Rejoinder

Article http://dx.doi.org/10.1002/bimj.4710360113 Letter to the editor http://dx.doi.org/10.1002/bimj.200810429     

First jet lag symptoms after travelling across multiple time zones

Jet lag is a consequence of desynchronisation of human endogenous circadian rhythm with respect to the immediate environment. The slower adaptation rate of the internal rhythm in contrast to rapid travel in commercial aircraft results in symptoms such as insomnia or daytime fatigue. A group of 53 travelling subjects answered the Charité Jet Lag Scale (CJLS) questionnaire, the first of its kind in German. The CJLS represents a holistic approach to the individual symptoms of jet lag. Study results indicate a possible enhancement by shortening the CJLS to a morning and evening report. Moreover, our study determined a decreasing exponential gradient for jet lag during the first days after travel. Physical and mental symptoms are identified as the primary predictors of jet lag. The CJLS and its future translations could lead to a consistent interviewing method – one key factor for development of future intervention methods to manage jet lag.     

Sudden death and its predictors in myocardial infarction survivors in an Indian population

ObjectiveThis study was conducted to assess the incidence of sudden cardiac death (SCD) in post myocardial infarction patients and to determine the predictive value of various risk markers in identifying cardiac mortality and SCD.MethodsLeft ventricular function, arrhythmias on Holter and microvolt T wave alternans (MTWA) were assessed in patients with prior myocardial infarction and ejection fraction ≤ 40%. The primary outcome was a composite of cardiac death and resuscitated cardiac arrest during follow up. Secondary outcomes included total mortality and SCD.ResultsFifty-eight patients were included in the study. Eight patients (15.5%) died during a mean follow-up of 22.3 ± 6.6 months. Seven of them (12.1%) had SCD. Among the various risk markers studied, left ventricular ejection fraction (LVEF) ≤ 30% (Hazard ratio 5.6, 95% CI 1.39 to 23) and non-sustained ventricular tachycardia (NSVT) in holter (5.7, 95% CI 1.14 to 29) were significantly associated with the primary outcome in multivariate analysis. Other measures, including QRS width, heart rate variability, heart rate turbulence and MTWA showed no association.ConclusionsAmong patients with prior myocardial infarction and reduced left ventricular function, the rate of cardiac death was substantial, with most of these being sudden cardiac death. Both LVEF ≤30% and NSVT were associated with cardiac death whereas only LVEF predicted SCD. Other parameters did not appear useful for prediction of events in these patients. These findings have implications for decision making for the use of implantable cardioverter defibrillators for primary prevention in these patients.     

Building generalized linear models with ultrahigh dimensional features: A sequentially conditional approach

Conditional screening approaches have emerged as a powerful alternative to the commonly used marginal screening, as they can identify marginally weak but conditionally important variables. However, most existing conditional screening methods need to fix the initial conditioning set, which may determine the ultimately selected variables. If the conditioning set is not properly chosen, the methods may produce false negatives and positives. Moreover, screening approaches typically need to involve tuning parameters and extra modeling steps in order to reach a final model. We propose a sequential conditioning approach by dynamically updating the conditioning set with an iterative selection process. We provide its theoretical properties under the framework of generalized linear models. Powered by an extended Bayesian information criterion as the stopping rule, the method will lead to a final model without the need to choose tuning parameters or threshold parameters. The practical utility of the proposed method is examined via extensive simulations and analysis of a real clinical study on predicting multiple myeloma patients’ response to treatment based on their genomic profiles.     

Measurement of Left Atrial Pressure is a Good Predictor of Freedom From Atrial Fibrillation

Background

It is suggested that an elevated left atrial pressure (LAP) promotes ectopic beats emanating in the pulmonary veins (PVs) and that LAP might be a marker for structural remodeling. This study aimed to identify if the quantification of LAP correlates with structural changes of the LA and may therefore be associated with outcomes following pulmonary vein isolation (PVI).

Methods

We analysed data from 120 patients, referred to PVI due to drug-refractory atrial fibrillation (AF) (age 63±8; 57% men). The maximum (mLAP) and mean LAP (meLAP) were measured after transseptal puncture.

Results and Conclusions

Within a mean follow-up of 303±95 days, 60% of the patients maintained in sinus rhythm after the initial procedure and 78% after repeated PVI. Performing univariate Cox-regression analysis, type of AF, LA-volume (LAV), mLAP and the meLAP were significant predictors of recurrence after PVI (p=0.03; p=0.001; p=0.01). In multivariate analysis mLAP>18mmHg, LAV>100 ml and the presence of persistent AF were significant predictors (p=0.001; p=0.019; p=0.017). The mLAP >18 mmHg was associated with a hazard ratio of 3.8. Analyzing receiver-operator characteristics, the area under the curve for mLAP was 0.75 (p<0.01). mLAP >18 mmHg predicts recurrence with a sensitivity of 77 % and specificity of 60 %. There was a linear correlation between the LAV from MDCT and mLAP (p = 0.01, R2 = 0.61). The mLAP measured invasively displays a significant predictor for AF recurrence after PVI. There is a good correlation between LAP and LAV and both factors may be useful to quantify LA remodeling.     

