The effect of continuous positive airway pressure on total cerebral blood flow in healthy awake volunteers.

PURPOSE: Continuous positive airway pressure (CPAP) is the gold standard treatment for obstructive sleep apnea. However, the physiologic impact of CPAP on cerebral blood flow (CBF) is not well established. Ultrasound can be used to estimate CBF, but there is no widespread accepted protocol. We studied the physiologic influence of CPAP on CBF using a method integrating arterial diameter and flow velocity (FV) measurements obtained for each vessel supplying blood to the brain. METHODS: FV and lumen diameter of the left and right internal carotid, vertebral, and middle cerebral arteries were measured using duplex Doppler ultrasound with and without CPAP at 15 cm H(2)O, applied in a random order. Transcutaneous carbon dioxide (PtcCO(2)), heart rate (HR), blood pressure (BP), and oxygen saturation were monitored. Results were compared with a theoretical prediction of CBF change based on the effect of partial pressure of carbon dioxide on CBF. RESULTS: Data were obtained from 23 healthy volunteers (mean ± SD; 12 male, age 25.1 ± 2.6 years, body mass index 21.8 ± 2.0 kg/m(2)). The mean experimental and theoretical CBF decrease under CPAP was 12.5 % (p < 0.001) and 11.9 % (p < 0.001), respectively. The difference between experimental and theoretical CBF reduction was not statistically significant (3.84 ± 79 ml/min, p = 0.40). There was a significant reduction in PtcCO(2) with CPAP (p = <0.001) and a significant increase in mean BP (p = 0.0017). No significant change was observed in SaO(2) (p = 0.21) and HR (p = 0.62). CONCLUSION: Duplex Doppler ultrasound measurements of arterial diameter and FV allow for a noninvasive bedside estimation of CBF. CPAP at 15 cm H(2)O significantly decreased CBF in healthy awake volunteers. This effect appeared to be mediated predominately through the hypocapnic vasoconstriction coinciding with PCO(2) level reduction. The results suggest that CPAP should be used cautiously in patients with unstable cerebral hemodynamics.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

A comparison of methods for differential expression analysis of RNA-seq data.

BACKGROUND: Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data. RESULTS: We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data. CONCLUSIONS: Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). INTERPRETATION: The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.

Two Signatures For A New Blood-Based Test For Colorectal Cancer Screening

Background: Detection rates for adenoma and early colorectal cancer (CRC) are unsatisfactory due to low compliance towards invasive screening procedures such as colonoscopy. There is a large unmet screening need calling for an accurate, non-invasive and cost-effective test to screen for early neoplastic and pre-neoplastic lesions. Our goal is to identify effective biomarker combinations to develop a screening test aimed at detecting precancerous lesions and early CRC stages, based on a multigene assay performed on peripheral blood mononuclear cells (PBMC).Methods: A pilot study was conducted on 92 subjects. Colonoscopy revealed 21 CRC, 30 adenomas larger than 1 cm and 41 healthy controls. A panel of 103 biomarkers was selected by two approaches: a candidate gene approach based on literature review and whole transcriptome analysis of a subset of this cohort by Illumina TAG profiling. Blood samples were taken from each patient and PBMC purified. Total RNA was extracted and the 103 biomarkers were tested by multiplex RT-qPCR on the cohort. Different univariate and multivariate statistical methods were applied on the PCR data and 60 biomarkers, with significant p-value (< 0.01) for most of the methods, were selected.Results: The 60 biomarkers are involved in several different biological functions, such as cell adhesion, cell motility, cell signaling, cell proliferation, development and cancer. Two distinct molecular signatures derived from the biomarker combinations were established based on penalized logistic regression to separate patients without lesion from those with CRC or adenoma. These signatures were validated using bootstrapping method, leading to a separation of patients without lesion from those with CRC (Se 67%, Sp 93%, AUC 0.87) and from those with adenoma larger than 1cm (Se 63%, Sp 83%, AUC 0.77). In addition, the organ and disease specificity of these signatures was confirmed by means of patients with other cancer types and inflammatory bowel diseases.Conclusions: The two defined biomarker combinations effectively detect the presence of CRC and adenomas larger than 1 cm with high sensitivity and specificity. A prospective, multicentric, pivotal study is underway in order to validate these results in a larger cohort.

Label-free detection of tobramycin in serum by transmission-localized surface plasmon resonance.

