Miracle-dz/UniFAR-FTUs huggingface dataset:
Recurrence of Papillary Thyroid Cancer: A Systematic Appraisal of Risk Factors

Abstract Context Thyroid cancer recurrence is associated with increased mortality and adverse outcomes. Recurrence risk is currently predicted using clinical tools, often restaging patients after treatment. Detailed understanding of recurrence risk at disease onset could lead to personalized and improved patient care. Objective We aimed to perform a comprehensive bioinformatic and experimental analysis of 3 levels of genetic change (mRNA, microRNA, and somatic mutation) apparent in recurrent tumors and construct a new combinatorial prognostic risk model. Methods We analyzed The Cancer Genome Atlas data (TCGA) to identify differentially expressed genes (mRNA/microRNA) in 46 recurrent vs 455 nonrecurrent thyroid tumors. Two exonic mutational pipelines were used to identify somatic mutations. Functional gene analysis was performed in cell-based assays in multiple thyroid cell lines. The prognostic value of genes was evaluated with TCGA datasets. Results We identified 128 new potential biomarkers associated with recurrence, including 40 mRNAs, 39 miRNAs, and 59 genetic variants. Among differentially expressed genes, modulation of FN1, ITGα3, and MET had a significant impact on thyroid cancer cell migration. Similarly, ablation of miR-486 and miR-1179 significantly increased migration of TPC-1 and SW1736 cells. We further utilized genes with a validated functional role and identified a 5-gene risk score classifier as an independent predictor of thyroid cancer recurrence. Conclusion Our newly proposed risk model based on combinatorial mRNA and microRNA expression has potential clinical utility as a prognostic indicator of recurrence. These findings should facilitate earlier prediction of recurrence with implications for improving patient outcome by tailoring treatment to disease risk and increasing posttreatment surveillance.
Classification of road surface profiles

This paper introduces a universal classification methodology for discretely sampled sealed bituminous road profile data for the study of shock and vibrations related to the road transportation process. Data representative of a wide variety of Victorian (Australia) road profiles were used to develop a universal classification methodology with special attention to their non-Gaussian and nonstationary properties. This resulted in the design of computer software to automatically detect and extract transient events from the road spatial acceleration data as well as to identify segments of the constant RMS level enabling transients to be analyzed separately from the underlying road process. Nine universal classification parameters are introduced to describe road profile spatial acceleration based on the statistical characteristics of the transient amplitude and stationary RMS segments. Results from this study are aimed at the areas of road transport simulation as well as road surface characterization.
Effects of Hair dyes on Sequence Analysis of Hair Mitochondrial DNA Hypervariable Region 1

Hair can be a valuable source of DNA especially in forensic casework and for noninvasive studies of human, when blood samples not available. This study emphasizes the impact of hair dyes on DNA sequence analysis. Samples collected from forty Iraqi families; each sample was divided in to two parts hair follicles and hair shaft. DNA extracted by using two different techniques, Phenol-chloroform (organic) method and prepFiler forensic DNA extraction kit. After quantification of DNA by real time PCR to confirm the exact DNA yield, Mitochondrial DNA (MtDNA) hypervariable region 1 successfully amplified from (50% of samples include hair follicle and 20% samples include shaft only), which all extracted by organic method. Whereas by using prepFiler kit the ratio of amplification success reach to 95% of samples included hair follicles, but there wais no DNA outcome from hair shaft by using this kit. Our results demonstrate that treated hair by dyed or henna had a significant influence on the sequence analysis results. Organic method was an appropriate method for extraction DNA from hair shaft, since this method used for extracting the old and degraded samples. While prepFiler DNA extraction kit was more convenient for isolation DNA from, hair samples included follicles only with excellent result.
Effects of 16 weeks of pyramidal and polarized training intensity distributions in well‐trained endurance runners

