Miracle-dz/UniFAR-FTUs huggingface dataset:
Alexithymia and Psychopathology in Patients Suffering From Inflammatory Bowel Disease: Arising Differences and Correlations to Tailoring Therapeutic Strategies

Comorbidity with anxiety or depression is common in patients with Inflammatory Bowel Disease (IBD) as Crohn Disease (CD) and Ulcerative Colitis (UC). Data suggest that the cognitive construct of alexithymia has high prevalence in people suffering from anxiety and mood disorders and even in people with IBD. Most studies have investigated mainly anxiety and depression, considering IBD population as a homogeneous group of patients. Little evidence shows the impact of alexithymia on the course of IBD. We evaluated a broad spectrum of psychopathological symptoms and alexithymia levels in a group of outpatients affected by IBD in clinical remission, comparing CD and UC and investigating the relationship with clinical and socio-demographic variables. One hundred and seventy IBD outpatients were screened by using the Hospital Anxiety Depression Scale (HADS), the Self-report Symptom Inventory-90-Revised (SCL-90-R) and the Toronto Alexithymia Scale (TAS-20). A high prevalence of anxious and depressive symptoms (42.35 and 25.8% respectively) together with alexithymia (31.76%) was confirmed. CD patients experienced high levels of depression (HADS Depression 35.2% p = 0.034; SCL-90-R mean 1.39 p < 0.001), somatisation (SCL-90-R mean 1.04 p < 0.001), obsessive-compulsive symptoms (SCL-90-R mean 1.2 p < 0.001), and global severity (SCL-90-R mean 1.15 p < 0.001). There is no statistical difference in the prevalence of alexithymia in both subpopulations. The levels of alexithymia are correlated to the levels of anxiety (HADS Anxiety rs = 0.516 p < 0.001), depression (HADS Depression rs = 0.556 p < 0.001; SCL-90-R rs = 0.274 p = 0.001), somatisation (SCL-90-R rs = 0.229 p = 0.005), obsessive-compulsive symptoms (SCL-90-R rs = 0.362 p < 0.001), and global severity (SCL-90-R rs = 0.265 p = 0.001). Furthermore, alexithymia is associated with a delay of diagnosis of IBD, poly-therapies and greater IBD extension. Older age, female gender, greater IBD extension, surgery, and delay of diagnosis seem to be related to a high prevalence of psychopathological symptoms such as anxiety, depression, somatisation, and obsessive-compulsive symptoms. Psychopathological symptoms and high levels of alexithymia are frequent in IBD patients and seem to be related to a high risk of poor clinical outcome. CD patients could be considered at higher risk of mental comorbidity. A more comprehensive psychiatric assessment, including alexithymia, and an integrated treatment of underlying conditions, must be taken into account in order to improve the global prognosis of the disease.
Arterial Spin-Labeling in Children with Brain Tumor: A Meta-Analysis

BACKGROUND: The value of arterial spin-labeling in a pediatric population has not been assessed in a meta-analysis. PURPOSE: Our aim was to assess the diagnostic accuracy of arterial spin-labeling–derived cerebral blood flow to discriminate low- and high-grade tumors. DATA SOURCES: MEDLINE, EMBASE, the Web of Science Core Collection, and the Cochrane Library were used. STUDY SELECTION: Pediatric patients with arterial spin-labeling MR imaging with verified neuropathologic diagnoses were included. DATA ANALYSIS: Relative CBF and absolute CBF and tumor grade were extracted, including sequence-specific information. Mean differences in CBF between low- and high-grade tumors were calculated. Study quality was assessed. DATA SYNTHESIS: Data were aggregated using the bivariate summary receiver operating characteristic curve model. Heterogeneity was explored with meta-regression and subgroup analyses. The study protocol was published at PROSPERO (CRD42017075055). Eight studies encompassing 286 pediatric patients were included. The mean differences in absolute CBF were 29.62 mL/min/100 g (95% CI, 10.43–48.82 mL/min/100 g), I2 = 74, P = . 002, and 1.34 mL/min/100 g (95% CI, 0.95–1.74 mL/min/100 g), P < . 001, I2 = 38 for relative CBF. Pooled sensitivity for relative CBF ranged from 0.75 to 0.90, and specificity, from 0.77 to 0.92 with an area under curve = 0.92. Meta-regression showed no moderating effect of sequence parameters TE, TR, acquisition time, or ROI method. LIMITATIONS: Included tumor types, analysis method, and original data varied among included studies. CONCLUSIONS: Arterial spin-labeling–derived CBF measures showed high diagnostic accuracy for discriminating low- and high-grade tumors in pediatric patients with brain tumors. The relative CBF showed less variation among studies than the absolute CBF.
Investigating accuracy of pitch-accent annotations in neural network-based speech synthesis and denoising effects

