Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell death markers in patients with cirrhosis and acute decompensation

The aims of this study were to determine the role of cell death in patients with cirrhosis and acute decompensation (AD) and acute on chronic liver failure (ACLF) using plasma‐based biomarkers. The patients studied were part of the CANONIC (CLIF Acute‐on‐Chronic Liver Failure in Cirrhosis) study (N = 337; AD, 258; ACLF, 79); additional cohorts included healthy volunteers, stable patients with cirrhosis, and a group of 16 AD patients for histological studies. Caspase‐cleaved keratin 18 (cK18) and keratin 18 (K18), which reflect apoptotic and total cell death, respectively, and cK18:K18 ratio (apoptotic index) were measured in plasma by enzyme‐linked immunosorbent assay. The concentrations of cK18 and K18 increased and the cK18:K18 ratio decreased with increasing severity of AD and ACLF (P < 0.001, respectively). Alcohol etiology, no previous decompensation, and alcohol abuse were associated with increased cell death markers whereas underlying infection was not. Close correlation was observed between the cell death markers and, markers of systemic inflammation, hepatic failure, alanine aminotransferase, and bilirubin, but not with markers of extrahepatic organ injury. Terminal deoxynucleotidyl transferase dUTP nick‐end labeling staining confirmed evidence of greater hepatic cell death in patients with ACLF as opposed to AD. Inclusion of cK18 and K18 improved the performance of the CLIF‐C AD score in prediction of progression from AD to ACLF (P < 0.05). Conclusion: Cell death, likely hepatic, is an important feature of AD and ACLF and its magnitude correlates with clinical severity. Nonapoptotic forms of cell death predominate with increasing severity of AD and ACLF. The data suggests that ACLF is a heterogeneous entity and shows that the importance of cell death in its pathophysiology is dependent on predisposing factors, precipitating illness, response to injury, and type of organ failure. (Hepatology 2018;67:989–1002)
Informed and Uninformed Naïve Assessment Constructors’ Strategies for Item Selection

We present a descriptive analysis of 53 naïve assessment constructors’ explanations for selecting test items to include on a summative assessment. We randomly assigned participants to an informed and uninformed condition (i.e., informed participants read an article describing a Table of Specifications). Through recursive thematic analyses of participants’ explanations, we identified 14 distinct strategies that coalesced into three families of strategies: Alignment, Item Evaluation, and Affective Evaluation. We describe the nature of the strategies and the degree to which participants used strategies with frequency and effect size analysis. Results can inform teacher education on assessment construction through explicit instruction in the three families of strategies identified.
Association between ZIC2, RASGRF1, and SHISA6 genes and high myopia in Japanese subjects.

PURPOSE We investigated the association of genetic variations, which were identified recently in a large-scale genome-wide association study (GWAS) to confer risk of refractive error and common myopia in Caucasians, with high myopia in Japanese subjects. METHODS The 5 single-nucleotide polymorphisms (SNPs) from the 5 genes TOX, RDH5, ZIC2, RASGRF1, and SHISA6, were genotyped in 1339 unrelated highly myopic Japanese patients and 3248 healthy Japanese participants in the Nagahama Study. In addition, genotypes were compared between high myopia patients without choroidal neovascularization (CNV) and patients with myopic CNV. RESULTS Significant associations between rs8000973 near ZIC2 (P = 7.16 × 10(-7)), rs4778879 in RASGRF1 (P = 3.40 × 10(-7)), and rs2969180 in SHISA6 (P = 0.033) and high myopia were observed. Odds ratios (95% confidence intervals) were 1.33 (1.19-1.49), 0.78 (0.71-0.86), and 1.11 (1.01-1.22) for the rs8000973 C allele, rs4778879 A allele, and rs2969180 G allele, respectively. The effect of the rs2969180 allele G contrasted with that observed in the original report, whereas the effect of the other 2 SNPs agreed. Further analysis using controls with -1.0 diopter (D) ≤ spherical equivalent ≤ +1.0 D showed a significant association between ZIC2 and RASGRF1, but not SHISA6. Among the patients with high myopia, 516 had myopic CNV in either eye, while 823 patients did not have myopic CNV in eyes. No evaluated genes showed a significant association with the development of myopic CNV. CONCLUSIONS ZIC2 and RASGRF1 are susceptibility genes, not only for common myopia, but also for high myopia.
Arguing security: validating security requirements using structured argumentation

