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India has the highest burden of Tuberculosis (TB) and multidrug-resistant TB (MDR-TB) worldwide. Innovative technology is the need of the hour to identify these cases that remain either undiagnosed or inadequately diagnosed due to the unavailability of appropriate tools at primary healthcare settings. We developed and evaluated 3 kits, namely ‘TB Detect’ (containing BioFM-Filter device), ‘TB Concentration and Transport’ (containing Trans-Filter device) and ‘TB DNA Extraction’ kits. These kits enable bio-safe equipment-free concentration of sputum on filters and improved fluorescence microscopy at primary healthcare centres, ambient temperature transport of dried inactivated sputum filters to central laboratories and molecular detection of drug resistance by PCR and DNA sequencing (Mol-DST). In a 2-site evaluation (n = 1190 sputum specimens) on presumptive TB patients, BioFM-Filter smear exhibited a significant increase in positivity of 7% and 4% over ZN smear and LED-FM smear (p<0.05), respectively and an increment in smear grade status (1+ or 2+ to 3+) of 16% over ZN smear and 20% over LED-FM smear. The sensitivity of Mol-DST in presumptive MDR-TB and XDR-TB cases (n = 148) was 90% for Rifampicin (95% confidence interval [CI], 78–96%), 84% for Isoniazid (95% CI, 72–92%), 83% for Fluoroquinolones (95% CI, 66–93%) and 75% for Aminoglycosides (95% CI, 35–97%), using phenotypic DST as the reference standard. Test specificity was 88–93% and concordance was ~89–92% (κ value 0.8–0.9). The patient-friendly kits described here address several of the existing challenges and are designed to provide ‘Universal Access’ to rapid TB diagnosis, including drug-resistant disease. Their utility was demonstrated by application to sputum at 2 sites in India. Our findings pave the way for larger studies in different point-of-care settings, including high-density urban areas and remote geographical locations. [ABSTRACT FROM AUTHOR]

Background: Alzheimer’s disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. Methods: Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. Results: During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. Conclusions: Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD. [ABSTRACT FROM AUTHOR]

Background: Our systematic review summarizes the evidence concerning the accuracy of serum diagnostic and prognostic tests for colorectal cancer (CRC). Methods: The databases MEDLINE and EMBASE were searched iteratively to identify the relevant literature for serum markers of CRC published from 1950 to August 2012. The articles that provided adequate information to meet the requirements of the meta-analysis of diagnostic and prognostic markers were included. A 2-by-2 table of each diagnostic marker and its hazard ratio (HR) and the confidence interval (CI) of each prognostic marker was directly or indirectly extracted from the included papers, and the pooled sensitivity and specificity of the diagnostic marker and the pooled HR and the CI of the prognostic marker were subsequently calculated using the extracted data. Results: In total, 104 papers related to the diagnostic markers and 49 papers related to the prognostic serum markers of CRC were collected, and only 19 of 92 diagnostic markers were investigated in more than two studies, whereas 21 out of 44 prognostic markers were included in two or more studies. All of the pooled sensitivities of the diagnostic markers with > = 3 repetitions were less than 50%, and the meta-analyses of the prognostic markers with more than 3 studies were performed, VEGF with highest (2.245, CI: 1.347–3.744) and MMP-7 with lowest (1.099, CI: 1.018–1.187)) pooled HRs are presented. Conclusions: The quality of studies addressing the diagnostic and prognostic accuracy of the tests was poor, and the results were highly heterogeneous. The poor characteristics indicate that these tests are of little value for clinical practice. [ABSTRACT FROM AUTHOR]

Type 2 diabetes leads to premature death and reduced quality of life for 8% of Americans. Nutrition management is critical to maintaining glycemic control, yet it is difficult to achieve due to the high individual differences in glycemic response to nutrition. Anticipating glycemic impact of different meals can be challenging not only for individuals with diabetes, but also for expert diabetes educators. Personalized computational models that can accurately forecast an impact of a given meal on an individual’s blood glucose levels can serve as the engine for a new generation of decision support tools for individuals with diabetes. However, to be useful in practice, these computational engines need to generate accurate forecasts based on limited datasets consistent with typical self-monitoring practices of individuals with type 2 diabetes. This paper uses three forecasting machines: (i) data assimilation, a technique borrowed from atmospheric physics and engineering that uses Bayesian modeling to infuse data with human knowledge represented in a mechanistic model, to generate real-time, personalized, adaptable glucose forecasts; (ii) model averaging of data assimilation output; and (iii) dynamical Gaussian process model regression. The proposed data assimilation machine, the primary focus of the paper, uses a modified dual unscented Kalman filter to estimate states and parameters, personalizing the mechanistic models. Model selection is used to make a personalized model selection for the individual and their measurement characteristics. The data assimilation forecasts are empirically evaluated against actual postprandial glucose measurements captured by individuals with type 2 diabetes, and against predictions generated by experienced diabetes educators after reviewing a set of historical nutritional records and glucose measurements for the same individual. The evaluation suggests that the data assimilation forecasts compare well with specific glucose measurements and match or exceed in accuracy expert forecasts. We conclude by examining ways to present predictions as forecast-derived range quantities and evaluate the comparative advantages of these ranges. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this cross-sectional observational study was to compare the prevalence of different oral Candida spp. in patients with Type 2 Diabetes and chronic periodontitis in two oral sites: dorsal surface of the tongue and subgingival area. In order to determine subgingival areas as potential reservoirs of yeasts, this study aimed to find differences in the yeasts’ detection between the dorsum of the tongue, as the oral site most commonly inhabited with microorganisms, and subgingival samples. Additionally, potential predictors for the yeasts prevalence were determined. Material and methods: Subjects (N = 146) were divided into four groups: group A- healthy individuals without periodontitis, group B- healthy individuals with chronic periodontitis, group C- Type 2 Diabetes patients with good glycoregulation and Chronic periodontitis and group D- Type 2 Diabetes patients with poor glycoregulation and Chronic periodontitis. Samples were obtained from the tongue by swabbing. Subgingival plaque samples were taken by paper points and periodontal curette. Isolation and identification of different Candida spp. was done using ChromAgar medium. In addition, germ-tube production and carbohydrate assimilation tests were performed. Results: The prevalence of Candida spp. was higher in diabetics with poor glycoregulation. The most frequently isolated species was Candida albicans followed by Candida glabrata and Candida tropicalis. In 15.6% of cases, Candida spp. was present in the subgingival area while absent on the tongue. Multivariate regression model showed that HbA1c was Candida spp. predictor for both locations. Conclusions: Our results confirmed that there are Candida spp. carriers among subjects with clinically healthy oral mucosa. Also, this study identified subgingival areas as potential reservoirs of these pathogenic species. Glycoregulation has been recognized as a positive predictor factor of Candida spp. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this review was to identify risk factors, prognostic factors, and comorbidities associated with common spinal disorders. Methods: A scoping review of the literature of common spinal disorders was performed through September 2016. To identify search terms, we developed 3 terminology groups for case definitions: 1) spinal pain of unknown origin, 2) spinal syndromes, and 3) spinal pathology. We used a comprehensive strategy to search PubMed for meta-analyses and systematic reviews of case-control studies, cohort studies, and randomized controlled trials for risk and prognostic factors and cross-sectional studies describing associations and comorbidities. Results: Of 3,453 candidate papers, 145 met study criteria and were included in this review. Risk factors were reported for group 1: non-specific low back pain (smoking, overweight/obesity, negative recovery expectations), non-specific neck pain (high job demands, monotonous work); group 2: degenerative spinal disease (workers’ compensation claim, degenerative scoliosis), and group 3: spinal tuberculosis (age, imprisonment, previous history of tuberculosis), spinal cord injury (age, accidental injury), vertebral fracture from osteoporosis (type 1 diabetes, certain medications, smoking), and neural tube defects (folic acid deficit, anti-convulsant medications, chlorine, influenza, maternal obesity). A range of comorbidities was identified for spinal disorders. Conclusion: Many associated factors for common spinal disorders identified in this study are modifiable. The most common spinal disorders are co-morbid with general health conditions, but there is a lack of clarity in the literature differentiating which conditions are merely comorbid versus ones that are risk factors. Modifiable risk factors present opportunities for policy, research, and public health prevention efforts on both the individual patient and community levels. Further research into prevention interventions for spinal disorders is needed to address this gap in the literature. [ABSTRACT FROM AUTHOR]