We investigated the impact of noisy linguistic features on the performance of a Japanese speech synthesis system based on neural network that uses WaveNet vocoder. We compared an ideal system that uses manually corrected linguistic features including phoneme and prosodic information in training and test sets against a few other systems that use corrupted linguistic features. Both subjective and objective results demonstrate that corrupted linguistic features, especially those in the test set, affected the ideal system's performance significantly in a statistical sense due to a mismatched condition between the training and test sets. Interestingly, while an utterance-level Turing test showed that listeners had a difficult time differentiating synthetic speech from natural speech, it further indicated that adding noise to the linguistic features in the training set can partially reduce the effect of the mismatch, regularize the model, and help the system perform better when linguistic features of the test set are noisy.
DNA hydroxymethylation mediated traumatic spinal injury by influencing cell death–related gene expression

Spinal cord injury (SCI) is a serious neurological disease, often leading to segmental injury following severe limb dysfunction. Recent studies showed that epigenetic regulation is involved in the pathogenesis of SCI. In this study, we examined the change in 5‐hydroxymethylcytosine (5hmC), a mechanism of demethylation, and its role in SCI in rats. We found that global 5hmC modification significantly increased in traumatic spinal cord tissues. Ten‐eleven translocation (Tet) enzymes are the limiting‐rate enzyme to catalyze the conversion of 5‐methylcytosine to 5hmC. In our study, the data indicated that Tet2, but not Tet1 and Tet3, significantly increased in traumatic spinal cord tissues. Further, we treated rats with SC‐1, a Tet2 expression inhibitor. SC‐1 increased necrotic volume after SCI. To further demonstrate that the damage caused by SC‐1 was related to DNA 5hmC, we examined the messenger RNA (mRNA) expression of many genes that related to cell death and cell survival. Our data showed that the 5hmC levels were related to the mRNA levels of these genes. In conclusion, targeting Tet2 to cause change in 5hmC levels in cell death–related genes may be new therapeutic strategy for the treatment of SCI.
Protein kinase Cε targets respiratory chain and mitochondrial membrane potential but not F0F1‐ATPase in renal cells injured by oxidant

We have previously shown that protein kinase Cε (PKCε) is involved in mitochondrial dysfunction in renal proximal tubular cells (RPTC). This study examined mitochondrial targets of active PKCε in RPTC injured by the model oxidant tert‐butyl hydroperoxide (TBHP). TBHP exposure augmented the levels of phosphorylated (active) PKCε in mitochondria, which suggested translocation of PKCε to mitochondria after oxidant exposure. Oxidant injury decreased state 3 respiration, adenosine triphosphate (ATP) production, ATP content, and complex I activity. Further, TBHP exposure increased ΔΨm and production of reactive oxygen species (ROS), and induced mitochondrial fragmentation and RPTC death. PKCε activation by overexpressing constitutively active PKCε exacerbated decreases in state 3 respiration, complex I activity, ATP content, and augmented RPTC death. In contrast, inhibition of PKCε by overexpressing dnPKCε mutant restored state 3 respiration, respiratory control ratio, complex I activity, ΔΨm, and ATP production and content, but did not prevent decreases in F0F1‐ATPase activity. Inhibition of PKCε prevented oxidant‐induced production of ROS and mitochondrial fragmentation, and reduced RPTC death. We conclude that activation of PKCε mediates: (a) oxidant‐induced changes in ΔΨm, decreases in mitochondrial respiration, complex I activity, and ATP content; (b) mitochondrial fragmentation; and (c) RPTC death. In contrast, oxidant‐induced inhibition of F0F1‐ATPase activity is not mediated by PKCε. These results show that, in contrast to the protective effects of PKCε in the heart, PKCε activation is detrimental to mitochondrial function and viability in RPTC and mediates oxidant‐induced injury.
Changing the Approach to Anticoagulant Therapy in Older Patients with Multimorbidity Using a Precision Medicine Approach

