Buoyancy under Control: Underwater Locomotor Performance in a Deep Diving Seabird Suggests Respiratory Strategies for Reducing Foraging Effort

Background

Because they have air stored in many body compartments, diving seabirds are expected to exhibit efficient behavioural strategies for reducing costs related to buoyancy control. We study the underwater locomotor activity of a deep-diving species from the Cormorant family (Kerguelen shag) and report locomotor adjustments to the change of buoyancy with depth.

Methodology/Principal Findings

Using accelerometers, we show that during both the descent and ascent phases of dives, shags modelled their acceleration and stroking activity on the natural variation of buoyancy with depth. For example, during the descent phase, birds increased swim speed with depth. But in parallel, and with a decay constant similar to the one in the equation explaining the decrease of buoyancy with depth, they decreased foot-stroke frequency exponentially, a behaviour that enables birds to reduce oxygen consumption. During ascent, birds also reduced locomotor cost by ascending passively. We considered the depth at which they started gliding as a proxy to their depth of neutral buoyancy. This depth increased with maximum dive depth. As an explanation for this, we propose that shags adjust their buoyancy to depth by varying the amount of respiratory air they dive with.

Conclusions/Significance

Calculations based on known values of stored body oxygen volumes and on deep-diving metabolic rates in avian divers suggest that the variations of volume of respiratory oxygen associated with a respiration mediated buoyancy control only influence aerobic dive duration moderately. Therefore, we propose that an advantage in cormorants - as in other families of diving seabirds - of respiratory air volume adjustment upon diving could be related less to increasing time of submergence, through an increased volume of body oxygen stores, than to reducing the locomotor costs of buoyancy control.     

Brain Damage in Commercial Breath-Hold Divers

Background

Acute decompression illness (DCI) involving the brain (Cerebral DCI) is one of the most serious forms of diving-related injuries which may leave residual brain damage. Cerebral DCI occurs in compressed air and in breath-hold divers, likewise. We conducted this study to investigate whether long-term breath-hold divers who may be exposed to repeated symptomatic and asymptomatic brain injuries, show brain damage on magnetic resonance imaging (MRI).

Subjects and Methods

Our study subjects were 12 commercial breath-hold divers (Ama) with long histories of diving work in a district of Japan. We obtained information on their diving practices and the presence or absence of medical problems, especially DCI events. All participants were examined with MRI to determine the prevalence of brain lesions.

Results

Out of 12 Ama divers (mean age: 54.9±5.1 years), four had histories of cerebral DCI events, and 11 divers demonstrated ischemic lesions of the brain on MRI studies. The lesions were situated in the cortical and/or subcortical area (9 cases), white matters (4 cases), the basal ganglia (4 cases), and the thalamus (1 case). Subdural fluid collections were seen in 2 cases.

Conclusion

These results suggest that commercial breath-hold divers are at a risk of clinical or subclinical brain injury which may affect the long-term neuropsychological health of divers.     

Verbal Memory Deficits Are Correlated with Prefrontal Hypometabolism in 18FDG PET of Recreational MDMA Users

Introduction

3,4-Methylenedioxymethamphetamine (MDMA, “ecstasy”) is a recreational club drug with supposed neurotoxic effects selectively on the serotonin system. MDMA users consistently exhibit memory dysfunction but there is an ongoing debate if these deficits are induced mainly by alterations in the prefrontal or mediotemporal cortex, especially the hippocampus. Thus, we investigated the relation of verbal memory deficits with alterations of regional cerebral brain glucose metabolism (rMRGlu) in recreational MDMA users.

Methods

Brain glucose metabolism in rest was assessed using 2-deoxy-2-(¹⁸F)fluoro-D-glucose positron emission tomography (¹⁸FDG PET) in 19 male recreational users of MDMA and 19 male drug-naïve controls. ¹⁸FDG PET data were correlated with memory performance assessed with a German version of the Rey Auditory Verbal Learning Test.