The aim of this study was to investigate the effects of four different training periodizations, based on two different training intensity distributions during a 16‐week training block in well‐trained endurance runners. Sixty well‐trained male runners were divided into four groups. Each runner completed one of the following 16‐week training interventions: a pyramidal periodization (PYR); a polarized periodization (POL); a pyramidal periodization followed by a polarized periodization (PYR → POL); and a polarized periodization followed by a pyramidal periodization (POL → PYR). The PYR and POL groups trained with a pyramidal or polarized distribution for 16 weeks. To allow for the change in periodization for the PYR → POL and POL → PYR groups, the 16‐week intervention was split into two 8‐week phases, starting with pyramidal or polarized distribution and then switching to the other. The periodization patterns were isolated manipulations of training intensity distribution, while training load was kept constant. Participants were tested pre‐, mid‐ and post‐intervention for body mass, velocity at 2 and 4 mmol·L−1 of blood lactate concentration (vBLa2, vBLa4), absolute and relative peak oxygen consumption ( V˙O2peak ) and 5‐km running time trial performance. There were significant group × time interactions for relative V˙O2peak (p < 0.0001), vBLa2 (p < 0.0001) and vBLa4 (p < 0.0001) and 5‐km running time trial performance (p = 0.0001). Specifically, participants in the PYR → POL group showed the largest improvement in all these variables (~3.0% for relative V˙O2peak , ~1.7% for vBLa2, ~1.5% for vBLa4, ~1.5% for 5‐km running time trial performance). No significant interactions were observed for body mass, absolute V˙O2peak , peak heart rate, lactate peak and rating of perceived exertion. Each intervention effectively improved endurance surrogates and performance in well‐trained endurance runners. However, the change from pyramidal to polarized distribution maximized performance improvements, with relative V˙O2peak representing the only physiological correlate.
Review of OCT Angiography Findings in Diabetic Retinopathy: Insights and Perspectives

Diabetes mellitus (DM), a disorder rapidly growing in prevalence, is linked to the retinal microvasculature complication diabetic retinopathy (DR). As one of the leading global causes of vision impairment and loss, imaging techniques to detect and monitor DR must continue to improve in order to address this growing burden. Optical coherence tomography angiography (OCTA) is a nascent imaging modality that generates three-dimensional visualizations of the retinal and choroidal microvasculature. Compared to fluorescein angiography, the gold-standard imaging modality for retinal vessels, OCTA offers the advantages of being non-invasive, quick, and able to resolve the multiple plexuses within the retina. Quantitative OCTA studies have explored parameters such as vessel density (VD), foveal avascular zone (FAZ), acircularity index, vessel tortuosity (VT), and fractal dimension (FD) amongst DR patients. This review synthesizes the main trends emerging from quantitative OCTA-based studies of DR and interrogates them within the context of DR pathophysiology. We offer a glimpse into how analysis techniques have shifted in the years since OCTA came into existence, while speculating on its future role in clinical practice.
Avaliação de índices de conforto térmico de instalações para poedeiras no nordeste do Brasil

In this study the thermal comfort indexes were analyzed in the growth phase of laying hens housed in installation with different types of roofing materials in the Northeast of Brazil. The laying hen-houses were assessed through black globe temperature and humidity index (WBGT), radiating thermal load (RTL) and the relative humidity. The mean analysis had showed that the laying-hen houses provided uncomfortable environmental indexes in all growth phases, where the thermal comfort indexes were below the thermal comfort zone during the early begining of chicken growing as well as in final phase when the indices were above the zone. During the hottest hours of the day, the laying-hen houses under ceramic roof tiles showed results in RTL better than the laying-hen houses using asbestos roofing tiles, providing best thermal comfort for laying hens in the growth phase.
Mapping the genetic architecture of suicide attempt and suicide death using polygenic risk scores for clinically-related psychiatric disorders and traits