The ageing of the world population has resulted in an increase in the number of older patients with multimorbid conditions receiving multiple therapies. This emerging clinical scenario poses new challenges, which are mostly related to the increased incidence of adverse effects. This translates into poor clinical care, reduced cost-effectiveness of drug therapies, and social isolation of multimorbid patients due to reduced autonomy. A strategy to address these emerging challenges could involve the personalization of therapies based on the clinical, molecular, and genetic characterization of multimorbid patients. Anticoagulation therapy is a feasible model to implement personalized medicine since it generally involves older multimorbid patients receiving multiple drugs. In this study, in patients with atrial fibrillation, the use of the new generation of anticoagulation therapy, i.e., direct oral anti-coagulants (DOACs), is based on a preliminary assessment of the molecular targets of DOACS and any possible drug–drug interactions. Then, the genetic polymorphism of enzymes metabolizing DOACs is studied. After DOAC prescription, its circulating levels are measured. Clinical data are being collected to assess whether this personalized approach improves the safety and efficacy profiles of anticoagulation therapy using DOACs, thereby reducing the costs of healthcare for ageing multimorbid patients.
Genome-Wide Identification and Characterization of NODULE-INCEPTION-Like Protein (NLP) Family Genes in Brassica napus

NODULE-INCEPTION-like proteins (NLPs) are conserved, plant-specific transcription factors that play crucial roles in responses to nitrogen deficiency. However, the evolutionary relationships and characteristics of NLP family genes in Brassica napus are unclear. In this study, we identified 31 NLP genes in B. napus, including 16 genes located in the A subgenome and 15 in the C subgenome. Subcellular localization predictions indicated that most BnaNLP proteins are localized to the nucleus. Phylogenetic analysis suggested that the NLP gene family could be divided into three groups and that at least three ancient copies of NLP genes existed in the ancestor of both monocots and dicots prior to their divergence. The ancestor of group III NLP genes may have experienced duplication more than once in the Brassicaceae species. Three-dimensional structural analysis suggested that 14 amino acids in BnaNLP7-1 protein are involved in DNA binding, whereas no binding sites were identified in the two RWP-RK and PB1 domains conserved in BnaNLP proteins. Expression profile analysis indicated that BnaNLP genes are expressed in most organs but tend to be highly expressed in a single organ. For example, BnaNLP6 subfamily members are primarily expressed in roots, while the four BnaNLP7 subfamily members are highly expressed in leaves. BnaNLP genes also showed different expression patterns in response to nitrogen-deficient conditions. Under nitrogen deficiency, all members of the BnaNLP1/4/5/9 subfamilies were upregulated, all BnaNLP2/6 subfamily members were downregulated, and BnaNLP7/8 subfamily members showed various expression patterns in different organs. These results provide a comprehensive evolutionary history of NLP genes in B. napus, and insight into the biological functions of BnaNLP genes in response to nitrogen deficiency.
Exploiting Clustering Manifold Structure for Hyperspectral Imagery Super-Resolution

Fusing a low-resolution hyperspectral image (HSI) with a high-resolution (HR) conventional image into an HR HSI has become a prevalent HSIs super-resolution scheme. However, in most previous works, little attention has been paid on exploiting the underlying manifold structure in the spatial domain of the latent HR HSI. In this paper, we advance a provable prior knowledge that the clustering manifold structure of the latent HSI can be well preserved in the spatial domain of the input conventional image. Inspired by this, we first conduct clustering in the spatial domain of the input conventional image and adopt the intra-cluster self-expressiveness model to implicitly depict the clustering manifold structure, which enables learning the complicated manifold structure via solving a constrained ridge regression model without knowing the exact form of the manifold. Then, we incorporate the learned structure into a variational super-resolution framework to regularize the latent HSI. The resulted framework can be effectively optimized by a standard alternating direction method of multipliers. Since the learned structure can well depict the underlying spatial manifold of the latent HSI, the proposed method shows the state-of-the-art super-resolution performance on two benchmark data sets.
Work-In-Progress: DEEC-VD: A Hybrid Energy Utilization Cluster-Based Routing Protocol for WSN for Application in IoT

