Miracle-dz/UniFAR-FTUs huggingface dataset:
Burned Adults Develop Profound Glucose Intolerance

Objectives:Metabolic alterations after burn injury have been well described in children; however, in adult patients, glucose metabolism and insulin sensitivity are essentially unknown. We sought to characterize metabolic alterations and insulin resistance after burn injury and determine their magnitude and persistence at discharge. Design:Prospective, cohort study. Setting:Tertiary burn centre. Patients:Nondiabetic adults with an acute burn involving greater than or equal to 20% total body surface area. Interventions:An oral glucose tolerance test was administered at discharge. Measurements and Main Results:Glucose, insulin, and C-peptide levels were measured to derive surrogate measures of insulin resistance and &bgr;-cell function, including quantitative insulin sensitivity check index, homeostasis model assessment of &bgr;-cell function, homeostasis model assessment of insulin sensitivity, homeostasis model assessment of insulin resistance, and the composite whole-body insulin sensitivity index. Patients were grouped according to the degree of glucose tolerance: normal glucose tolerance, impaired fasting glucose/impaired glucose tolerance, or diabetes. Forty-five adults, 44 ± 15 years old and with 38% ± 14% total body surface area burned, underwent an oral glucose tolerance test at discharge. Median quantitative insulin sensitivity check index (0.348 [0.332–0.375]) and median homeostasis model assessment of insulin resistance (1.13 [0.69–1.45]) were abnormal, indicating insulin resistance and impaired insulin production at discharge. Two-thirds of patients (n = 28) met criteria for impaired fasting glucose/impaired glucose tolerance or diabetes. Conclusions:We have demonstrated that burn-injured adults remain hyperglycemic, are insulin resistant, and express defects in insulin secretion at discharge. Patients with lower burn severity (total body surface area, 20–30%) express similar metabolic alterations as patients with larger burns (total body surface area, ≥ 30%). Glucose tolerance testing at discharge offers an opportunity for early identification of burn patients who may be at high risk of prediabetes and diabetes. Our findings demonstrated that two-thirds of burn patients had some degree of glucose intolerance. With this in mind, surveillance of glucose intolerance post discharge should be considered. As hyperglycemia and insulin resistance are associated with poor outcomes, studies should focus on how long these profound alterations persist.
Time-Varying Network Models of Neurodegenerative Disease Spread in Biological Neural Networks

— Although some cognitive decline over time is considered normal, neurodegenerative diseases such as dementia can exacerbate loss of memory and physical functionality, and even lead to death, especially within the elderly population. Currently, clinical understanding of these types of diseases is limited by inadequate knowledge of how they progress throughout the brain. Emerging studies show that the spreading and buildup of beta-amyloid proteins in certain grey matter regions of the brain could be a possible indicator of disease progression, specifically in Alzheimer's. In order to address a debate on the method of protein spreading, we created two dynamic spreading models that could predict the progression of Alzheimer's disease by looking at the brain as a network throughout which proteins can spread along varying pathways. The hope is that these models will predict the progress of neurodegeneration throughout the brain network of people diagnosed with Alzheimer's and perhaps identify the underlying process for protein spreading. Future studies into the buildup of proteins that affect grey matter density could use this model to target the specific areas for intervention with potential treatments. Our model could also be applied to the spreading processes of other diseases and be used to help patients and families better understand and prepare for the progression of their illness. INTRODUCTION As mapping of nervous systems becomes easier and more feasible, many questions arise about the network structure of neurons in the brain and information flow within this network. Therefore, neural network modeling and analysis has become a more prominently researched topic. This has also become an interdisciplinary field, bringing together computer science and medicine in order to predict, analyze, and interpret the effects on disease on the human brain. Those diseases that are particularly interesting to network analysts are those that affect the structure and functionality of the biological neural network including dementia and multiple sclerosis. Approximately 25 million people worldwide suffer from dementia [1]; therefore, it is a prominent disease worthy of the research directed at reducing its impact on our population.
Sexual minority and depression: The moderating role of parental support