Background: Despite elimination efforts, the number of Mycobacterium leprae (M. leprae) infected individuals who develop leprosy, is still substantial. Solid evidence exists that individuals living in close proximity to patients are at increased risk to develop leprosy. Early diagnosis of leprosy in endemic areas requires field-friendly tests that identify individuals at risk of developing the disease before clinical manifestation. Such assays will simultaneously contribute to reduction of current diagnostic delay as well as transmission. Antibody (Ab) levels directed against the M.leprae-specific phenolic glycolipid I (PGL-I) represents a surrogate marker for bacterial load. However, it is insufficiently defined whether anti-PGL-I antibodies can be utilized as prognostic biomarkers for disease in contacts. Particularly, in Bangladesh, where paucibacillary (PB) patients form the majority of leprosy cases, anti-PGL-I serology seems an inadequate method for leprosy screening in contacts as a directive for prophylactic treatment. Methods: Between 2002 and 2009, fingerstick blood from leprosy patients’ contacts without clinical signs of disease from a field-trial in Bangladesh was collected on filter paper at three time points covering six years of follow-up per person. Analysis of anti-PGL-I Ab levels for 25 contacts who developed leprosy during follow-up and 199 contacts who were not diagnosed with leprosy, was performed by ELISA after elution of bloodspots from filter paper. Results: Anti-PGL-I Ab levels at intake did not significantly differ between contacts who developed leprosy during the study and those who remained free of disease. Moreover, anti-PGL-I serology was not prognostic in this population as no significant correlation was identified between anti-PGL-I Ab levels at intake and the onset of leprosy. Conclusion: In this highly endemic population in Bangladesh, no association was observed between anti-PGL-I Ab levels and onset of disease, urging the need for an extended, more specific biomarker signature for early detection of leprosy in this area. Trial registration: ClinicalTrials.gov [ABSTRACT FROM AUTHOR]

A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs), which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules). While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate) learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1) induces task-specific learning in groups of nodes and connections (task-specific localized learning), which 2) produces functional modules for each subtask, and 3) yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting. [ABSTRACT FROM AUTHOR]

Background and aims: Persistent intestinal damage is associated with higher complication rates in celiac disease. We aimed to assess the potential modifiers of mucosal recovery. Materials and methods: We screened databases (PubMed, Embase, Cochrane Trials, and Web of Science) for papers on celiac disease. Papers discussing (1) celiac patients (2) follow-up biopsy and (3) mucosal recovery after commencement of a gluten-free diet were included. The primary outcome was to produce a comprehensive analysis of complete mucosal recovery (i.e., Marsh 0 on follow-up). We compared children’s recovery ratios to those of adults. Patients following a strict gluten-free dietary regimen were included in a subgroup. Summary point estimates, 95% confidence intervals (CIs), and 95% predictive intervals (PIs) were calculated. Heterogeneity was tested with I2-statistic. The PROSPERO registration number is CRD42016053482. Results: The overall complete mucosal recovery ratio, calculated from 37 observational studies, was 0.36 (CI: 0.28–0.44, PI: -0.12–0.84; I2: 98.4%, p<0.01). Children showed higher complete mucosal recovery ratio than adults (p<0.01): 0.65 (CI: 0.44–0.85, PI: -0.10–1.39; I2: 96.5%, p<0.01) as opposed to 0.24 (CI: 0.15–0.33, PI: -0.19–1.08; I2: 96.3%, p<0.01). In the strict dietary adherence subgroup, complete mucosal recovery ratio was 0.47 (CI: 0.24–0.70, PI: -0.47–1.41; I2: 98.8%, p<0.001). On meta-regression, diagnostic villous atrophy (Marsh 3) ratio (-8.97, p<0.01) and male ratio (+6.04, p<0.01) proved to be a significant determinant of complete mucosal recovery, unlike duration of gluten-free diet (+0.01, p = 0.62). The correlation between complete mucosal recovery ratio and age on diagnosis is of borderline significance (-0.03, p = 0.05). Conclusions: There is considerable heterogeneity across studies concerning complete mucosal recovery ratios achieved by a gluten-free diet in celiac disease. Several celiac patients fail to achieve complete mucosal recovery even if a strict dietary regimen is followed. Younger age on diagnosis, less severe initial histologic damage and male gender predispose for achieving mucosal recovery. [ABSTRACT FROM AUTHOR]

Background: Cancer and Diabetes Mellitus (DM) are leading causes of death worldwide and the prevalence of both is escalating. People with co-morbid cancer and DM have increased morbidity and premature mortality compared with cancer patients with no DM. The reasons for this are likely to be multifaceted but will include the impact of hypo/hyperglycaemia and diabetes therapies on cancer treatment and disease progression. A useful step toward addressing this disparity in treatment outcomes is to establish the impact of cancer treatment on diabetes control. Aim: The aim of this review is to identify and analyse current evidence reporting glycaemic control (HbA1c) during and after cancer treatment. Methods: Systematic searches of published quantitative research relating to comorbid cancer and type 2 diabetes mellitus were conducted using databases, including Medline, Embase, PsychINFO, CINAHL and Web of Science (February 2017). Full text publications were eligible for inclusion if they: were quantitative, published in English language, investigated the effects of cancer treatment on glycaemic control, reported HbA1c (%/mmols/mol) and included adult populations with diabetes. Means, standard deviations and sample sizes were extracted from each paper; missing standard deviations were imputed. The completed datasets were analysed using a random effects model. A mixed-effects analysis was undertaken to calculate mean HbA1c (%/mmols/mol) change over three time periods compared to baseline. Results: The available literature exploring glycaemic control post-diagnosis was mixed. There was increased risk of poor glycaemic control during this time if studies of surgical treatment for gastric cancer are excluded, with significant differences between baseline and 12 months (p < 0.001) and baseline and 24 months (p = 0.002). Conclusion: We found some evidence to support the contention that glycaemic control during and/or after non-surgical cancer treatment is worsened, and the reasons are not well defined in individual studies. Future studies should consider the reasons why this is the case. [ABSTRACT FROM AUTHOR]

Purpose: Overweight and underweight conditions are considered relative contraindications to lung transplantation due to their association with excess mortality. Yet, recent work suggests that body mass index (BMI) does not accurately reflect adipose tissue mass in adults with advanced lung diseases. Alternative and more accurate measures of adiposity are needed. Chest fat estimation by routine computed tomography (CT) imaging may therefore be important for identifying high-risk lung transplant candidates. In this paper, an approach to chest fat quantification and quality assessment based on a recently formulated concept of standardized anatomic space (SAS) is presented. The goal of the paper is to seek answers to several key questions related to chest fat quantity and quality assessment based on a single slice CT (whether in the chest, abdomen, or thigh) versus a volumetric CT, which have not been addressed in the literature. Methods: Unenhanced chest CT image data sets from 40 adult lung transplant candidates (age 58 ± 12 yrs and BMI 26.4 ± 4.3 kg/m2), 16 with chronic obstructive pulmonary disease (COPD), 16 with idiopathic pulmonary fibrosis (IPF), and the remainder with other conditions were analyzed together with a single slice acquired for each patient at the L5 vertebral level and mid-thigh level. The thoracic body region and the interface between subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in the chest were consistently defined in all patients and delineated using Live Wire tools. The SAT and VAT components of chest were then segmented guided by this interface. The SAS approach was used to identify the corresponding anatomic slices in each chest CT study, and SAT and VAT areas in each slice as well as their whole volumes were quantified. Similarly, the SAT and VAT components were segmented in the abdomen and thigh slices. Key parameters of the attenuation (Hounsfield unit (HU) distributions) were determined from each chest slice and from the whole chest volume separately for SAT and VAT components. The same parameters were also computed from the single abdominal and thigh slices. The ability of the slice at each anatomic location in the chest (and abdomen and thigh) to act as a marker of the measures derived from the whole chest volume was assessed via Pearson correlation coefficient (PCC) analysis. Results: The SAS approach correctly identified slice locations in different subjects in terms of vertebral levels. PCC between chest fat volume and chest slice fat area was maximal at the T8 level for SAT (0.97) and at the T7 level for VAT (0.86), and was modest between chest fat volume and abdominal slice fat area for SAT and VAT (0.73 and 0.75, respectively). However, correlation was weak for chest fat volume and thigh slice fat area for SAT and VAT (0.52 and 0.37, respectively), and for chest fat volume for SAT and VAT and BMI (0.65 and 0.28, respectively). These same single slice locations with maximal PCC were found for SAT and VAT within both COPD and IPF groups. Most of the attenuation properties derived from the whole chest volume and single best chest slice for VAT (but not for SAT) were significantly different between COPD and IPF groups. Conclusions: This study demonstrates a new way of optimally selecting slices whose measurements may be used as markers of similar measurements made on the whole chest volume. The results suggest that one or two slices imaged at T7 and T8 vertebral levels may be enough to estimate reliably the total SAT and VAT components of chest fat and the quality of chest fat as determined by attenuation distributions in the entire chest volume. [ABSTRACT FROM AUTHOR]

