907 resultados para Models and Methods
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A general scheme for devising efficient cluster dynamics proposed in a previous paper [Phys. Rev. Lett. 72, 1541 (1994)] is extensively discussed. In particular, the strong connection among equilibrium properties of clusters and dynamic properties as the correlation time for magnetization is emphasized. The general scheme is applied to a number of frustrated spin models and the results discussed.
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Aim: The insulin sensitizer rosiglitazone (RTZ) acts by activating peroxisome proliferator and activated receptor gamma (PPAR gamma), an effect accompanied in vivo in humans by an increase in fat storage. We hypothesized that this effect concerns PPARgamma(1) and PPARgamma(2) differently and is dependant on the origin of the adipose cells (subcutaneous or visceral). To this aim, the effect of RTZ, the PPARgamma antagonist GW9662 and lentiviral vectors expressing interfering RNA were evaluated on human pre-adipocyte models. Methods: Two models were investigated: the human pre-adipose cell line Chub-S7 and primary pre-adipocytes derived from subcutaneous and visceral biopsies of adipose tissue (AT) obtained from obese patients. Cells were used to perform oil-red O staining, gene expression measurements and lentiviral infections. Results: In both models, RTZ was found to stimulate the differentiation of pre-adipocytes into mature cells. This was accompanied by significant increases in both the PPARgamma(1) and PPARgamma(2) gene expression, with a relatively stronger stimulation of PPARgamma(2). In contrast, RTZ failed to stimulate differentiation processes when cells were incubated in the presence of GW9662. This effect was similar to the effect observed using interfering RNA against PPARgamma(2). It was accompanied by an abrogation of the RTZ-induced PPARgamma(2) gene expression, whereas the level of PPARgamma(1) was not affected. Conclusions: Both the GW9662 treatment and interfering RNA against PPARgamma(2) are able to abrogate RTZ-induced differentiation without a significant change of PPARgamma(1) gene expression. These results are consistent with previous results obtained in animal models and suggest that in humans PPARgamma(2) may also be the key isoform involved in fat storage.
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INTRODUCTION: The importance of the micromovements in the mechanism of aseptic loosening is clinically difficult to evaluate. To complete the analysis of a series of total knee arthroplasties (TKA), we used a tridimensional numerical model to study the micromovements of the tibial implant. MATERIAL AND METHODS: Fifty one patients (with 57 cemented Porous Coated Anatomic TKAs) were reviewed (mean follow-up 4.5 year). Radiolucency at the tibial bone-cement interface was sought on the AP radiographs and divided in 7 areas. The distribution of the radiolucency was then correlated with the axis of the lower limb as measured on the orthoradiograms. The tridimensional numerical model is based on the finite element method. It allowed the measurement of the cemented prosthetic tibial implant's displacements and the micromovements generated at bone-ciment interface. A total load (2000 Newton) was applied at first vertically and asymetrically on the tibial plateau, thereby simulating an axial deviation of the lower limbs. The vector's posterior inclination then permitted the addition of a tangential component to the axial load. This type of effort is generated by complex biomechanical phenomena such as knee flexion. RESULTS: 81 per cent of the 57 knees had a radiolucent line of at least 1 mm, at one or more of the tibial cement-epiphysis jonctional areas. The distribution of these lucent lines showed that they came out more frequently at the periphery of the implant. The lucent lines appeared most often under the unloaded margin of the tibial plateau, when axial deviation of lower limbs was present. Numerical simulations showed that asymetrical loading on the tibial plateau induced a subsidence of the loaded margin (0-100 microns) and lifting off at the opposite border (0-70 microns). The postero-anterior tangential component induced an anterior displacement of the tibial implant (160-220 microns), and horizontal micromovements with non homogenous distribution at the bone-ciment interface (28-54 microns). DISCUSSION: Comparison of clinical and numerical results showed a relation between the development of radiolucent lines and the unloading of the tibial implant's margin. The deleterious effect of lower limbs' axial deviation is thereby proven. The irregular distribution of lucent lines under the tibial plateau was similar of the micromovements' repartition at the bone-cement interface when tangential forces were present. A causative relation between the two phenomenaes could not however be established. Numerical simulation is a truly useful method of study; it permits to calculate micromovements which are relative, non homogenous and of very low amplitude. However, comparative clinical studies remain as essential to ensure the credibility of results.