Results

As previously shown, MDMA users showed significant impairment in verbal declarative memory performance. PET scans revealed significantly decreased rMRGlu in the bilateral dorsolateral prefrontal and inferior parietal cortex, bilateral thalamus, right hippocampus, right precuneus, right cerebellum, and pons (at the level of raphe nuclei) of MDMA users. Among MDMA users, learning and recall were positively correlated with rMRGlu predominantly in bilateral frontal and parietal brain regions, while recognition was additionally related to rMRGlu in the right mediotemporal and bihemispheric lateral temporal cortex. Moreover, cumulative lifetime dose of MDMA was negatively correlated with rMRGlu in the left dorsolateral and bilateral orbital and medial PFC, left inferior parietal and right lateral temporal cortex.

Conclusions

Verbal learning and recall deficits of recreational MDMA users are correlated with glucose hypometabolism in prefrontal and parietal cortex, while word recognition was additionally correlated with mediotemporal hypometabolism. We conclude that memory deficits of MDMA users arise from combined fronto-parieto-mediotemporal dysfunction.     

Species accumulation curves and incidence-based species richness estimators to appraise the diversity of cultivable yeasts from beech forest soils

Background

Yeast-like fungi inhabit soils throughout all climatic zones in a great abundance. While recent estimations predicted a plethora of prokaryotic taxa in one gram of soil, similar data are lacking for fungi, especially yeasts.

Methodology/Principal Findings

We assessed the diversity of soil yeasts in different forests of central Germany using cultivation-based techniques with subsequent identification based on rDNA sequence data. Based on experiments using various pre-cultivation sample treatment and different cultivation media we obtained the highest number of yeasts by analysing mixed soil samples with a single nutrient-rich medium. Additionally, several species richness estimators were applied to incidence-based data of 165 samples. All of them predicted a similar range of yeast diversity, namely 14 to 16 species. Randomized species richness curves reached saturation in all applied estimators, thus indicating that the majority of species is detected after approximately 30 to 50 samples analysed.

Conclusions/Significance

In this study we demonstrate that robust species identification as well as mathematical approaches are essential to reliably estimate the sampling effort needed to describe soil yeast communities. This approach has great potential for optimisation of cultivation techniques and allows high throughput analysis in the future.     

ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers

Background

With the explosion of genomic data over the last decade, there has been a tremendous amount of effort to understand the molecular basis of cancer using informatics approaches. However, this has proven to be extremely difficult primarily because of the varied etiology and vast genetic heterogeneity of different cancers and even within the same cancer. One particularly challenging problem is to predict prognostic outcome of the disease for different patients.

Results

Here, we present ENCAPP, an elastic-net-based approach that combines the reference human protein interactome network with gene expression data to accurately predict prognosis for different human cancers. Our method identifies functional modules that are differentially expressed between patients with good and bad prognosis and uses these to fit a regression model that can be used to predict prognosis for breast, colon, rectal, and ovarian cancers. Using this model, ENCAPP can also identify prognostic biomarkers with a high degree of confidence, which can be used to generate downstream mechanistic and therapeutic insights.

Conclusion

ENCAPP is a robust method that can accurately predict prognostic outcome and identify biomarkers for different human cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1465-9) contains supplementary material, which is available to authorized users.     

Resting Energy Expenditure Prediction in Recreational Athletes of 18–35 Years: Confirmation of Cunningham Equation and an Improved Weight-Based Alternative

Introduction

Resting energy expenditure (REE) is expected to be higher in athletes because of their relatively high fat free mass (FFM). Therefore, REE predictive equation for recreational athletes may be required. The aim of this study was to validate existing REE predictive equations and to develop a new recreational athlete specific equation.

Methods

90 (53M, 37F) adult athletes, exercising on average 9.1±5.0 hours a week and 5.0±1.8 times a week, were included. REE was measured using indirect calorimetry (Vmax Encore n29), FFM and FM were measured using air displacement plethysmography. Multiple linear regression analysis was used to develop a new FFM-based and weight-based REE predictive equation. The percentage accurate predictions (within 10% of measured REE), percentage bias, root mean square error and limits of agreement were calculated.

Results

The Cunningham equation and the new weight-based equation and the new FFM-based equation performed equally well. De Lorenzo''s equation predicted REE less accurate, but better than the other generally used REE predictive equations. Harris-Benedict, WHO, Schofield, Mifflin and Owen all showed less than 50% accuracy.

Conclusion

For a population of (Dutch) recreational athletes, the REE can accurately be predicted with the existing Cunningham equation. Since body composition measurement is not always possible, and other generally used equations fail, the new weight-based equation is advised for use in sports nutrition.     

