Miracle-dz/UniFAR-FTUs huggingface dataset:
Addictive Behaviors, Depression, and Quality of Life among Korean Fishermen

This study investigated addictive behaviors (alcohol dependence and gambling tendencies), depression, and quality of life (QoL) among Korean fishermen in the Jeju Island region, Korea. The study utilized the Alcohol Use Disorder Identification Test—Korean version, the Korean version of the Canadian Problem Gambling Index, the Center for Epidemiological Studies Depression Scale, and the Korean version of the World Health Organization QOL-BREF to measure the study variables. The results showed that 18.1% of the fishermen had alcohol dependence and 9.9% abused alcohol, 13.6% were categorized as problem gamblers, 15.2% were moderate risk gamblers, and 14.4% were low-risk gamblers; 25.1% and 20.8% suffered from severe and mild depression, respectively. The mean QoL score was 3.13 ± 0.56, and the psychological health section scored the highest. The degree of alcohol dependence varied by age, education level, and job satisfaction; gambling tendency varied by age, job position, and job satisfaction; depression varied by religion and job satisfaction; QoL varied by religion and job satisfaction. Alcohol dependence, gambling tendency, and depression were significantly negatively correlated with QoL. Specifically, higher levels of alcohol dependence were associated with lower QoL scores in the subcategories of physical health and psychological health, while higher levels of gambling tendencies were associated with lower QoL scores in the subcategories of physical health, psychological health, social relationships, and general subcategories. Finally, higher levels of depression were associated with lower QoL scores across all five subcategories. Overall, participants exhibited remarkably elevated levels of alcohol dependence, gambling tendencies, and depression, and lower QoL compared with the general population. Further efforts are required to increase Korean fishermen’s job satisfaction to improve these problems. In addition, public health policies must address and promote fishermen’s QoL.
Effective Early Detection of Epileptic Seizures through EEG Signals Using Classification Algorithms Based on t-Distributed Stochastic Neighbor Embedding and K-Means

Epilepsy is a neurological disorder in the activity of brain cells that leads to seizures. An electroencephalogram (EEG) can detect seizures as it contains physiological information of the neural activity of the brain. However, visual examination of EEG by experts is time consuming, and their diagnoses may even contradict each other. Thus, an automated computer-aided diagnosis for EEG diagnostics is necessary. Therefore, this paper proposes an effective approach for the early detection of epilepsy. The proposed approach involves the extraction of important features and classification. First, signal components are decomposed to extract the features via the discrete wavelet transform (DWT) method. Principal component analysis (PCA) and the t-distributed stochastic neighbor embedding (t-SNE) algorithm were applied to reduce the dimensions and focus on the most important features. Subsequently, K-means clustering + PCA and K-means clustering + t-SNE were used to divide the dataset into subgroups to reduce the dimensions and focus on the most important representative features of epilepsy. The features extracted from these steps were fed to extreme gradient boosting, K-nearest neighbors (K-NN), decision tree (DT), random forest (RF) and multilayer perceptron (MLP) classifiers. The experimental results demonstrated that the proposed approach provides superior results to those of existing studies. During the testing phase, the RF classifier with DWT and PCA achieved an accuracy of 97.96%, precision of 99.1%, recall of 94.41% and F1 score of 97.41%. Moreover, the RF classifier with DWT and t-SNE attained an accuracy of 98.09%, precision of 99.1%, recall of 93.9% and F1 score of 96.21%. In comparison, the MLP classifier with PCA + K-means reached an accuracy of 98.98%, precision of 99.16%, recall of 95.69% and F1 score of 97.4%.
Maternal Preconception Glucose Homeostasis and Insulin Resistance Are Associated with Singleton and Twin Birthweight of Neonates Conceived by PCOS Women Undergoing IVF/ICSI Cycles