5 Útdráttur . 5 Method . 9 Participants . 9 Instruments and Measures . 9 Procedure . 11 Statistical analysis . 11 Results . 12 Discussion . 16 References . 21 Appendix A . 25 SEXUAL MINORITY, DEPRESSION AND PARENTAL SUPPORT 4 Tables Table 1. Descriptive statistics . 12 Table 2. Descriptive statistics showing mean levels of depressed mood, standard deviation and number in each category, by parental support and same-sex sexual attraction . 13 Table 3. Pearson r bivariate correlations for all variables used in the study . 14 Table 4. Test of between-subjects effect with depressed mood as dependent variable . 15 Figures Figure 1. Estimated marginal means for depressed mood by same sex sexual attraction and parental support. 15
Multisensory Stimulation on Mood, Behavior, and Biomedical Parameters in People With Dementia

The purpose of this study was to assess the effects of multisensory stimulation in a multisensory stimulation environment (MSSE) such as a Snoezelen room versus one-to-one activity sessions with regard to mood, behavior, and biomedical parameters (heart rate and blood oxygen saturation). The MSSE group and activity group (one-to-one activities) of patients with dementia participated in 2 weekly individualized intervention sessions over 16 weeks, where mood and behavior before, during, and after the sessions, and biomedical parameters immediately before and after, were recorded. Immediately after the sessions, patients spoke more spontaneously, related better to others, were more attentive to their environments, more active/alert, less bored/inactive, and more relaxed/content. Both groups exhibited decreases in heart rate and increases in oxygen saturation (Spo 2) values from before to after the sessions. The MSSE sessions in a Snoezelen room were found to be as effective as activity sessions, highlighting the importance of the one-to-one interaction with the therapist.
Substrate specificities of peroxisomal members of short-chain alcohol dehydrogenase superfamily: expression and characterization of dehydrogenase part of Candida tropicalis multifunctional enzyme.

In addition to several other enzymes, the short-chain alcohol dehydrogenase superfamily includes a group of peroxisomal multifunctional enzymes involved in fatty acid and cholesterol side-chain beta-oxidation. Mammalian peroxisomal multifunctional enzyme type 2 (perMFE-2) is a 2-enoyl-CoA hydratase-2/(R)-3-hydroxyacyl-CoA dehydrogenase. As has been shown previously, perMFE-2 hydrates (24E)-3alpha,7alpha, 12alpha-trihydroxy-5beta-cholest-24-enoyl-CoA to (24R, 25R)-3alpha, 7alpha,12alpha,24xi-tetrahydroxy-5beta-choles tanoyl-CoA, which has been characterized as a physiological intermediate in cholic acid synthesis. Out of four possible stereoisomers of 3alpha,7alpha, 12alpha,24xi-tetrahydroxy-5beta-cholestanoyl-CoA , the mammalian perMFE-2 dehydrogenates only the (24R,25R)-isomer. The yeast peroxisomal multifunctional enzyme (MFE) was first described as 2-enoyl-CoA hydratase-2/(R)-3-hydroxyacyl-CoA dehydrogenase. To investigate the stereospecificity of yeast peroxisomal MFE, the two dehydrogenase domains of C. tropicalis MFE were expressed in E. coli as a 65 kDa recombinant protein. This protein catalyzes the dehydrogenation of straight-chain (R)-3-hydroxyacyl-CoAs, but it is devoid of (S)-3-hydroxyacyl-CoA dehydrogenase and 2-enoyl-CoA hydratase activities. The protein dehydrogenates (24R,25R)- and (24R, 25S)-isomers of 3alpha,7alpha, 12alpha, 24xi-tetrahydroxy-5beta-cholestanoyl-CoA. Interestingly, the protein also shows 17beta-estradiol dehydrogenase activity. As a monofunctional (R)-specific 3-hydroxyacyl-CoA dehydrogenase is currently unavailable, this recombinant enzyme can be used to study the stereochemistry of bile acid synthesis.
Intersection of Geospatial Information and Information Technology Content and Knowledge Distillation Data mining and knowledge discovery in the geographical domain