Genetic immunisation by liver stage antigen 3 protects chimpanzees against malaria despite low immune responses

Background

The true interest of genetic immunisation might have been hastily underestimated based on overall immunogenicity data in humans and lack of parallelism with other, more classical immunisation methods.

Principal Findings

Using malaria Liver Stage Antigen-3 (LSA-3), we report that genetic immunization induces in chimpanzees, the closest relative of humans, immune responses which are as scarce as those reported using other DNA vaccines in humans, but which nonetheless confer strong, sterile and reproducible protection. The pattern was consistent in 3/4 immunized apes against two high dose sporozoite challenges performed as late as 98 and 238 days post-immunization and by a heterologous strain.

Conclusions

These results should, in our opinion, lead to a revisiting of the value of this unusual means of immunisation, using as a model a disease, malaria, in which virulent challenges of volunteers are ethically acceptable.     

Uncertainty in population growth rates: determining confidence intervals from point estimates of parameters

Background

Demographic models are widely used in conservation and management, and their parameterisation often relies on data collected for other purposes. When underlying data lack clear indications of associated uncertainty, modellers often fail to account for that uncertainty in model outputs, such as estimates of population growth.

Methodology/Principal Findings

We applied a likelihood approach to infer uncertainty retrospectively from point estimates of vital rates. Combining this with resampling techniques and projection modelling, we show that confidence intervals for population growth estimates are easy to derive. We used similar techniques to examine the effects of sample size on uncertainty. Our approach is illustrated using data on the red fox, Vulpes vulpes, a predator of ecological and cultural importance, and the most widespread extant terrestrial mammal. We show that uncertainty surrounding estimated population growth rates can be high, even for relatively well-studied populations. Halving that uncertainty typically requires a quadrupling of sampling effort.

Conclusions/Significance

Our results compel caution when comparing demographic trends between populations without accounting for uncertainty. Our methods will be widely applicable to demographic studies of many species.     

MCMC implementation of the optimal Bayesian classifier for non-Gaussian models: model-based RNA-Seq classification

Background

Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the detection of univariate differentially expressed genes. However, for classification, we must consider multiple genes and their interactions.

Results

Thus, we introduce a hierarchical multivariate Poisson model (MP) and the associated optimal Bayesian classifier (OBC) for classifying samples using sequencing data. Lacking closed-form solutions, we employ a Monte Carlo Markov Chain (MCMC) approach to perform classification. We demonstrate superior or equivalent classification performance compared to typical classifiers for two synthetic datasets and over a range of classification problem difficulties. We also introduce the Bayesian minimum mean squared error (MMSE) conditional error estimator and demonstrate its computation over the feature space. In addition, we demonstrate superior or leading class performance over an RNA-Seq dataset containing two lung cancer tumor types from The Cancer Genome Atlas (TCGA).

Conclusions

Through model-based, optimal Bayesian classification, we demonstrate superior classification performance for both synthetic and real RNA-Seq datasets. A tutorial video and Python source code is available under an open source license at http://bit.ly/1gimnss.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0401-3) contains supplementary material, which is available to authorized users.     

A Case-Control Study of Maternal Periconceptual and Pregnancy Recreational Drug Use and Fetal Malformation Using Hair Analysis

Objective

Maternal recreational drug use may be associated with the development of fetal malformations such as gastroschisis, brain and limb defects, the aetiology due to vascular disruption during organogenesis. Using forensic hair analysis we reported evidence of recreational drug use in 18% of women with a fetal gastroschisis. Here we investigate this association in a variety of fetal malformations using the same method.

Methods

In a multi-centre study, women with normal pregnancies (controls) and those with fetal abnormalities (cases) gave informed consent for hair analysis for recreational drug metabolites using mass spectrometry. Hair samples cut at the root were tested in sections corresponding to 3 month time periods (pre and periconceptual period).