In order to improve the efficacy and safety of treatments, drug dosage needs to be adjusted to the actual needs of each patient in a truly personalized medicine approach. Key for widespread dosage adjustment is the availability of point-of-care devices able to measure plasma drug concentration in a simple, automated, and cost-effective fashion. In the present work, we introduce and test a portable, palm-sized transmission-localized surface plasmon resonance (T-LSPR) setup, comprised of off-the-shelf components and coupled with DNA-based aptamers specific to the antibiotic tobramycin (467 Da). The core of the T-LSPR setup are aptamer-functionalized gold nanoislands (NIs) deposited on a glass slide covered with fluorine-doped tin oxide (FTO), which acts as a biosensor. The gold NIs exhibit localized plasmon resonance in the visible range matching the sensitivity of the complementary metal oxide semiconductor (CMOS) image sensor employed as a light detector. The combination of gold NIs on the FTO substrate, causing NIs size and pattern irregularity, might reduce the overall sensitivity but confers extremely high stability in high-ionic solutions, allowing it to withstand numerous regeneration cycles without sensing losses. With this rather simple T-LSPR setup, we show real-time label-free detection of tobramycin in buffer, measuring concentrations down to 0.5 μM. We determined an affinity constant of the aptamer-tobramycin pair consistent with the value obtained using a commercial propagating-wave based SPR. Moreover, our label-free system can detect tobramycin in filtered undiluted blood serum, measuring concentrations down to 10 μM with a theoretical detection limit of 3.4 μM. While the association signal of tobramycin onto the aptamer is masked by the serum injection, the quantification of the captured tobramycin is possible during the dissociation phase and leads to a linear calibration curve for the concentrations over the tested range (10-80 μM). The plasmon shift following surface binding is calculated in terms of both plasmon peak location and hue, with the latter allowing faster data elaboration and real-time display of the results. The presented T-LSPR system shows for the first time label-free direct detection and quantification of a small molecule in the complex matrix of filtered undiluted blood serum. Its uncomplicated construction and compact size, together with the remarkable performances, represent a leap forward toward effective point-of-care devices for therapeutic drug concentration monitoring.

Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients.

PURPOSE: The purpose of our study was to assess whether a model combining clinical factors, MR imaging features, and genomics would better predict overall survival of patients with glioblastoma (GBM) than either individual data type. METHODS: The study was conducted leveraging The Cancer Genome Atlas (TCGA) effort supported by the National Institutes of Health. Six neuroradiologists reviewed MRI images from The Cancer Imaging Archive (http://cancerimagingarchive.net) of 102 GBM patients using the VASARI scoring system. The patients' clinical and genetic data were obtained from the TCGA website (http://www.cancergenome.nih.gov/). Patient outcome was measured in terms of overall survival time. The association between different categories of biomarkers and survival was evaluated using Cox analysis. RESULTS: The features that were significantly associated with survival were: (1) clinical factors: chemotherapy; (2) imaging: proportion of tumor contrast enhancement on MRI; and (3) genomics: HRAS copy number variation. The combination of these three biomarkers resulted in an incremental increase in the strength of prediction of survival, with the model that included clinical, imaging, and genetic variables having the highest predictive accuracy (area under the curve 0.679±0.068, Akaike's information criterion 566.7, P<0.001). CONCLUSION: A combination of clinical factors, imaging features, and HRAS copy number variation best predicts survival of patients with GBM.

Liquid chromatography-tandem mass spectrometry (LC/APCI-MS/MS) methods for the quantification of captan and folpet phthalimide metabolites in human plasma and urine.

Captan and folpet are fungicides largely used in agriculture. They have similar chemical structures, except that folpet has an aromatic ring unlike captan. Their half-lives in blood are very short, given that they are readily broken down to tetrahydrophthalimide (THPI) and phthalimide (PI), respectively. Few authors measured these biomarkers in plasma or urine, and analysis was conducted either by gas chromatography coupled to mass spectrometry or liquid chromatography with UV detection. The objective of this study was thus to develop simple, sensitive and specific liquid chromatography-atmospheric pressure chemical ionization-tandem mass spectrometry (LC/APCI-MS/MS) methods to quantify both THPI and PI in human plasma and urine. Briefly, deuterated THPI was added as an internal standard and purification was performed by solid-phase extraction followed by LC/APCI-MS/MS analysis in negative ion mode for both compounds. Validation of the methods was conducted using spiked blank plasma and urine samples at concentrations ranging from 1 to 250 μg/L and 1 to 50 μg/L, respectively, along with samples of volunteers and workers exposed to captan or folpet. The methods showed a good linearity (R (2) > 0.99), recovery (on average 90% for THPI and 75% for PI), intra- and inter-day precision (RSD, <15%) and accuracy (<20%), and stability. The limit of detection was 0.58 μg/L in urine and 1.47 μg/L in plasma for THPI and 1.14 and 2.17 μg/L, respectively, for PI. The described methods proved to be accurate and suitable to determine the toxicokinetics of both metabolites in human plasma and urine.

Anti-doping testing at the 2008 European football championship.

Big sports events like the 2008 European Football Championship are a challenge for anti-doping activities, particularly when the sports event is hosted by two different countries and there are two laboratories accredited by the World Anti-Doping Agency. This challenges the logistics of sample collection as well as the chemical analyses, which must be carried out timeously. The following paper discusses the handling of whereabouts information for each athlete and the therapeutic use exemption system, experiences in sample collection and transportation of blood and urine samples, and the results of the chemical analysis in two different accredited laboratories. An overview of the analytical results of blood profiling and growth hormone testing in comparison with the distribution of the normal population is also presented.

Antidoping programme and biological monitoring before and during the 2014 FIFA World Cup Brazil.

