Length of activity season drives geographic variation in body size of a widely distributed lizard

Understanding the factors that drive geographic variation in life history is an important challenge in evolutionary ecology. Here, we analyze what predicts geographic variation in life-history traits of the common lizard, Zootoca vivipara, which has the globally largest distribution range of all terrestrial reptile species. Variation in body size was predicted by differences in the length of activity season, while we found no effects of environmental temperature per se. Females experiencing relatively short activity season mature at a larger size and remain larger on average than females in populations with relatively long activity seasons. Interpopulation variation in fecundity was largely explained by mean body size of females and reproductive mode, with viviparous populations having larger clutch size than oviparous populations. Finally, body size-fecundity relationship differs between viviparous and oviparous populations, with relatively lower reproductive investment for a given body size in oviparous populations. While the phylogenetic signal was weak overall, the patterns of variation showed spatial effects, perhaps reflecting genetic divergence or geographic variation in additional biotic and abiotic factors. Our findings emphasize that time constraints imposed by the environment rather than ambient temperature play a major role in shaping life histories in the common lizard. This might be attributed to the fact that lizards can attain their preferred body temperature via behavioral thermoregulation across different thermal environments. Length of activity season, defining the maximum time available for lizards to maintain optimal performance, is thus the main environmental factor constraining growth rate and annual rates of mortality. Our results suggest that this factor may partly explain variation in the extent to which different taxa follow ecogeographic rules.

Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium.

OBJECTIVES: To investigate whether associations of smoking with depression and anxiety are likely to be causal, using a Mendelian randomisation approach. DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730) as a proxy for smoking heaviness, and observational meta-analyses of the associations of smoking status and smoking heaviness with depression, anxiety and psychological distress. PARTICIPANTS: Current, former and never smokers of European ancestry aged ≥16 years from 25 studies in the Consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). PRIMARY OUTCOME MEASURES: Binary definitions of depression, anxiety and psychological distress assessed by clinical interview, symptom scales or self-reported recall of clinician diagnosis. RESULTS: The analytic sample included up to 58 176 never smokers, 37 428 former smokers and 32 028 current smokers (total N=127 632). In observational analyses, current smokers had 1.85 times greater odds of depression (95% CI 1.65 to 2.07), 1.71 times greater odds of anxiety (95% CI 1.54 to 1.90) and 1.69 times greater odds of psychological distress (95% CI 1.56 to 1.83) than never smokers. Former smokers also had greater odds of depression, anxiety and psychological distress than never smokers. There was evidence for positive associations of smoking heaviness with depression, anxiety and psychological distress (ORs per cigarette per day: 1.03 (95% CI 1.02 to 1.04), 1.03 (95% CI 1.02 to 1.04) and 1.02 (95% CI 1.02 to 1.03) respectively). In Mendelian randomisation analyses, there was no strong evidence that the minor allele of rs16969968/rs1051730 was associated with depression (OR=1.00, 95% CI 0.95 to 1.05), anxiety (OR=1.02, 95% CI 0.97 to 1.07) or psychological distress (OR=1.02, 95% CI 0.98 to 1.06) in current smokers. Results were similar for former smokers. CONCLUSIONS: Findings from Mendelian randomisation analyses do not support a causal role of smoking heaviness in the development of depression and anxiety.

The Impact of Cannabis Use on Cognitive Functioning in Patients With Schizophrenia: A Meta-analysis of Existing Findings and New Data in a First-Episode Sample.

Cannabis use is highly prevalent among people with schizophrenia, and coupled with impaired cognition, is thought to heighten the risk of illness onset. However, while heavy cannabis use has been associated with cognitive deficits in long-term users, studies among patients with schizophrenia have been contradictory. This article consists of 2 studies. In Study I, a meta-analysis of 10 studies comprising 572 patients with established schizophrenia (with and without comorbid cannabis use) was conducted. Patients with a history of cannabis use were found to have superior neuropsychological functioning. This finding was largely driven by studies that included patients with a lifetime history of cannabis use rather than current or recent use. In Study II, we examined the neuropsychological performance of 85 patients with first-episode psychosis (FEP) and 43 healthy nonusing controls. Relative to controls, FEP patients with a history of cannabis use (FEP + CANN; n = 59) displayed only selective neuropsychological impairments while those without a history (FEP - CANN; n = 26) displayed generalized deficits. When directly compared, FEP + CANN patients performed better on tests of visual memory, working memory, and executive functioning. Patients with early onset cannabis use had less neuropsychological impairment than patients with later onset use. Together, these findings suggest that patients with schizophrenia or FEP with a history of cannabis use have superior neuropsychological functioning compared with nonusing patients. This association between better cognitive performance and cannabis use in schizophrenia may be driven by a subgroup of "neurocognitively less impaired" patients, who only developed psychosis after a relatively early initiation into cannabis use.

