Miracle-dz/UniFAR-FTUs huggingface dataset:
The heterogeneity of “major depression”

World Psychiatry 10:3 October 2011 The concept of major depression, in both the ICD and the DSM, has been a flagship for mental health in general medical settings. It is the principal mental disorder emphasized to general practitioners and hospital doctors, and it has been used by governments to raise awareness of mental health issues in the population at large and in the medical community (1-3). It has encouraged the development of specialized forms of psychotherapy for depression, it has allowed the formation of community groups to propagate accurate information about depression, and has led to the development of computer programmes to assist self-treatment using the principles of cognitive-behavioural therapy (4,5). These are substantial achievements, but they come at a price. This is the belief that “major depression” is a homogeneous entity, and indeed that it is usually a “major” disorder. The DSM diagnosis of major depression is made when a patient has any 5 out of 9 symptoms, several of which are opposites. Thus, a patient who has psychomotor retardation, hypersomnia and gaining weight is scored as having identical symptoms as another who is agitated, sleeping badly and has weight loss. This causes real problems with research designs: for example, Lux and Kendler (6) had to group these opposite symptoms together. Even so, it was possible for them to distinguish between “cognitive” and “neurovegetative” symptoms, and show that these have different relationships to a larger set of potential validators. They concluded that their results “challenge our understanding of major depression as a homogeneous categorical entity”. Others have been able to separate the various depressive symptoms, and to compare the relative efficiency of each symptom to making the diagnosis (7). Jang et al (8) factor analysed a larger set of depressive symptom scales, and found that they could identify 14 different subscales, which had rather low intercorrelations, and very different heritabilities. Given these findings, to declare that all those satisfying the DSM criteria for the diagnosis of major depression are suffering from the same disorder seems like magical thinking. We know that many milder cases remit without specific treatment, suggesting that they are indeed homeostatic responses to life stress (9). Depression may be a toxic reaction to drugs or may result from endocrine disorders such as myxoedema or Cushing’s syndrome. The depressed phase of bipolar illness may be difficult or impossible to distinguish from unipolar depression. Melancholic, atypical and psychotic forms of depression are yet other variants. Agitated depression needs to be distinguished from retarded depression when choosing the most suitable antidepressant. But even with these exclusions, there are five other forms of maThe heterogeneity of “major depression” PERSPECTIVE
2016 Ieee International Conference on Big Data (big Data) Improving Item-based Recommendation Accuracy with User's Preferences on Apache Mahout

—Recommendation systems play a critical role in the Information Science application domain, especially in e-commerce ecosystems. In almost all recommender systems, statistical methods and machine learning techniques are used to recommend items to the users. Although the user-based col-laborative filtering approaches have been applied successfully in many different domains, some serious challenges remain especially in regards to large e-commerce sites, for recommender systems need to manage millions of users and millions of catalog products. In particular, the need to scan a vast number of potential neighbors makes it very hard to compute predictions. Many researchers have been trying to come up with solutions like using neighborhood-based collaborative filtering algorithms, model-based collaborative filtering algorithms, and text mining algorithms. Others have proposed new methods or have built various architectures/frameworks. In this paper, we proposed a new data model based on users'preferences to improve item-based recommendation accuracy by using the Apache Mahout library. We also present details of the implementation of this model on a dataset taken from Amazon. Our experimental results indicate that the proposed model can achieve appreciable improvements in terms of recommendation quality.
Heme Oxygenase-1 Inhibits HLA Class I Antibody-Dependent Endothelial Cell Activation

