Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection and Molecular Characterization of Two FAD3 Genes Controlling Linolenic Acid Content and Development of Allele-Specific Markers in Yellow Mustard (Sinapis alba)

Development of yellow mustard (Sinapis alba L.) with superior quality traits (low erucic and linolenic acid contents, and low glucosinolate content) can make this species as a potential oilseed crop. We have recently isolated three inbred lines Y1127, Y514 and Y1035 with low (3.8%), medium (12.3%) and high (20.8%) linolenic acid (C18∶3) content, respectively, in this species. Inheritance studies detected two fatty acid desaturase 3 (FAD3) gene loci controlling the variation of C18∶3 content. QTL mapping revealed that the two FAD3 gene loci responsible for 73.0% and 23.4% of the total variation and were located on the linkage groups Sal02 and Sal10, respectively. The FAD3 gene on Sal02 was referred to as SalFAD3.LA1 and that on Sal10 as SalFAD3.LA2. The dominant and recessive alleles were designated as LA1 and la1 for SalFAD3.LA1, and LA2 and la2 for SalFAD3.LA2. Cloning and alignment of the coding and genomic DNA sequences revealed that the SalFAD3.LA1 and SalFAD3.LA2 genes each contained 8 exons and 7 introns. LA1 had a coding DNA sequence (CDS) of 1143 bp encoding a polypeptide of 380 amino acids, whereas la1 was a loss-of-function allele due to an insertion of 584 bp in exon 3. Both LA2 and la2 had a CDS of 1152 bp encoding a polypeptide of 383 amino acids. Allele-specific markers for LA1, la1, LA2 and la2 co-segregated with the C18∶3 content in the F2 populations and will be useful for improving fatty acid composition through marker assisted selection in yellow mustard breeding.
Maternal plasma fetuin-A concentration is lower in patients who subsequently developed preterm preeclampsia than in uncomplicated pregnancy: a longitudinal study*

Abstract Objective: Fetuin-A is a negative acute phase protein reactant that acts as a mediator for lipotoxicity, leading to insulin resistance. Intravascular inflammation and insulin resistance have been implicated in the mechanisms of disease responsible for preeclampsia (PE). Maternal plasma concentrations of fetuin-A at the time of diagnosis of preterm PE are lower than in control patients with a normal pregnancy outcome. However, it is unknown if the changes in maternal plasma fetuin-A concentrations precede the clinical diagnosis of the disease. We conducted a longitudinal study to determine whether patients who subsequently developed PE had a different profile of maternal plasma concentrations of fetuin-A as a function of gestational age (GA) than those with uncomplicated pregnancies. Methods: A longitudinal case–control study was performed and included 200 singleton pregnancies in the following groups: (1) patients with uncomplicated pregnancies who delivered appropriate for gestational age (AGA) neonates (n = 160); and (2) patients who subsequently developed PE (n = 40). Longitudinal samples were collected at each prenatal visit and scheduled at 4-week intervals from the first or early second trimester until delivery. Plasma fetuin-A concentrations were determined by ELISA. Analysis was performed using mixed-effects models. Results: The profiles of maternal plasma concentrations of fetuin-A differ between PE and uncomplicated pregnancies. Forward analysis indicated that the rate of increase of plasma fetuin-A concentration in patients who subsequently developed PE was lower at the beginning of pregnancy (p = 0.001), yet increased faster mid-pregnancy (p = 0.0017) and reached the same concentration level as controls by 26 weeks. The rate of decrease was higher towards the end of pregnancy in patients with PE than in uncomplicated pregnancies (p = 0.002). The mean maternal plasma fetuin-A concentration was significantly lower in patients with preterm PE at the time of clinical diagnosis than in women with uncomplicated pregnancies (p < 0.05). In contrast, there were no significant differences in maternal plasma fetuin-A concentration in patients who developed PE at term. Conclusions: (1) The profile of maternal plasma concentrations of fetuin-A over time (GA) in patients who develop PE is different from that of normal pregnant women; (2) the rate of change of maternal plasma concentrations of fetuin-A is positive (increases over time) in the midtrimester of normal pregnancy, and negative (decreases over time) in patients who subsequently develop PE; (3) at the time of diagnosis, the maternal plasma fetuin-A concentration is lower in patients with preterm PE than in those with a normal pregnancy outcome; however, such differences were not demonstrable in patients with term PE.
Comprehensive home-based care coordination for vulnerable elders with dementia: Maximizing Independence at Home-Plus—Study protocol