Despite enormous efforts in quantification, our understanding of many of the Earth’s systems remains non-axiomatic; the systems are ‘open’ and consequently it is not possible to deduce all outcomes from known laws. Science must therefore adopt a manner that encourages the creation or uncovering of new knowledge (Baker, 1999; Takatsuka & Gahegan, 2001). For this reason aloneand completely uncoupled from concerns about increasing data volumesit is vital that knowledge discovery methods can be brought successfully to bear across the geosciences.
A Mathematical Introduction to Deep Reinforcement Learning for 5G/6G Applications

Algorithmic innovation can unleash the potential of the beyond 5G (B5G)/6G communication systems. Artificial intelligence (AI)-driven zero-touch network slicing is envisaged as a promising cutting-edge technology to harness the full potential of heterogeneous 6G networks and enable the automation of demand-aware management and orchestration (MANO). The network slicing continues towards numerous slices with micro or macro services in 6G networks, and thereby, designing a robust, stable, and distributed learning mechanism is considered a necessity. In this regard, robust brain-inspired and dopamine-like learning methods, such as Actor-Critic approaches, can play a vital role. The tutorial begins with an introduction to network slicing, reinforcement learning (RL), and recent state-of-the-art (SoA) algorithms. Then, the paper elaborates on the combination of value-based and policy-based methods in the form of Actor-Critic techniques tailored to the needs of future wireless networks.
Il Design di WiRoni: hardware, software e interfaccia utente

In questo articolo presentiamo il progetto WiRoni, che affronta il design tecnologico di artefatti che permettono di accedere ai contenuti Internet in uno spazio pubblico attraverso delle interazioni naturali. Per fare questo abbiamo utilizzato tre tecnologie abilitanti: sensori a ultrasuoni, MEMS e mash-up di applicazioni Internet. Queste tecnologie sono state scelte in base alla natura dell’attivita umana, e non viceversa, permettendo un’interazione il piu possibile naturale e legata al luogo e all’attivita svolta dall’utente. I concetti sui quali il progetto si basa sono Ubiquitous Computing, Tangible User Interface, Pervasive Computing, e Internet of Things, questi vanno tutti nella stessa direzione, cioe che i computer, telefoni e console di gioco non sono piu gli unici dispositivi nel nostro ambiente che hanno potenza di calcolo e che offrono la possibilita di essere connessi alla rete Internet. Nell’articolo saranno presentate le scelte tecnologie, che sono alla base del progetto e del concetto delle fontane, che permettono di gestire i servizi legati a WiRoni.
Cognitive Specificity in Trait Anger in Relation to Depression and Anxiety in a Community Sample

The current research explored 16 of Young's schemas in relation to trait anger and to anxiety and depression symptoms among 262 non‐clinical Australian adults with low‐level symptomatology and average anger levels. The study partially replicated previous work with a sample of Spanish students that investigated the relationship between anger, depression, and anxiety and Young's schemas. Predictions derived from Beck's notion of cognitive specificity were examined using structural equation modelling and showed that of the sixteen schemas, Vulnerability was linked to anxiety, Social Isolation and Enmeshment were linked to depression, and Entitlement, Insufficient Self‐Control, Mistrust and Abuse, Subjugation (negatively), and Abandonment were linked to anger. The discrepancies between these and the Spanish findings and the difficulties of other researchers in establishing higher order aggregations of Young's schemas prompted further consideration of the range of such schemas with respect to anger, depression, and anxiety, and the possibility that sample characteristics may play a critical role in determining the varying affect—schema relationships.
Cover's Algorithm Modified for Nonparametric Estimation of a Log-Optimal Portfolio Selection Function

Cover's algorithm yields an iterative portfolio choice for maximizing expected log investment return where the distribution function of the stock market vector is known. In the case that the stock market vectors form a stationary ergodic sequence with unknown distribution, by stochastic approximation and nonparametric regression estimation the algorithm is modified for iterative estimation of a log-optimal portfolio selection function of the last observed vectors (fixed d ∈ ℕ) on the basis of an observed training sequence of vectors. Under a boundedness and a mild -mixing condition, a strong consistency result is established.
Improving $\Lambda$ Signal Extraction with Domain Adaptation via Normalizing Flows