Diagnostic Performances of 18F-FDG Positron Emission Tomography in Large Vessels Vasculitis: Meta-analysis

Toperform a meta-analysis of FDG-PET performances in the diagnosis of largevessels vasculitis (Giant Cell Arteritis (GCA) associated or not withPolymyalgia Rheumatica(PMR), Takayasu). Materials and methods : The MEDLINE,Cochrane Library, Embase were searched for relevant original articlesdescribing FDG-PET for vasculitis assessment, using MesH terms ("GiantCell Arteritis or Vasculitis" AND "PET"). Criteria for inclusionwere:(1)FDG-PET for diagnosis of vasculitis(2)American College of Rheumatologycriteria as reference standard(3)control group. After data extraction, analyseswere performed using a random-effects model. Results : Of 184 citations(database search and references screening),70 articles were reviewed of which12 eligible studies were extracted (sensitivity range from 32% to 97%). 7studies fulfilled all inclusion criteria. Owing to overlapping population, 1study was excluded. Statistical heterogeneity justified the random-effectsmodel. Pooled 6 studies analysis(116 vasculitis,224 controls) showed a 81%sensitivity (95%CI:70-89%);a 89% specificity (95%CI:77-95%);a 85%PPV(95%CI:63-95%); a 90% NPV(95%CI:79-95%);a 7.1 positive LR(95%CI:3.4-14.9); a0.2 negative LR(95%CI:0.14-0.35) and 90.1 DOR(95%CI: 18.6-437). Conclusion :FDG-PET has good diagnostic performances in the detection of large vesselsvasculitis. Its promising role could be extended to follow up patients undertreatment, but further studies are needed to confirm this possibility.

Risk factors for survival after lung metastasectomy in colorectal cancer patients: a systematic review and meta-analysis.

BACKGROUND: Resection of lung metastases (LM) from colorectal cancer (CRC) is increasingly performed with a curative intent. It is currently not possible to identify those CRC patients who may benefit the most from this surgical strategy. The aim of this study was to perform a systematic review of risk factors for survival after lung metastasectomy for CRC. METHODS: We performed a meta-analysis of series published between 2000 and 2011, which focused on surgical management of LM from CRC and included more than 40 patients each. Pooled hazard ratios (HR) were calculated by using random effects model for parameters considered as potential prognostic factors. RESULTS: Twenty-five studies including a total of 2925 patients were considered in this analysis. Four parameters were associated with poor survival: (1) a short disease-free interval between primary tumor resection and development of LM (HR 1.59, 95 % confidence interval [CI] 1.27-1.98); (2) multiple LM (HR 2.04, 95 % CI 1.72-2.41); (3) positive hilar and/or mediastinal lymph nodes (HR 1.65, 95 % CI 1.35-2.02); and (4) elevated prethoracotomy carcinoembryonic antigen (HR 1.91, 95 % CI 1.57-2.32). By comparison, a history of resected liver metastases (HR 1.22, 95 % CI 0.91-1.64) did not achieve statistical significance. CONCLUSIONS: Clinical variables associated with prolonged survival after surgery for LM in CRC patients include prolonged disease-free interval between primary tumor and metastatic spread, normal prethoracotomy carcinoembryonic antigen, absence of thoracic node involvement, and a single pulmonary lesion.

Meta-analysis of estrogen response in MCF-7 distinguishes early target genes involved in signaling and cell proliferation from later target genes involved in cell cycle and DNA repair.