This paper proposes using both formal and structured informal arguments to show that an eventual realized system can satisfy its security requirements. These arguments, called 'satisfaction arguments', consist of two parts: a formal argument based upon claims about domain properties, and a set of informal arguments that justify the claims. Building on our earlier work on trust assumptions and security requirements, we show how using satisfaction arguments assists in clarifying how a system satisfies its security requirements, in the process identifying those properties of domains that are critical to the requirements.
Exceptional hiatuses in Spanish

This paper provides a close examination of how Spanish speakers syllabify sequences of vocoids of rising sonority within the lexicon (e.g., piano ‘piano’, persiana ‘blind’ or historia ‘history’). A survey with 246 words administered to 15 Peninsular Spanish speakers has enabled us to examine in a quantitative way the strength of prosodic and morphological conditions on the appearance of the so-called exceptional hiatuses (Navarro Tomas 1948; Hualde 1999, 2005; Colina 1999). The data in our study reveals that the word initiality effect is not as strong as stated in the literature and that there are large differences between speakers: within the same dialect, half of the informants have the word-initiality effect in words such as piano ‘piano’ or dialogo ‘dialogue’, while the rest have practically generalized the presence of a diphthong in this position. Interestingly, morpheme boundary effects are found in conservative speakers and their conditions differ depending on the paradigm: (a) in nominal forms, gliding is blocked when there is an intervening morpheme boundary and when the glide is a high back vowel ( virt [u.Ao] so ‘virtuous’ vs. od [Ajo] so ‘hateful’, act [u.Aa] l ‘present’ vs. cord [Aja] l ‘cordial’); (b) in verbal paradigms, gliding is blocked when there is an intervening morpheme boundary and when the high vowel can be stressed in some form of the paradigm ( conf [i.Aa] r ‘to trust’, confio ‘I trust’ vs. camb [Aja] r ‘to change’, cambio ‘I change’). In general, the situation indicates that language change is in progress and that, for some speakers, the presence of lexical items that are pronounced with a hiatus is gradually disappearing. The article presents an analysis in terms of a correspondence-based OT analysis which captures the prosodic and analogical forces governing this process together with the interspeaker variation found in the data.
Implementation of a Guided, Digital Cognitive Behavioral Program for Anxiety in Primary Care: Preliminary Findings of Engagement and Effectiveness.

BACKGROUND Implementation of digital behavioral health programs in primary care (PC) can improve access to care for patients in need. INTRODUCTION This study provides preliminary data on user engagement and anxiety symptom change among patients referred by their PC provider to a guided, mobile cognitive behavioral program, Lantern. MATERIALS AND METHODS Adults aged 20-65 years with at least mild anxiety (GAD-7 ≥ 5) during routine clinical screening in two PC practices were offered Lantern. The primary outcome was self-reported anxiety collected at baseline and 2 months. Linear mixed effects modeling was used to examine anxiety symptom reduction from baseline to 2 months. Post hoc analyses evaluated how number of units completed, number of techniques practiced, and days of usage impacted symptom change. RESULTS Sixty-three participants signed up for Lantern and had both baseline and 2- month GAD-7. A mixed effects model adjusted for age, gender, medical complexity score, and physical health found a significant effect of time on GAD-7 (β = -2.08, standard error = 0.77, t(62) = -2.71, p = 0.009). Post hoc analyses indicated that mean number of units, techniques, and usage days did not significantly impact GAD-7 change over 2 months. However, there was significantly greater improvement in anxiety in participants who completed at least three techniques. DISCUSSION Results benchmark to previous studies that have found statistically significant symptom change among participants after 4-9 weeks of face-to-face or Internet-based cognitive behavioral therapy (CBT). CONCLUSIONS This study suggests that use of Lantern is associated with anxiety reduction and provides proof-of-concept for the dissemination and implementation of guided, CBT-based mobile behavioral health interventions in PC settings.
Evolving Unsupervised Deep Neural Networks for Learning Meaningful Representations