Antibody-mediated rejection (AMR) is a key limiting factor for long-term graft survival in solid organ transplantation. Human leukocyte antigen (HLA) class I (HLA I) antibodies (Abs) play a major role in the pathogenesis of AMR via their interactions with HLA molecules on vascular endothelial cells (ECs). The antioxidant enzyme heme oxygenase (HO)-1 has anti-inflammatory functions in the endothelium. As complement-independent effects of HLA I Abs can activate ECs, it was the goal of the current study to investigate the role of HO-1 on activation of human ECs by HLA I Abs. In cell cultures of various primary human macro- and microvascular ECs treatment with monoclonal pan- and allele-specific HLA I Abs up-regulated the expression of inducible proinflammatory adhesion molecules and chemokines (vascular cell adhesion molecule-1 [VCAM-1], intercellular cell adhesion molecule-1 [ICAM-1], interleukin-8 [IL-8] and monocyte chemotactic protein 1 [MCP-1]). Pharmacological induction of HO-1 with cobalt-protoporphyrin IX reduced, whereas inhibition of HO-1 with either zinc-protoporphyrin IX or siRNA-mediated knockdown increased HLA I Ab-dependent up-regulation of VCAM-1. Treatment with two carbon monoxide (CO)-releasing molecules, which liberate the gaseous HO product CO, blocked HLA I Ab-dependent EC activation. Finally, in an in vitro adhesion assay exposure of ECs to HLA I Abs led to increased monocyte binding, which was counteracted by up-regulation of HO-1. In conclusion, HLA I Ab-dependent EC activation is modulated by endothelial HO-1 and targeted induction of this enzyme may be a novel therapeutic approach for the treatment of AMR in solid organ transplantation.
Psychometric Evaluation of the Adherence in Diabetes Questionnaire

OBJECTIVE To assess the psychometric properties of a short, new, self-administered questionnaire (17–19 items) for evaluating the adherence behavior of children and adolescents with type 1 diabetes and their caregivers. This instrument has separate versions depending on the means of insulin administration, i.e., continuous subcutaneous insulin infusion (Adherence in Diabetes Questionnaire [ADQ]-I), or conventional insulin injection (ADQ-C). RESEARCH DESIGN AND METHODS A total of 1,028 caregivers and 766 children and adolescents 2–17 years of age were recruited through the Danish Registry of Childhood Diabetes and completed the national web survey, including the ADQ and psychosocial measures of self-efficacy, parental support, family conflict, and aspects of diabetes-related quality of life. Blood samples were obtained for central HbA1c analysis. The psychometric properties of the ADQ were evaluated, and the association with glycemic control was assessed. RESULTS There was good internal consistency for both the youth and caregiver reports and strong agreement between the caregiver and youth reports. Higher ADQ scores, indicating better adherence, were associated with better self-efficacy, more parental support, less diabetes-related conflict, and less experience with treatment barriers. Factor analysis supported maintaining the one-factor structure of the ADQ. Higher ADQ scores were associated with lower HbA1c levels. CONCLUSIONS The ADQ showed good psychometric properties. Although the test-retest reliability and sensitivity to change of the instrument still need to be established, the ADQ appears to be a valuable tool for assessing adherence in families with children and adolescents with type 1 diabetes in both clinical and research settings.
Mitochondrial and Nuclear Genomic Responses to Loss of LRPPRC Expression*

Rapid advances in genotyping and sequencing technology have dramatically accelerated the discovery of genes underlying human disease. Elucidating the function of such genes and understanding their role in pathogenesis, however, remain challenging. Here, we introduce a genomic strategy to characterize such genes functionally, and we apply it to LRPPRC, a poorly studied gene that is mutated in Leigh syndrome, French-Canadian type (LSFC). We utilize RNA interference to engineer an allelic series of cellular models in which LRPPRC has been stably silenced to different levels of knockdown efficiency. We then combine genome-wide expression profiling with gene set enrichment analysis to identify cellular responses that correlate with the loss of LRPPRC. Using this strategy, we discovered a specific role for LRPPRC in the expression of all mitochondrial DNA-encoded mRNAs, but not the rRNAs, providing mechanistic insights into the enzymatic defects observed in the disease. Our analysis shows that nuclear genes encoding mitochondrial proteins are not collectively affected by the loss of LRPPRC. We do observe altered expression of genes related to hexose metabolism, prostaglandin synthesis, and glycosphingolipid biology that may either play an adaptive role in cell survival or contribute to pathogenesis. The combination of genetic perturbation, genomic profiling, and pathway analysis represents a generic strategy for understanding disease pathogenesis.
Copeptin levels in carbon monoxide poisoning.