Abstract Background Suicidal behavior is moderately heritable and a consequence of a combination of the diathesis traits for suicidal behavior and suicide-related major psychiatric disorders. Here, we sought to examine shared polygenic effects between various psychiatric disorders/traits and suicidal behavior and to compare the shared polygenic effects of various psychiatric disorders/traits on non-fatal suicide attempt and suicide death. Methods We used our genotyped European ancestry sample of 260 non-fatal suicide attempters, 317 suicide decedents and 874 non-psychiatric controls to test whether polygenic risk scores (PRSs) obtained from large GWASs for 22 suicide-related psychiatric disorders/traits were associated with suicidal behavior. Results were compared between non-fatal suicide attempt and suicide death in a sensitivity analysis. Results PRSs for major depressive disorder, bipolar disorder, schizophrenia, ADHD, alcohol dependence, sensitivity to environmental stress and adversity, educational attainment, cognitive performance, and IQ were associated with suicidal behavior (Bonferroni-corrected p < 2.5 × 10−4). The polygenic effects of all 22 psychiatric disorders/traits had the same direction (p for binomial tests = 4.8 × 10−7) and were correlated (Spearman's ρ = 0.85) between non-fatal suicide attempters and suicide decedents. Conclusions We found that polygenic effects for major psychiatric disorders and diathesis-related traits including stress responsiveness and intellect/cognitive function contributed to suicidal behavior. While we found comparable polygenic architecture between non-fatal suicide attempters and suicide decedents based on correlations with PRSs of suicide-related psychiatric disorders/traits, our analyses are limited by small sample size resulting in low statistical power to detect difference between non-fatal suicide attempt and suicide death.
Hypoglycemia, Vascular Disease and Cognitive Dysfunction in Diabetes: Insights from Text Mining-Based Reconstruction and Bioinformatics Analysis of the Gene Networks

Hypoglycemia has been recognized as a risk factor for diabetic vascular complications and cognitive decline, but the molecular mechanisms of the effect of hypoglycemia on target organs are not fully understood. In this work, gene networks of hypoglycemia and cardiovascular disease, diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, cognitive decline, and Alzheimer’s disease were reconstructed using ANDSystem, a text-mining-based tool. The gene network of hypoglycemia included 141 genes and 2467 interactions. Enrichment analysis of Gene Ontology (GO) biological processes showed that the regulation of insulin secretion, glucose homeostasis, apoptosis, nitric oxide biosynthesis, and cell signaling are significantly enriched for hypoglycemia. Among the network hubs, INS, IL6, LEP, TNF, IL1B, EGFR, and FOS had the highest betweenness centrality, while GPR142, MBOAT4, SLC5A4, IGFBP6, PPY, G6PC1, SLC2A2, GYS2, GCGR, and AQP7 demonstrated the highest cross-talk specificity. Hypoglycemia-related genes were overrepresented in the gene networks of diabetic complications and comorbidity; moreover, 14 genes were mutual for all studied disorders. Eleven GO biological processes (glucose homeostasis, nitric oxide biosynthesis, smooth muscle cell proliferation, ERK1 and ERK2 cascade, etc.) were overrepresented in all reconstructed networks. The obtained results expand our understanding of the molecular mechanisms underlying the deteriorating effects of hypoglycemia in diabetes-associated vascular disease and cognitive dysfunction.
An Update of Medical Nutrition Therapy in Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a serious and frequent pregnancy complication that can lead to short and long-term risks for both mother and fetus. Different health organizations proposed different algorithms for the screening, diagnosis, and management of GDM. Medical Nutrition Therapy (MNT), together with physical exercise and frequent self-monitoring, represents the milestone for GDM treatment in order to reduce maternal and fetal complications. The pregnant woman should benefit from her family support and make changes in their lifestyles, changes that, in the end, will be beneficial for the whole family. The aim of this manuscript is to review the literature about the Medical Nutrition Therapy in GDM and its crucial role in GDM management.
Mapping of the Flood Distribution in an Urban Environment: The Case of Palma (Mallorca, Spain) in the First Two Decades of the 21st Century

The City of Palma de Mallorca has been historically affected by flood events, with the latest flood of great magnitude occurring in 1962. After decades without large flooding events, since the start of the 21st century, 28 floods have been identified within the city boundaries. As change in the spatial location of these events has been observed, a research to identify where the floods are located nowadays and which causes can be related to such distribution has been undertaken. Six types of floods were identified and the events classified accordingly, with the deficient planned infrastructures, flat urban areas without defined drainage and coastal sectors the three most common types. The results highlight the importance of the urban sprawl and malpractices related to flood risk areas, thus increasing the occurrence of floods of less spatial impact but with greater disturbance on the daily activity of the city inhabitants. Nevertheless, some uncertainties are identified in this research, demonstrating the need of further investigations.
A new thermal unit commitment approach using constraint logic programming