BACKGROUND: The FIFA has implemented an important antidoping programme for the 2014 FIFA World Cup. AIM: To perform the analyses before and during the World Cup with biological monitoring of blood and urine samples. METHODS: All qualified players from the 32 teams participating in the World Cup were tested out-of-competition. During the World Cup, 2-8 players per match were tested. Over 1000 samples were collected in total and analysed in the WADA accredited Laboratory of Lausanne. RESULTS: The quality of the analyses was at the required level as described in the WADA technical documents. The urinary steroid profiles of the players were stable and consistent with previously published papers on football players. During the competition, amphetamine was detected in a sample collected on a player who had a therapeutic use exemption for attention deficit hyperactivity disorder. The blood passport data showed no significant difference in haemoglobin values between out-of-competition and postmatch samples. CONCLUSIONS: Logistical issues linked to biological samples collection, and the overseas shipment during the World Cup did not impair the quality of the analyses, especially when used as the biological passport of football players.

Task force IV: Clinical use of ambulatory blood pressure monitoring. Participants of the 1999 Consensus Conference on Ambulatory Blood Pressure Monitoring

OBJECTIVE: To reach a consensus on the clinical use of ambulatory blood pressure monitoring (ABPM). METHODS: A task force on the clinical use of ABPM wrote this overview in preparation for the Seventh International Consensus Conference (23-25 September 1999, Leuven, Belgium). This article was amended to account for opinions aired at the conference and to reflect the common ground reached in the discussions. POINTS OF CONSENSUS: The Riva Rocci/Korotkoff technique, although it is prone to error, is easy and cheap to perform and remains worldwide the standard procedure for measuring blood pressure. ABPM should be performed only with properly validated devices as an accessory to conventional measurement of blood pressure. Ambulatory recording of blood pressure requires considerable investment in equipment and training and its use for screening purposes cannot be recommended. ABPM is most useful for identifying patients with white-coat hypertension (WCH), also known as isolated clinic hypertension, which is arbitrarily defined as a clinic blood pressure of more than 140 mmHg systolic or 90 mmHg diastolic in a patient with daytime ambulatory blood pressure below 135 mmHg systolic and 85 mmHg diastolic. Some experts consider a daytime blood pressure below 130 mmHg systolic and 80 mmHg diastolic optimal. Whether WCH predisposes subjects to sustained hypertension remains debated. However, outcome is better correlated to the ambulatory blood pressure than it is to the conventional blood pressure. Antihypertensive drugs lower the clinic blood pressure in patients with WCH but not the ambulatory blood pressure, and also do not improve prognosis. Nevertheless, WCH should not be left unattended. If no previous cardiovascular complications are present, treatment could be limited to follow-up and hygienic measures, which should also account for risk factors other than hypertension. ABPM is superior to conventional measurement of blood pressure not only for selecting patients for antihypertensive drug treatment but also for assessing the effects both of non-pharmacological and of pharmacological therapy. The ambulatory blood pressure should be reduced by treatment to below the thresholds applied for diagnosing sustained hypertension. ABPM makes the diagnosis and treatment of nocturnal hypertension possible and is especially indicated for patients with borderline hypertension, the elderly, pregnant women, patients with treatment-resistant hypertension and patients with symptoms suggestive of hypotension. In centres with sufficient financial resources, ABPM could become part of the routine assessment of patients with clinic hypertension. For patients with WCH, it should be repeated at annual or 6-monthly intervals. Variation of blood pressure throughout the day can be monitored only by ABPM, but several advantages of the latter technique can also be obtained by self-measurement of blood pressure, a less expensive method that is probably better suited to primary practice and use in developing countries. CONCLUSIONS: ABPM or equivalent methods for tracing the white-coat effect should become part of the routine diagnostic and therapeutic procedures applied to treated and untreated patients with elevated clinic blood pressures. Results of long-term outcome trials should better establish the advantage of further integrating ABPM as an accessory to conventional sphygmomanometry into the routine care of hypertensive patients and should provide more definite information on the long-term cost-effectiveness. Because such trials are not likely to be funded by the pharmaceutical industry, governments and health insurance companies should take responsibility in this regard.

Acute creatine loading enhances human growth hormone secretion.

BACKGROUND: The main objective of this study was to explore the effect of acute creatine (Cr) ingestion on the secretion of human growth hormone (GH). METHODS: In a comparative cross-sectional study, 6 healthy male subjects ingested in resting conditions a single dose of 20 g creatine (Cr-test) vs a control (c-test). During 6 hours the Cr, creatinine and GH concentrations in blood serum were measured after Cr ingestion (Cr-test). RESULTS: During the Cr-test, all subjects showed a significant stimulation of GH (p<0.05), but with a large interindividual variability in the GH response: the difference between Cr-test and c-test averaged 83% (SD 45%). For the majority of subjects the maximum GH concentration occurred between 2 hrs and 6 hrs after the acute Cr ingestion. CONCLUSIONS: In resting conditions and at high dosages Cr enhances GH secretion, mimicking the response of strong exercise which also stimulates GH secretion. Acute body weight gain and strength increase observed after Cr supplementation should consider the indirect anabolic property of Cr.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.