The Internet of Things(IoT) is an integration of the existing and evolving Internet with future network developments such as self-configuring capabilities and enhanced network lifetime with proper power management to create an intelligent network that can be sensed, controlled and programmed. Due to multi-hop communication, cluster-based routing protocols become an essential step in designing any IoT network. Distributed Energy Efficient Clustering (DEEC) is one of the cluster- based hierarchical routing protocols which are used for the heterogeneous networks in WSN. The proposed technique DEEC-VD not only uses cluster and active cluster head forming with the help of vector quantization but also it uses Dijkstra Algorithm to find the shortest path between the active cluster heads (CHs) to provide high energy utilization. DEEC-V provides the intra -cluster communication between the cluster head and using Dijkstra's Algorithm, the minimum distance is calculated connecting the active cluster heads which create the shortest path results in energy efficient technique. From simulation result, it has been found that after implementing the proposed technique, the average energy utilization of the network has increased to almost 60%.
Broken dreams of a better life in Sweden: Thai women’s lived experiences of intimate partner violence by Swedish men in international marriages

ABSTRACT Background: Intimate partner violence by men against women has detrimental effects on equality, health and integration. Migrated and ‘imported’ wives experience an increased risk of intimate partner violence. Objectives: The purpose of this study was to explore Thai immigrant women’s lived experiences of intimate partner violence in Sweden. Method: Semi-structured interviews based on the critical incident technique with specific questions about experiences of male-to-female intimate partner violence were used to collect data. The participants were Thai immigrant women who had lived in Sweden for more than five years. Qualitative content analysis was used to identify patterns and variations in the transcribed data material. Results: Eighteen interviewees reported psychological, physical, economic and/or sexual violence in their international marriages. These Thai women described being faithful and silent and reliable housewives. However, this did not keep them from being replaced and losing dignity as a result of intimate partner violence, including experiencing broken dreams and deception. Although their dreams were broken, they did not give up their efforts to achieve better lives in Sweden. Conclusions: The vulnerability of imported wives in international marriages needs to be further recognised by health and welfare agencies in Sweden, as elsewhere, to ensure that these women have equal access to human rights, welfare and health as other citizens. From a health promotion perspective, home-based health check-ups are needed to stop the exploitation of imported wives. In Thailand, information and education about the unrecognised negative conditions of the Mia farang role (Imported wife role) need to be disseminated.
Macrophage Markers Are Poorly Associated With Liver Histology in Children With Nonalcoholic Fatty Liver Disease

Objectives: We have previously demonstrated associations between the macrophage activation marker soluble (s)CD163 and histology of nonalcoholic fatty liver disease (NAFLD) in adults, and elevated sCD163 levels in children with obesity with NAFLD. Macrophage activation has, however, not been investigated in children with biopsy-proven NAFLD, which was the objective of the present study. Methods: We used in-house enzyme-linked immunosorbent assays to measure sCD163 and the novel macrophage marker soluble mannose receptor (sMR) in a cross-sectional (n = 155) pediatric NAFLD cohort, and a cohort of NAFLD children (n = 36) undergoing a randomized trial by the probiotic VSL#3. We included 56 healthy nonobese children for comparison. Results: Levels of sCD163 and sMR were higher in both of the NAFLD cohorts compared with controls (P < 0.001). In the cross-sectional cohort, sCD163 only showed trends toward association with ballooning (rho = 0.14, P = 0.08) and portal inflammation (rho = 0.17, P = 0.08). sMR showed similar associations with liver histology. In the VSL#3 cohort, sCD163 correlated inversely with steatosis (rho = −0.35, P = 0.04), and lobular (rho = −0.57, P < 0.001) and portal inflammation (rho = −0.38, P = 0.02); sMR was not associated with any histological scores. Neither sCD163 nor sMR changed significantly during intervention, and without association with NAFLD resolution. Conclusions: The macrophage activation markers sCD163 and sMR showed poor associations with liver histology in 2 different cohorts of children with biopsy-proven NAFLD, and none of the markers decreased during successful intervention. These results are in contrast with studies of adult NAFLD and may suggest a possibility of different roles for macrophages in the pathogenesis of adult and pediatric NAFLD.
Impacts of demographic and laboratory parameters on key hematological indices in an adult population of southern Taiwan: A cohort study