Polycystic ovary syndrome (PCOS) can induce fertility and metabolism disorders, which may increase the prevalence of glucose metabolism disorders and cause health hazards to women and their offspring. We aim to evaluate the effect of maternal preconception glucose metabolism on neonatal birthweight in PCOS women undergoing IVF/ICSI cycles. We retrospectively analyzed 269 PCOS women who delivered 190 singletons and 79 twins via IVF/ICSI at a reproductive center. The effects of maternal preconception glucose metabolism indicators on singleton and twin birthweight were evaluated using generalized linear models and generalized estimate equations, respectively. The potential nonlinear associations were evaluated using generalized additive models. The analyses were further stratified by maternal preconception BMI and delivery mode to evaluate the possible interaction effects. Among PCOS women, maternal preconception fasting plasma glucose (FPG) and glycohemoglobin (HbA1c) had significant negative associations with singleton birthweight (all p for trends = 0.04). We also found an overweight-specific association between elevated maternal preconception 2 h plasma insulin (2hPI) and twin birthweight (p for interactions = 0.05) and a caesarean-specific association between maternal preconception HbA1c and singleton birthweight (p for interactions = 0.02) in PCOS women. Maternal preconception glucose metabolism may affect neonatal birthweight, suggesting the importance of preconception glucose and insulin management for PCOS women. Further large prospective cohorts and animal studies are needed to confirm these findings and investigate the potential mechanisms.
Is Health Education among the Decisive Factors for the Diet Quality of Pregnant Women in Poland?

Health education (HE), an educational process that leads to increased nutritional awareness and improved health, is one of the factors influencing diet quality (DQ) during pregnancy. The aim was to evaluate the DQ of pregnant women and its determinants considering their HE. The study included 122 pregnant women aged 20–40 years. DQ was assessed using the Kom-PAN® questionnaire and the Pro-Healthy Diet Index (pHDI). Data collected included dietary habits, socio-demographic data, education level, place of residence, and maternal lifestyle-related characteristics, namely, pre-pregnancy weight, trimester of pregnancy, and pre-pregnancy and pregnancy physical activity (PA). Weekly energy expenditure was determined using the Polish version of the PPAQ questionnaire. HE at school more than tripled the odds of a higher DQ. Women in their second trimester were 54% more likely to have a higher DQ than women in their third trimester of pregnancy. Undertaking pre-pregnancy PA increased the odds of a higher DQ 2.5 times. Comparative analyses performed in a group of women with HE (HEG, n = 33) and without HE (nHEG, n = 89) showed better DQ in the former, but this was still unsatisfactory in health-promoting properties. The results obtained showed that the HE and trimester of pregnancy and pre-pregnancy Pa influenced DQ in pregnant women.
Impact of Robotic-Assisted Gait Training in Subacute Spinal Cord Injury Patients on Outcome Measure

The improvement of walking ability is a primary goal for spinal cord injury (SCI) patients. Robotic-assisted gait training (RAGT) is an innovative method for its improvement. This study evaluates the influence of RAGT vs. dynamic parapodium training (DPT) in improving gait motor functions in SCI patients. In this single-centre, single-blinded study, we enrolled 105 (39 and 64 with complete and incomplete SCI, respectively) patients. The investigated subjects received gait training with RAGT (experimental S1-group) and DPT (control S0-group), with six training sessions per week over seven weeks. The American Spinal Cord Injury Association Impairment Scale Motor Score (MS), Spinal Cord Independence Measure, version-III (SCIM-III), Walking Index for Spinal Cord Injury, version-II (WISCI-II), and Barthel Index (BI) were assessed in each patient before and after sessions. Patients with incomplete SCI assigned to the S1 rehabilitation group achieved more significant improvement in MS [2.58 (SE 1.21, p < 0.05)] and WISCI-II [3.07 (SE 1.02, p < 0.01])] scores in comparison with patients assigned to the S0 group. Despite the described improvement in the MS motor score, no progression between grades of AIS (A to B to C to D) was observed. A nonsignificant improvement between the groups for SCIM-III and BI was found. RAGT significantly improved gait functional parameters in SCI patients in comparison with conventional gait training with DPT. RAGT is a valid treatment option in SCI patients in the subacute phase. DPT should not be recommended for patients with incomplete SCI (AIS-C); in those patients, RAGT rehabilitation programs should be taken into consideration.
Comparison of sub-pixel algorithms based on digital image correlation

Digital image correlation is usually used for the measurement of displacement and deformation of rigid body.In this paper,three algorithms in digital image correlation including quadratic surface fitting,Lagrange interpolation method and gradient method are studied.Through the numerical simulations,a comprehensive evaluation of three algorithms is made.The results show that the accuracy of the gradient method is the highest.
Effect of the Combination of Hibiscus sabdariffa in Combination with Other Plant Extracts in the Prevention of Metabolic Syndrome: A Systematic Review and Meta-Analysis