Results

Women whose fetus had gastroschisis, compared to women with a normal control fetus, were younger (mean age 23.78±SD4.79 years, 18–37 vs 29.79±SD6 years, 18–42, p = 0.00001), were more likely to have evidence of recreational drug use (15, 25.4% vs 21, 13%, OR2.27, 95^thCI 1.08–4.78, p = 0.028), and were less likely to report periconceptual folic acid use (31, 53.4% vs 124, 77.5%, OR0.33, 95^thCI 0.18–0.63, p = 0.001). Age-matched normal control women were no less likely to test positive for recreational drugs than women whose fetus had gastroschisis. After accounting for all significant factors, only young maternal age remained significantly associated with gastroschisis. Women with a fetus affected by a non-neural tube central nervous system (CNS) anomaly were more likely to test positive for recreational drugs when compared to women whose fetus was normal (7, 35% vs 21, 13%, OR3.59, 95^th CI1.20–10.02, p = 0.01).

Conclusions

We demonstrate a significant association between non neural tube CNS anomalies and recreational drug use in the periconceptual period, first or second trimesters, but we cannot confirm this association with gastroschisis. We confirm the association of gastroschisis with young maternal age.     

A Mathematical Model of Sentimental Dynamics Accounting for Marital Dissolution

Background

Marital dissolution is ubiquitous in western societies. It poses major scientific and sociological problems both in theoretical and therapeutic terms. Scholars and therapists agree on the existence of a sort of second law of thermodynamics for sentimental relationships. Effort is required to sustain them. Love is not enough.

Methodology/Principal Findings

Building on a simple version of the second law we use optimal control theory as a novel approach to model sentimental dynamics. Our analysis is consistent with sociological data. We show that, when both partners have similar emotional attributes, there is an optimal effort policy yielding a durable happy union. This policy is prey to structural destabilization resulting from a combination of two factors: there is an effort gap because the optimal policy always entails discomfort and there is a tendency to lower effort to non-sustaining levels due to the instability of the dynamics.

Conclusions/Significance

These mathematical facts implied by the model unveil an underlying mechanism that may explain couple disruption in real scenarios. Within this framework the apparent paradox that a union consistently planned to last forever will probably break up is explained as a mechanistic consequence of the second law.     

Using Highly Detailed Administrative Data to Predict Pneumonia Mortality

Background

Mortality prediction models generally require clinical data or are derived from information coded at discharge, limiting adjustment for presenting severity of illness in observational studies using administrative data.

Objectives

To develop and validate a mortality prediction model using administrative data available in the first 2 hospital days.

Research Design

After dividing the dataset into derivation and validation sets, we created a hierarchical generalized linear mortality model that included patient demographics, comorbidities, medications, therapies, and diagnostic tests administered in the first 2 hospital days. We then applied the model to the validation set.

Subjects

Patients aged ≥18 years admitted with pneumonia between July 2007 and June 2010 to 347 hospitals in Premier, Inc.’s Perspective database.

Measures

In hospital mortality.

Results

The derivation cohort included 200,870 patients and the validation cohort had 50,037. Mortality was 7.2%. In the multivariable model, 3 demographic factors, 25 comorbidities, 41 medications, 7 diagnostic tests, and 9 treatments were associated with mortality. Factors that were most strongly associated with mortality included receipt of vasopressors, non-invasive ventilation, and bicarbonate. The model had a c-statistic of 0.85 in both cohorts. In the validation cohort, deciles of predicted risk ranged from 0.3% to 34.3% with observed risk over the same deciles from 0.1% to 33.7%.

Conclusions

A mortality model based on detailed administrative data available in the first 2 hospital days had good discrimination and calibration. The model compares favorably to clinically based prediction models and may be useful in observational studies when clinical data are not available.     

Clinicians’ Involvement of Patients in Decision Making. A Video Based Comparison of Their Behavior in Public vs. Private Practice

Background

Little is known about the extent to which Peruvian physicians seek to involve patients in shared decision making, or about the variation in these efforts across different settings.

Objective

To measure the extent to which Peruvian clinicians involve their patients in decision making and to explore the differences between clinicians’ behavior in private vs. public practice.

Design

Videographic analysis.

Participants and Setting

Seven academic physicians who provided care to patients in a public and a private setting participate in this study. All the encounters in both settings were filmed on one random day of February 2012. Approach: Two raters, working independently and in duplicate used the 12-item OPTION scale to quantify the extent of physician effort to involve patients in shared decision making (with 0 indicating no effort and 100 maximum possible effort) in 58 video recordings of usual clinical encounters in private and public practice.

Results

The mean OPTION score was 14.3 (SD 7.0). Although the OPTION score in the private setting (mean 16.5, SD 7.3) was higher than in the public setting (mean 12.3 SD 6.1) this difference was not statistically significant (p = .09).

