A Co-Adaptive Brain-Computer Interface for End Users with Severe Motor Impairment

Co-adaptive training paradigms for event-related desynchronization (ERD) based brain-computer interfaces (BCI) have proven effective for healthy users. As of yet, it is not clear whether co-adaptive training paradigms can also benefit users with severe motor impairment. The primary goal of our paper was to evaluate a novel cue-guided, co-adaptive BCI training paradigm with severely impaired volunteers. The co-adaptive BCI supports a non-control state, which is an important step toward intuitive, self-paced control. A secondary aim was to have the same participants operate a specifically designed self-paced BCI training paradigm based on the auto-calibrated classifier. The co-adaptive BCI analyzed the electroencephalogram from three bipolar derivations (C3, Cz, and C4) online, while the 22 end users alternately performed right hand movement imagery (MI), left hand MI and relax with eyes open (non-control state). After less than five minutes, the BCI auto-calibrated and proceeded to provide visual feedback for the MI task that could be classified better against the non-control state. The BCI continued to regularly recalibrate. In every calibration step, the system performed trial-based outlier rejection and trained a linear discriminant analysis classifier based on one auto-selected logarithmic band-power feature. In 24 minutes of training, the co-adaptive BCI worked significantly (p = 0.01) better than chance for 18 of 22 end users. The self-paced BCI training paradigm worked significantly (p = 0.01) better than chance in 11 of 20 end users. The presented co-adaptive BCI complements existing approaches in that it supports a non-control state, requires very little setup time, requires no BCI expert and works online based on only two electrodes. The preliminary results from the self-paced BCI paradigm compare favorably to previous studies and the collected data will allow to further improve self-paced BCI systems for disabled users.     

Linguistic Traces of a Scientific Fraud: The Case of Diederik Stapel

When scientists report false data, does their writing style reflect their deception? In this study, we investigated the linguistic patterns of fraudulent (N  =  24; 170,008 words) and genuine publications (N  =  25; 189,705 words) first-authored by social psychologist Diederik Stapel. The analysis revealed that Stapel''s fraudulent papers contained linguistic changes in science-related discourse dimensions, including more terms pertaining to methods, investigation, and certainty than his genuine papers. His writing style also matched patterns in other deceptive language, including fewer adjectives in fraudulent publications relative to genuine publications. Using differences in language dimensions we were able to classify Stapel''s publications with above chance accuracy. Beyond these discourse dimensions, Stapel included fewer co-authors when reporting fake data than genuine data, although other evidentiary claims (e.g., number of references and experiments) did not differ across the two article types. This research supports recent findings that language cues vary systematically with deception, and that deception can be revealed in fraudulent scientific discourse.     

Identifiable Images of Bystanders Extracted from Corneal Reflections

Criminal investigations often use photographic evidence to identify suspects. Here we combined robust face perception and high-resolution photography to mine face photographs for hidden information. By zooming in on high-resolution face photographs, we were able to recover images of unseen bystanders from reflections in the subjects'' eyes. To establish whether these bystanders could be identified from the reflection images, we presented them as stimuli in a face matching task (Experiment 1). Accuracy in the face matching task was well above chance (50%), despite the unpromising source of the stimuli. Participants who were unfamiliar with the bystanders'' faces (n = 16) performed at 71% accuracy [t(15) = 7.64, p<.0001, d = 1.91], and participants who were familiar with the faces (n = 16) performed at 84% accuracy [t(15) = 11.15, p<.0001, d = 2.79]. In a test of spontaneous recognition (Experiment 2), observers could reliably name a familiar face from an eye reflection image. For crimes in which the victims are photographed (e.g., hostage taking, child sex abuse), reflections in the eyes of the photographic subject could help to identify perpetrators.     

Role of HLA-DP Polymorphisms on Chronicity and Disease Activity of Hepatitis B Infection in Southern Chinese

Background and Aims

The association between HLA-DP single nucleotide polymorphisms (SNPs) and chronic hepatitis B virus (HBV) infection varies between different populations. We aimed to study the association between HLA-DP SNPs and HBV infection and disease activity in the Chinese population of Hong Kong.