Introduction Despite availability of effective care strategies for dementia, most health care systems are not yet organized or equipped to provide comprehensive family-centered dementia care management. Maximizing Independence at Home-Plus is a promising new model of dementia care coordination being tested in the U.S. through a Health Care Innovation Award funded by the Centers for Medicare and Medicaid Services that may serve as a model to address these delivery gaps, improve outcomes, and lower costs. This report provides an overview of the Health Care Innovation Award aims, study design, and methodology. Methods This is a prospective, quasi-experimental intervention study of 342 community-living Medicare–Medicaid dual eligibles and Medicare-only beneficiaries with dementia in Maryland. Primary analyses will assess the impact of Maximizing Independence at Home-Plus on risk of nursing home long-term care placement, hospitalization, and health care expenditures (Medicare, Medicaid) at 12, 18 (primary end point), and 24 months, compared to a propensity-matched comparison group. Discussion The goals of the Maximizing Independence at Home-Plus model are to improve care coordination, ability to remain at home, and life quality for participants and caregivers, while reducing total costs of care for this vulnerable population. This Health Care Innovation Award project will provide timely information on the impact of Maximizing Independence at Home-Plus care coordination model on a variety of outcomes including effects on Medicaid and Medicare expenditures and service utilization. Participant characteristic data, cost savings, and program delivery costs will be analyzed to develop a risk-adjusted payment model to encourage sustainability and facilitate spread.
Direct Whole-Genome Sequencing of Cutaneous Strains of Haemophilus ducreyi

Haemophilus ducreyi, which causes chancroid, has emerged as a cause of pediatric skin disease. Isolation of H. ducreyi in low-income settings is challenging, limiting phylogenetic investigation. Next-generation sequencing demonstrates that cutaneous strains arise from class I and II H. ducreyi clades and that class II may represent a distinct subspecies.
Opportunistic Radar in IEEE 802.11ad Networks

In this paper, we study the feasibility of an opportunistic radar, which exploits the probing signals transmitted during the sector level sweep of the IEEE 802.11ad beamforming training protocol. Several solutions are presented to detect the presence of prospective obstacles and estimate their position, radial velocity, and backscattered signal amplitude, which differ in the amount of prior information as to the transmitted signal and the channel fluctuation. Also, we derive the Cramér–Rao bound as a benchmark for the proposed estimators: The derivation of these bounds is per se relevant, as it generalizes classical results to the case where the echo is not entirely contained in the observation window. Numerical examples are provided to assess performance of the proposed solutions. The results indicate that the close-to-one detection probability is achievable up to 90 m with a probability of false alarm of 1e-4 and Swerling-I target fluctuation; in this region, the target delay is estimated with an accuracy smaller than the symbol interval (corresponding to a range resolution smaller than 10 cm) with probability close to one, while the velocity estimate is generally quite poor as a consequence of the very short duration of the probing signal.
Nurse Task Shifting for Antiretroviral Treatment Services in Namibia: Implementation Research to Move Evidence into Action