Measurement of telomere length is crucial for the study of telomere maintenance and its role in molecular pathophysiology of diseases and in aging. Several methods are used to measure telomere length, the choice of which usually depends on the type and size of sample to be assayed, as well as cost and throughput considerations. The goal of this study was to investigate the factors that may influence the reliability of qPCR-based relative telomere length measurements in whole blood. Day to day intra-individual variability, types of blood anticoagulant, sample storage conditions, processing and site of blood draw were investigated. Two qPCR-based methods to measure telomere length (monoplex vs. multiplex) were also investigated and showed a strong correlation between them. Freezing and thawing of the blood and storage of the blood at 4°C for up to 4 days did not affect telomere length values. Telomere lengths in dried blood spots were significantly higher than both whole blood and peripheral mononuclear blood cells, and were highly correlated with both. We found that telomere length measurements were significantly higher in dried blood spots collected directly from fingertip prick compared to dried blood spots prepared with anticoagulated whole blood collected from the finger, and non-blotted whole blood taken from both finger and arm venipuncture. This suggests that DNA from cells blotted on paper is not equivalent to that collected from venipuncture whole blood, and caution should be taken when comparing between blood sample types. [ABSTRACT FROM AUTHOR]

Purpose: Many studies have reported that carbohydrate antigen 153 (CA153) in breast secretions (BS) can discriminate breast cancer (BC) patients from healthy individuals, indicating CA153 in BS as a potential index for BC. This meta-analysis aimed to evaluate the actual diagnostic value of CA153 in BS. Methods: Related papers were obtained from Pubmed, Embase, Scopus, Ovid, Sciverse, the Cochrane library, Chinese Biomedical literature Database (CBM), Technology of Chongqing (VIP), Wan Fang Data, and Chinese National Knowledge Infrastructure (CNKI). Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) of CA153 in BS for BC diagnosis were analyzed with the random effect model. SROC and the area under the curve (AUC) were applied to assess overall diagnostic efficiency. Results: This meta-analysis included five studies with a total of 329 BC patients and 381 healthy subjects. For CA153 in BS, the summary sensitivity, specificity, and DOR to diagnose BC were 0.63 (95% confidence interval (CI): 0.57∼0.68), 0.82 (95% CI: 0.78∼0.86), and 9.18 (95% CI: 4.22∼19.95), respectively. Furthermore, the AUC of BS CA153 in the diagnosis of BC was 0.8614. Conclusions: CA153 in BS is a valuable molecular marker in diagnosing BC and should be applied in standard clinical practices of BC screening upon confirmation of our findings in a larger prospective study. [ABSTRACT FROM AUTHOR]

Purpose: Quantitative image analysis in previous research in obstructive sleep apnea syndrome (OSAS) has focused on the upper airway or several objects in its immediate vicinity and measures of object size. In this paper, we take a more general approach of considering all major objects in the upper airway region and measures pertaining to their individual morphological properties, their tissue characteristics revealed by image intensities, and the 3D architecture of the object assembly. We propose a novel methodology to select a small set of salient features from this large collection of measures and demonstrate the ability of these features to discriminate with very high prediction accuracy between obese OSAS and obese non-OSAS groups. Materials and Methods: Thirty children were involved in this study with 15 in the obese OSAS group with an apnea-hypopnea index (AHI) = 14.4 ± 10.7) and 15 in the obese non-OSAS group with an AHI = 1.0 ± 1.0 (p<0.001). Subjects were between 8–17 years and underwent T1- and T2-weighted magnetic resonance imaging (MRI) of the upper airway during wakefulness. Fourteen objects in the vicinity of the upper airways were segmented in these images and a total of 159 measurements were derived from each subject image which included object size, surface area, volume, sphericity, standardized T2-weighted image intensity value, and inter-object distances. A small set of discriminating features was identified from this set in several steps. First, a subset of measures that have a low level of correlation among the measures was determined. A heat map visualization technique that allows grouping of parameters based on correlations among them was used for this purpose. Then, through T-tests, another subset of measures which are capable of separating the two groups was identified. The intersection of these subsets yielded the final feature set. The accuracy of these features to perform classification of unseen images into the two patient groups was tested by using logistic regression and multi-fold cross validation. Results: A set of 16 features identified with low inter-feature correlation (< 0.36) yielded a high classification accuracy of 96% with sensitivity and specificity of 97.8% and 94.4%, respectively. In addition to the previously observed increase in linear size, surface area, and volume of adenoid, tonsils, and fat pad in OSAS, the following new markers have been found. Standardized T2-weighted image intensities differed between the two groups for the entire neck body region, pharynx, and nasopharynx, possibly indicating changes in object tissue characteristics. Fat pad and oropharynx become less round or more complex in shape in OSAS. Fat pad and tongue move closer in OSAS, and so also oropharynx and tonsils and fat pad and tonsils. In contrast, fat pad and oropharynx move farther apart from the skin object. Conclusions: The study has found several new anatomic bio-markers of OSAS. Changes in standardized T2-weighted image intensities in objects may imply that intrinsic tissue composition undergoes changes in OSAS. The results on inter-object distances imply that treatment methods should respect the relationships that exist among objects and not just their size. The proposed method of analysis may lead to an improved understanding of the mechanisms underlying OSAS. [ABSTRACT FROM AUTHOR]