Methods

We genotyped SNPs rs3077 (near HLA-DPA1) and rs9277378 and rs3128917 (both near HLA-DPB1) in 500 HBV carriers (hepatitis B surface antigen [HBsAg]-positive), 245 non-HBV infected controls (HBsAg- and antibody to hepatitis B core protein [anti-HBc]-negative), and 259 subjects with natural HBV clearance (HBsAg-negative, anti-HBc-positive). Inactive HBV carriers state was defined by HBV DNA levels <2,000 IU/ml and persistently normal alanine aminotransferase level for least 12 months.

Results

Compared to the non-HBV infected subjects, the HBV carriers had a significantly lower frequency of the rs3077 T allele (p = 0.0040), rs9277378 A allele (p = 0.0068) and a trend for lower frequency of rs3128917 T allele (p = 0.054). These alleles were associated with an increased chance of HBV clearance (rs3077: OR = 1.41, p = 0.0083; rs9277378: OR = 1.61, p = 0.00011; rs3128917: OR = 1.54, p = 0.00017). Significant associations between HLA-DP genotypes and HBV clearance were also found under different genetic models. Haplotype TAT was associated with an increased chance of HBV clearance (OR = 1.64, p = 0.0013). No association was found between these SNPs and HBV disease activity.

Conclusion

HLA-DP SNPs rs3077, rs9277378 and rs3128917 were associated with chronicity of HBV disease in the Chinese. Further studies are required to determine whether these SNPs influence the disease endemicity in different ethnic populations.     

Plasma Level of Adrenomedullin Is Influenced by a Single Nucleotide Polymorphism in the Adiponectin Gene

Objective

Adrenomedullin (ADM) and adiponectin are both involved in inflammation and cardiovascular diseases. The plasma levels of these peptides are influenced by single nucleotide polymorphisms (SNPs) in the ADM and ADIPOQ genes respectively. There is some evidence that ADM may regulate adiponectin gene expression, but whether adiponectin can regulate ADM expression is unclear, and was therefore investigated.

Methods

Plasma ADM level was measured in 476 subjects in the Hong Kong Cardiovascular Risk Factor Prevalence Study-2 (CRISPS2). We genotyped them for 2 ADIPOQ SNPs that are known to be associated with plasma adiponectin level.

Results

The minor allele frequencies of ADIPOQ SNPs rs182052 and rs12495941 were 40.6% and 42.2% respectively. Plasma ADM level was significantly associated with rs182052 after adjusting for age and sex (β = 0.104, P = 0.023) but not with rs12495941 (β = 0.071, P = 0.120). In multivariate analysis, plasma ADM level increased with the number of minor alleles of rs182052 (P = 0.013). Compared to subjects with GG genotype, subjects with AA genotype had 17.7% higher plasma ADM level (95% CI: 3.6%–33.7%). Subgroup analysis revealed that the association was significant in diabetic patients (β = 0.344, P = 0.001) but not in non-diabetic subjects.

Conclusion

Plasma ADM level is related to SNP rs182052 in the ADIPOQ gene. Our findings provide new evidence of the interplay between these two important peptides in cardiovascular disease and diabetes. Knowing the genotype may help to refine the interpretation of these biomarkers.     

Automatic Classification of Early Parkinson's Disease with Multi-Modal MR Imaging

Background

In recent years, neuroimaging has been increasingly used as an objective method for the diagnosis of Parkinson''s disease (PD). Most previous studies were based on invasive imaging modalities or on a single modality which was not an ideal diagnostic tool. In this study, we developed a non-invasive technology intended for use in the diagnosis of early PD by integrating the advantages of various modals.

Materials and Methods

Nineteen early PD patients and twenty-seven normal volunteers participated in this study. For each subject, we collected resting-state functional magnetic resonance imaging (rsfMRI) and structural images. For the rsfMRI images, we extracted the characteristics at three different levels: ALFF (amplitude of low-frequency fluctuations), ReHo (regional homogeneity) and RFCS (regional functional connectivity strength). For the structural images, we extracted the volume characteristics from the gray matter (GM), the white matter (WM) and the cerebrospinal fluid (CSF). A two-sample t-test was used for the feature selection, and then the remaining features were fused for classification. Finally a classifier for early PD patients and normal control subjects was identified from support vector machine training. The performance of the classifier was evaluated using the leave-one-out cross-validation method.

