Temporal quantification of MAPK induced expression in single yeast cells.

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Heterogeneity and event dependence in the analysis of sickness absence

Sickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultaneous analysis of event dependence and heterogeneity due to unknown, unmeasured, or unmeasurable factors. However, its use may encounter computational limitations when applied to very large data sets, as may frequently occur in the analysis of SA duration. To overcome the computational issue, we propose a Poisson-based conditional frailty model (CFPM) for repeated SA events that accounts for both event dependence and heterogeneity. To demonstrate the usefulness of the model proposed in the SA duration context, we used data from all non-work-related SA episodes that occurred in Catalonia (Spain) in 2007, initiated by either a diagnosis of neoplasm or mental and behavioral disorders. As expected, the CFPM results were very similar to those of the CFM for both diagnosis groups. The CPU time for the CFPM was substantially shorter than the CFM. The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events,especially with large databases.

Rib fractures at postmortem computed tomography (PMCT) validated against the autopsy

To evaluate the sensitivity of postmortem computed tomography (PMCT) in rib fracture detection validated against autopsy. Fifty-one forensic cases underwent a postmortem CT prior to forensic autopsy. Two image readers (radiologist and forensic pathologist) assessed high resolution CT data sets for rib fractures. Correct recognition rates (CRR), sensitivity and specificity values were calculated over all observations as well as individually for every rib and region. Additionally, for partial rib fractures the sensitivity of autopsy was calculated vice versa. 3876 entries in each study protocol (autopsy, PMCT radiologist and PMCT forensic pathologist) were investigated. A total of 690 fractures (autopsy), 491 (PMCT and radiologist) and 559 (PMCT and forensic pathologist) were detected. The CRR was 0.85. Sensitivity and specificity of PMCT for rib fracture detection were 0.63 (0.58 radiologist, 0.68 forensic pathologist) and 0.97 (both readers 0.97), respectively. Low CRR and sensitivity values were obtained for antero-lateral fractures. Partial rib fractures were better detected by PMCT. PMCT has a rather low sensitivity for rib fracture detection when validated against autopsy and indicates that clinical CT may also demonstrate a reasonable number of false negatives. Partial rib fractures often remain undetected at autopsy.

Inversion of multiple intersecting high-resolution crosshole GPR profiles for hydrological characterization at the Boise Hydrogeophysical Research Site

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. In particular, crosshole ground-penetrating radar (GPR) tomography has shown much promise in hydrology because of its ability to provide highly detailed images of subsurface radar wave velocity, which is strongly linked to soil water content. Here, we develop and demonstrate a procedure for inverting together multiple crosshole GPR data sets in order to characterize the spatial distribution of radar wave velocity below the water table at the Boise Hydrogeophysical Research Site (BHRS) near Boise, Idaho, USA. Specifically, we jointly invert 31 intersecting crosshole GPR profiles to obtain a highly resolved and consistent radar velocity model along the various profile directions. The model is found to be strongly correlated with complementary neutron porosity-log data and is further corroborated by larger-scale structural information at the BHRS. This work is an important prerequisite to using crosshole GPR data together with existing hydrological measurements for improved groundwater flow and contaminant transport modeling.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Digital forensic osteology--possibilities in cooperation with the Virtopsy project.

The present study was carried out to check whether classic osteometric parameters can be determined from the 3D reconstructions of MSCT (multislice computed tomography) scans acquired in the context of the Virtopsy project. To this end, four isolated and macerated skulls were examined by six examiners. First the skulls were conventionally (manually) measured using 32 internationally accepted linear measurements. Then the skulls were scanned by the use of MSCT with slice thicknesses of 1.25 mm and 0.63 mm, and the 33 measurements were virtually determined on the digital 3D reconstructions of the skulls. The results of the traditional and the digital measurements were compared for each examiner to figure out variations. Furthermore, several parameters were measured on the cranium and postcranium during an autopsy and compared to the values that had been measured on a 3D reconstruction from a previously acquired postmortem MSCT scan. The results indicate that equivalent osteometric values can be obtained from digital 3D reconstructions from MSCT scans using a slice thickness of 1.25 mm, and from conventional manual examinations. The measurements taken from a corpse during an autopsy could also be validated with the methods used for the digital 3D reconstructions in the context of the Virtopsy project. Future aims are the assessment and biostatistical evaluation in respect to sex, age and stature of all data sets stored in the Virtopsy project so far, as well as of future data sets. Furthermore, a definition of new parameters, only measurable with the aid of MSCT data would be conceivable.

