Conditional independence relations among biological markers may improve clinical decision as in the case of triple negative breast cancers

The associations existing among different biomarkers are important in clinical settings because they contribute to the characterisation of specific pathways related to the natural history of the disease, genetic and environmental determinants. Despite the availability of binary/linear (or at least monotonic) correlation indices, the full exploitation of molecular information depends on the knowledge of direct/indirect conditional independence (and eventually causal) relationships among biomarkers, and with target variables in the population of interest. In other words, that depends on inferences which are performed on the joint multivariate distribution of markers and target variables. Graphical models, such as Bayesian Networks, are well suited to this purpose. Therefore, we reconsidered a previously published case study on classical biomarkers in breast cancer, namely estrogen receptor (ER), progesterone receptor (PR), a proliferative index (Ki67/MIB-1) and to protein HER2/neu (NEU) and p53, to infer conditional independence relations existing in the joint distribution by inferring (learning) the structure of graphs entailing those relations of independence. We also examined the conditional distribution of a special molecular phenotype, called triple-negative, in which ER, PR and NEU were absent. We confirmed that ER is a key marker and we found that it was able to define subpopulations of patients characterized by different conditional independence relations among biomarkers. We also found a preliminary evidence that, given a triple-negative profile, the distribution of p53 protein is mostly supported in 'zero' and 'high' states providing useful information in selecting patients that could benefit from an adjuvant anthracyclines/alkylating agent-based chemotherapy

Activation of RAAS in a rat model of liver cirrhosis: no effect of losartan on renal sodium excretion

Abstract Background Liver cirrhosis is characterized by avid sodium retention where the activation of the renin angiotensin aldosterone system (RAAS) is considered to be the hallmark of the sodium retaining mechanisms. The direct effect of angiotensin II (ANGII) on the AT-1 receptor in the proximal tubules is partly responsible for the sodium retention. The aim was to estimate the natriuretic and neurohumoral effects of an ANGII receptor antagonist (losartan) in the late phase of the disease in a rat model of liver cirrhosis. Methods Bile duct ligated (BDL) and sham operated rats received 2 weeks of treatment with losartan 4 mg/kg/day or placebo, given by gastric gavage 5 weeks after surgery. Daily sodium and potassium intakes and renal excretions were measured. Results The renal sodium excretion decreased in the BDL animals and this was not affected by losartan treatment. At baseline the plasma renin concentration (PRC) was similar in sham and BDL animals, but increased urinary excretion of ANGII and an increase P-Aldosterone was observed in the placebo treated BDL animals. The PRC was more than 150 times higher in the losartan treated BDL animals (p < 0.001) which indicated hemodynamic impairment. Conclusions Losartan 4 mg/kg/day did not increase renal sodium excretion in this model of liver cirrhosis, although the urinary ANGII excretion was increased. The BDL animals tolerated Losartan poorly, and the treatment induced a 150 times higher PRC

Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems

International audienceTime‐lapse applications of seismic methods have been recently suggested at the near‐surface scale to track hydrological properties variations due to climate, water level changes or permafrost thaw for instance. But when it comes to traveltime tomography or surface‐wave dispersion inversion, a careful estimation of the data variability associated to the picking process must be considered prior to any time‐lapse interpretation. In this study, we propose to estimate picking errors that are due to the inherent subjectivity of human operators using statistical analysis based on picking repeatability. Two seismic datasets were collected along the same profile under distinct hydrological conditions, across a granite‐micaschist contact at the Ploemeur hydrological observatory (France). Both datasets were recorded using identical equipment and acquisition parameters. A thorough statistical analysis is conducted to estimate picking uncertainties, at the 99 % confidence level, for both Pressure (P) wave first arrival time and surface‐wave phase velocity. With the suggested workflow, we are able to identify 33 % of the P‐wave traveltimes and 16 % of the surface‐wave dispersion data that can be considered significant enough for time‐lapse interpretations. In this selected portion of the data, point‐by‐point differences are highlighting important variations linked to different hydrogeological properties of the subsurface. These variations show strong contrasts with a non‐monotonous behaviour along the line, offering new insights to better constrain the dynamics of this hydrosystem

Inhibition of poliovirus RNA synthesis as a molecular mechanism contributing to viral persistence in the mouse central nervous system

International audienceMany survivors of poliomyelitis, several decades after the acute phase of the disease, develop a set of new muscle symptoms called post-polio syndrome. The persistence of poliovirus (PV) in the central nervous system (CNS) may be involved in the aetiology of this syndrome. By using a mouse model, we have shown that PV persists in the CNS of paralysed mice for over a year after the acute disease. Detection of PV plus- and minus-strand RNAs in the spinal cord of paralysed mice suggested continuous PV RNA replication in the CNS. However, infectious PV particles could not be recovered from homogenates of CNS from paralysed mice beyond 20 days post-paralysis, indicating that PV replication was restricted. In an attempt to identify the molecular mechanism by which PV replication was limited, PV plus- and minus-strand RNA levels were estimated in the CNS of persistently infected mice by a semi-quantitative RT-nested PCR method. Results revealed that RNA replication was inhibited at the level of plus-strand RNA synthesis during persistent infection. Similar results were obtained in neuroblastoma IMR-32 cell cultures persistently infected with PV Restriction of PV RNA synthesis could be involved in persistence by limiting PV replication