Deep learning (DL) aims at learning the meaningful representations. A meaningful representation gives rise to significant performance improvement of associated machine learning (ML) tasks by replacing the raw data as the input. However, optimal architecture design and model parameter estimation in DL algorithms are widely considered to be intractable. Evolutionary algorithms are much preferable for complex and nonconvex problems due to its inherent characteristics of gradient-free and insensitivity to the local optimal. In this paper, we propose a computationally economical algorithm for evolving unsupervised deep neural networks to efficiently learn meaningful representations, which is very suitable in the current big data era where sufficient labeled data for training is often expensive to acquire. In the proposed algorithm, finding an appropriate architecture and the initialized parameter values for an ML task at hand is modeled by one computational efficient gene encoding approach, which is employed to effectively model the task with a large number of parameters. In addition, a local search strategy is incorporated to facilitate the exploitation search for further improving the performance. Furthermore, a small proportion labeled data is utilized during evolution search to guarantee the learned representations to be meaningful. The performance of the proposed algorithm has been thoroughly investigated over classification tasks. Specifically, error classification rate on MNIST with 1.15% is reached by the proposed algorithm consistently, which is considered a very promising result against state-of-the-art unsupervised DL algorithms.
A case study on using speech-to-translation alignments for language documentation

For many low-resource or endangered languages, spoken language resources are more likely to be annotated with translations than with transcriptions. Recent work exploits such annotations to produce speech-to-translation alignments, without access to any text transcriptions. We investigate whether providing such information can aid in producing better (mismatched) crowdsourced transcriptions, which in turn could be valuable for training speech recognition systems, and show that they can indeed be beneficial through a small-scale case study as a proof-of-concept. We also present a simple phonetically aware string averaging technique that produces transcriptions of higher quality.
ATM, BCL2, and TGFβ Gene Polymorphisms as Radiotherapy Outcome Biomarkers in Head and Neck Squamous Cell Carcinoma Patients.

AIMS Polymorphisms in cell cycle genes are considered prognostic as radiosensitivity markers in patients with head and neck squamous cell carcinoma. Therefore, we aimed to investigate the relationship of ATM 5557G>A, ATM IVS62 + 60G>A, TP53 215G>C, BCL2-938C>A, TGFβ-509C>T, and TGFβ 29C>T with radiotherapy response. MATERIALS AND METHODS Genotyping was performed by polymerase chain reaction followed by restriction fragment length polymorphism in 210 patients with oral cavity/oropharyngeal carcinoma and 101 patients with laryngeal tumors. RESULTS In irradiated oral cavity/oropharyngeal tumors, the ATM IVS62 + 60G>A AA genotype significantly increased local recurrence risk (odds ratio [OR] = 4.43; confidence interval [CI] = 1.22-16.13) and the BCL2-938C>A C allele and the TGFβ-509C>T T allele were associated with worse disease-specific survival (hazard ratio [HR] = 0.46; CI = 0.24-0.90 and HR = 2.20; CI = 1.12-4.29, respectively). In irradiated laryngeal carcinoma, the TGFβ 29C>T C allele was associated with increased local recurrence risk (OR = 0.09; CI = 0.02-0.53), death rate (OR = 0.18; CI = 0.04-0.86), and worse local disease-free and disease-specific survival rates (HR = 0.13; CI = 0.03-0.59 and HR = 0.21; CI = 0.07-0.60, respectively), while the BCL2-938C>A C allele was related to a worse disease-specific survival (HR = 0.32; CI = 0.12-0.83). DISCUSSION These results can help individualize treatment according to a patient's genetic markers. We demonstrated that ATM IVS62 + 60G>A, TGFβ 29C>T, TGFβ-509C>T, and BCL2-938C>A can function as biomarkers of tumor radiosensitivity, being candidates for a predictive genetic profile of radiotherapy response.
Adult Spinal Cord Radial Glia Display a Unique Progenitor Phenotype

