On the Impact of Link Layer Retransmissions on TCP for Aeronautical Communications

In this article, we evaluate the impact of link layer retransmissions on the performance of TCP in the context of aeronautical communications.We present the architecture of aeronautical networks, which is manly driven by an important channel access delay, and the various retransmission strategies that can be implemented at both link and transport layers. We consider a worst case scenario to illustrate the benefits provided by the ARQ scheme at the link layer in terms of transmission delay.We evaluate the trade-off between allowing a fast data transmission and a low usage of satellite capacity by adjusting link layer parameters

Creatine Protects against Excitoxicity in an In Vitro Model of Neurodegeneration

Creatine has been shown to be neuroprotective in aging, neurodegenerative conditions and brain injury. As a common molecular background, oxidative stress and disturbed cellular energy homeostasis are key aspects in these conditions. Moreover, in a recent report we could demonstrate a life-enhancing and health-promoting potential of creatine in rodents, mainly due to its neuroprotective action. In order to investigate the underlying pharmacology mediating these mainly neuroprotective properties of creatine, cultured primary embryonal hippocampal and cortical cells were challenged with glutamate or H2O2. In good agreement with our in vivo data, creatine mediated a direct effect on the bioenergetic balance, leading to an enhanced cellular energy charge, thereby acting as a neuroprotectant. Moreover, creatine effectively antagonized the H2O2-induced ATP depletion and the excitotoxic response towards glutamate, while not directly acting as an antioxidant. Additionally, creatine mediated a direct inhibitory action on the NMDA receptor-mediated calcium response, which initiates the excitotoxic cascade. Even excessive concentrations of creatine had no neurotoxic effects, so that high-dose creatine supplementation as a health-promoting agent in specific pathological situations or as a primary prophylactic compound in risk populations seems feasible. In conclusion, we were able to demonstrate that the protective potential of creatine was primarily mediated by its impact on cellular energy metabolism and NMDA receptor function, along with reduced glutamate spillover, oxidative stress and subsequent excitotoxicity

A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression.

BACKGROUND: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) genes from the study and determining which genes are differentially expressed. Often these analysis stages are applied disregarding the fact that the data is drawn from a time series. In this paper we propose a simple model for accounting for the underlying temporal nature of the data based on a Gaussian process. RESULTS: We review Gaussian process (GP) regression for estimating the continuous trajectories underlying in gene expression time-series. We present a simple approach which can be used to filter quiet genes, or for the case of time series in the form of expression ratios, quantify differential expression. We assess via ROC curves the rankings produced by our regression framework and compare them to a recently proposed hierarchical Bayesian model for the analysis of gene expression time-series (BATS). We compare on both simulated and experimental data showing that the proposed approach considerably outperforms the current state of the art. CONCLUSIONS: Gaussian processes offer an attractive trade-off between efficiency and usability for the analysis of microarray time series. The Gaussian process framework offers a natural way of handling biological replicates and missing values and provides confidence intervals along the estimated curves of gene expression. Therefore, we believe Gaussian processes should be a standard tool in the analysis of gene expression time series

Predictors of dizziness in older persons: a 10-year prospective cohort study in the community

BACKGROUND: The current diagnosis-oriented approach of dizziness does not suit older patients. Often, it is difficult to identify a single underlying cause, and when a diagnosis is made, therapeutic options may be limited. Identification of predictors of dizziness may provide new leads for the management of dizziness in older patients. The aim of the present study was to investigate long-term predictors of regular dizziness in older persons. METHODS: Population-based cohort study of 1,379 community-dwelling participants, aged ≥60 years, from the Longitudinal Aging Study Amsterdam (LASA). Regular dizziness was ascertained during face-to-face medical interviews during 7- and 10-year follow-up. We investigated 26 predictors at baseline from six domains: socio-demographic, medical history, medication, psychological, sensory, and balance/gait. We performed multivariate logistic regression analyses with presence of regular dizziness at 7- and 10-year follow-up as dependent variables. We assessed the performance of the models by calculating calibration and discrimination. RESULTS: Predictors of regular dizziness at 7-year follow-up were living alone, history of dizziness, history of osteo/rheumatoid arthritis, use of nitrates, presence of anxiety or depression, impaired vision, and impaired function of lower extremities. Predictors of regular dizziness at 10-year follow-up were history of dizziness and impaired function of lower extremities. Both models showed good calibration (Hosmer-Lemeshow P value of 0.36 and 0.31, respectively) and acceptable discrimination (adjusted AUC after bootstrapping of 0.77 and 0.71). CONCLUSIONS: Dizziness in older age was predicted by multiple factors. A multifactorial approach, targeting potentially modifiable predictors (e.g., physical exercise for impaired function of lower extremities), may add to the current diagnosis-oriented approach. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2318-14-133) contains supplementary material, which is available to authorized users