Persistence of psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort: a prospective two‐year follow‐up

Prospective evaluation of youths with early psychotic‐like experiences can enrich our knowledge of clinical, biobehavioral and environmental risk and protective factors associated with the development of psychotic disorders. We aimed to investigate the predictors of persistence or worsening of psychosis spectrum features among US youth through the first large systematic study to evaluate subclinical symptoms in the community. Based on Time 1 screen of 9,498 youth (age 8‐21) from the Philadelphia Neurodevelopmental Cohort, a subsample of participants was enrolled based on the presence (N=249) or absence (N=254) of baseline psychosis spectrum symptoms, prior participation in neuroimaging, and current neuroimaging eligibility. They were invited to participate in a Time 2 assessment two years on average following Time 1. Participants were administered the Structured Interview for Prodromal Syndromes, conducted blind to initial screen status, along with the Schizotypal Personality Questionnaire and other clinical measures, computerized neurocognitive testing, and neuroimaging. Clinical and demographic predictors of symptom persistence were examined using logistic regression. At Time 2, psychosis spectrum features persisted or worsened in 51.4% of youths. Symptom persistence was predicted by higher severity of subclinical psychosis, lower global functioning, and prior psychiatric medication at baseline. Youths classified as having psychosis spectrum symptoms at baseline but not at follow‐up nonetheless exhibited comparatively higher symptom levels and lower functioning at both baseline and follow‐up than typically developing youths. In addition, psychosis spectrum features emerged in a small number of young people who previously had not reported significant symptoms but who had exhibited early clinical warning signs. Together, our findings indicate that varying courses of psychosis spectrum symptoms are evident early in US youth, supporting the importance of investigating psychosis risk as a dynamic developmental process. Neurocognition, brain structure and function, and genomics may be integrated with clinical data to provide early indices of symptom persistence and worsening in youths at risk for psychosis.     

Climate versus weather extremes: Temporal predictor resolution matters for future rather than current regional species distribution models

Aim

Climate is considered a major driver of species distributions. Long‐term climatic means are commonly used as predictors in correlative species distribution models (SDMs). However, this coarse temporal resolution does not reflect local conditions that populations experience, such as short‐term weather extremes, which may have a strong impact on population dynamics and local distributions. We here compare the performance of climate‐ and weather‐based predictors in regional SDMs and their influence on future predictions, which are increasingly used in conservation planning.

Location

South‐western Germany.

Methods

We built different SDMs for 20 Orthoptera species based on three predictor sets at a regional scale for current and future climate scenarios. We calculated standard bioclimatic variables and yearly and seasonal sets of climate change indicating variables of weather extremes. As the impact of extreme events may be stronger for habitat specialists than for generalists, we distinguished species’ degrees of specialization. We computed linear mixed‐effects models to identify significant effects of algorithm, predictor set and specialization on model performance and calculated correlations and geographical niche overlap between spatial predictions.

Results

Current predictions were rather similar among all predictor sets, but highly variable for future climate scenarios. Bioclimatic and seasonal weather predictors performed slightly better than yearly weather predictors, though performance differences were minor. We found no evidence that specialists are more sensitive to weather extremes than generalists.

Main conclusions

For future projections of species distributions, SDM predictor selection should not solely be based on current performances and predictions. As long‐term climate and short‐term weather predictors represent different environmental drivers of a species’ distribution, we argue to interpret diverging future projections as complements. Even if similar current performances and predictions might imply their equivalency, favouring one predictor set neglects important aspects of future distributions and might mislead conservation decisions based on them.

     

Predictors of outcome of dream work for East Asian volunteer clients: Dream factors, attachment anxiety, Asian values, and therapist input.

Eighty-eight East Asian volunteers were paired with 6 East Asian therapists who provided low or high input in single-dream sessions. Volunteer clients with poor initial functioning on the target problem associated with their dreams and high self-efficacy for working with dreams profited more from dream sessions than did their counterparts. Although no main effects were found for therapist input, volunteer clients who scored higher on attachment anxiety had better outcome in the low-input condition, whereas clients who scored lower on attachment anxiety had better outcome in the high-input condition. Volunteer clients with lower Asian values evaluated low-input sessions more positively, whereas volunteer clients with higher Asian values evaluated high-input sessions more positively. Implications for dream work and future research are suggested. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Physical predictors,behavioural/emotional attributes and neurochemical determinants of dominant behaviour

Significant differences in physical and behavioural/emotional/cognitive predictors and attributes, as well as of neurochemical inducers of behaviour, between dominant and subordinate animals are discussed. It is still unknown whether these factors are the causes of differences between dominants and subordinates, or vice versa whether the differences between dominants and subordinates are the origin of differences in these factors. The possibility is discussed that no differences exist among juveniles in the concentrations of neurochemical agents (known in the literature as determinants of dominance) between the brains of future dominants and future subordinates. We describe a study design that makes the assessment of the ‘original’ neurochemical profile of the brain possible.     

A guideline to proteome-wide α-helical membrane protein topology predictions

For current state-of-the-art methods, the prediction of correct topology of membrane proteins has been reported to be above 80%. However, this performance has only been observed in small and possibly biased data sets obtained from protein structures or biochemical assays. Here, we test a number of topology predictors on an "unseen" set of proteins of known structure and also on four "genome-scale" data sets, including one recent large set of experimentally validated human membrane proteins with glycosylated sites. The set of glycosylated proteins is also used to examine the ability of prediction methods to separate membrane from nonmembrane proteins. The results show that methods utilizing multiple sequence alignments are overall superior to methods that do not. The best performance is obtained by TOPCONS, a consensus method that combines several of the other prediction methods. The best methods to distinguish membrane from nonmembrane proteins belong to the "Phobius" group of predictors. We further observe that the reported high accuracies in the smaller benchmark sets are not quite maintained in larger scale benchmarks. Instead, we estimate the performance of the best prediction methods for eukaryotic membrane proteins to be between 60% and 70%. The low agreement between predictions from different methods questions earlier estimates about the global properties of the membrane proteome. Finally, we suggest a pipeline to estimate these properties using a combination of the best predictors that could be applied in large-scale proteomics studies of membrane proteins.