaluation metrics including time dependent-area under receiver operating characteristic curve (TD-AUC), time dependent-classification accuracy (TD-ACC), together with other evaluation approaches including time dependent-receiver operating characteristic curve (TD-ROC), calibration curve and DCA.
Diffuse interstellar band from the spectrum of auto-ionizing helium

We explore the possibility of using transition energies of a doubly excited helium atom to describe the absorption lines of interstellar medium. We follow the method of approximated separation of variables in hypersperical coordinate in solving the energy levels of doubly excited helium. Although the results do not exactly match with the absorption spectrum of the diffuse interstellar bands, they show some correlation. We have also shown that the distribution of the difference between observed spectrum and the calculated result can be fit by normal distribution with the mean value close to zero. Furthermore, we argued that the distribution obtained from randomly generated lines are significantly different from the calculated result.
An innovative approach based on hyperspectral imaging (HSI) combined with chemometrics for soil phytoremediation monitoring

An innovative approach, based on hyperspectral imaging (HSI) coupled with chemometrics, allowing the detection of arsenic (As) in the hyper-accumulator fern Pteris Vittata L. , is presented in this study. The aim of this work was to investigate the possibility of monitoring by HSI the As sequestration capacity of plants grown on As-contaminated soils, in order to perform soil remediation. The proposed approach is based on the acquisition by HSI in the SWIR range (1000-2500 nm) of fern leaves, followed by the implementation of a classification model based on Partial Least Square Discriminant Analysis (PLS-DA). Following this procedure, false color maps, representative of the chemical elements distribution on the leaves were obtained, where As is clearly detected without performing any chemical analysis. The proposed approach is not invasive and not destructive. Comparative evaluations were carried out analyzing Pteris Vittata L. leaves collected from plants grown on natural soils containing different As concentrations. To evaluate reliability, robustness and analytical correctness of the proposed HSI approach, micro X-ray fluorescence (μXRF) analyses were carried out on the same samples in order to quantitatively and topologically assess As presence in the leaves of the plants. The achieved results are very promising for monitoring the phytoremediation process by detecting and controlling the uptake of As plants growing on contaminated soils.
Wavelength framing technique based on a diffractive optical element

Framing camera is a powerful tool to investigate the ultrafast phenomena in chemical reaction process. Wavelength framing technique is one of the key technologies in the development of framing cameras. The wavelength resolution of the images generated by wavelength framing system determines the interval time of the wavelength framing camera, that is, the time resolution of the wavelength framing camera. In this paper, a wavelength framing system based on a diffractive optical element (DOE) and a band-pass filter (BPF) was set up. The wavelength characteristics of the wavelength framing system were simulated utilizing the theory of multi-beam interference. The central wavelength of each image got from the system, which varies with the position relationship between DOE and BPF, has been obtained. Experiments were carried out through imaging a target of 6 mm × 6 mm by using the wavelength framing system. The spectral characteristics of each image were also studied experimentally. The result we have got proves that the system we have generated can achieve 16-frame imaging, every image has different spectral properties. For the target with a size of 6 mm × 6 mm, the resolution of a single image got from the system is 610 × 610, and the central wavelength ranges from 784 nm to 814 nm. The average difference in central wavelength between adjacent images is 1.95 nm. If the dispersion of the incident pulse light source is 0.46 ps/nm, the time resolution of the system is 0.9 ps.
Asia's surging interest in binary analysis

B IN ARY CODE ANALYSIS (binary analysis, for short) is a vital security approach for protecting commercial off-the-shelf (COTS) software and understanding malware, where there is no source code available. From the perspective of computer security, it is imperative to analyze binary code, as source-level scrutiny does not always reveal lurking software bugs due to compiler or interpreter misbehavior. Since the late 1990s, there has been significant research interest worldwide on binary analysis. The BitBlaze project (by Carnegie Mellon University and University of California, Berkeley) is one of the few pioneering research prototypes that incorporates a variety of tools for binary analysis, such as VINE for static analysis, TEMU for dynamic analysis, and Rudder for symbolic execution. Following up on BitBlaze, BAP (by Carnegie Mellon University) provides a wealth of APIs that can be used to build a custom binary analyzer, while DECAF (by Syracuse University) provides efficient, platform-neutral support for dynamic binary analysis. Angr (by University of California, Santa Barbara) offers a user-friendly platform for common binary analysis tasks, such as disassembly, instrumentation, and symbolic execution that are utilized by an active user community. In recent years, the expanding cyber infrastructure supporting governments and industry sectors in Asia has ignited strong interests in software security, leading to a surge of research activities in binary analysis in the region. Thanks to the broad international support, researchers have begun to drive new ideas and delve into various research topics in binary analysis, such as automatic exploit generation, vulnerability discovery, and automated reverse-engineering. This article outlines the key research developments and trends in binary analysis led by researchers in the East Asia and Oceania region.
Exploiting biomedical literature to mine out a large multimodal dataset of rare cancer studies

The overall lower survival rate of patients with rare cancers can be explained, among other factors, by the limitations resulting from the scarce available information about them. Large biomedical data repositories, such as PubMed Central Open Access (PMC-OA), have been made freely available to the scientific community and could be exploited to advance the clinical assessment of these diseases. A multimodal approach using visual deep learning and natural language processing methods was developed to mine out 15,028 light microscopy human rare cancer images. The resulting data set is expected to foster the development of novel clinical research in this field and help researchers to build resources for machine learning.
Cloud Computing Load Balancing Algorithms Comparison Based Survey

— Cloud computing is an online primarily based computing. This computing paradigm has increased the employment of network wherever the potential of 1 node may be used by alternative node. Cloud provides services on demand to distributive resources like info, servers, software, infrastructure etc. in pay as you go basis. Load reconciliation is one amongst the vexing problems in distributed atmosphere. Resources of service supplier have to be compelled to balance the load of shopper request. Totally different load reconciliation algorithms are planned so as to manage the resources of service supplier with efficiency and effectively. This paper presents a comparison of assorted policies used for load reconciliation.
Complete facial point cloud obtainment of patients with port wine stains based on point cloud fusion technology

Objective and accurate lesion assessment is one of the key factors for the optimal photodynamic therapy (PDT) of Port Wine Stains (PWS). The evaluation method based on 3D point cloud can effectively solve the problems. Comparing to the traditional point cloud registration algorithms such as ICP which tend to global registration, the feature description method is more suitable for facial point clouds fusion since each clouds is obtained from different angle and just overlap in certain area. In this paper, the method of fusion of multiple point clouds is applied, in which point cloud fusion is achieved by characterizing randomly selected sampling points. The point cloud fusion result is obtained by matching the public area between the two point clouds. Several fusion experiments are designed and conducted using the facial point cloud acquired by Artec Eva three-dimensional scanner. The experimental results show that it can accomplish the point cloud fusion of patient facial point cloud (including all the information on the skin lesions of PWS), which could be an efficient support for effective 3D lesion assessment.