FM127: Systemic metal ion levels in patients with modular neck total hip arthroplasties: a prospective cohort study

There is increasing evidence that modular neck stems are prone to corrosion-related complications. Recent studies showed elevated metal ions levels and occasional pseudotumor formation in patients with such implants. The purpose of this study was to compare systemic metal-ion levels in patients after primary THA with modular neck stems to those of patients after non-modular implants. To our knowledge, this is the first cohort study including a control group, THA without CoCr heads and dry-assembled neck-stem connections. Methods: 50 patients after THA at a minimum follow-up of 1 year have been selected for the study. Patients with multiple prosthesis or other implants have been deselected. All received a cementless SPS stem from Symbios (Ti6Al4V). 40 patients have the modular neck (CoCr) version and 10 a monobloc version. All bearings were either ceramic-ceramic or ceramic-polyethylene to minimize other sources of CoCr ion release. In the modular group, the neck was chosen pre-operatively based on a 3D planning, allowing for a dry assembly of the stem and neck on the back table before implantation. A plasma system coupled to mass spectrometry was used for a complete elementary quantification in blood and serum separately. Clinical outcome was measured using the Oxford Hip Score. Results : Complete data sets of 29 patients (24 in the modular neck-group (10male, mean age 63y, 35-84y) and 5 in the monobloc-group (3 male, 69 y, 51-83y) are available to date. Mean Co blood levels were .95 ug/L (.14-12.4) in the modular group vs .27 ug/L (.10-.73) in the monobloc group (p=.2). Respective values for Cr were significantly higher in the modular group (.99 g/L; range .75-1.21) compared to those in the monobloc group (.74 g/L ;.62-.86; p=.001). No significant difference was found when comparing serum levels. 5/24 patients had Co levels above 1 g/L (12/24 for Cr), which is by some considered as a relevant elevation. The maximum Co level was measured in an asymptomatic patient. The Oxford Hip Scores were similar in both groups. Conclusion: Cr levels were significantly elevated in the modular neck group compared to those in the monobloc group. 1/24 patients with a modular prosthesis exhibited Co levels, which are beyond the threshold accepted even for metal-on-metal bearing couples. These results have contributed to our decision to abandon the use of modular neck stems. Routine follow-up including annual measurements of systemic CoCr concentrations should be considered.

Combining RT-PCR-seq and RNA-seq to catalog all genic elements encoded in the human genome.

Within the ENCODE Consortium, GENCODE aimed to accurately annotate all protein-coding genes, pseudogenes, and noncoding transcribed loci in the human genome through manual curation and computational methods. Annotated transcript structures were assessed, and less well-supported loci were systematically, experimentally validated. Predicted exon-exon junctions were evaluated by RT-PCR amplification followed by highly multiplexed sequencing readout, a method we called RT-PCR-seq. Seventy-nine percent of all assessed junctions are confirmed by this evaluation procedure, demonstrating the high quality of the GENCODE gene set. RT-PCR-seq was also efficient to screen gene models predicted using the Human Body Map (HBM) RNA-seq data. We validated 73% of these predictions, thus confirming 1168 novel genes, mostly noncoding, which will further complement the GENCODE annotation. Our novel experimental validation pipeline is extremely sensitive, far more than unbiased transcriptome profiling through RNA sequencing, which is becoming the norm. For example, exon-exon junctions unique to GENCODE annotated transcripts are five times more likely to be corroborated with our targeted approach than with extensive large human transcriptome profiling. Data sets such as the HBM and ENCODE RNA-seq data fail sampling of low-expressed transcripts. Our RT-PCR-seq targeted approach also has the advantage of identifying novel exons of known genes, as we discovered unannotated exons in ~11% of assessed introns. We thus estimate that at least 18% of known loci have yet-unannotated exons. Our work demonstrates that the cataloging of all of the genic elements encoded in the human genome will necessitate a coordinated effort between unbiased and targeted approaches, like RNA-seq and RT-PCR-seq.

A comparison of alpha and gamma spectrometry for environmental natural radioactivity surveys.