The authors propose a constraint logic programming (CLP) algorithm to solve the thermal unit commitment (UC) problem in this paper. The algorithm combines the characteristics of the logic programming with the constraint satisfaction as well as the depth-first branch and bound (B&B) search techniques to provide an efficient and flexible approach to the UC problem. Through the constraint satisfaction techniques, the constraints, which consist of the upper bound on the objective value, are propagated as much as possible to actively reduce the search space of the UC problem in a priori way. Consequently, the optimal solution can be acquired in a very early stage. To demonstrate the effectiveness of the proposed approach, the practical thermal UC problem of Taiwan Power (Taipower) 38-unit system over a 24-hour period is solved by the CLP algorithm implemented in CHIP language, The results obtained are compared with those from the established methods of dynamic programming, Lagrangian relaxation as well as simulated annealing.
Forecasting Photosynthetic Photon Flux Density Under Cloud Effects: Novel Predictive Model Using Convolutional Neural Network Integrated With Long Short-term Memory Network

Forecast models of solar radiation incorporating cloud effects are useful tools to evaluate the impact of stochastic behaviour of cloud movement, real-time integration of photovoltaic energy in power grids, skin cancer and eye disease risk minimisation through solar ultraviolet (UV) index prediction and bio-photosynthetic processes through the modelling of solar photosynthetic photon flux density (PPFD). This research has developed deep learning hybrid model (i.e., CNN-LSTM) to factor in role of cloud effects integrating the merits of convolutional neural networks with long short-term memory networks to forecast near real-time (i.e., 5-minute) PPFD in a sub-tropical region Queensland, Australia. The prescribed CLSTM model is trained with real-time sky images that depict stochastic cloud movements captured through a Total Sky Imager (TSI-440) utilising advanced sky image segmentation to reveal cloud chromatic features into their statistical values, and to purposely factor in the cloud variation to optimise the CLSTM model. The model, with its competing algorithms (i.e., CNN, LSTM, deep neural network, extreme learning machine and multivariate adaptive regression spline), are trained with 17 distinct cloud cover inputs considering the chromaticity of red, blue, thin, and opaque cloud statistics, supplemented by solar zenith angle (SZA) to predict short-term PPFD. The models developed with cloud inputs yield accurate results, outperforming the SZA-based models while the best testing performance is recorded by the objective method (i.e., CLSTM) tested over a 7-day measurement period. Specifically, CLSTM yields a testing performance with correlation coefficient r = 0.92, root mean square error RMSE = 210.31 μ mol of photons m-2 s-1, mean absolute error MAE = 150.24 μ mol of photons m-2 s-1, including a relative error of RRMSE = 24.92% MAPE = 38.01%, and Nash Sutcliffe’s coefficient ENS = 0.85, and Legate & McCabe’s Index LM = 0.68 using cloud cover in addition to the SZA as an input. The study shows the importance of cloud inclusion in forecasting solar radiation and evaluating the risk with practical implications in monitoring solar energy, greenhouses and high-value agricultural operations affected by stochastic behaviour of clouds. Additional methodological refinements such as retraining the CLSTM model for hourly and seasonal time scales may aid in the promotion of agricultural crop farming and environmental risk evaluation applications such as predicting the solar UV index and direct normal solar irradiance for renewable energy monitoring systems.
A contribution to the modeling of longitudinally periodic waveguides by the help of the TLM method

To efficiently simulate longitudinally periodic waveguide, the Floquet's theorem is implemented to modify the transmission-line matrix (TLM) algorithm. In the literature, similar algorithms are presented for the finite-difference time-domain method and fundamental problems are addressed. The aim of this paper is to explain and solve these problems and misunderstandings and to extend the approach to the TLM method. Simulation results show the validity of the technique proposed.
Factors Associated with the Development of Secondary School Students’ Interest towards STEM Studies