In recent years, several high-dimensional, accurate, and effective classification methods have been proposed for the automatic discrimination of the subject between Alzheimer’s disease (AD) or its prodromal phase {i.e., mild cognitive impairment (MCI)} and healthy control (HC) persons based on T1-weighted structural magnetic resonance imaging (sMRI). These methods emphasis only on using the individual feature from sMRI images for the classification of AD, MCI, and HC subjects and their achieved classification accuracy is low. However, latest multimodal studies have shown that combining multiple features from different sMRI analysis techniques can improve the classification accuracy for these types of subjects. In this paper, we propose a novel classification technique that precisely distinguishes individuals with AD, aAD (stable MCI, who had not converted to AD within a 36-month time period), and mAD (MCI caused by AD, who had converted to AD within a 36-month time period) from HC individuals. The proposed method combines three different features extracted from structural MR (sMR) images using voxel-based morphometry (VBM), hippocampal volume (HV), and cortical and subcortical segmented region techniques. Three classification experiments were performed (AD vs. HC, aAD vs. mAD, and HC vs. mAD) with 326 subjects (171 elderly controls and 81 AD, 35 aAD, and 39 mAD patients). For the development and validation of the proposed classification method, we acquired the sMR images from the dataset of the National Research Center for Dementia (NRCD). A five-fold cross-validation technique was applied to find the optimal hyperparameters for the classifier, and the classification performance was compared by using three well-known classifiers: K-nearest neighbor, support vector machine, and random forest. Overall, the proposed model with the SVM classifier achieved the best performance on the NRCD dataset. For the individual feature, the VBM technique provided the best results followed by the HV technique. However, the use of combined features improved the classification accuracy and predictive power for the early classification of AD compared to the use of individual features. The most stable and reliable classification results were achieved when combining all extracted features. Additionally, to analyze the efficiency of the proposed model, we used the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset to compare the classification performance of the proposed model with those of several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Background: The purpose of this paper was to analyze the general diagnostic strength and performance of in vitro diagnostics for C-reactive protein and procalcitonin based on the results of external quality assessment schemes (EQAs). Methods: We analyzed qualitative and quantitative data on both markers collected by the Society for Promotion Quality Assurance in Medical Laboratories (INSTAND e.V.) from 20 EQAs. The C-reactive protein evaluation was method-specific and the procalcitonin evaluation manufacturer-specific (pseudonymized). Coefficients of variation were determined in order to evaluate interlaboratory comparability and the performance of individual laboratories during the analyzed period was examined. Results: Overall most of our participants were able to correctly distinguish the positive from the negative samples, but we occasionally observed also false-positive results for the immunological detection of C-reactive protein. For the semi-quantitative results of C-reactive protein we observed an overall median difference below 5% except for dry chemistry methods (≤ 21%). For procalcitonin two manufacturer collectives showed a good comparability, while one manufacturer detected up to 42% higher results. The coefficients of variation are promising for both analytes even though they surpass the manufacturer’s indication for some collectives. The performance of individual laboratories during the analyzed period was more stable for C-reactive protein than for procalcitonin. Conclusion: In-vitro diagnostic testing for C-reactive protein and procalcitonin showed promising results in our EQAs but still further improvements are needed. We recommend stepping up research on reference measurement methods for both parameters to possibly enhancing the accuracy and diagnostic strength of such assays. [ABSTRACT FROM AUTHOR]

Low serum levels of high-density lipoprotein cholesterol (HDL-C) have been shown to be a risk factor for coronary artery disease independent of low-density lipoprotein cholesterol (LDL-C) in different populations. In this study, we investigated genetic variants through genome-wide association studies to determine their association with HDL-C levels in a sample of 2,700 patients. We identified several SNPs associated with HDL-C levels in the Lebanese population using unadjusted and adjusted by biological factors models. We replicated the association of rs3764261 within CETP with HDL-C levels in the study population, and found other previously unidentified SNPs to be significant at the suggestive level, in both previously identified and unidentified genes. This paper reports the first genome-wide analysis of HDL-C in the Lebanese, Middle Eastern, population and supports the importance of genome-wide association studies across different and minor ethnicities to understand better the etiology of complex human diseases. [ABSTRACT FROM AUTHOR]

The Wingate Anaerobic Test (WAnT) is a short-term maximal intensity cycle ergometer test, which provides anaerobic mechanical power output variables. Despite the physiological significance of the variables extracted from the WAnT, the test is very intense, and generally applies for athletes. Our goal, in this paper, was to develop a new approach to predict the anaerobic mechanical power outputs using maximal incremental cardiopulmonary exercise stress test (CPET). We hypothesized that maximal incremental exercise stress test hold hidden information about the anaerobic components, which can be directly translated into mechanical power outputs. We therefore designed a computational model that included aerobic variables (features), and used a new computational \ predictive algorithm, which enabled the prediction of the anaerobic mechanical power outputs. We analyzed the chosen predicted features using clustering on a network. For peak power (PP) and mean power (MP) outputs, the equations included six features and four features, respectively. The combination of these features produced a prediction model of r = 0.94 and r = 0.9, respectively, on the validation set between the real and predicted PP/MP values (P< 0.001). The newly predictive model allows the accurate prediction of the anaerobic mechanical power outputs at high accuracy. The assessment of additional tests is desired for the development of a robust application for athletes, older individuals, and/or non-healthy populations. [ABSTRACT FROM AUTHOR]

Background: Early diagnosis of Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI) is essential for timely treatment. Machine learning and multivariate pattern analysis (MVPA) for the diagnosis of brain disorders are explicitly attracting attention in the neuroimaging community. In this paper, we propose a voxel-wise discriminative framework applied to multi-measure resting-state fMRI (rs-fMRI) that integrates hybrid MVPA and extreme learning machine (ELM) for the automated discrimination of AD and MCI from the cognitive normal (CN) state. Materials and methods: We used two rs-fMRI cohorts: the public Alzheimer’s disease Neuroimaging Initiative database (ADNI2) and an in-house Alzheimer’s disease cohort from South Korea, both including individuals with AD, MCI, and normal controls. After extracting three-dimensional (3-D) patterns measuring regional coherence and functional connectivity during the resting state, we performed univariate statistical t-tests to generate a 3-D mask that retained only voxels showing significant changes. Given the initial univariate features, to enhance discriminative patterns, we implemented MVPA feature reduction using support vector machine-recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO), in combination with the univariate t-test. Classifications were performed by an ELM, and its efficiency was compared to linear and nonlinear (radial basis function) SVMs. Results: The maximal accuracies achieved by the method in the ADNI2 cohort were 98.86% (p<0.001) and 98.57% (p<0.001) for AD and MCI vs. CN, respectively. In the in-house cohort, the same accuracies were 98.70% (p<0.001) and 94.16% (p<0.001). Conclusion: From a clinical perspective, combining extreme learning machine and hybrid MVPA applied on concatenations of multiple rs-fMRI biomarkers can potentially assist the clinicians in AD and MCI diagnosis. [ABSTRACT FROM AUTHOR]

Diabetic peripheral neuropathy (DPN), the most common chronic complication of diabetes, has become an important public health crisis worldwide. Given that DPN is extremely difficult to treat, determining its risk factors and controlling it at an early stage is critical to preventing its serious consequences and the burden of social disease. Current studies suggest that the risk factors for diabetic peripheral neuropathy are the duration of diabetes, age, glycosylated hemoglobin A1c (HbA1c), diabetic retinopathy (DR), smoking, and body mass Index (BMI). However, most of the aforementioned studies are cross-sectional, and the sample sizes are very limited, so the strength of causal reasoning is relatively low. The current study systematically evaluated DPN’s influencing factors in patients with type 2 diabetes using evidence-based medicine. Overall, 16 included studies (14 cross-sectional studies and 2 case-control studies including 12,116 cases) that conformed to the present criteria were included in the final analysis. The results suggested that the duration of diabetes (MD 2.5, 95% CI 1.71~3.29), age (MD 4.00, 95% CI 3.05~4.95), HbA1c (MD 0.48, 95% CI 0.33~0.64), and DR (OR 2.34, 95% CI 1.74~3.16) are associated with significantly increased risks of DPN among diabetic patients, while BMI, smoking, total triglyceride (TG), and total cholesterol (TC) did not indicate any risks of increasing DPN. The findings provide a scientific basis for a further understanding of the causes of type 2 diabetes complicated with peripheral neuropathy and the improvement of preventive strategies. The next step is to conduct further high-quality prospective cohort studies to validate this paper’s findings. [ABSTRACT FROM AUTHOR]

Robustly predicting outcome for cancer patients from gene expression is an important challenge on the road to better personalized treatment. Network-based outcome predictors (NOPs), which considers the cellular wiring diagram in the classification, hold much promise to improve performance, stability and interpretability of identified marker genes. Problematically, reports on the efficacy of NOPs are conflicting and for instance suggest that utilizing random networks performs on par to networks that describe biologically relevant interactions. In this paper we turn the prediction problem around: instead of using a given biological network in the NOP, we aim to identify the network of genes that truly improves outcome prediction. To this end, we propose SyNet, a gene network constructed ab initio from synergistic gene pairs derived from survival-labelled gene expression data. To obtain SyNet, we evaluate synergy for all 69 million pairwise combinations of genes resulting in a network that is specific to the dataset and phenotype under study and can be used to in a NOP model. We evaluated SyNet and 11 other networks on a compendium dataset of >4000 survival-labelled breast cancer samples. For this purpose, we used cross-study validation which more closely emulates real world application of these outcome predictors. We find that SyNet is the only network that truly improves performance, stability and interpretability in several existing NOPs. We show that SyNet overlaps significantly with existing gene networks, and can be confidently predicted (~85% AUC) from graph-topological descriptions of these networks, in particular the breast tissue-specific network. Due to its data-driven nature, SyNet is not biased to well-studied genes and thus facilitates post-hoc interpretation. We find that SyNet is highly enriched for known breast cancer genes and genes related to e.g. histological grade and tamoxifen resistance, suggestive of a role in determining breast cancer outcome. [ABSTRACT FROM AUTHOR]