Studies in Caucasians have shown that values of hematological indices could be affected by a wide variety of factors. However, parallel work in other ethnical populations, particularly from the Asia-Pacific region, is lacking. Therefore, we designed this study to explore the association between clinical/laboratory parameters and hemogram levels. Adult individuals who came to our hospital for health exams were screened. Information on demographics and laboratory profiles was obtained. We analyzed the impacts of these parameters on the variation of hemogram. Overall, 26,497 adults were included in the current analysis after excluding those with abnormal hemogram. Multivariate regression analysis showed increasing age and male gender negatively affected the number of platelets, whereas a higher serum apolipoprotein B level was associated with an elevated platelet count. Gender and serum albumin level were the major determinants of variation in hemoglobin level. A modestly increased white cell count was seen in men as well as individuals with elevated apolipoprotein B levels, but it was inversely correlated with changes in age and serum albumin levels. Conversely, some variables, although statistically significantly associated with the hematological indices, only provided a trivial explanation for the heterogeneity observed. We further established predictive models for the approximate estimation of hematological indices in healthy adults. Our data indicate that age, gender, and serum levels of apolipoprotein B and albumin affect hematological indices in various ways. We also demonstrate that variation in hemogram could be successfully predicted by a number of clinical and laboratory parameters.
Neural Arithmetic Logic Units

Neural networks can learn to represent and manipulate numerical information, but they seldom generalize well outside of the range of numerical values encountered during training. To encourage more systematic numerical extrapolation, we propose an architecture that represents numerical quantities as linear activations which are manipulated using primitive arithmetic operators, controlled by learned gates. We call this module a neural arithmetic logic unit (NALU), by analogy to the arithmetic logic unit in traditional processors. Experiments show that NALU-enhanced neural networks can learn to track time, perform arithmetic over images of numbers, translate numerical language into real-valued scalars, execute computer code, and count objects in images. In contrast to conventional architectures, we obtain substantially better generalization both inside and outside of the range of numerical values encountered during training, often extrapolating orders of magnitude beyond trained numerical ranges.
Metric Driven Classification: A Non-Parametric Approach Based on the Henze–Penrose Test Statistic

Entropy-based divergence measures have proven their effectiveness in many areas of computer vision and pattern recognition. However, the complexity of their implementation might be prohibitive in resource-limited applications, as they require estimates of probability densities which are expensive to compute directly for high-dimensional data. In this paper, we investigate the usage of a non-parametric distribution-free metric, known as the Henze–Penrose test statistic to obtain bounds for the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-nearest neighbors (<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-NN) classification accuracy. Simulation results demonstrate the effectiveness and the reliability of this metric in estimating the inter-class separability. In addition, the proposed bounds on the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-NN classification are exploited for evaluating the efficacy of different pre-processing techniques as well as selecting the least number of features that would achieve the desired classification performance.
The Quest for the Golden Activation Function

Deep Neural Networks have been shown to be beneficial for a variety of tasks, in particular allowing for end-to-end learning and reducing the requirement for manual design decisions. However, still many parameters have to be chosen in advance, also raising the need to optimize them. One important, but often ignored system parameter is the selection of a proper activation function. Thus, in this paper we target to demonstrate the importance of activation functions in general and show that for different tasks different activation functions might be meaningful. To avoid the manual design or selection of activation functions, we build on the idea of genetic algorithms to learn the best activation function for a given task. In addition, we introduce two new activation functions, ELiSH and HardELiSH, which can easily be incorporated in our framework. In this way, we demonstrate for three different image classification benchmarks that different activation functions are learned, also showing improved results compared to typically used baselines.