Results

Using the proposed methods to classify the data set, good results (accuracy  = 86.96%, sensitivity  = 78.95%, specificity  = 92.59%) were obtained.

Conclusions

This method demonstrates a promising diagnosis performance by the integration of information from a variety of imaging modalities, and it shows potential for improving the clinical diagnosis and treatment of PD.     

A Booklet on Participants’ Rights to Improve Consent for Clinical Research: A Randomized Trial

Objective

Information on the rights of subjects in clinical trials has become increasingly complex and difficult to understand. This study evaluates whether a simple booklet which is relevant to all research studies improves the understanding of rights needed for subjects to provide informed consent.

Methods

21 currently used informed consent forms (ICF) from international clinical trials were separated into information related to the specific research study, and general information on participants’ rights. A booklet designed to provide information on participants’ rights which used simple language was developed to replace this information in current ICF’s Readability of each component of ICF’s and the booklet was then assessed using the Flesch-Kincaid Reading ease score (FK). To further evaluate the booklet 282 hospital inpatients were randomised to one of three ways to present research information; a standard ICF, the booklet combined with a short ICF, or the booklet combined with a simplified ICF. Comprehension of information related to the research proposal and to participant’s rights was assessed by questionnaire.

Results

Information related to participants’ rights contributed an average of 44% of the words in standard ICFs, and was harder to read than information describing the clinical trial (FK 25 versus (vs.) 41 respectively, p = 0.0003). The booklet reduced the number of words and improved FK from 25 to 42. The simplified ICF had a slightly higher FK score than the standard ICF (50 vs. 42). Comprehension assessed in inpatients was better for the booklet and short ICF 62%, (95% confidence interval (CI) 56 to 67) correct, or simplified ICF 62% (CI 58 to 68) correct compared to 52%, (CI 47 to 57) correct for the standard ICF, p = 0.009. This was due to better understanding of questions on rights (62% vs. 49% correct, p = 0.0008). Comprehension of study related information was similar for the simplified and standard ICF (60% vs. 64% correct, p = 0.68).

Conclusions

A booklet provides a simple consistent approach to providing information on participant rights which is relevant to all research studies, and improves comprehension of patients who typically participate in clinical trials.     

Computerized Cognitive Training in Cognitively Healthy Older Adults: A Systematic Review and Meta-Analysis of Effect Modifiers

Background

New effective interventions to attenuate age-related cognitive decline are a global priority. Computerized cognitive training (CCT) is believed to be safe and can be inexpensive, but neither its efficacy in enhancing cognitive performance in healthy older adults nor the impact of design factors on such efficacy has been systematically analyzed. Our aim therefore was to quantitatively assess whether CCT programs can enhance cognition in healthy older adults, discriminate responsive from nonresponsive cognitive domains, and identify the most salient design factors.

Methods and Findings

We systematically searched Medline, Embase, and PsycINFO for relevant studies from the databases'' inception to 9 July 2014. Eligible studies were randomized controlled trials investigating the effects of ≥4 h of CCT on performance in neuropsychological tests in older adults without dementia or other cognitive impairment. Fifty-two studies encompassing 4,885 participants were eligible. Intervention designs varied considerably, but after removal of one outlier, heterogeneity across studies was small (I ² = 29.92%). There was no systematic evidence of publication bias. The overall effect size (Hedges'' g, random effects model) for CCT versus control was small and statistically significant, g = 0.22 (95% CI 0.15 to 0.29). Small to moderate effect sizes were found for nonverbal memory, g = 0.24 (95% CI 0.09 to 0.38); verbal memory, g = 0.08 (95% CI 0.01 to 0.15); working memory (WM), g = 0.22 (95% CI 0.09 to 0.35); processing speed, g = 0.31 (95% CI 0.11 to 0.50); and visuospatial skills, g = 0.30 (95% CI 0.07 to 0.54). No significant effects were found for executive functions and attention. Moderator analyses revealed that home-based administration was ineffective compared to group-based training, and that more than three training sessions per week was ineffective versus three or fewer. There was no evidence for the effectiveness of WM training, and only weak evidence for sessions less than 30 min. These results are limited to healthy older adults, and do not address the durability of training effects.