The aim of the paper was to assess indicators of muscle and intestinal damage in triathletes. The study involved 15 triathletes whose objective for the season was to start in the XTERRA POLAND 2017 event (1,500-m swimming, 36-km cycling, and 10-km mountain running). Before the 14-week preparatory period, the competitors’ body composition was measured, aerobic capacity was tested (graded treadmill test) and blood samples were collected to determine markers showing the level of muscle and intestinal damage. Subsequent tests for body composition were carried out before and after the competition. Blood samples for biochemical indicators were collected the day before the competition, after the completed race, and 24 and 48 hours later. A significant decrease in body mass was observed after completing the race (–3.1±1.5%). The mean maximal oxygen uptake level among the studied athletes equalled 4.9±0.4 L·min–1, 58.8±4.5 mL·kg–1·min–1. The significant increase in concentrations of cortisol, c-reactive protein and myoglobin after the competition, significantly correlated with the significant increase in zonulin concentration (post 1h: r = 0.88, p = 0.007, r = 0,79, p = 0.001, r = 0.78, p = 0.001, and post 12h: r = 0.75, p = 0.01, r = 0.71, p = 0.011, r = 0.83, p = 0.02). No significant changes in the concentration of tumour necrosis factor alpha among the examined competitors were noted at following stages of the study. The results of our research showed that in order to monitor overload in the training of triathletes, useful markers reflecting the degree of muscle and intestinal damage include cortisol, testosterone, testosterone to cortisol ratio, c-reactive protein, myoglobin and zonulin. Changes in muscle cell damage markers strongly correlated with changes in zonulin concentration at particular stages of the study. Thus, one can expect that the concentrations of markers depicting the level of muscle cell damage after an intense and long-lasting effort will significantly influence the level of the intestinal barrier. [ABSTRACT FROM AUTHOR]

Background: Naja annulifera is a medically important venomous snake occurring in some of the countries in Sub-Saharan Africa. Accidental bites result in severe coagulation disturbances, systemic inflammation and heart damage, as reported in dogs, and death, by respiratory arrest, in humans. Despite the medical importance of N. annulifera, little is known about its venom composition and the pathogenesis of envenomation. In this paper, the toxic, inflammatory and immunogenic properties of N. annulifera venom were analyzed. Methodology/Principal findings: Venom proteomic analysis identified 79 different proteins, including Three Finger Toxins, Cysteine Rich Secretory Proteins, Metalloproteinases, Phospholipases A2 (PLA2), Hyaluronidase, L-amino-acid oxidase, Cobra Venom Factor and Serine Proteinase. The presence of PLA2, hyaluronidase, fibrinogenolytic and anticoagulant activities was detected using functional assays. The venom was cytotoxic to human keratinocytes. In an experimental murine model of envenomation, it was found that the venom induced local changes, such as swelling, which was controlled by anti-inflammatory drugs. Moreover, the venom caused death, which was preceded by systemic inflammation and pulmonary hemorrhage. The venom was shown to be immunogenic, inducing a strong humoral immune response, with the production of antibodies able to recognize venom components with high molecular weight and to neutralize its lethal activity. Conclusions/Significance: The results obtained in this study demonstrate that N. annulifera venom contains toxins able to induce local and systemic inflammation, which can contribute to lung damage and death. Moreover, the venom is immunogenic, an important feature that must be considered during the production of a therapeutic anti-N. annulifera antivenom. [ABSTRACT FROM AUTHOR]

Introduction: Type 2 diabetes (T2D) is a major health priority worldwide and the majority of people with diabetes live with multimorbidity (MM) (the co-occurrence of ≥2 chronic conditions). The aim of this systematic review was to explore the association between MM and all-cause mortality and glycaemic outcomes in people with T2D. Methods: The search strategy centred on: T2D, MM, comorbidity, mortality and glycaemia. Databases searched: MEDLINE, EMBASE, CINAHL Complete, The Cochrane Library, and SCOPUS. Restrictions included: English language, quantitative empirical studies. Two reviewers independently carried out: abstract and full text screening, data extraction, and quality appraisal. Disagreements adjudicated by a third reviewer. Results: Of the 4882 papers identified; 41 met inclusion criteria. The outcome was all-cause mortality in 16 studies, glycaemia in 24 studies and both outcomes in one study. There were 28 longitudinal cohort studies and 13 cross-sectional studies, with the number of participants ranging from 96–892,223. Included studies were conducted in high or upper-middle-income countries. Fifteen of 17 studies showed a statistically significant association between increasing MM and higher mortality. Ten of 14 studies showed no significant associations between MM and HbA1c. Four of 14 studies found higher levels of MM associated with higher HbA1c. Increasing MM was significantly associated with hypoglycaemia in 9/10 studies. There was no significant association between MM and fasting glucose (one study). No studies explored effects on glycaemic variability. Conclusions: This review demonstrates that MM in T2D is associated with higher mortality and hypoglycaemia, whilst evidence regarding the association with other measures of glycaemic control is mixed. The current single disease focused approach to management of T2D seems inappropriate. Our findings highlight the need for clinical guidelines to support a holistic approach to the complex care needs of those with T2D and MM, accounting for the various conditions that people with T2D may be living with. Systematic review registration: International Prospective Register of Systematic Reviews CRD42017079500 [ABSTRACT FROM AUTHOR]

People in different subgroups age at different rates. Surveys containing biomarkers can be used to assess these subgroup differences. We illustrate this using hand-grip strength to produce an easily interpretable, physical-based measure that allows us to compare characteristic-based ages across educational subgroups in the United States. Hand-grip strength has been shown to be a good predictor of future mortality and morbidity, and therefore a useful indicator of population aging. Data from the Health and Retirement Survey (HRS) were used. Two education subgroups were distinguished, those with less than a high school diploma and those with more education. Regressions on hand-grip strength were run for each sex and race using age and education, their interactions and other covariates as independent variables. Ages of identical mean hand-grip strength across education groups were compared for people in the age range 60 to 80. The hand-grip strength of 65 year old white males with less education was the equivalent to that of 69.6 (68.2, 70.9) year old white men with more education, indicating that the more educated men had aged more slowly. This is a constant characteristic age, as defined in the Sanderson and Scherbov article “The characteristics approach to the measurement of population aging” published 2013 in Population and Development Review. Sixty-five year old white females with less education had the same average hand-grip strength as 69.4 (68.2, 70.7) year old white women with more education. African-American women at ages 60 and 65 with more education also aged more slowly than their less educated counterparts. African American men with more education aged at about the same rate as those with less education. This paper expands the toolkit of those interested in population aging by showing how survey data can be used to measure the differential extent of aging across subpopulations. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D.Methods and Findings: In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), "lipodystrophy-like" fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry.Conclusion: Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management. [ABSTRACT FROM AUTHOR]