The aim of this study is to investigate the predictive factors that predispose secondary school students’ interest in studying STEM (Science, Technology, Engineering, and Mathematics) fields in higher education. For this purpose, an already existing questionnaire was used and modified properly, according to the Greek educational system. The survey was attended by 301 secondary school students, who study in Piraeus, one of the largest cities in Greece. Research findings indicated that the principles of Social Cognitive Career Theory (SCCT) are well supported. It is worth mentioning that this is the first time that such a number of variables had been examined, in order to support the SCCT. In particular, very few studies exist in literature—to the best of our knowledge—investigating the effect of more than four factors influencing students’ interest towards STEM higher studies. Learning experiences, students’ exposure to STEM activities within the school environment and outside of it (OR = 0.071, p = 0.002), as well as their involvement with high difficulty STEM courses (OR = 0.203, p = 0.038), appear to be positively correlated with the development of interest towards studies in the STEM fields. In addition, students from low-income families are more likely to follow STEM studies (OR = 0.198, p = 0.034). On the contrary, it has been revealed that parental educational background only supports the student’s decision to continue studies after high school, without specifying the educational field in higher education (OR = 0.769, p = 0.703; father’s educational level, OR = 0.698, p = 0.552; mother’s educational level). Data revealed that outcome expectations and self-efficacy (OR = 14.366, p = 0.005) are positively related to the procedure of students’ interest development to pursue STEM fields in higher education, while gender seems to be a non-regulatory factor (OR = 0.886, p = 0.831).
Combinations of Hydrogels and Mesenchymal Stromal Cells (MSCs) for Cartilage Tissue Engineering—A Review of the Literature

Cartilage offers limited regenerative capacity. Cell-based approaches have emerged as a promising alternative in the treatment of cartilage defects and osteoarthritis. Due to their easy accessibility, abundancy, and chondrogenic potential mesenchymal stromal cells (MSCs) offer an attractive cell source. MSCs are often combined with natural or synthetic hydrogels providing tunable biocompatibility, biodegradability, and enhanced cell functionality. In this review, we focused on the different advantages and disadvantages of various natural, synthetic, and modified hydrogels. We examined the different combinations of MSC-subpopulations and hydrogels used for cartilage engineering in preclinical and clinical studies and reviewed the effects of added growth factors or gene transfer on chondrogenesis in MSC-laden hydrogels. The aim of this review is to add to the understanding of the disadvantages and advantages of various combinations of MSC-subpopulations, growth factors, gene transfers, and hydrogels in cartilage engineering.
Arrugas Bone Trephine Assisted Flapless Dacryocystorhinostomy with Circumosteal - Mitomycin C Versus External Dacryocystorhinostomy: A Hospital Based Comparative Study.

INTRODUCTION Primary acquired nasolacrimal duct obstruction is a common ophthalmic condition and has conventionally been managed by external dacryocystorhinostomy. However this procedure is time consuming and involves making mucosal flaps. The aim of this study was to compare the surgical outcome in Arrugas bone trephine-assisted flapless dacryocystorhinostomy with Circumosteal - Mitomycin C versus conventional external dacryocystorhinostomy. MATERIALS AND METHODS This is a retrospective non-randomized study of surgical outcome in patients of primary acquired nasolacrimal duct obstruction who underwent an Arrugas bone trephine assisted flapless dacryocystorhinostomy with Circumosteal - Mitomycin C (group A) versus those who underwent conventional external dacryocystorhinostomy (group B) in a teaching hospital in North India. Patients with previously failed dacryocystorhinostomy, lacrimal fistula, canalicular and common canalicular obstruction were excluded. Success was defined as patent syringing at the end of one year. Surgical time was calculated from skin incision to skin suturing. RESULTS There was complete resolution of epiphora with patent syringing in 43 out of 52 patients in group A, while in group B, 47 out of 55 patients had complete resolution of epiphora with patent syringing at the end of one year (p= 0.77). Mean surgical time was significantly lower in Group A than in Group B (p=<.05). Scarring and closure of the ostium was the most common cause of failure in both groups (Group A, n=5, 9.6%; Group B, n= 3, 5.45%). CONCLUSION Arrugas bone trephine-assisted flapless dacryocystorhinostomy with Circumosteal - Mitomycin C is a viable alternative to conventional external dacryocystorhinostomy with comparable success rate and shorter surgical time and a faster learning curve.