Background Evidence from several sub-Saharan countries support nurse-initiated antiretroviral treatment as a feasible alternative to doctor-led models characteristic of early responses to the HIV epidemic. However, service delivery models shown to be effective in one country may not be readily adopted in another. This study used an implementation research approach to assist policy makers and other stakeholders to assess the acceptability and feasibility of task shifting in the Namibian context. Methods The Namibian Ministry of Health and Social Services implemented a Task Shifting Demonstration Project (TSDP) at 9 sites at different levels of the health system. Six months after implementation, a mixed methods evaluation was conducted. Seventy semi-structured interviews were conducted with patients, managers, doctors and nurses directly involved with the TSDP. Physician-evaluators observed and compared health service provision between doctors and nurses for 40 patients (80 observations), documenting performance in agreement with the national guidelines on 13 clinical care indicators. Results Doctors, nurses, and patients interviewed believed task shifting would improve access to and quality of HIV services. Doctors and nurses both reported an increase in nurses’ skills as a result of the project. Observation data showed doctors and nurses were in considerable agreement (>80%) with each other on all dimensions of HIV care and ≥90% on eight dimensions. To ensure success of national scale-up of the task shifting model, challenges involving infrastructure, on-going mentoring, and nursing scope of practice should be anticipated and addressed. Conclusion In combination with findings from other studies in the region, data from the TSDP provided critical and timely information to the Namibian Ministry of Health and Social Services, thus helping to move evidence into action. Small-scale implementation research projects enable stakeholders to learn by doing, and provide an opportunity to test and modify the intervention before expansion.
Identification and In Silico Characterization of a Genetically Distinct Avian Rotavirus D Capsid Gene, VP7

Rotavirus D (RV-D) is gaining importance as a cause of gastroenteritis and runting and stunting syndrome (RSS) in poultry. To date, information is scarce on the molecular analysis of RV-D isolates worldwide. In this study, the VP7 gene, a major constituent of outer capsid structural protein, from a RV-D isolate (UKD48) obtained from Uttarakhand state was analyzed. Phylogenetically, the RV-D isolate was found to be closely related to a South Korean strain, and the nucleotide percent identity varied from 80.4–84.2% with other RV-D strains available globally. Furthermore, domain investigation within 21 aligned amino acid sequences of the VP7 gene affirmed that this gene has several domains: a conserved glycosylation site (N–I–T) having an important role in protein folding; a N-terminal signal peptide (“ITG”) for endoplasmic reticulum retention; and two hydrophobic sites for elucidating transmembrane portions, antigenic structures, and so forth. The findings suggest that the VP7 gene of the Indian RV-D isolate is genetically distinct from those of other avian RV-Ds. Although biological evidence is still needed to prove the functional characteristics of these domains in outer capsid structural proteins, the present study adds new knowledge and derives the need for further investigation.
DeepTracker

Deep Convolutional Neural Networks (CNNs) have achieved remarkable success in various fields. However, training an excellent CNN is practically a trial-and-error process that consumes a tremendous amount of time and computer resources. To accelerate the training process and reduce the number of trials, experts need to understand what has occurred in the training process and why the resulting CNN behaves as it does. However, current popular training platforms, such as TensorFlow, only provide very little and general information, such as training/validation errors, which is far from enough to serve this purpose. To bridge this gap and help domain experts with their training tasks in a practical environment, we propose a visual analytics system, DeepTracker, to facilitate the exploration of the rich dynamics of CNN training processes and to identify the unusual patterns that are hidden behind the huge amount of information in training log. Specifically, we combine a hierarchical index mechanism and a set of hierarchical small multiples to help experts explore the entire training log from different levels of detail. We also introduce a novel cube-style visualization to reveal the complex correlations among multiple types of heterogeneous training data, including neuron weights, validation images, and training iterations. Three case studies are conducted to demonstrate how DeepTracker provides its users with valuable knowledge in an industry-level CNN training process; namely, in our case, training ResNet-50 on the ImageNet dataset. We show that our method can be easily applied to other state-of-the-art “very deep” CNN models.
ECG Signal Analysis for Abnormality Detection in the Heart beat