Background: The Introduction of mobile health (mHealth) devices to health intervention studies challenges us as researchers to adapt how we analyse the impact of these technologies. For interventions involving chronic illness self-management, we must consider changes in behaviour in addition to changes in health. Fortunately, these mHealth technologies can record participants’ interactions via usage-logs during research interventions. Objective: The objective of this paper is to demonstrate the potential of analysing mHealth usage-logs by presenting an in-depth analysis as a preliminary study for using behavioural theories to contextualize the user-recorded results of mHealth intervention studies. We use the logs collected by persons with type 2 diabetes during a randomized controlled trial (RCT) as a use-case. Methods: The Few Touch Application was tested in a year-long intervention, which allowed participants to register and review their blood glucose, diet and physical activity, goals, and access general disease information. Usage-logs, i.e. logged interactions with the mHealth devices, were collected from participants (n = 101) in the intervention groups. HbA1c was collected (baseline, 4- and 12-months). Usage logs were categorized into registrations or navigations. Results: There were n = 29 non-mHealth users, n = 11 short-term users and n = 61 long-term users. Non-mHealth users increased (+0.33%) while Long-term users reduced their HbA1c (-0.86%), which was significantly different (P = .021). Long-term users significantly decreased their usage over the year (P < .001). K-means clustering revealed two clusters: one dominated by diet/exercise interactions (n = 16), and one dominated by BG interactions and navigations in general (n = 40). The only significant difference between these two clusters was that the first cluster spent more time on the goals functionalities than the second (P < .001). Conclusion: By comparing participants based upon their usage-logs, we were able to discern differences in HbA1c as well as usage patterns. This approach demonstrates the potential of analysing usage-logs to better understand how participants engage during mHealth intervention studies. [ABSTRACT FROM AUTHOR]

Because of the importance of bone in the biomedical, forensic and archaeological contexts, new investigation techniques are constantly required to better characterize bone ultrastructure. In the present paper, we provide an extended investigation of the vibrational features of bone tissue in the 0.1-3 THz frequency range by time-domain THz spectroscopy. Their assignment is supported by a combination of X-ray diffraction and DFT-normal modes calculations. We investigate the effect of heating on bone tissue and synthetic calcium-phosphates compounds with close structure and composition to bone mineral, including stoichiometric and non-stoichiometric hydroxyapatite (HA), tricalcium phosphate, calcium pyrophosphate and tetracalcium phosphate. We thus demonstrate that the narrow vibrational mode at 2.1 THz in bone samples exposed to thermal treatment above 750 °C arises from a lattice mode of stoichiometric HA. This feature is also observed in the other synthetic compounds, although weaker or broader, but is completely smeared out in the non-stoichiometric HA, close to natural bone mineral composition, or in synthetic poorly crystalline HA powder. The THz spectral range therefore provides a clear signature of the crystalline state of the investigated bone tissue and could, therefore be used to monitor or identify structural transitions occurring in bone upon heating. [ABSTRACT FROM AUTHOR]

Pain and inflammation are complex clinical conditions that are present in a wide variety of disorders. Most drugs used to treat pain and inflammation have potential side effects, which makes it necessary to search for new sources of bioactive molecules. In this paper, we describe the ability of LASSBio-1586, an N-acylhydrazone derivative, to attenuate nociceptive behavior and the inflammatory response in mice. Antinociceptive activity was evaluated through acetic acid-induced writhing and formalin-induced nociception tests. In these experimental models, LASSBio-1586 significantly (p<0.05) reduced nociceptive behavior. Several methods of acute and chronic inflammation induced by different chemical (carrageenan, histamine, croton oil, arachidonic acid) and physical (cotton pellet) agents were used to evaluate the anti-inflammatory effect of LASSBio-1586. LASSBio-1586 exhibited potent anti-inflammatory activity in all tests (p<0.05). Study of the mechanism of action demonstrated the possible involvement of the nitrergic, serotonergic and histamine signaling pathways. In addition, a molecular docking study was performed, indicating that LASSBio-1586 is able to block the COX-2 enzyme, reducing arachidonic acid metabolism and consequently decreasing the production of prostaglandins, which are important inflammatory mediators. In summary, LASSBio-1586 exhibited relevant antinociceptive and anti-inflammatory potential and acted on several targets, making it a candidate for a new multi-target oral anti-inflammatory drug. [ABSTRACT FROM AUTHOR]

How can we predict the occurrence of acute kidney injury (AKI) in cancer patients based on machine learning with serum creatinine data? Given irregular and heterogeneous clinical data, how can we make the most of it for accurate AKI prediction? AKI is a common and significant complication in cancer patients, and correlates with substantial morbidity and mortality. Since no effective treatment for AKI still exists, it is important to take timely preventive measures. While several approaches have been proposed for predicting AKI, their scope and applicability are limited as they either assume regular data measured over a short hospital stay, or do not fully utilize heterogeneous data. In this paper, we provide an AKI prediction model with a greater applicability, which relaxes the constraints of existing approaches, and fully utilizes irregular and heterogeneous data for learning the model. In a cohort of 21,022 cancer patients who were registered into Korea Central Cancer Registry (KCCR) in Seoul National University Hospital between January 1, 2004 and December 31, 2013, our method achieves 0.7892 precision, 0.7506 recall, and 0.7576 F-measure in predicting whether a patient will develop AKI during the next 14 days. [ABSTRACT FROM AUTHOR]

Triticum vulgare has been extensively used in traditional medicine thanks to its properties of accelerating tissue repair. The specific extract of Triticum vulgare manufactured by Farmaceutici Damor (TVE-DAMOR) is already present in some pharmaceutical formulations used in the treatment of decubitus ulcers, skin lesions and burns. It has been recently suggested that this Triticum vulgare extract may possess potential anti-inflammatory properties. In the light of these premises the aim of the present paper was to verify the anti-inflammatory role of TVE, using the LPS-stimulated microglia model of inflammation. In particular the effect of different concentrations of TVE on the release of several mediators of inflammation such as nitric oxide, IL-6, PGE2 and TNF alpha was evaluated. More important, the anti-inflammatory effect of TVE was confirmed also in primary rat microglia cultures. The results of the present study show that TVE exerts anti-inflammatory properties since it reduces the release of all the evaluated markers of inflammation, such as NO, IL6, TNF alpha and PGE2 in LPS-activated BV2 microglial cells. Intriguingly, TVE reduced microglia activation and NO release also in primary microglia. Indeed, to verify the pathway of modulation of the inflammatory markers reported above, we found that TVE restores the cytoplasmic expression of p65 protein, kwown as specific marker associated with activation of inflammatory response. The evidence for an inhibitory activity on inflammation of this specific extract of Triticum vulgare may open the way to the possibility of a therapeutical use of the Triticum vulgare extract as an anti-inflammatory compound in certain pathological states such as burns, decubitus ulcers, folliculitis and inflammation of peripheral nerve. [ABSTRACT FROM AUTHOR]

Due to its strong proliferation-reducing effects on keratinocytes, and also anti-inflammatory properties, the isoflavone genistein has already been proposed as a possible antipsoriatic compound. As there is still no detailed information on this topic, we examined the effects of genistein by using an in vitro model of both, normal and “psoriasis-like” keratinocytes at this stage of our work exhaustively testing the selected flavonoid in a mono-treated experimental design. Gene expression studies revealed transcriptional changes that confirms known disease-associated pathways and highlights many psoriasis-related genes. Our results suggested that aberrant expression of genes contributing to the progress of psoriasis could be improved by the action of genistein. Genistein prevented “cytokine mix” as well as TNF-α-induced NF-κB nuclear translocation, with no effect on the PI3K signaling cascade, indicating the luck of turning this pathway into NF-κB activation. It could have attenuated TNF-α and LPS-induced inflammatory responses by suppressing ROS activation. Regardless of the type of keratinocyte stimulation used, reduction of cytokine IL-8, IL-20 and CCL2 production (both at RNA and protein level) following genistein treatment was visible. Because investigations of other groups supported our commentary on potential administration of genistein as a potential weapon in the armamentarium against psoriasis, it is believed that this paper should serve to encourage researchers to conduct further studies on this subject. [ABSTRACT FROM AUTHOR]