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PURPOSE: Mutations within the KRAS proto-oncogene have predictive value but are of uncertain prognostic value in the treatment of advanced colorectal cancer. We took advantage of PETACC-3, an adjuvant trial with 3,278 patients with stage II to III colon cancer, to evaluate the prognostic value of KRAS and BRAF tumor mutation status in this setting. PATIENTS AND METHODS: Formalin-fixed paraffin-embedded tissue blocks (n = 1,564) were prospectively collected and DNA was extracted from tissue sections from 1,404 cases. Planned analysis of KRAS exon 2 and BRAF exon 15 mutations was performed by allele-specific real-time polymerase chain reaction. Survival analyses were based on univariate and multivariate proportional hazard regression models. RESULTS: KRAS and BRAF tumor mutation rates were 37.0% and 7.9%, respectively, and were not significantly different according to tumor stage. In a multivariate analysis containing stage, tumor site, nodal status, sex, age, grade, and microsatellite instability (MSI) status, KRAS mutation was associated with grade (P = .0016), while BRAF mutation was significantly associated with female sex (P = .017), and highly significantly associated with right-sided tumors, older age, high grade, and MSI-high tumors (all P < 10(-4)). In univariate and multivariate analysis, KRAS mutations did not have a major prognostic value regarding relapse-free survival (RFS) or overall survival (OS). BRAF mutation was not prognostic for RFS, but was for OS, particularly in patients with MSI-low (MSI-L) and stable (MSI-S) tumors (hazard ratio, 2.2; 95% CI, 1.4 to 3.4; P = .0003). CONCLUSION: In stage II-III colon cancer, the KRAS mutation status does not have major prognostic value. BRAF is prognostic for OS in MS-L/S tumors.
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BACKGROUND: Over 50% of patients with head and neck squamous cell carcinoma (HNSCC) present with locoregionally advanced disease. Those at intermediate-to-high risk of recurrence after definitive therapy exhibit advanced disease based on tumour size or lymph node involvement, non-oropharynx primary sites, human papillomavirus (HPV)-negative oropharyngeal cancer, or HPV-positive oropharynx cancer with smoking history (>10-pack-years). Non-surgical approaches include concurrent chemoradiotherapy, induction chemotherapy followed by definitive radiotherapy or chemoradiotherapy, or radiotherapy alone. Following locoregional therapies (including surgical salvage of residual cervical nodes), no standard intervention exists. Overexpression of epidermal growth factor receptor (EGFR), an ErbB family member, is associated with poor prognosis in HNSCC. EGFR-targeted cetuximab is the only targeted therapy that impacts overall survival and is approved for HNSCC in the USA or Europe. However, resistance often occurs, and new approaches, such as targeting multiple ErbB family members, may be required. Afatinib, an irreversible ErbB family blocker, demonstrated antiproliferative activity in preclinical models and comparable clinical efficacy with cetuximab in a randomized phase II trial in recurrent or metastatic HNSCC. LUX-Head & Neck 2, a phase III study, will assess adjuvant afatinib versus placebo following chemoradiotherapy in primary unresected locoregionally advanced intermediate-to-high-risk HNSCC. METHODS/DESIGN: Patients with primary unresected locoregionally advanced HNSCC, in good clinical condition with unfavourable risk of recurrence, and no evidence of disease after chemoradiotherapy will be randomized 2:1 to oral once-daily afatinib (40 mg starting dose) or placebo. As HPV status will not be determined for eligibility, unfavourable risk is defined as non-oropharynx primary site or oropharynx cancer in patients with a smoking history (>10 pack-years). Treatment will continue for 18 months or until recurrence or unacceptable adverse events occur. The primary endpoint measure is duration of disease-free survival; secondary endpoint measures are disease-free survival rate at 2 years, overall survival, health-related quality of life and safety. DISCUSSION: Given the unmet need in the adjuvant treatment of intermediate-to-high-risk HNSCC patients, it is expected that LUX-Head & Neck 2 will provide new insights into treatment in this setting and might demonstrate the ability of afatinib to significantly improve disease-free survival, compared with placebo. TRIAL REGISTRATION: ClinicalTrials.gov NCT01345669.
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OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.
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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.
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Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activity of neurons under temporally structured current injection. It is, however, difficult to compare the advantages of various models and algorithms since each model is designed for a different set of data. Here, we report about one of the first attempts to establish a benchmark test that permits a systematic comparison of methods and performances in predicting the activity of rat cortical pyramidal neurons. We present early submissions to the benchmark test and discuss implications for the design of future tests and simple neurons models
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Objectives To prospectively assess respiratory health in wastewater workers and garbage collectors over 5 years. Methods Exposure, respiratory symptoms and conditions, spirometry and lung-specific proteins were assessed yearly in a cohort of 304 controls, 247 wastewater workers and 52 garbage collectors. Results were analysed with random coefficient models and linear regression taking into account several potential confounders. Results Symptoms, spirometry and lung-specific proteins were not affected by occupational exposure. Conclusions In this population no effects of occupational exposure to bioaerosols were found, probably because of good working conditions.
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How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.
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It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.