An alpha-spectrometry, using automated borate fusion and sequential extraction and exchange chromatography, was used to determine the uranium and thorium based on environmental radioactivity of 20 soil samples. The same set of the samples was analysed using gamma-spectrometry with an HPGe detector. The two data sets were checked for coherence using Z-score and chi2 statistical tests. We show that gamma-spectrometry is a valid alternative to time-consuming alpha-spectrometry for the determination of natural uranium and thorium activity in soil (activity range: 12.5-58.2 Bq/kg). The measured activities were compared with the theoretical activities to ensure secular equilibrium in the 238U and 232Th series. For 226Ra, a special study was made on deconvolution of the 186 keV multiplet with the Levenberg-Marquardt algorithm. Finally, the combined use of Z-score and chi2-tests was found to be a powerful tool for comparing the results obtained with two different methods.

Pulse oximetry and transcutaneous oxygen tension for detection of hypoxemia in critically ill infants and children.

We tested the performance of transcutaneous oxygen monitoring (TcPO2) and pulse oximetry (tcSaO2) in detecting hypoxia in critically ill neonatal and pediatric patients. In 54 patients (178 data sets) with a mean age of 2.4 years (range 1 to 19 years), arterial saturation (SaO2) ranged from 9.5 to 100%, and arterial oxygen tension (PaO2) from 16.4 to 128 mmHg. Linear correlation analysis of pulse oximetry vs measured SaO2 revealed an r value of 0.95 (p less than 0.001) with an equation of y = 21.1 + 0.749x, while PaO2 vs tcPO2 showed a correlation coefficient of r = 0.95 (p less than 0.001) with an equation of y = -1.04 + 0.876x. The mean difference between measured SaO2 and tcSaO2 was -2.74 +/- 7.69% (range +14 to - 29%) and the mean difference between PaO2 and tcPO2 was +7.43 +/- 8.57 mmHg (range -14 to +49 mmHg). Pulse oximetry was reliable at values above 65%, but was inaccurate and overestimated the arterial SaO2 at lower values. TcPO2 tended to underestimate the arterial value with increasing PaO2. Pulse oximetry had the best sensitivity to specificity ratio for hypoxia between 65 and 90% SaO2; for tcPO2 the best results were obtained between 35 and 55 mmHg PaO2.

Software for interpolation of vegetative growth of yerba mate plants in 3D

The objective of this work was to build mock-ups of complete yerba mate plants in several stages of development, using the InterpolMate software, and to compute photosynthesis on the interpolated structure. The mock-ups of yerba-mate were first built in the VPlants software for three growth stages. Male and female plants grown in two contrasting environments (monoculture and forest understory) were considered. To model the dynamic 3D architecture of yerba-mate plants during the biennial growth interval between two subsequent prunings, data sets of branch development collected in 38 dates were used. The estimated values obtained from the mock-ups, including leaf photosynthesis and sexual dimorphism, are very close to those observed in the field. However, this similarity was limited to reconstructions that included growth units from original data sets. The modeling of growth dynamics enables the estimation of photosynthesis for the entire yerba mate plant, which is not easily measurable in the field. The InterpolMate software is efficient for building yerba mate mock-ups.

Técnicas composicionales para concentraciones geoquímicas por debajo del límite de detección

In most geochemical analyses log-ratio techniques are required to analyse compositional data sets. When a chemical element is present at a low concentration in is usally identified as a value below the detection límit and added to the data set either as zero or simply by attaching a less-than label. In any case, the occirrence of such concentration prevents us from applying the log-ratio approach. We review here the tehoretical bases of the most recent proposals for dealing with these types of observation, give some advice on their practical application and illustrate their performance throgh some examples using geochemical data

Senescence rates are determined by ranking on the fast-slow life-history continuum.

Comparative analyses of survival senescence by using life tables have identified generalizations including the observation that mammals senesce faster than similar-sized birds. These generalizations have been challenged because of limitations of life-table approaches and the growing appreciation that senescence is more than an increasing probability of death. Without using life tables, we examine senescence rates in annual individual fitness using 20 individual-based data sets of terrestrial vertebrates with contrasting life histories and body size. We find that senescence is widespread in the wild and equally likely to occur in survival and reproduction. Additionally, mammals senesce faster than birds because they have a faster life history for a given body size. By allowing us to disentangle the effects of two major fitness components our methods allow an assessment of the robustness of the prevalent life-table approach. Focusing on one aspect of life history - survival or recruitment - can provide reliable information on overall senescence.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

A genome-wide association study of anorexia nervosa.

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01 × 10(-7)) in SOX2OT and rs17030795 (P=5.84 × 10(-6)) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76 × 10(-)(6)) between CUL3 and FAM124B and rs1886797 (P=8.05 × 10(-)(6)) near SPATA13. Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4 × 10(-6)), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.