BACKGROUND/AIM The aim of this study is to identify the copeptin levels in patients presenting with carbon monoxide (CO) poisoning to the emergency department and to investigate its correlation with the neurological effects. MATERIALS AND METHODS The study group consisted of patients presenting with CO poisoning and carboxyhemoglobin levels >10%. Blood samples for copeptin levels were obtained twice, first at presentation then at the fourth hour of observation. The data were analyzed using SPSS 16 for Windows. RESULTS The median copeptin levels of the patient group were identified as 0.63 (0.39-1.06) ng/mL at hour 0 and 0.41 (0.31-0.49) at hour 4. The copeptin levels of the control group were 0.34 (0.25-0.42) ng/mL and were significantly lower than those of the patient group (P < 0.000). According to our results, 0.345 ng/mL for plasma copeptin level as the best cut-off level may be used with sensitivity of 94.0% and specificity of 60%. The copeptin levels at hour 0 were statistically significantly higher in the neurologically affected patients than those not affected (P < 0.001). CONCLUSION In this study it was shown that blood copeptin levels increase in patients presenting to the emergency department with CO poisoning.
Analysis of Sentinel-1 Radiometric Stability and Quality for Land Surface Applications

Land monitoring using temporal series of Synthetic Aperture Radar (SAR) images requires radiometrically well calibrated sensors. In this paper, the radiometric stability of the new SAR Sentinel-1A 'S-1A' sensor was first assessed by analyzing temporal variations of the backscattering coefficient (sigma°) returned from invariant targets. Second, the radiometric level of invariant targets was compared from S-1A and Radarsat-2 "RS-2" data. The results show three stable sub-time series of S-1A data. The first (between 1 October 2014 and 19 March 2015) and third (between 25 November 2015 and 1 February 2016) sub-time series have almost the same mean sigma°-values (a difference lower than 0.3 dB). The mean sigma°-value of the second sub-time series (between 19 March 2015 and 25 November 2015) is higher than that of the first and the third sub-time series by roughly 0.9 dB. Moreover, our results show that the stability of each sub-time series is better than 0.48 dB. In addition, the results show that S-1A images of the first and third sub-time series appear to be well calibrated in comparison to RS-2 data, with a difference between S-1A and RS-2 lower than 0.3 dB. However, the S-1A images of the second sub-time series have sigma°-values that are higher than those from RS-2 by roughly 1 dB.
Bone Mineral Density Values Derived from Routine Lumbar Spine Multidetector Row CT Predict Osteoporotic Vertebral Fractures and Screw Loosening

BACKGROUND AND PURPOSE: Established methods of assessing bone mineral density are associated with additional radiation exposure to the patient. In this study, we aimed to validate a method of assessing bone mineral density in routine multidetector row CT of the lumbar spine. MATERIALS AND METHODS: In 38 patients, bone mineral density was assessed in quantitative CT as a standard of reference and in sagittal reformations derived from standard multidetector row CT studies without IV contrast. MDCT-to-quantitative CT conversion equations were calculated and then applied to baseline multidetector row scans of another 62 patients. After a mean follow-up of 15 ± 6 months, patients were re-assessed for incidental fractures and screw loosening after spondylodesis (n = 49). RESULTS: We observed conversion equations bone mineral densityMDCT = 0.78 × Hounsfield unitMDCTmg/mL (correlation with bone mineral densityquantitative CT, R2 = 0.92, P < .001) for 120 kV(peak) tube voltage and bone mineral densityMDCT = 0.86 × Hounsfield unitMDCTmg/mL (R2 = 0.81, P < .001) for 140 kVp, respectively. Seven patients (11.3%) had existing osteoporotic vertebral fractures at baseline, while 8 patients (12.9%) showed incidental osteoporotic vertebral fractures. Screw loosening was detected in 28 patients (57.1% of patients with spondylodesis). Patients with existing vertebral fractures showed significantly lower bone mineral densityMDCT than patients without fractures (P < .01). At follow-up, patients with incidental fractures and screw loosening after spondylodesis, respectively, showed significantly lower baseline bone mineral densityMDCT (P < .001 each). CONCLUSIONS: This longitudinal study demonstrated that converted bone mineral density values derived from routine lumbar spine multidetector row CT adequately differentiated patients with and without osteoporotic fractures and could predict incidental fractures and screw loosening after spondylodesis.
Cell geometric constraints induce modular gene-expression patterns via redistribution of HDAC3 regulated by actomyosin contractility