Metabolic syndrome is a complex and multifactorial disorder associated with increased risk of cardiovascular disease and type 2 diabetes, exacerbated by a sedentary lifestyle and situations such as the COVID-19 pandemic. Recent studies have shown that consumption of fruits and vegetables high in polyphenols has a protective effect, reducing cardiovascular risk. Hibiscus sabdariffa (HS) in combination with other plant extracts has recently attracted scientists’ attention due to its potential use in the treatment of metabolic syndrome. This systematic review and meta-analysis examines the effects of HS in combination with other plant extracts on the prevention of metabolic syndrome, exploring their synergistic effects and potential as therapeutic agents. For this purpose, a systematic search of randomized clinical trials (RCTs) was conducted in four different databases and the data obtained were then used for a meta-analysis. Initially, the titles and abstracts of 1368 studies were read. From these, 16 studies were examined closely for their eligibility, and finally, seven RCTs with 332 participants were included in both the meta-analysis and the qualitative analysis. Our results show that HS in combination with other plant extracts improved anthropometric parameters, blood pressure, and lipid profile (low density lipoprotein cholesterol and total cholesterol) compared to a placebo control group. It is important to note that although this meta-analysis suggests that HS in combination with other plant extracts may have a beneficial effect on cardiovascular parameters, further research is needed to determine the optimal dose and intake duration.
Deep-learning reconstruction for the evaluation of lumbar spinal stenosis in computed tomography

To compare the quality and interobserver agreement in the evaluation of lumbar spinal stenosis (LSS) on computed tomography (CT) images between deep-learning reconstruction (DLR) and hybrid iterative reconstruction (hybrid IR). This retrospective study included 30 patients (age, 71.5 ± 12.5 years; 20 men) who underwent unenhanced lumbar CT. Axial and sagittal CT images were reconstructed using hybrid IR and DLR. In the quantitative analysis, a radiologist placed regions of interest within the aorta and recorded the standard deviation of the CT attenuation (i.e., quantitative image noise). In the qualitative analysis, 2 other blinded radiologists evaluated the subjective image noise, depictions of structures, overall image quality, and degree of LSS. The quantitative image noise in DLR (14.8 ± 1.9/14.2 ± 1.8 in axial/sagittal images) was significantly lower than that in hybrid IR (21.4 ± 4.4/20.6 ± 4.0) (P < .0001 for both, paired t test). Subjective image noise, depictions of structures, and overall image quality were significantly better with DLR than with hybrid IR (P < .006, Wilcoxon signed-rank test). Interobserver agreements in the evaluation of LSS (with 95% confidence interval) were 0.732 (0.712–0.751) and 0.794 (0.781–0.807) for hybrid IR and DLR, respectively. DLR provided images with improved quality and higher interobserver agreement in the evaluation of LSS in lumbar CT than hybrid IR.
Modulation of Dietary Choline Uptake in a Mouse Model of Acid Sphingomyelinase Deficiency

Acid sphingomyelinase deficiency (ASMD) is a lysosomal storage disorder caused by mutations in the gene-encoding acid sphingomyelinase (ASM). ASMD impacts peripheral organs in all patients, including the liver and spleen. The infantile and chronic neurovisceral forms of the disease also lead to neuroinflammation and neurodegeneration for which there is no effective treatment. Cellular accumulation of sphingomyelin (SM) is a pathological hallmark in all tissues. SM is the only sphingolipid comprised of a phosphocholine group linked to ceramide. Choline is an essential nutrient that must be obtained from the diet and its deficiency promotes fatty liver disease in a process dependent on ASM activity. We thus hypothesized that choline deprivation could reduce SM production and have beneficial effects in ASMD. Using acid sphingomyelinase knock-out (ASMko) mice, which mimic neurovisceral ASMD, we have assessed the safety of a choline-free diet and its effects on liver and brain pathological features such as altered sphingolipid and glycerophospholipid composition, inflammation and neurodegeneration. We found that the choline-free diet was safe in our experimental conditions and reduced activation of macrophages and microglia in the liver and brain, respectively. However, there was no significant impact on sphingolipid levels and neurodegeneration was not prevented, arguing against the potential of this nutritional strategy to assist in the management of neurovisceral ASMD patients.
Bronchopulmonary Dysplasia: Ongoing Challenges from Definitions to Clinical Care