Conclusions

CCT is modestly effective at improving cognitive performance in healthy older adults, but efficacy varies across cognitive domains and is largely determined by design choices. Unsupervised at-home training and training more than three times per week are specifically ineffective. Further research is required to enhance efficacy of the intervention. Please see later in the article for the Editors'' Summary     

Assessment of Metabolomic and Proteomic Biomarkers in Detection and Prognosis of Progression of Renal Function in Chronic Kidney Disease

Chronic kidney disease (CKD) is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR) at mild (59.9±16.5 mL/min/1.73 m²; n = 10) or advanced (8.9±4.5 mL/min/1.73 m²; n = 10) CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = −0.8031; p<0.0001 and ρ = −0.6009; p = 0.0019, respectively). Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = −0.6557; p = 0.0001 and ρ = −0.6574; p = 0.0005). A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = −0.7752; p<0.0001 and ρ = −0.8400; p<0.0001). The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In conclusion, we found excellent association of plasma and urinary metabolites and urinary peptides with kidney function, and disease progression, but no added value in combining the different biomarkers data.     

α-Synuclein and Anti-α-Synuclein Antibodies in Parkinson’s Disease,Atypical Parkinson Syndromes,REM Sleep Behavior Disorder,and Healthy Controls

α-synuclein is thought to play a key role in Parkinson’s disease (PD) because it is the major protein in Lewy bodies, and because its gene mutations, duplication, and triplication are associated with early-onset PD. There are conflicting reports as to whether serum and plasma concentrations of α-synuclein and anti-α-synuclein antibodies differ between PD and control subjects. The objectives of this study were to compare the levels of α-synuclein and its antibodies between individuals with typical PD (n = 14), atypical Parkinson syndromes (n = 11), idiopathic rapid eye movement sleep behavior disorder (n = 10), and healthy controls (n = 9), to assess the strength of association between these serum proteins, and to determine group sizes needed for a high probability (80% power) of detecting statistical significance for 25% or 50% differences between typical PD and control subjects for these measurements. Analysis of log-transformed data found no statistically significant differences between groups for either α-synuclein or its antibodies. The concentrations of these proteins were weakly correlated (Spearman rho = 0.16). In subjects with typical PD and atypical Parkinson syndromes, anti-α-synuclein antibody levels above 1.5 µg/ml were detected only in subjects with no more than four years of clinical disease. Power analysis indicated that 236 and 73 samples per group would be required for an 80% probability that 25% and 50% differences, respectively, in mean α-synuclein levels between typical PD and control subjects would be statistically significant; for anti-α-synuclein antibodies, 283 and 87 samples per group would be required. Our findings are consistent with those previous studies which suggested that serum concentrations of α-synuclein and its antibodies are not significantly altered in PD.     

Effects of Barbell Deadlift Training on Submaximal Motor Unit Firing Rates for the Vastus Lateralis and Rectus Femoris

Previous investigations that have studied motor unit firing rates following strength training have been limited to small muscles, isometric training, or interventions involving exercise machines. We examined the effects of ten weeks of supervised barbell deadlift training on motor unit firing rates for the vastus lateralis and rectus femoris during a 50% maximum voluntary contraction (MVC) assessment. Twenty-four previously untrained men (mean age  = 24 years) were randomly assigned to training (n = 15) or control (n = 9) groups. Before and following the intervention, the subjects performed isometric testing of the right knee extensors while bipolar surface electromyographic signals were detected from the two muscles. The signals were decomposed into their constituent motor unit action potential trains, and motor units that demonstrated accuracy levels less than 92.0% were not considered for analysis. One thousand eight hundred ninety-two and 2,013 motor units were examined for the vastus lateralis and rectus femoris, respectively. Regression analyses were used to determine the linear slope coefficients (pulses per second [pps]/% MVC) and y-intercepts (pps) of the mean firing rate and firing rate at recruitment versus recruitment threshold relationships. Deadlift training significantly improved knee extensor MVC force (Cohen''s d = .70), but did not influence force steadiness. Training had no influence on the slopes and y-intercepts for the mean firing rate and firing rate at recruitment versus recruitment threshold relationships. In agreement with previous cross-sectional comparisons and randomized control trials, our findings do not support the notion that strength training affects the submaximal control of motor units.     