Food can trigger a diverse array of symptoms in food allergic individuals from isolated local symptoms affecting skin or gut to multi-system severe reactions (systemic anaphylaxis). Although we know that gastrointestinal and systemic manifestations of food allergy are mediated by tissue mast cells (MCs), it is not clear why allergen exposure by the oral route can result in such distinct clinical manifestations. Our aim was to assess the contribution of mast cell subsets to different manifestations of food allergy. We used two common models of IgE-mediated food allergy, one resulting in systemic anaphylaxis and the other resulting in acute gastrointestinal symptoms, to study the immune basis of allergic reactions. We used responders and non-responders in each model system, as well as naïve controls to identify the association of mast cell activation with clinical reactivity rather than sensitization. Systemic anaphylaxis was uniquely associated with activation of connective tissue mast cells (identified by release of mouse mast cell protease (MMCP) -7 into the serum) and release of histamine, while activation of mucosal mast cells (identified by release of MMCP-1 in the serum) did not correlate with symptoms. Gastrointestinal manifestations of food allergy were associated with an increase of MMCP-1-expressing mast cells in the intestine, and evidence of both mucosal and connective tissue mast cell activation. The data presented in this paper demonstrates that mast cell heterogeneity is an important contributor to manifestations of food allergy, and identifies the connective tissue mast cell subset as key in the development of severe systemic anaphylaxis. [ABSTRACT FROM AUTHOR]

To study the genetic diversity of enterovirus G (EV-G) among Japanese pigs, metagenomics sequencing was performed on fecal samples from pigs with or without diarrhea, collected between 2014 and 2016. Fifty-nine EV-G sequences, which were >5,000 nucleotides long, were obtained. By complete VP1 sequence analysis, Japanese EV-G isolates were classified into G1 (17 strains), G2 (four strains), G3 (22 strains), G4 (two strains), G6 (two strains), G9 (six strains), G10 (five strains), and a new genotype (one strain). Remarkably, 16 G1 and one G2 strain identified in diarrheic (23.5%; four strains) or normal (76.5%; 13 strains) fecal samples possessed a papain-like cysteine protease (PL-CP) sequence, which was recently found in the USA and Belgium in the EV-G genome, at the 2C–3A junction site. This paper presents the first report of the high prevalence of viruses carrying PL-CP in the EV-G population. Furthermore, possible inter- and intragenotype recombination events were found among EV-G strains, including G1-PL-CP strains. Our findings may advance the understanding of the molecular epidemiology and genetic evolution of EV-Gs. [ABSTRACT FROM AUTHOR]

The identification of microbial species has depended predominantly upon culture-based techniques. However, the difficulty with which types of organisms are cultured implies that the grown species may be overrepresented by both cultivation and plate counts. In recent years, culture-independent analysis using high-throughput sequencing has been advocated for use as a point-of-care diagnostic tool. Although it offers a rapid and unbiased survey to characterize the pathogens in clinical specimens, its accuracy is reduced by the high level of contamination of human DNA. In this paper, we propose using a culture-independent analysis for a Klebsiella pneumoniae clinical strain within a liver abscess using nanopore sequencing. Owing to the highly-contaminated cell population within a liver abscess, we managed to reduce the confounding effects of human DNA through the use of DNase and differential centrifugation. Genomic DNA was sequenced through the use of Nanopore MinION sequencer and analyzed using a suite of bioinformatics approaches. K. pneumoniae was successfully identified along with antibiotic-resistant genes. Our results indicate that, by integrating real-time nanopore sequencing and bioinformatics software, real-time pathogen identification in a liver abscess can be achieved. [ABSTRACT FROM AUTHOR]

The consolidated way of diagnosing and treating osteoporosis in order to prevent fragility fractures has recently been questioned by some papers, which complained of overdiagnosis and consequent overtreatment of this pathology with underestimating other causes of the fragility fractures, like falls. A new clinical approach is proposed for identifying the subgroup of patients prone to fragility fractures. This retrospective observational study was conducted from January to June 2015 at the Nuclear Medicine-Bone Metabolic Unit of the of the Fondazione IRCCS Ca' Granda, Milan, Italy. An Italian population of 125 consecutive postmenopausal women was investigated for bone quantity and bone quality. Patients with neurological diseases regarding balance and vestibular dysfunction, sarcopenia, past or current history of diseases and use of drugs known to affect bone metabolism were excluded. Dual X-ray absorptiometry was used to assess bone quantity (bone mineral density) and bone quality (trabecular bone score and bone strain). Biochemical markers of bone turnover (type I collagen carboxy-terminal telopeptide, alkaline phosphatase, vitamin D) have been measured. Morphometric fractures have been searched by spine radiography. Balance was evaluated by the Romberg test. The data were evaluated with the neural network analysis using the Auto Contractive Map algorithm. The resulting semantic map shows the Minimal Spanning Tree and the Maximally Regular Graph of the interrelations between bone status parameters, balance conditions and fractures of the studied population. A low fracture risk seems to be related to a low carboxy-terminal cross-linking telopeptide of type I collagen level, whereas a positive Romberg test, together with compromised bone trabecular microarchitecture DXA parameters, appears to be strictly connected with fragility fractures. A simple assessment of the risk of fragility fracture is proposed in order to identify those frail patients at risk for osteoporotic fractures, who may have the best benefit from a pharmacological and physiotherapeutic approach. [ABSTRACT FROM AUTHOR]

The multiple extremes resistant bacterium Deinococcus radiodurans is able to withstand harsh conditions of simulated outer space environment. The Tanpopo orbital mission performs a long-term space exposure of D. radiodurans aiming to investigate the possibility of interplanetary transfer of life. The revealing of molecular machinery responsible for survivability of D. radiodurans in the outer space environment can improve our understanding of underlying stress response mechanisms. In this paper, we have evaluated the molecular response of D. radiodurans after the exposure to space-related conditions of UVC irradiation and vacuum. Notably, scanning electron microscopy investigations showed that neither morphology nor cellular integrity of irradiated cells was affected, while integrated proteomic and metabolomic analysis revealed numerous molecular alterations in metabolic and stress response pathways. Several molecular key mechanisms of D. radiodurans, including the tricarboxylic acid cycle, the DNA damage response systems, ROS scavenging systems and transcriptional regulators responded in order to cope with the stressful situation caused by UVC irradiation under vacuum conditions. These results reveal the effectiveness of the integrative proteometabolomic approach as a tool in molecular analysis of microbial stress response caused by space-related factors. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to systematically review intervention studies on self-management of type 2 diabetes in Gulf Cooperation Council (GCC) countries to determine the most effective self-management strategies for individuals with type 2 diabetes in this region. Methods: A search strategy was developed using multiple databases: Medline and Embase (via Ovid), CINAHL (via EBSCO), and PubMed. Study and intervention characteristics, intervention structure, content, cultural adaptation, and outcomes were extracted from the included studies. To be included in the review the studies should have met the following criteria: have examined the effectiveness of at least one intervention involving a type 2 DSME programme, have involved participants over 18 years old diagnosed with type 2 diabetes, have taken place to in a GCC country, have a study design that was observational, quasi-experimental or controlled, have reported at least one individual and have a quantitative outcome. A narrative data synthesis was used to describe the studies and comment on their methodological quality. Results: Of the 737 retrieved papers, only eight met the inclusion criteria. Only one study was a randomised controlled trial. A statistically significant improvement in HbA1c was reported in five of the eight studies. There was a significant improvement in physical activity levels as reported in four of the eight studies. Only three studies referred to aspects of cultural design or adaptation of the intervention implemented. Conclusions: Self-management interventions may have a positive impact on HbA1 levels in patients with type 2 diabetes in the GCC area. A greater emphasis placed on culturally appropriate self-management programmes may improve the effectiveness of self-management interventions for adults with type 2 diabetes in the GCC. [ABSTRACT FROM AUTHOR]