Automatic recognition of cardiac arrhythmias is important for diagnosis of cardiac abnormalities. Detection of various abnormalities in the heart to identify various heart diseases can be made through an Adaptive Neuro-Fuzzy Inference System (ANFIS) preprocessed by subtractive clustering. Some recordings of the MIT-BIH database has been used for training and testing our neural network based classifier. Six types of heartbeats are classified: normal sinus rhythm, premature ventricular contraction (PVC), atrial premature contraction (APC), left bundle branch block (LBBB), right bundle branch block (RBBB), and paced beats. Our goal is to detect important characteristics of an ECG signal to determine if the heartbeat is normal or irregular. Therefore, in this paper, an expert system for Electrocardiogram (ECG) classification is analyzed. DWT is used in preprocessing for filtering ECG recordings, and extraction of some features performs the classification task. KeywordsANFIS, Arrhythmias, ECG, MIT-BIH, Subtractive Clustering
Stochastic Adversarial Video Prediction

Being able to predict what may happen in the future requires an in-depth understanding of the physical and causal rules that govern the world. A model that is able to do so has a number of appealing applications, from robotic planning to representation learning. However, learning to predict raw future observations, such as frames in a video, is exceedingly challenging -- the ambiguous nature of the problem can cause a naively designed model to average together possible futures into a single, blurry prediction. Recently, this has been addressed by two distinct approaches: (a) latent variational variable models that explicitly model underlying stochasticity and (b) adversarially-trained models that aim to produce naturalistic images. However, a standard latent variable model can struggle to produce realistic results, and a standard adversarially-trained model underutilizes latent variables and fails to produce diverse predictions. We show that these distinct methods are in fact complementary. Combining the two produces predictions that look more realistic to human raters and better cover the range of possible futures. Our method outperforms prior and concurrent work in these aspects.
Association of Autoimmune Addison's Disease with Alleles of STAT4 and GATA3 in European Cohorts

Background Gene variants known to contribute to Autoimmune Addison's disease (AAD) susceptibility include those at the MHC, MICA, CIITA, CTLA4, PTPN22, CYP27B1, NLRP-1 and CD274 loci. The majority of the genetic component to disease susceptibility has yet to be accounted for. Aim To investigate the role of 19 candidate genes in AAD susceptibility in six European case-control cohorts. Methods A sequential association study design was employed with genotyping using Sequenom iPlex technology. In phase one, 85 SNPs in 19 genes were genotyped in UK and Norwegian AAD cohorts (691 AAD, 715 controls). In phase two, 21 SNPs in 11 genes were genotyped in German, Swedish, Italian and Polish cohorts (1264 AAD, 1221 controls). In phase three, to explore association of GATA3 polymorphisms with AAD and to determine if this association extended to other autoimmune conditions, 15 SNPs in GATA3 were studied in UK and Norwegian AAD cohorts, 1195 type 1 diabetes patients from Norway, 650 rheumatoid arthritis patients from New Zealand and in 283 UK Graves' disease patients. Meta-analysis was used to compare genotype frequencies between the participating centres, allowing for heterogeneity. Results We report significant association with alleles of two STAT4 markers in AAD cohorts (rs4274624: P = 0.00016; rs10931481: P = 0.0007). In addition, nominal association of AAD with alleles at GATA3 was found in 3 patient cohorts and supported by meta-analysis. Association of AAD with CYP27B1 alleles was also confirmed, which replicates previous published data. Finally, nominal association was found at SNPs in both the NF-κB1 and IL23A genes in the UK and Italian cohorts respectively. Conclusions Variants in the STAT4 gene, previously associated with other autoimmune conditions, confer susceptibility to AAD. Additionally, we report association of GATA3 variants with AAD: this adds to the recent report of association of GATA3 variants with rheumatoid arthritis.
Exposure to General Anesthesia and Risk of Dementia: A Nationwide Population-Based Cohort Study.