Intersession Consistency of Single-Trial Classification of the Prefrontal Response to Mental Arithmetic and the No-Control State by NIRS

Near-infrared spectroscopy (NIRS) has been recently investigated for use in noninvasive brain-computer interface (BCI) technologies. Previous studies have demonstrated the ability to classify patterns of neural activation associated with different mental tasks (e.g., mental arithmetic) using NIRS signals. Though these studies represent an important step towards the realization of an NIRS-BCI, there is a paucity of literature regarding the consistency of these responses, and the ability to classify them on a single-trial basis, over multiple sessions. This is important when moving out of an experimental context toward a practical system, where performance must be maintained over longer periods. When considering response consistency across sessions, two questions arise: 1) can the hemodynamic response to the activation task be distinguished from a baseline (or other task) condition, consistently across sessions, and if so, 2) are the spatiotemporal characteristics of the response which best distinguish it from the baseline (or other task) condition consistent across sessions. The answers will have implications for the viability of an NIRS-BCI system, and the design strategies (especially in terms of classifier training protocols) adopted. In this study, we investigated the consistency of classification of a mental arithmetic task and a no-control condition over five experimental sessions. Mixed model linear regression on intrasession classification accuracies indicate that the task and baseline states remain differentiable across multiple sessions, with no significant decrease in accuracy (p = 0.67). Intersession analysis, however, revealed inconsistencies in spatiotemporal response characteristics. Based on these results, we investigated several different practical classifier training protocols, including scenarios in which the training and test data come from 1) different sessions, 2) the same session, and 3) a combination of both. Results indicate that when selecting optimal classifier training protocols for NIRS-BCI, a compromise between accuracy and convenience (e.g., in terms of duration/frequency of training data collection) must be considered.     

From Genus to Phylum: Large-Subunit and Internal Transcribed Spacer rRNA Operon Regions Show Similar Classification Accuracies Influenced by Database Composition

We compared the classification accuracy of two sections of the fungal internal transcribed spacer (ITS) region, individually and combined, and the 5′ section (about 600 bp) of the large-subunit rRNA (LSU), using a naive Bayesian classifier and BLASTN. A hand-curated ITS-LSU training set of 1,091 sequences and a larger training set of 8,967 ITS region sequences were used. Of the factors evaluated, database composition and quality had the largest effect on classification accuracy, followed by fragment size and use of a bootstrap cutoff to improve classification confidence. The naive Bayesian classifier and BLASTN gave similar results at higher taxonomic levels, but the classifier was faster and more accurate at the genus level when a bootstrap cutoff was used. All of the ITS and LSU sections performed well (>97.7% accuracy) at higher taxonomic ranks from kingdom to family, and differences between them were small at the genus level (within 0.66 to 1.23%). When full-length sequence sections were used, the LSU outperformed the ITS1 and ITS2 fragments at the genus level, but the ITS1 and ITS2 showed higher accuracy when smaller fragment sizes of the same length and a 50% bootstrap cutoff were used. In a comparison using the larger ITS training set, ITS1 and ITS2 had very similar accuracy classification for fragments between 100 and 200 bp. Collectively, the results show that any of the ITS or LSU sections we tested provided comparable classification accuracy to the genus level and underscore the need for larger and more diverse classification training sets.     

Evoked Potentials and Neuropsychological Tests Validate Positron Emission Topography (PET) Brain Metabolism in Cognitively Impaired Patients

Fluorodeoxyglucose (FDG) Positron Emission Topography (PET) brain hypometabolism (HM) correlates with diminished cognitive capacity and risk of developing dementia. However, because clinical utility of PET is limited by cost, we sought to determine whether a less costly electrophysiological measure, the P300 evoked potential, in combination with neuropsychological test performance, would validate PET HM in neuropsychiatric patients. We found that patients with amnestic and non-amnestic cognitive impairment and HM (n = 43) evidenced significantly reduced P300 amplitudes, delayed latencies, and neuropsychological deficits, compared to patients with normal brain metabolism (NM; n = 187). Data from patients with missing cognitive test scores (n = 57) were removed from the final sample, and logistic regression modeling was performed on the modified sample (n = 173, p = .000004). The logistic regression modeling, based on P300 and neuropsychological measures, was used to validate membership in the HM vs. NM groups. It showed classification validation in 13/25 HM subjects (52.0%) and in 125/148 NM subjects (84.5%), correlating with total classification accuracy of 79.8%. In this paper, abnormal P300 evoked potentials coupled with cognitive test impairment validates brain metabolism and mild/moderate cognitive impairment (MCI). To this end, we cautiously propose incorporating electrophysiological and neuropsychological assessments as cost-effective brain metabolism and MCI indicators in primary care. Final interpretation of these results must await required additional studies confirming these interesting results.     