Physical forces in the form of substrate rigidity or geometrical constraints have been shown to alter gene expression profile and differentiation programs. However, the underlying mechanism of gene regulation by these mechanical cues is largely unknown. In this work, we use micropatterned substrates to alter cellular geometry (shape, aspect ratio, and size) and study the nuclear mechanotransduction to regulate gene expression. Genome-wide transcriptome analysis revealed cell geometry-dependent alterations in actin-related gene expression. Increase in cell size reinforced expression of matrix-related genes, whereas reduced cell-substrate contact resulted in up-regulation of genes involved in cellular homeostasis. We also show that large-scale changes in gene-expression profile mapped onto differential modulation of nuclear morphology, actomyosin contractility and histone acetylation. Interestingly, cytoplasmic-to-nuclear redistribution of histone deacetylase 3 modulated histone acetylation in an actomyosin-dependent manner. In addition, we show that geometric constraints altered the nuclear fraction of myocardin-related transcription factor. These fractions exhibited hindered diffusion time scale within the nucleus, correlated with enhanced serum-response element promoter activity. Furthermore, nuclear accumulation of myocardin-related transcription factor also modulated NF-κB activity. Taken together, our work provides modularity in switching gene-expression patterns by cell geometric constraints via actomyosin contractility.
Structural analysis of a Lotus japonicus genome. V. Sequence features and mapping of sixty-four TAC clones which cover the 6.4 mb regions of the genome.

We determined the nucleotide sequences of 64 TAC (transformation-competent artificial chromosome) clones selected from genomic libraries of Lotus japonicus accession Miyakojima MG-20 based on the sequence information of expressed sequence tags (ESTs), cDNAs, genes and DNA markers from L. japonicus and other legumes. The length of the DNA regions sequenced in this study was 6,370,255 bp, and the total length of the L. japonicus genome sequenced so far is 32,537,698 bp together with the nucleotide sequences of 256 TAC clones previously reported. Five hundred forty-eight potential protein-encoding genes with known or predicted functions, 127 gene segments and 224 pseudogenes were assigned to the newly sequenced regions by computer prediction and similarity searches against the sequences in protein and EST databases. Based on the nucleotide sequences of the clones, simple sequence repeat length polymorphism (SSLP) or derived cleaved amplified polymorphic sequence (dCAPS) markers were generated, and each clone was genetically localized onto the linkage map of two accessions of L. japonicus, MG-20 and Gifu B-129. The sequence data, gene information and mapping information are available through the World Wide Web at http://www.kazusa. or.jp/lotus/.
Gradient theory for plasticity via homogenization of discrete dislocations

We deduce a macroscopic strain gradient theory for plasticity from a model of discrete dislocations. We restrict our analysis to the case of a cylindrical symmetry for the crystal under study, so that the mathematical formulation will involve a two-dimensional variational problem. The dislocations are introduced as point topological defects of the strain fields, for which we compute the elastic energy stored outside the so-called core region.We show that the G-limit of this energy (suitably rescaled), as the core radius tends to zero and the number of dislocations tends to infinity, takes the form E = fO (W(se) + f (Curl se)) dx, where e represents the elastic part of the macroscopic strain, and Curl se represents the geometrically necessary dislocation density. The plastic energy density f is defined explicitly through an asymptotic cell formula, depending only on the elastic tensor and the class of the admissible Burgers vectors, accounting for the crystalline structure. It turns out to be positively 1-homogeneous, so that concentration on lines is permitted, accounting for the presence of pattern formations observed in crystals such as dislocation walls.
Non-Linear Spectral Unmixing by Geodesic Simplex Volume Maximization