Bronchopulmonary dysplasia (BPD) is the most common complication of extreme prematurity. Its etiology is multifactorial and is attributed to genetic susceptibility to prenatal and postnatal factors. As advancements in neonatology have led to the increased survival of premature infants, a parallel increase in the incidence of BPD has occurred. Over time, the definition and diagnostic criteria for BPD have evolved, as have management strategies. However, challenges continue to exist in the management of these infants, which is not surprising given the complexity of the disease. We summarize the key diagnostic criteria and provide insight into the challenges related to various aspects of BPD definitions, data comparisons, and clinical care implementation.
Eltrombopag for Low-Risk Myelodysplastic Syndromes With Thrombocytopenia: Interim Results of a Phase II, Randomized, Placebo-Controlled Clinical Trial (EQOL-MDS)

PURPOSE In myelodysplastic syndromes (MDS), severe thrombocytopenia is associated with poor prognosis. This multicenter trial presents the second-part long-term efficacy and safety results of eltrombopag in patients with low-risk MDS and severe thrombocytopenia. METHODS In this single-blind, randomized, placebo-controlled, phase-II trial of adult patients with International Prognostic Scoring System low- or intermediate-1-risk MDS, patients with a stable platelet (PLT) count (<30 × 103/mm3) received eltrombopag or placebo until disease progression. Primary end points were duration of PLT response (PLT-R; calculated from the time of PLT-R to date of loss of PLT-R, defined as bleeding/PLT count <30 × 103/mm3 or last date in observation) and long-term safety and tolerability. Secondary end points included incidence and severity of bleeding, PLT transfusions, quality of life, leukemia-free survival, progression-free survival, overall survival and pharmacokinetics. RESULTS From 2011 to 2021, of 325 patients screened, 169 patients were randomly assigned oral eltrombopag (N = 112) or placebo (N = 57) at a starting dose of 50 mg once daily to maximum of 300 mg. PLT-R, with 25-week follow-up (IQR, 14-68) occurred in 47/111 (42.3%) eltrombopag patients versus 6/54 (11.1%) in placebo (odds ratio, 5.9; 95% CI, 2.3 to 14.9; P < .001). In eltrombopag patients, 12/47 (25.5%) lost the PLT-R, with cumulative thrombocytopenia relapse-free survival at 60 months of 63.6% (95% CI, 46.0 to 81.2). Clinically significant bleeding (WHO bleeding score ≥ 2) occurred less frequently in the eltrombopag arm than in the placebo group (incidence rate ratio, 0.54; 95% CI, 0.38 to 0.75; P = .0002). Although no difference in the frequency of grade 1-2 adverse events (AEs) was observed, a higher proportion of eltrombopag patients experienced grade 3-4 AEs (χ2 = 9.5, P = .002). AML evolution and/or disease progression occurred in 17% (for both) of eltrombopag and placebo patients with no difference in survival times. CONCLUSION Eltrombopag was effective and relatively safe in low-risk MDS with severe thrombocytopenia. This trial is registered with ClinicalTrials.gov identifier: NCT02912208 and EU Clinical Trials Register: EudraCT No. 2010-022890-33.
Finding motifs using DNA images derived from sparse representations

Abstract Motivation Motifs play a crucial role in computational biology, as they provide valuable information about the binding specificity of proteins. However, conventional motif discovery methods typically rely on simple combinatoric or probabilistic approaches, which can be biased by heuristics such as substring-masking for multiple motif discovery. In recent years, deep neural networks have become increasingly popular for motif discovery, as they are capable of capturing complex patterns in data. Nonetheless, inferring motifs from neural networks remains a challenging problem, both from a modeling and computational standpoint, despite the success of these networks in supervised learning tasks. Results We present a principled representation learning approach based on a hierarchical sparse representation for motif discovery. Our method effectively discovers gapped, long, or overlapping motifs that we show to commonly exist in next-generation sequencing datasets, in addition to the short and enriched primary binding sites. Our model is fully interpretable, fast, and capable of capturing motifs in a large number of DNA strings. A key concept emerged from our approach—enumerating at the image level—effectively overcomes the k-mers paradigm, enabling modest computational resources for capturing the long and varied but conserved patterns, in addition to capturing the primary binding sites. Availability and implementation Our method is available as a Julia package under the MIT license at https://github.com/kchu25/MOTIFs.jl, and the results on experimental data can be found at https://zenodo.org/record/7783033.
Analyzing political formation through historical isiXhosa text analysis: Using frequency analysis to examine emerging African Nationalism in South Africa