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OBJECTIVE: This systematic review and meta-analysis of randomized controlled trials (RCTs) assesses the effect of pharmacist care on cardiovascular disease (CVD) risk factors among outpatients with diabetes. RESEARCH DESIGN AND METHODS: MEDLINE, EMBASE, CINAHL, and the Cochrane Central Register of Controlled Trials were searched. Pharmacist interventions were classified, and a meta-analysis of mean changes of blood pressure (BP), total cholesterol (TC), LDL cholesterol, HDL cholesterol, and BMI was performed using random-effects models. RESULTS: The meta-analysis included 15 RCTs (9,111 outpatients) in which interventions were conducted exclusively by pharmacists in 8 studies and in collaboration with physicians, nurses, dietitians, or physical therapists in 7 studies. Pharmacist interventions included medication management, educational interventions, feedback to physicians, measurement of CVD risk factors, or patient-reminder systems. Compared with usual care, pharmacist care was associated with significant reductions for systolic BP (12 studies with 1,894 patients; -6.2 mmHg [95% CI -7.8 to -4.6]); diastolic BP (9 studies with 1,496 patients; -4.5 mmHg [-6.2 to -2.8]); TC (8 studies with 1,280 patients; -15.2 mg/dL [-24.7 to -5.7]); LDL cholesterol (9 studies with 8,084 patients; -11.7 mg/dL [-15.8 to -7.6]); and BMI (5 studies with 751 patients; -0.9 kg/m(2) [-1.7 to -0.1]). Pharmacist care was not associated with a significant change in HDL cholesterol (6 studies with 826 patients; 0.2 mg/dL [-1.9 to 2.4]). CONCLUSIONS: This meta-analysis supports pharmacist interventions-alone or in collaboration with other health care professionals-to improve major CVD risk factors among outpatients with diabetes.
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BACKGROUND: Prognostic models and nomograms were recently developed to predict survival of patients with newly diagnosed glioblastoma multiforme (GBM).1 To improve predictions, models should be updated with the most recent patient and disease information. Nomograms predicting patient outcome at the time of disease progression are required. METHODS: Baseline information from 299 patients with recurrent GBM recruited in 8 phase I or II trials of the EORTC Brain Tumor Group was used to evaluate clinical parameters as prognosticators of patient outcome. Univariate (log rank) and multivariate (Cox models) analyses were made to assess the ability of patients' characteristics (age, sex, performance status [WHO PS], and MRC neurological deficit scale), disease history (prior treatments, time since last treatment or initial diagnosis, and administration of steroids or antiepileptics) and disease characteristics (tumor size and number of lesions) to predict progression free survival (PFS) and overall survival (OS). Bootstrap technique was used for models internal validation. Nomograms were computed to provide individual patients predictions. RESULTS: Poor PS and more than 1 lesion had a significant prognostic impact for both PFS and OS. Antiepileptic drug use was significantly associated with worse PFS. Larger tumors (split by the median of the largest tumor diameter >42.5 mm) and steroid use had shorter OS. Age, sex, neurologic deficit, prior therapies, and time since last therapy or initial diagnosis did not show independent prognostic value for PFS or OS. CONCLUSIONS: This analysis confirms that PS but not age is a major prognostic factor for PFS and OS. Multiple or large tumors and the need to administer steroids significantly increase the risk of progression and death. Nomograms at the recurrence could be used to obtain accurate predictions for the design of new targeted therapy trials or retrospective analyses. (1. T. Gorlia et al., Nomograms for predicting survival of patients with newly diagnosed glioblastoma. Lancet Oncol 9 (1): 29-38, 2008.)
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Purpose/Objective: Tuberculosis (TB) is the second worldwide leading cause of death from an infectious disease after HIV infection. Protective immunity to Mycobacterium tuberculosis (Mtb) remains poorly understood and the role of Mtb-specific CD8 T-cells is controversial. We performed comprehensive functional and phenotypic characterizations of Mtb-specific CD8 T-cell responses in 273 subjects with either latent Mtb infection (LTBI) or active TB disease (TB) to assess their profile and relevance in TB. Materials and methods: Using multi-parametric flow cytometry, we assessed Mtb-specific CD8 T-cell functional (production of IFNgamma, IL-2 and TNF-alpha; proliferation capacity and cytotoxicity) and phenotypic (T-cell differentiation and exhaustion) profiles in cells isolated from peripheral blood and correlated these profiles with distinct clinical presentations. Results: Mtb-specific CD8 T-cells were detected in most TB patients and few LTBI subjects (65% and 15%, respectively; P < 0.00001) and were of similar magnitude with a comparable cytokines profile (IFNg+TNFa+IL2-) in both groups. Mtb-specific CD8 T-cells were mostly TEMRA (CD45RA+ CCR7-) co-expressing 2B4 and CD160 in LTBI subjects and mostly TEM (CD45RA-CCR7-) lacking PD-1/ CD160/2B4 in TB patients. Furthermore, Mtb-specific CD8 T-cells mostly expressed very little perforin and granulysin but contained granzymes A and B or lacked all these cytotoxic markers in TB and LTBI subjects, respectively. However, in vitro expanded Mtb-specific CD8 T-cells acquired perforin, granulysin and granzymes. Finally, Mtb-specific CD8 T-cell responses were more robust and prone to proliferate in patients with extrapulmonary compared to pulmonary TB. Conclusions: The clinical status and TB presentation are associated to specific profiles of Mtb-specific CD8 T-cell responses, thus indicating distinct dynamics between the mycobacteria, the CD8 T-cell response and the clinical outcome. Our data shed light on the controversial reached by studies performed in human and animal models, thus advancing the current knowledge on the complex dynamic of TB immunity.
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Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.