Conclusion

Peruvian academic physicians in this convenience sample barely sought to involve their patients in shared decision making. Additional studies are required to confirm these results which suggest that patient-centered care remains an unfulfilled promise and a source of inequity within and across the private and the public sectors in Peru.     

Is Aquatic Life Correlated with an Increased Hematocrit in Snakes?

Background

Physiological adaptations that allow air-breathing vertebrates to remain underwater for long periods mainly involve modifications of the respiratory system, essentially through increased oxygen reserves. Physiological constraints on dive duration tend to be less critical for ectotherms than for endotherms because the former have lower mass-specific metabolic rates. Moreover, comparative studies between marine and terrestrial ectotherms have yet to show overall distinct physiological differences specifically associated with oxygen reserves.

Methodology/Principal Findings

We used phylogenetically informed statistical models to test if habitat affects hematocrit (an indicator of blood oxygen stores) in snakes, a lineage that varies widely in habitat use. Our results indicate that both phylogenetic position (clade) and especially habitat are significant predictors of hematocrit. Our analysis also confirms the peculiar respiratory physiology of the marine Acrochordus granulatus.

Conclusion/Significance

Contrary to previous findings, marine snakes have significantly–albeit slightly–elevated hematocrit, which should facilitate increased aerobic dive times. Longer dives could have consequences for foraging, mate searching, and predation risks. Alternatively, but not exclusively, increased Hct in marine species might also help to fuel other oxygen-demanding physiological adaptations, such as those involved in osmoregulation.     

Measuring the Conservation Value of Tropical Primary Forests: The Effect of Occasional Species on Estimates of Biodiversity Uniqueness

Background

Developing effective conservation plans for multi-functional landscapes requires an accurate knowledge of the relative conservation value of different land-uses. A growing number of tropical ecologists have evaluated conservation value using the number (or proportion) of species that are unique to primary or old-growth forests. However, estimates of the conservation value of modified land-uses may be inflated by the presence of occasional species (e.g. singletons and doubletons) that may be unable to exist as viable populations in isolation.

Methodology/Principal Findings

We use a unique 15-taxa dataset from a mixed-use forest landscape in the Brazilian Amazon to test the hypothesis that the removal of occasional species from sample data can increase estimates of the value of primary forest for biodiversity conservation.

Conclusions/Significance

Estimates of conservation value that are based on the proportion of species that are unique to tropical primary or old-growth forests are highly sensitive to decisions researchers make regarding the inclusion or exclusion of occasional species. By removing singletons from modified forest samples, and considering only those species known to occur in primary forest, we almost double estimates of the conservation value of tropical primary forests.     

Predicting the Location and Spatial Extent of Submerged Coral Reef Habitat in the Great Barrier Reef World Heritage Area,Australia

Aim

Coral reef communities occurring in deeper waters have received little research effort compared to their shallow-water counterparts, and even such basic information as their location and extent are currently unknown throughout most of the world. Using the Great Barrier Reef as a case study, habitat suitability modelling is used to predict the distribution of deep-water coral reef communities on the Great Barrier Reef, Australia. We test the effectiveness of a range of geophysical and environmental variables for predicting the location of deep-water coral reef communities on the Great Barrier Reef.

Location

Great Barrier Reef, Australia.

Methods

Maximum entropy modelling is used to identify the spatial extent of two broad communities of habitat-forming megabenthos phototrophs and heterotrophs. Models were generated using combinations of geophysical substrate properties derived from multibeam bathymetry and environmental data derived from Bio-ORACLE, combined with georeferenced occurrence records of mesophotic coral communities from autonomous underwater vehicle, remotely operated vehicle and SCUBA surveys. Model results are used to estimate the total amount of mesophotic coral reef habitat on the GBR.

Results

Our models predict extensive but previously undocumented coral communities occurring both along the continental shelf-edge of the Great Barrier Reef and also on submerged reefs inside the lagoon. Habitat suitability for phototrophs is highest on submerged reefs along the outer-shelf and the deeper flanks of emergent reefs inside the GBR lagoon, while suitability for heterotrophs is highest in the deep waters along the shelf-edge. Models using only geophysical variables consistently outperformed models incorporating environmental data for both phototrophs and heterotrophs.