This paper showcases new research avenues made possible by applying computational methods to historical isiXhosa text. I outline a method for isiXhosa computational text analysis which adapts word frequency analysis to be applied to isiXhosa texts focusing on root words. The paper showcases the value of the approach in a study of emerging political identities in early African nationalism, examining a novel dataset of isiXhosa newspapers from 1874 to 1890. The analysis shows how a shared identity of ‘Blackness’ (Abantsundu and Abamnyama) dynamically emerged, and follows the impact of leading intellectuals as well as African voter mobilization in shaping communal political discourse.
Theta phase precession at encoding predicts subsequent memory of sensory-driven vector fields, & occurs in memory-dependent fields at retrieval

Theta phase precession is thought to confer key computational advantages (e.g. temporal compression suiting spike-timing related plasticity, cognitive relations as phase distances, and population-level coding for directions and sequences). However, direct evidence speaking to: 1) its widely-theorised role in enhancing memorability; 2) its dependence upon sensory input, is lacking. We leveraged the Vector trace cell (VTC) phenomenon to examine these issues. VTCs in subiculum show a simple, unambiguous memory correlate: VTCs remember the distance and direction to a cue after the cue is removed, with a new ‘trace field’ which was not present before the cue was inserted. Regarding memorability, here we show that subsequently-remembered cue fields (those which become trace fields) exhibit higher levels of phase precession than subsequently-forgotten cue fields (those which produce no trace). Thus, phase precession does appear to enhance memorability, consistent with long-established theory. The second issue concerns the extent of phase precession in sensory-elicited vs memory-dependent firing. Phase precession in CA1 is strongly disrupted following deprivation of its Entorhinal, but not CA3, inputs; this could indicate that theta phase precession is largely sensory-driven and absent in memory-dependent fields. Here, however, we show that phase precession is robust in subicular VTC trace fields, i.e. when the cue that originally elicited the new vector field is no longer present. Thus, the much-theorised benefits of phase precession likely apply to memory-dependent fields. These findings have wide implications for oscillatory-based models of memory.
The intra‐individual reliability of 1H‐MRS measurement in the anterior cingulate cortex across 1 year

Magnetic resonance spectroscopy (MRS) is the primary method that can measure the levels of metabolites in the brain in vivo. To achieve its potential in clinical usage, the reliability of the measurement requires further articulation. Although there are many studies that investigate the reliability of gamma‐aminobutyric acid (GABA), comparatively few studies have investigated the reliability of other brain metabolites, such as glutamate (Glu), N‐acetyl‐aspartate (NAA), creatine (Cr), phosphocreatine (PCr), or myo‐inositol (mI), which all play a significant role in brain development and functions. In addition, previous studies which predominately used only two measurements (two data points) failed to provide the details of the time effect (e.g., time‐of‐day) on MRS measurement within subjects. Therefore, in this study, MRS data located in the anterior cingulate cortex (ACC) were repeatedly recorded across 1 year leading to at least 25 sessions for each subject with the aim of exploring the variability of other metabolites by using the index coefficient of variability (CV); the smaller the CV, the more reliable the measurements. We found that the metabolites of NAA, tNAA, and tCr showed the smallest CVs (between 1.43% and 4.90%), and the metabolites of Glu, Glx, mI, and tCho showed modest CVs (between 4.26% and 7.89%). Furthermore, we found that the concentration reference of the ratio to water results in smaller CVs compared to the ratio to tCr. In addition, we did not find any time‐of‐day effect on the MRS measurements. Collectively, the results of this study indicate that the MRS measurement is reasonably reliable in quantifying the levels of metabolites.