Radial glia (RG) are primarily embryonic neuroglial progenitors that express Brain Lipid Binding Protein (Blbp a.k.a. Fabp7) and Glial Fibrillary Acidic Protein (Gfap). We used these transcripts to demarcate the distribution of spinal cord radial glia (SCRG) and screen for SCRG gene expression in the Allen Spinal Cord Atlas (ASCA). We reveal that neonatal and adult SCRG are anchored in a non-ventricular niche at the spinal cord (SC) pial boundary, and express a “signature” subset of 122 genes, many of which are shared with “classic” neural stem cells (NSCs) of the subventricular zone (SVZ) and SC central canal (CC). A core expressed gene set shared between SCRG and progenitors of the SVZ and CC is particularly enriched in genes associated with human disease. Visualizing SCRG in a Fabp7-EGFP reporter mouse reveals an extensive population of SCRG that extend processes around the SC boundary and inwardly (through) the SC white matter (WM), whose abundance increases in a gradient from cervical to lumbar SC. Confocal analysis of multiple NSC-enriched proteins reveals that postnatal SCRG are a discrete and heterogeneous potential progenitor population that become activated by multiple SC lesions, and that CC progenitors are also more heterogeneous than previously appreciated. Gene ontology analysis highlights potentially unique regulatory pathways that may be further manipulated in SCRG to enhance repair in the context of injury and SC disease.
A Data-driven Model for Interaction-Aware Pedestrian Motion Prediction in Object Cluttered Environments

This paper reports on a data-driven, interaction-aware motion prediction approach for pedestrians in environments cluttered with static obstacles. When navigating in such workspaces shared with humans, robots need accurate motion predictions of the surrounding pedestrians. Human navigation behavior is mostly influenced by their surrounding pedestrians and by the static obstacles in their vicinity. In this paper we introduce a new model based on Long-Short Term Memory (LSTM) neural networks, which is able to learn human motion behavior from demonstrated data. To the best of our knowledge, this is the first approach using LSTMs, that incorporates both static obstacles and surrounding pedestrians for trajectory forecasting. As part of the model, we introduce a new way of encoding surrounding pedestrians based on a 1d-grid in polar angle space. We evaluate the benefit of interaction-aware motion prediction and the added value of incorporating static obstacles on both simulation and real-world datasets by comparing with state-of-the-art approaches. The results show, that our new approach outperforms the other approaches while being very computationally efficient and that taking into account static obstacles for motion predictions significantly improves the prediction accuracy, especially in cluttered environments.
Data-driven brain network models differentiate variability across language tasks

The relationship between brain structure and function has been probed using a variety of approaches, but how the underlying structural connectivity of the human brain drives behavior is far from understood. To investigate the effect of anatomical brain organization on human task performance, we use a data-driven computational modeling approach and explore the functional effects of naturally occurring structural differences in brain networks. We construct personalized brain network models by combining anatomical connectivity estimated from diffusion spectrum imaging of individual subjects with a nonlinear model of brain dynamics. By performing computational experiments in which we measure the excitability of the global brain network and spread of synchronization following a targeted computational stimulation, we quantify how individual variation in the underlying connectivity impacts both local and global brain dynamics. We further relate the computational results to individual variability in the subjects’ performance of three language-demanding tasks both before and after transcranial magnetic stimulation to the left-inferior frontal gyrus. Our results show that task performance correlates with either local or global measures of functional activity, depending on the complexity of the task. By emphasizing differences in the underlying structural connectivity, our model serves as a powerful tool to assess individual differences in task performances, to dissociate the effect of targeted stimulation in tasks that differ in cognitive demand, and to pave the way for the development of personalized therapeutics.
Human placental oxygenation in late gestation: experimental and theoretical approaches

The placenta is crucial for life. It is an ephemeral but complex organ acting as the barrier interface between maternal and fetal circulations, providing exchange of gases, nutrients, hormones, waste products and immunoglobulins. Many gaps exist in our understanding of the detailed placental structure and function, particularly in relation to oxygen handling and transfer in healthy and pathological states in utero. Measurements to understand oxygen transfer in vivo in the human are limited, with no general agreement on the most appropriate methods. An invasive method for measuring partial pressure of oxygen in the intervillous space through needle electrode insertion at the time of Caesarean sections has been reported. This allows for direct measurements in vivo whilst maintaining near normal placental conditions; however, there are practical and ethical implications in using this method for determination of placental oxygenation. Furthermore, oxygen levels are likely to be highly heterogeneous within the placenta. Emerging non‐invasive techniques, such as MRI, and ex vivo research are capable of enhancing and improving current imaging methodology for placental villous structure and increase the precision of oxygen measurement within placental compartments. These techniques, in combination with mathematical modelling, have stimulated novel cross‐disciplinary approaches that could advance our understanding of placental oxygenation and its metabolism in normal and pathological pregnancies, improving clinical treatment options and ultimately outcomes for the patient.
The impact of sperm protamine deficiency and sperm DNA damage on human male fertility: a systematic review and meta‐analysis