Main Conclusion

Extensive submerged coral reef communities that are currently undocumented are likely to occur throughout the Great Barrier Reef. High-quality bathymetry data can be used to identify these reefs, which may play an important role in resilience of the GBR ecosystem to climate change.     

Antenatal Screening for Down Syndrome Using Serum Placental Growth Factor with the Combined,Quadruple, Serum Integrated and Integrated Tests

Objective

To estimate the value of first or second trimester placental growth factor (PlGF) as an additional antenatal screening marker for Down syndrome.

Design

Nested case-control study.

Setting

Antenatal screening service.

Population or Sample

532 Down syndrome pregnancies and 1,155 matched unaffected pregnancies.

Methods

Stored maternal serum samples (−40°C) were assayed for PlGF. Monte Carlo simulation was used to estimate the screening performance of PlGF with the Combined, Quadruple, serum Integrated and Integrated tests.

Main Outcome Measures

Median PlGF levels in affected and unaffected pregnancies and screening performance (detection rates [DR] for specified false-positive rates [FPR] and vice versa).

Results

First trimester median PlGF was 15%, 28% and 39% lower in Down syndrome than unaffected pregnancies at 11, 12 and 13 completed weeks’ gestation respectively (all p<0.001). Second trimester median PlGF was 31% lower at 14 weeks (p<0.001), and the difference decreased (6% lower at 17 weeks). At a 90% DR with first trimester markers measured at 13 weeks, adding PlGF decreased the FPR from 11.1 to 5.1% using the Combined test, 9.3% to 4.5% using the serum Integrated test, and 3.4% to 1.5% using the Integrated test (or 1.5 to 1.4% with first trimester markers measured at 11 weeks). Adding PlGF to the Quadruple test (measured at 15 weeks) decreased the FPR from 10.0% to 9.6% at a 90% DR.

Conclusions

First trimester PlGF measurements improve the performance of antenatal screening for Down syndrome using the Combined, serum Integrated and Integrated tests. Second trimester PlGF measurements are of limited value.     

The Heterogeneity of Early Parkinson’s Disease: A Cluster Analysis on Newly Diagnosed Untreated Patients

Background

The variability in the clinical phenotype of Parkinson’s disease seems to suggest the existence of several subtypes of the disease. To test this hypothesis we performed a cluster analysis using data assessing both motor and non-motor symptoms in a large cohort of newly diagnosed untreated PD patients.

Methods

We collected data on demographic, motor, and the whole complex of non-motor symptoms from 100 consecutive newly diagnosed untreated outpatients. Statistical cluster analysis allowed the identification of different subgroups, which have been subsequently explored.

Results

The data driven approach identified four distinct groups of patients, we have labeled: 1) Benign Pure Motor; 2) Benign mixed Motor-Non-Motor; 3) Non-Motor Dominant; and 4) Motor Dominant.

Conclusion

Our results confirmed the existence of different subgroups of early PD patients. Cluster analysis revealed the presence of distinct subtypes of patients profiled according to the relevance of both motor and non-motor symptoms. Identification of such subtypes may have important implications for generating pathogenetic hypotheses and therapeutic strategies.     

Prognostic role of c-met expression in breast cancer patients

Background

Hepatocyte growth factor plays an important role in tumor growth, metastasis and angiogenesis. C-met is HGF''s high affinity receptor.

Aim

The aim of the study was to assess the correlations between c-met expression and clinic-pathological factors in breast cancer tissues. Furthermore, the purpose of the study was to evaluate the prognostic value of the hepatocyte growth factor receptor (HGFR, c-met) expressions in homogenous group of breast cancer patients.

Materials and methods

Tumor samples were collected from 302 patients with breast carcinoma treated with primary surgery. We have assessed the percentage of tumor cells with c-met expression, the intensity of reaction and the ratio of these two factors—immunoreactivity according to the Remmele score.

Results

We have observed no correlations between HGFR immunoreactivities and clinical parameters (tumor size, grade, axillary lymph node status, age). In 5-year observation we have found prognostic value of assessing c-met immunoreactivity in primary tumor.

Conclusion

Our study has revealed prognostic value of c-met. Unlike in other authors’ studies, our patients’ group is very homogenous which might contribute to obtained results.