Men and COVID-19: the aftermath

The global pandemic as a result of the SARS-CoV2 virus has seen over 16m people infected and over 650,000 deaths, with men at double the risk of both developing the severe form of the disease and mortality. There are both biological (sex) and socio-cultural (gender) factors, compounded by socio-economic factors and ethnicity, that impact on the aftermath of what has occurred over the short time that this novel coronavirus has been circulating the world. The potential life-long morbidity as a result of the infection and as a consequence of highly invasive critical care treatment needs to be factored into the rehabilitation of survivors. There are also many men whose lives will have been severely affected both physically and emotionally by the pandemic without ever contracting the disease, with the widespread disruption to normal existence and its impact on their social world and the economy. The implications of the closure of many healthcare services over the initial lockdown will also have both a shorter- and longer-term impact on other diseases due to missed early diagnosis and disrupted treatment regimes. Getting effective public health messages out to the population is critical and this current pandemic is demonstrating that there needs to be a more focused view on men's health behaviour. Without effective public support for preventative action the more likely the disease will continue its path unabated. This review explores the wider ramifications of the disease both for those men who have survived the disease and those that have been affected by the wider social effects of the pandemic. The pandemic should be a wake-up call for all involved in the planning and delivery of health and social care for the greater attention to the central role of sex and gender

Prediction of pathological stage in patients with prostate cancer: a neuro-fuzzy model

The prediction of cancer staging in prostate cancer is a process for estimating the likelihood that the cancer has spread before treatment is given to the patient. Although important for determining the most suitable treatment and optimal management strategy for patients, staging continues to present significant challenges to clinicians. Clinical test results such as the pre-treatment Prostate-Specific Antigen (PSA) level, the biopsy most common tumor pattern (Primary Gleason pattern) and the second most common tumor pattern (Secondary Gleason pattern) in tissue biopsies, and the clinical T stage can be used by clinicians to predict the pathological stage of cancer. However, not every patient will return abnormal results in all tests. This significantly influences the capacity to effectively predict the stage of prostate cancer. Herein we have developed a neuro-fuzzy computational intelligence model for classifying and predicting the likelihood of a patient having Organ-Confined Disease (OCD) or Extra-Prostatic Disease (ED) using a prostate cancer patient dataset obtained from The Cancer Genome Atlas (TCGA) Research Network. The system input consisted of the following variables: Primary and Secondary Gleason biopsy patterns, PSA levels, age at diagnosis, and clinical T stage. The performance of the neuro-fuzzy system was compared to other computational intelligence based approaches, namely the Artificial Neural Network, Fuzzy C-Means, Support Vector Machine, the Naive Bayes classifiers, and also the AJCC pTNM Staging Nomogram which is commonly used by clinicians. A comparison of the optimal Receiver Operating Characteristic (ROC) points that were identified using these approaches, revealed that the neuro-fuzzy system, at its optimal point, returns the largest Area Under the ROC Curve (AUC), with a low number of false positives (FPR = 0.274, TPR = 0.789, AUC = 0.812). The proposed approach is also an improvement over the AJCC pTNM Staging Nomogram (FPR = 0.032, TPR = 0.197, AUC = 0.582)

Schizotypy and Behavioural Adjustment and the Role of Neuroticism

In the present study the relationship between behavioural adjustment following cognitive conflict and schizotypy was investigated using a Stroop colour naming paradigm. Previous research has found deficits with behavioural adjustment in schizophrenia patients. Based on these findings, we hypothesized that individual differences in schizotypy, a personality trait reflecting the subclinical expression of the schizophrenia phenotype, would be associated with behavioural adjustment. Additionally, we investigated whether such a relationship would be explained by individual differences in neuroticism, a non-specific measure of negative trait emotionality known to be correlated with schizotypy. 106 healthy volunteers (mean age: 25.1, 60% females) took part. Post-conflict adjustment was measured in a computer-based version of the Stroop paradigm. Schizotypy was assessed using the Schizotypal Personality Questionnaire (SPQ) and Neuroticism using the NEO-FFI. We found a negative correlation between schizotypy and post-conflict adjustment (r = -.30, p<.01); this relationship remained significant when controlling for effects of neuroticism. Regression analysis revealed that particularly the subscale No Close Friends drove the effect. Previous findings of deficits in cognitive control in schizophrenia patients were extended to the subclinical personality expression of the schizophrenia phenotype and found to be specific to schizotypal traits over and above the effects of negative emotionality