Spectral mixtures observed in hyperspectral imagery often display nonlinear mixing effects. Since most traditional unmixing techniques are based upon the linear mixing model, they perform poorly in finding the correct endmembers and their abundances in the case of nonlinear spectral mixing. In this paper, we present an unmixing algorithm that is capable of extracting endmembers and determining their abundances in hyperspectral imagery under nonlinear mixing assumptions. The algorithm is based upon simplex volume maximization, and uses shortest-path distances in a nearest-neighbor graph in spectral space, hereby respecting the nontrivial geometry of the data manifold in the case of nonlinearly mixed pixels. We demonstrate the algorithm on an artificial data set, the AVIRIS Cuprite data set, and a hyperspectral image of a heathland area in Belgium.
Potential Future Impact of a Partially Effective HIV Vaccine in a Southern African Setting

Background It is important for public health and within the HIV vaccine development field to understand the potential population level impact of an HIV vaccine of partial efficacy—both in preventing infection and in reducing viral load in vaccinated individuals who become infected—in the context of a realistic future implementation scenario in resource limited settings. Methods An individual level model of HIV transmission, progression and the effect of antiretroviral therapy was used to predict the outcome to 2060 of introduction in 2025 of a partially effective vaccine with various combinations of efficacy characteristics, in the context of continued ART roll-out in southern Africa. Results In the context of our base case epidemic (in 2015 HIV prevalence 28% and incidence 1.7 per 100 person years), a vaccine with only 30% preventative efficacy could make a substantial difference in the rate with which HIV incidence declines; the impact on incidence in relative terms is projected to increase over time, with a projected 67% lower HIV incidence in 2060 compared with no vaccine introduction. The projected mean decline in the general adult population death rate 2040–2060 is 11%. A vaccine with no prevention efficacy but which reduces viral load by 1 log is predicted to result in a modest (14%) reduction in HIV incidence and an 8% reduction in death rate in the general adult population (mean 2040–2060). These effects were broadly similar in multivariable uncertainty analysis. Interpretation Introduction of a partially effective preventive HIV vaccine would make a substantial long-term impact on HIV epidemics in southern Africa, in addition to the effects of ART. Development of an HIV vaccine, even of relatively low apparent efficacy at the individual level, remains a critical global public health goal.
Preprocessing the Nintendo Wii Board Signal to Derive More Accurate Descriptors of Statokinesigrams

During the past few years, the Nintendo Wii Balance Board (WBB) has been used in postural control research as an affordable but less reliable replacement for laboratory grade force platforms. However, the WBB suffers some limitations, such as a lower accuracy and an inconsistent sampling rate. In this study, we focus on the latter, namely the non uniform acquisition frequency. We show that this problem, combined with the poor signal to noise ratio of the WBB, can drastically decrease the quality of the obtained information if not handled properly. We propose a new resampling method, Sliding Window Average with Relevance Interval Interpolation (SWARII), specifically designed with the WBB in mind, for which we provide an open source implementation. We compare it with several existing methods commonly used in postural control, both on synthetic and experimental data. The results show that some methods, such as linear and piecewise constant interpolations should definitely be avoided, particularly when the resulting signal is differentiated, which is necessary to estimate speed, an important feature in postural control. Other methods, such as averaging on sliding windows or SWARII, perform significantly better on synthetic dataset, and produce results more similar to the laboratory-grade AMTI force plate (AFP) during experiments. Those methods should be preferred when resampling data collected from a WBB.