BACKGROUND There is a growing concern that general anesthesia could increase the risk of dementia. However, the relationship between anesthesia and subsequent dementia is still undetermined. OBJECTIVE To determine whether the risk of dementia increases after exposure to general anesthesia. METHODS A population-based prospective cohort study analyzing the Korean National Health Insurance Service-National Sample Cohort database was conducted of all persons aged over 50 years (n = 219,423) from 1 January 2003 and 31 December 2013. RESULTS 44,956 in the general anesthesia group and 174,469 in the control group were followed for 12 years. The risk of dementia associated with previous exposure to general anesthesia was increased after adjusting for all covariates such as gender, age, health care visit frequency, and co-morbidities (Hazard ratio = 1.285, 95% confidence interval = 1.262-1.384, time-varying Cox hazard model). In addition, the number of anesthetic agents administered, the number of exposures to general anesthesia, the cumulative exposure time, and the organ category involved in surgery were associated with risk of dementia. CONCLUSION In light of the increasing societal burden of dementia, careful surveillance for dementia and prevention guidelines for patients after general anesthesia are needed.
Intranuclear Inclusions in Renal Tubular Epithelium in Immunodeficient Mice Stain with Antibodies for Bovine Papillomavirus Type 1 L1 Protein

The kidneys from six immunodeficient mice examined by Cerberus Sciences and the Animal Resources Centre, displayed karyomegaly with pale eosinophilic, intranuclear inclusions upon histopathological examination. Electron microscopy performed on kidney tissue from 5/6 mice demonstrated margination of the chromatin in large nuclei. Laboratory tests were used to detect nucleic acid of papillomaviruses, polyomaviruses, circoviruses and anelloviruses (4/6 mice), a specific PCR was used to detect murine polyomavirus (1/6), and a panel of serological tests was used to detect seroconversion to major murine pathogens (1/6). All molecular and serological tests were negative. Immunohistochemistry using polyclonal anti-bovine papillomavirus type 1 (BPV-1) L1 antibody, Camvir monoclonal anti-papillomavirus antibody (directed against the seven amino acids GFGAMDF found in human papillomavirus (HPV) 16 L1 protein), a commercially available mixture of two monoclonal antibodies, anti-BPV-1 L1/1H8 + Camvir antibodies, and a monoclonal anti-Hsc70 antibody revealed specific, positive staining of murine renal tubular epithelial intranuclear inclusions in 6/6 mice using the anti-BPV-1 L1 containing antibodies only. Methyl pyronin green, PAS and Feulgen histochemical reactions revealed that the intranuclear inclusions did not consist of RNA, DNA or carbohydrate. An immunohistochemical method now exists that can be used to confirm and evaluate suspected cases of murine inclusion body nephropathy.
Prevalence analysis of urinary incontinence after radical prostatectomy and influential preoperative factors in a single institution

Abstract Aims: To assess prevalence of urinary incontinence (UI) after radical prostatectomy (RP) and to analyze which preoperative characteristics of the patients have influence on UI. Methods: Between 2002 and 2012, 746 consecutive patients underwent RP for clinically localized prostate cancer. We defined UI according to International Continence Society (ICS) definition: “the complaint of any involuntary leakage of urine” after 12 months of recovery, international consultation on incontinence questionnaire (ICIQ-SF) and pads/day was collected too. Clinical features and magnetic resonance imaging measurements were assessed. A multivariable logistic regression model predicting incontinence were built-in after adjust by cofounding factors and bootstrapping. Results: About 172 (23%) of the patients were classified as incontinent according to the ICS definition. The mean value of the ICIQ-SF was 10.87 (±4). 17.8% of patients use at least one pad/day, 11.9% use more than one pad/day. The preoperative factors independently influential in UI are: age [OR: 1.055; CI 95% (1.006–1.107), p = . 028], urethral wall thickness [OR: 5.03; CI 95% (1.11–22.8), p = . 036], history of transurethral resection of the prostate [OR: 6.13; CI 95% (1.86–20.18), p = . 003] and membranous urethral length [OR: 0.173; CI 95% (0.046–0.64), p = . 009]. The predictive accuracy of the model is 78.7% and the area under the curve (AUC) value 71.7%. Conclusions: Urinary incontinence after radical prostatectomy has different prevalence depending on the definition. Age, prior transurethral resection of the prostate (TURP), membranous urethral length (MUL) and urethral wall thickness (UWT) were risk factors.