Relationship of Circulating Soluble Urokinase Plasminogen Activator Receptor (suPAR) Levels to Disease Control in Asthma and Asthmatic Pregnancy

Asthma has a high burden of morbidity if not controlled and may frequently complicate pregnancy, posing a risk for pregnancy outcomes. Elevated plasma level of the inflammatory biomarker soluble urokinase plasminogen activator receptor (suPAR) is related to a worse prognosis in many conditions such as infectious, autoimmune, or pregnancy-related diseases; however the value of suPAR in asthma and asthmatic pregnancy is unknown. The present study aimed to investigate the suPAR, CRP and IL-6 levels in asthma (asthmatic non-pregnant, ANP; N = 38; female N = 27) and asthmatic pregnancy (AP; N = 15), compared to healthy non-pregnant controls (HNP; N = 29; female N = 19) and to healthy pregnant women (HP; N = 58). The relationship between suPAR levels and asthma control was also evaluated. The diagnostic efficacy of suPAR in asthma control was analyzed using ROC analysis. IL-6 and CRP levels were comparable in all study groups. Circulating suPAR levels were lower in HP and AP than in HNP and ANP subjects, respectively (2.01 [1.81–2.38] and 2.39 [2.07–2.69] vs. 2.60 [1.82–3.49] and 2.84 [2.33–3.72] ng/mL, respectively, p = 0.0001). suPAR and airway resistance correlated in ANP (r = 0.47, p = 0.004). ROC analysis of suPAR values in ANP patients with PEF above and below 80% yielded an AUC of 0.75 (95% CI: 0.57–0.92, p = 0.023) and with ACT total score above and below 20 an AUC of 0.80 (95% CI: 0.64–0.95, p = 0.006). The cut-off value of suPAR to discriminate between controlled and not controlled AP and ANP was 4.04 ng/mL. In conclusion, suPAR may help the objective assessment of asthma control, since it correlates with airway resistance and has good sensitivity in the detection of impaired asthma control. Decrease in circulating suPAR levels detected both in healthy and asthmatic pregnant women presumably represents pregnancy induced immune tolerance.     

Testing the Prognostic Accuracy of the Updated Pediatric Sepsis Biomarker Risk Model

Background

We previously derived and validated a risk model to estimate mortality probability in children with septic shock (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl). PERSEVERE uses five biomarkers and age to estimate mortality probability. After the initial derivation and validation of PERSEVERE, we combined the derivation and validation cohorts (n = 355) and updated PERSEVERE. An important step in the development of updated risk models is to test their accuracy using an independent test cohort.

Objective

To test the prognostic accuracy of the updated version PERSEVERE in an independent test cohort.

Methods

Study subjects were recruited from multiple pediatric intensive care units in the United States. Biomarkers were measured in 182 pediatric subjects with septic shock using serum samples obtained during the first 24 hours of presentation. The accuracy of PERSEVERE 28-day mortality risk estimate was tested using diagnostic test statistics, and the net reclassification improvement (NRI) was used to test whether PERSEVERE adds information to a physiology-based scoring system.

Results

Mortality in the test cohort was 13.2%. Using a risk cut-off of 2.5%, the sensitivity of PERSEVERE for mortality was 83% (95% CI 62–95), specificity was 75% (68–82), positive predictive value was 34% (22–47), and negative predictive value was 97% (91–99). The area under the receiver operating characteristic curve was 0.81 (0.70–0.92). The false positive subjects had a greater degree of organ failure burden and longer intensive care unit length of stay, compared to the true negative subjects. When adding PERSEVERE to a physiology-based scoring system, the net reclassification improvement was 0.91 (0.47–1.35; p<0.001).

Conclusions

The updated version of PERSEVERE estimates mortality probability reliably in a heterogeneous test cohort of children with septic shock and provides information over and above a physiology-based scoring system.     