Although leishmaniases are responsible for high morbidity and mortality all over the world, no really satisfying treatment exists. Furthermore, the corresponding parasite Leishmania undergoes a very characteristic form of programmed cell death. Indeed, different stimuli can induce morphological and biochemical apoptotic-like features. However, the key proteins involved in mammal apoptosis, such as caspases and death receptors, are not encoded in the genome of this parasite. Currently, little is known about Leishmania apoptosis, notably owing to the lack of specific tools for programmed cell death analysis in these parasites. Furthermore, there is a need for a better understanding of Leishmania programmed cell death in order (i) to better understand the role of apoptosis in unicellular organisms, (ii) to better understand apoptosis in general through the study of an ancestral eukaryote, and (iii) to identify new therapeutic targets against leishmaniases. To advance understanding of apoptosis in Leishmania, in this study we developed a new tool based on the quantification of calcein and propidium iodide by flow cytometry. This double labeling can be employed to distinguish early apoptosis, late apoptosis and necrosis in Leishmania live cells with a very simple and rapid assay. This paper should, therefore, be of interest for people working on Leishmania and related parasites. [ABSTRACT FROM AUTHOR]

In China, food safety problems have occurred frequently in the past ten years, causing great concern for the public. Adolescents, with higher exposure to problematic food, represent a unique target for interventions aimed at risk reduction. To understand their food safety knowledge, attitude and practice, a cross-sectional survey using paper questionnaire was carried out among 4,220 students (median age of 14 years, 50.3% females) from nine secondary schools in 3 districts of Beijing. The findings showed that the majority of respondents (42.0%) had a high knowledge level. Significant association was found between food safety knowledge score (median = 11, IQR:9–13) and demographic characteristics of region, school type, residence type, habit of smoking and alcohol use, academic record and parents’ education background. In terms of attitude and practice, only 17% of those surveyed regarded China’s food safety situation as good, 53.6% regarded it as worrying; almost all students (96.5%) did pay attention to food safety; 95.3% of the students had worried about the safety of the food provided by the small restaurants and street peddlers, but in reality, as many as 69.4% often or occasionally bought food from peddlers around their campuses and nearly half continued the consumption of such food in spite of worrying about its safety problems. Overall, the food safety knowledge among Beijing secondary school students was relatively good. They did not show much confidence in the country’s food safety situation, but many aware of the safety issues did not bother to change or take action. The study suggests that more systematic and targeted education on food safety is necessary for this age group. [ABSTRACT FROM AUTHOR]

Patients with chronic kidney disease (CKD) have an increased incidence of cardiovascular events (CVE). The contribution of subclinical atheromatosis extent, including femoral arteries, to CVE in CKD patients has not been investigated. In this paper, we examine the prognostic value of subclinical atheromatosis extent, assessed as the number of arterial territories with plaque, in predicting the incidence of major and minor CVE. The NEFRONA is a multicenter, prospective cohorts study that recruited 2445 CKD subjects and 559 controls, free from previous cardiovascular disease, in 81 medical centers across Spain. The presence of atheroma plaque was assessed by arterial ultrasound in ten arterial territories (carotid and femoral). The predictive power of the presence or absence of atheroma plaque in any territory was compared with the quantification of atheroma extent as the number of territories with plaque. During the median follow up of 48 months, 216 CVE were reported. Factors predicting the incidence of CVE in the whole cohort were being male, CKD patient, lower levels of 25(OH) vitamin D, higher levels of cholesterol and the extent of subclinical atheromatosis, yielding a higher concordance (C) index than the presence or absence of plaque. In stratified analysis including specific factors of CKD patients not on dialysis, the variables predicting CVE were the same as in the whole cohort, plus higher levels of potassium. Again, the inclusion of the information about atheromatosis as number of territories with plaque, presented a higher C index than the presence or absence of plaque. In the dialysis population, significant variables were older age, diabetes, dialysis vintage and higher levels of cholesterol and phosphate. In this case the higher C index was obtained with the information about plaque presence. Subclinical atheromatosis extent, including femoral arteries, influences CVE in CKD and its detection could improve the prediction of cardiovascular events. [ABSTRACT FROM AUTHOR]

This paper presents the precise dosimetry for highly resonant wireless power transfer (HR-WPT) system using an anatomically realistic human voxel model. The dosimetry for the HR-WPT system designed to operate at 13.56 MHz frequency, which one of the ISM band frequency band, is conducted in the various distances between the human model and the system, and in the condition of alignment and misalignment between transmitting and receiving circuits. The specific absorption rates in the human body are computed by the two-step approach; in the first step, the field generated by the HR-WPT system is calculated and in the second step the specific absorption rates are computed with the scattered field finite-difference time-domain method regarding the fields obtained in the first step as the incident fields. The safety compliance for non-uniform field exposure from the HR-WPT system is discussed with the international safety guidelines. Furthermore, the coupling factor concept is employed to relax the maximum allowable transmitting power. Coupling factors derived from the dosimetry results are presented. In this calculation, the external magnetic field from the HR-WPT system can be relaxed by approximately four times using coupling factor in the worst exposure scenario. [ABSTRACT FROM AUTHOR]

Native transthyretin (TTR) homotetramer dissociation is the first step of the fibrils formation process in amyloid disease. A large number of specific point mutations that destabilize TTR quaternary structure have shown pro-amyloidogenic effects. Besides, several compounds have been proposed as drugs in the therapy of TTR amyloidosis due to their TTR tetramer binding affinities, and therefore, contribution to its integrity. In the present paper we have explored key positions sustaining TTR tetramer dynamical stability. We have identified positions whose mutations alter the most the TTR tetramer equilibrium dynamics based on normal mode analysis and their response to local perturbations. We have found that these positions are mostly localized at β-strands E and F and EF-loop. The monomer-monomer interface is pointed out as one of the most vulnerable regions to mutations that lead to significant changes in the TTR-tetramer equilibrium dynamics and, therefore, induces TTR amyloidosis. Besides, we have found that mutations on residues localized at the dimer-dimer interface and/or at the T4 hormone binding site destabilize the tetramer more than the average. Finally, we were able to compare several compounds according to their effect on vibrations associated to the ligand binding. Our ligand comparison is discussed and analyzed in terms of parameters and measurements associated to TTR-ligand binding affinities and the stabilization of its native state. [ABSTRACT FROM AUTHOR]

Introduction: This paper investigates the role of Group II Secretory Phospholipase A2 (sPLA2-IIA) as a biomarker for the diagnosis of sepsis and bacterial infection in adults. Sepsis and bacterial infection are common problems encountered by patients in the hospital and often carry adverse outcomes if not managed early. Methods: Two independent reviewers conducted a comprehensive search using Ovid MEDLINE published from years 1993 to 2016 and SCOPUS published from year 1985 to 2017 to screen for relevant studies. The main inclusion criteria included adult subjects, patients with suspected or confirmed signs of infection and relevant outcomes which looked into the role of sPLA2-IIA in detecting the presence of sepsis and bacterial infection in the subjects. Results and discussion: Four studies met the inclusion criteria. SPLA2-IIA was found to be effective in detecting the presence of sepsis and bacterial infection in adults. The levels of serum sPLA2-IIA also correlated well with the presence of sepsis and bacterial infection. Conclusion: This systematic review highlights the role of sPLA2-IIA as a reliable tool to diagnose sepsis and bacterial infection in adult patients. Nonetheless, further studies should be done in the future to provide more compelling evidence on its application in the clinical setting. [ABSTRACT FROM AUTHOR]

Blood oxygenation mapping by the means of optical oximetry is of significant importance in clinical trials. This paper uses hyperspectral imaging technology to obtain in vivo images for blood oxygenation detection. The experiment involves dorsal skin fold window chamber preparation which was built on adult (8–10 weeks of age) female BALB/c nu/nu mice and in vivo image acquisition which was performed by hyperspectral imaging system. To get the accurate spatial and spectral information of targets, an automatic registration scheme is proposed. An adaptive feature detection method which combines the local threshold method and the level-set filter is presented to extract target vessels. A reliable feature matching algorithm with the correlative information inherent in hyperspectral images is used to kick out the outliers. Then, the registration images are used for blood oxygenation mapping. Registration evaluation results show that most of the false matches are removed and the smooth and concentrated spectra are obtained. This intensity invariant feature detection with outliers-removing feature matching proves to be effective in hyperspectral vessel image registration. Therefore, in vivo hyperspectral imaging system by the assistance of the proposed registration scheme provides a technique for blood oxygenation research. [ABSTRACT FROM AUTHOR]