Existing literature suggests evidence that protamine deficiency is related to DNA damage and male fertility. In this meta‐analysis, we analyzed the relationship between the ratio of protamine‐1 and protamine‐2 with male fertility and the association of protamine deficiency with sperm DNA damage. Quality of available cohort studies was evaluated using the Newcastle–Ottawa Scale checklist. Summary effect estimates with 95% confidence intervals (CI) were derived using a random effects model. The effect of the protamine ratio on male fertility was analyzed in nine studies demonstrating a significantly higher value of the protamine ratio in subfertile men (n = 633) when compared with controls (n = 453, SMD = 0.46, 95% CI 0.25–0.66, Z = 4.42, p < 0.00001). Both protamine mRNA (SMD = 0.45, 95% CI 0.11–0.79, Z = 2.63, p = 0.009) and protein ratio (SMD = 0.46, 95% CI 0.25–0.68, Z = 4.22, p < 0.0001) showed significantly increased values in subfertile patients. The association between protamine deficiency and DNA damage was analyzed in 12 studies (n = 845) exhibiting a combined overall correlation coefficient (COR) of 0.53 (95% CI 0.28–0.71, Z = 3.87, p < 0.001). Protamine deficiency measured by CMA3 staining was significantly associated with sperm DNA damage (COR = 0.71, 95% CI 0.48–0.85, Z = 4.87, p < 0.001), whereas the P1/P2 ratio was not (COR = 0.17, 95% CI −0.16 to 0.46, Z = 0.99, p = 0.33). It is concluded that the protamine ratio represents a suitable biomarker for the assessment of sperm quality and protamine deficiency is closely related with sperm DNA damage.
Optimal Containment of Epidemics over Temporal Activity-Driven Networks

In this paper, we study the dynamics of epidemic processes taking place in temporal and adaptive networks. Building on the activity-driven network model, we propose an adaptive model of epidemic processes, where the network topology dynamically changes due to both exogenous factors independent of the epidemic dynamics as well as endogenous preventive measures adopted by individuals in response to the state of the infection. A direct analysis of the model using Markov processes involves the spectral analysis of a transition probability matrix whose size grows exponentially with the number of nodes. To overcome this limitation, we derive an upper-bound on the decay rate of the number of infected nodes in terms of the eigenvalues of a $2 \times 2$ matrix. Using this upper bound, we propose an efficient algorithm to tune the parameters describing the endogenous preventive measures in order to contain epidemics over time. We confirm our theoretical results via numerical simulations.
Physical exercise in the treatment of alcohol use disorder (AUD) patients affects their drinking habits: A randomized controlled trial

Aim: The aim of this study is to compare the effect of exercise training on physical capacity and alcohol consumption in alcohol use disorder (AUD) patients. Methods: One hundred and five AUD patients were randomly assigned to treatment as usual combined with running and brisk walking for 30–45 min twice a week, either in small supervised groups (GR) or individually (IND), or to a control group with no running (C). Assessments were made after 6 and 12 months of training. Results: Training volume was estimated as 36 min per training bout at an intensity of 78% of HRmax with no differences between GR and IND (p>.05). A highly significant reduction in training frequency was seen in both training groups after the first month (p<.0001). Only IND increased VO2max, by 5.7% (p<.05), while no differences were seen between GR, IND and C. Alcohol intake decreased from 219 to 41 units per 30 days as the average for the entire sample with no significant difference of drinking outcomes between groups (p<.0001). Conclusions: We saw an effect on drinking habits after running in both groups. However, no additional effect was seen when compared with the control group. A drop in the training frequency during the intervention might have resulted in an insignificant training stimulus.