The Relationship between Adiponectin and Left Ventricular Mass Index Varies with the Risk of Left Ventricular Hypertrophy

Background

Adiponectin directly protects against cardiac remodeling. Despite this beneficial effect, most epidemiological studies have reported a negative relationship between adiponectin level and left ventricular mass index (LVMI). However, a positive relationship has also been reported in subjects at high risk of left ventricular hypertrophy (LVH). Based on these conflicting results, we hypothesized that the relationship between serum adiponectin level and LVMI varies with the risk of LVH.

Methods

A community-based, cross-sectional study was performed on 1414 subjects. LVMI was measured by echocardiography. Log-transformed adiponectin levels (Log-ADPN) were used for the analysis.

Results

Serum adiponectin level had a biphasic distribution (an increase after a decrease) with increasing LVMI. Although Log-ADPN did not correlate with LVMI, Log-ADPN was modestly associated with LVMI in the multivariate analysis (β = 0.079, p = 0.001). The relationship between adiponectin level and LVMI was bidirectional according to the risk of LVH. In normotensive subjects younger than 50 years, Log-ADPN negatively correlated with LVMI (r = −0.204, p = 0.005); however, Log-ADPN positively correlated with LVMI in ≥50-year-old obese subjects with high arterial stiffness (r = 0.189, p = 0.030). The correlation coefficient between Log-ADPN and LVMI gradually changed from negative to positive with increasing risk factors for LVH. The risk of LVH significantly interacted with the relationship between Log-ADPN and LVMI. In the multivariate analysis, Log-ADPN was associated with LVMI in the subjects at risk of LVH; however, Log-ADPN was either not associated or negatively associated with LVMI in subjects at low risk of LVH.

Conclusion

Adiponectin level and LVMI are negatively associated in subjects at low risk of LVH and are positively associated in subjects at high risk of LVH. Therefore, the relationship between adiponectin and LVMI varies with the risk of LVH.     

No Association of the BDNF Val66met Polymorphism with Implicit Associative Vocabulary and Motor Learning

Brain-derived neurotrophic factor (BDNF) has been suggested to play a major role in plasticity, neurogenesis and learning in the adult brain. The BDNF gene contains a common val66met polymorphism associated with decreased activity-dependent excretion of BDNF and a potential influence on behaviour, more specifically, on motor learning. The objective of this study was to determine the influence of the BDNF val66met polymorphism on short-term implicit associative learning and whether its influence is cognitive domain-specific (motor vs. language). A sample of 38 young healthy participants was genotyped, screened for background and neuropsychological differences, and tested with two associative implicit learning paradigms in two different cognitive domains, i.e., motor and vocabulary learning. Subjects performed the serial reaction time task (SRTT) to determine implicit motor learning and a recently established associative vocabulary learning task (AVL) for implicit learning of action and object words. To determine the influence of the BDNF polymorphism on domain-specific implicit learning, behavioural improvements in the two tasks were compared between val/val (n = 22) and met carriers (val/met: n = 15 and met/met: n = 1). There was no evidence for an impact of the BDNF val66met polymorphism on the behavioural outcome in implicit short-term learning paradigms in young healthy subjects. Whether this polymorphism plays a relevant role in long-term training paradigms or in subjects with impaired neuronal plasticity or reduced learning capacity, such as aged individuals, demented patients or patients with brain lesions, has to be determined in future studies.     

Sleep-Dependent Consolidation of Value-Based Learning

It has been suggested that sleep selectively enhances memories with future relevance. Given that sleep’s benefits can vary by item within a learning context, the present study investigated whether the amount of sleep-dependent consolidation may vary across items based on the value of the to-be-learned material. For this purpose, we used a value-based learning paradigm in which participants studied words paired with point values. There were two groups; participants either studied the words in the evening and were tested after a 12 hr interval containing a full night of sleep, or studied the words in the morning and were tested after 12 hr of continuous daytime wake. Free recall (F(1,36) = 19.35, p<.001) and recognition accuracy (F(1,36) = 7.59, p = .01) for words were better following sleep relative to wake. However there was no difference in the linear increase in the probability of delayed recall with increasing word value for sleep and wake groups (p = .74). Thus, while encoding may vary with the value of the to-be-learned item, sleep-dependent consolidation does not.