The present study presents a novel application for normalizing flows for domain adaptation. The study investigates the ability of flow based neural networks to improve signal extraction of $\Lambda$ Hyperons at CLAS12. Normalizing Flows can help model complex probability density functions that describe physics processes, enabling uses such as event generation. $\Lambda$ signal extraction has been improved through the use of classifier networks, but differences in simulation and data domains limit classifier performance; this study utilizes the flows for domain adaptation between Monte Carlo simulation and data. We were successful in training a flow network to transform between the latent physics space and a normal distribution. We also found that applying the flows lessened the dependence of the figure of merit on the cut on the classifier output, meaning that there was a broader range where the cut results in a similar figure of merit.
Human Umbilical Cord Blood Cells Restore Brain Damage Induced Changes in Rat Somatosensory Cortex

Intraperitoneal transplantation of human umbilical cord blood (hUCB) cells has been shown to reduce sensorimotor deficits after hypoxic ischemic brain injury in neonatal rats. However, the neuronal correlate of the functional recovery and how such a treatment enforces plastic remodelling at the level of neural processing remains elusive. Here we show by in-vivo recordings that hUCB cells have the capability of ameliorating the injury-related impairment of neural processing in primary somatosensory cortex. Intact cortical processing depends on a delicate balance of inhibitory and excitatory transmission, which is disturbed after injury. We found that the dimensions of cortical maps and receptive fields, which are significantly altered after injury, were largely restored. Additionally, the lesion induced hyperexcitability was no longer observed in hUCB treated animals as indicated by a paired-pulse behaviour resembling that observed in control animals. The beneficial effects on cortical processing were reflected in an almost complete recovery of sensorimotor behaviour. Our results demonstrate that hUCB cells reinstall the way central neurons process information by normalizing inhibitory and excitatory processes. We propose that the intermediate level of cortical processing will become relevant as a new stage to investigate efficacy and mechanisms of cell therapy in the treatment of brain injury.
New isoforms of VEGF are translated from alternative initiation CUG codons located in its 5'UTR.

Vascular endothelial growth factor (VEGF) has a central role in normal as well as in tumor angiogenesis. As such, VEGF is subjected to multi-level regulation at the transcriptional, post-transcriptional, translational, and post-translational levels to ensure proper expression during embryogenesis and adulthood. Its mRNA contains an exceptionally long (1038 bp) 5' untranslated region (5'UTR), which has a role in transcriptional as well as translational regulation of VEGF expression. In this communication, we provide new evidence showing that an open reading frame (ORF) present in the 5'UTR encodes for new putative isoforms of VEGF due to alternative translational initiation from CUG codons. Like VEGF, the translation of the new isoforms is not sensitive to stress signals such as anoxia. Most likely, these isoforms either possess new capabilities, which are different from the activity of the classical VEGF isoforms, or affect the efficiency and capacity of translational initiation from the canonical AUG codon.
Genome-Wide Identification, Phylogeny and Expression Profile of Vesicle Fusion Components in Verticillium dahliae

Vesicular trafficking plays a crucial role in protein localization and movement, signal transduction, and multiple developmental processes in eukaryotic cells. Vesicle fusion is the final and key step in vesicle-mediated trafficking and mainly relies on SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors), the regulators including SM (Sec1/Munc18) family proteins, Rab GTPases and exocyst subunits. Verticillium dahliae is a widespread soil fungus that causes disruptive vascular diseases on a wide range of plants. To date, no genes involved in vesicular fusion process have been identified and characterized in V. dahliae. The recent publication of the draft genome sequence of V. dahliae allowed us to conduct a genome-wide identification, phylogeny and expression profile of genes encoding vesicular fusion components. Using compared genomics and phylogenetic methods, we identified 44 genes encoding vesicle fusion components in the V. dahliae genome. According to the structural features of their encoded proteins, the 44 V. dahliae genes were classified into 22 SNAREs (6 Qa-, 4 Qb-, 6 Qc-, 1 Qbc- and 5 R-types), 4 SM family proteins, 10 Rab GTPases and 8 exocyst proteins. Based on phylogeny and motif constitution analysis, orthologs of vesicle fusion component in filamentous fungi were generally clustered together into the same subclasses with well-supported bootstrap values. Analysis of the expression profiles of these genes indicated that many of them are significantly differentially expressed during vegetative growth and microsclerotia formation in V. dahliae. The analysis show that many components of vesicle fusion are well conserved in filamentous fungi and indicate that vesicle fusion plays a critical role in microsclerotia formation of smoke tree wilt fungus V. dahliae. The genome-wide identification and expression analysis of components involved in vesicle fusion should facilitate research in this gene family and give new insights toward elucidating their functions in growth, development and pathogenesis of V. dahliae.
Modeling Earnings Dynamics

In this paper we use generalized indirect inference to estimate a joint model of earnings, employment, job changes, wage rates, and work hours over a career. Our model incorporates state and duration dependence in several variables, multiple sources of unobserved hetero-geneity, job-speci…c error components in both wages and hours, and measurement error. We provide estimates of the dynamic response of wage rates, hours, and earnings to various shocks, and measure the relative contributions of the shocks to the variance of earnings in a given year and over a lifetime. Shocks associated with job changes make a large contribution to the variance of career earnings and operate mostly through the job-speci…c error components in wages and hours. Unemployment shocks also make a large contribution and operate mostly through long-term e¤ects on the wage rate.
Haemodynamics in microvascular complications in type 1 diabetes

Type 1 diabetes is commonly associated with microvascular complications. Most of the microvascular blood vessels are involved but those in the kidney, retina and large nerves exhibit the more significant pathology. Haemodynamic and metabolic factors both alone and through the activation of a common pathway contribute to the characteristic dysfunction observed in diabetic vasculopathy. The haemodynamic abnormalities in type 1 diabetes are characterized by increased systemic blood pressure and altered blood flow with subsequent activation of various vasoactive factors, which can contribute to the maintenance of the haemodynamic alterations and to the development and progression of the microvascular complications. These vasoactive factors include vasoconstrictors such as angiotensin II, and endothelin, as well as vasodilators such as nitric oxide (NO). Systemic hypertension and vasoactive factors independently and in interaction with the metabolic pathway activate intracellular second messengers, nuclear transcription factors and various growth factors which lead to the typical functional and structural alterations of diabetic microvascular complications. Therapeutic strategies involved in the management and prevention of diabetic complications currently include antihypertensive agents, particularly those that interrupt the renin–angiotensin system. Further understanding of the interactions among the vasoactive factors, the intracellular second messengers and the growth factors may help to identify novel strategies to influence the action of the vasoactive factors. These novel therapies, together with specific inhibitors of the metabolic pathway or the common pathway, may provide the possibility of preventing or even reversing the progression of diabetic microvascular complications. Copyright © 2002 John Wiley & Sons, Ltd.
Anaesthesia of the posterior urethra and pain reduction during cystoscopy – a randomized controlled trial

Introduction Standard intra-urethral instillation of anaesthetic gel may not sufficiently exclude pain perception during cystoscopy. Aim To evaluate the impact of the anaesthesia within the posterior urethra on pain intensity related to cystoscopy in men. Material and methods One hundred and twenty-seven men undergoing cystoscopy were prospectively enrolled in the study. Patients were randomly assigned to the experimental or control group (66 vs. 61 patients). Intra-urethral instillation of 2% lidocaine gel was done in both groups. In the experimental group, the posterior urethra was additionally anaesthetized with distribution of the lidocaine gel by catheterisation. The study endpoints were pain intensity at successive time points of the procedure assessed on a numeric rating scale, overall pain intensity assessed on a Likert scale, the need for analgesics during 6 h after the procedure, and the frequency of urinary tract infections (UTIs) during 14 days after the procedure. Results Pain perception during cystoscopy did not differ significantly between the two groups (p > 0.05). However, after 6 h patients in the experimental group were more likely to declare that the cystoscopy was painless (81.8% vs. 70.2%, relative risk = 1.17). The need for analgesics and the incidence of UTI were similar in both groups (p > 0.05). Statistically significant differences regarding pain perception were observed depending on patients’ age and the number of transurethral procedures performed in the past, with no relation to type of anaesthesia (p < 0.05). Conclusions Anaesthesia of the posterior urethra is not more efficacious in reducing pain related to cystoscopy than standard instillation of anaesthetic gel. However, it improves the general perception of the procedure, and hence may positively influence patients’ compliance.