ABSTRACT: BACKGROUND: Many studies have been published outlining the global effects of 17 beta-estradiol (E2) on gene expression in human epithelial breast cancer derived MCF-7 cells. These studies show large variation in results, reporting between ~100 and ~1500 genes regulated by E2, with poor overlap. RESULTS: We performed a meta-analysis of these expression studies, using the Rank product method to obtain a more accurate and stable list of the differentially expressed genes, and of pathways regulated by E2. We analyzed 9 time-series data sets, concentrating on response at 3-4 hrs (early) and at 24 hrs (late). We found >1000 statistically significant probe sets after correction for multiple testing at 3-4 hrs, and >2000 significant probe sets at 24 hrs. Differentially expressed genes were examined by pathway analysis. This revealed 15 early response pathways, mostly related to cell signaling and proliferation, and 20 late response pathways, mostly related to breast cancer, cell division, DNA repair and recombination. CONCLUSIONS: Our results show that meta-analysis identified more differentially expressed genes than the individual studies, and that these genes act together in networks. These results provide new insight into E2 regulated mechanisms, especially in the context of breast cancer.

Active smoking and the risk of type 2 diabetes : a systematic review and meta-analysis

Rapport de synthèse : Introduction : plusieurs études observationnelles suggèrent qu'il existe une association entre le tabagisme actif et l'incidence du diabète de type 2. Toutefois de telles études n'ont jamais été synthétisées de façon systématique. Objectif : conduire une revue systématique avec meta-analyse des études évaluant l'association entre le tabagisme actif et l'incidence du diabète de type 2. Méthode : nous avons effectué une recherche dans les bases de donnée électroniques MEDLINE et EMBASE de 1966 à mai 2007, et l'avons complétée par une recherche manuelle des bibliographies des articles clés retenus ainsi que par la recherche d'abstracts de congrès scientifiques et le contact d'experts. Pour être inclues dans notre revue, les études devaient avoir un design de type cohorte, reporter un risque de glycémies jeun élevée, d'intolérance au glucose ou de diabète de type 2 en relation avec le statut tabagique des participants lors du recrutement et devaient exclure les sujets avec un diabète au début de l'étude. Deux auteurs ont sélectionné de façon indépendante les études et ont extrait les données. Les risques relatifs de diabète étaient ensuite compilés, utilisant un modèle de type « random effect ». Résultats : la recherche a aboutit à 25 études de cohorte prospectives (N=1'165'374 participants) et a reporté en tout 45'844 cas de diabète de type 2 pendant une durée de suivi s'étendant sur 5 à 30 années. Sur les 25 études, 24 reportaient un risque augmenté de diabète chez les fumeurs par comparaison aux non fumeurs. Le risque relatif (RR) commun de toutes les études était de 1.44 (intervalle de confiance (IC) à 95% : 1.31-1.58). Le risque de diabète était plus élevé chez les fumeurs de plus de 20 cigarettes par jour (RR : 1.61, IC 95% : 1.43-1.80) en comparaison aux fumeurs ayant une consommation inférieure (RR : 1.29, IC 95% : 1.13-1.48) et le risque était moindre pour les anciens fumeurs (RR :1.23; IC 95% : 1.14-1.33) comparé aux fumeurs actifs. Ces éléments parlent en faveur d'un effet dose-réponse et donc d'une relation de causalité, sans pour autant la prouver. Conclusion : notre étude révèle que le tabagisme actif est associé avec un risque augmenté de 44% de diabète de type 2. Des recherches futures sont nécessaires pour évaluer si cette association est causale et pour clarifier les mécanismes d'action. Dans l'intervalle, les professionnels de santé devraient mentionner l'éviction du diabète comme une raison supplémentaire d'arrêter de fumer ou de ne pas commencer à fumer.

Individual patient data systematic review and meta-analysis of optic nerve sheath diameter ultrasonography for detecting raised intracranial pressure: protocol of the ONSD research group.

BACKGROUND: The purpose of the optic nerve sheath diameter (ONSD) research group project is to establish an individual patient-level database from high quality studies of ONSD ultrasonography for the detection of raised intracranial pressure (ICP), and to perform a systematic review and an individual patient data meta-analysis (IPDMA), which will provide a cutoff value to help physicians making decisions and encourage further research. Previous meta-analyses were able to assess the diagnostic accuracy of ONSD ultrasonography in detecting raised ICP but failed to determine a precise cutoff value. Thus, the ONSD research group was founded to synthesize data from several recent studies on the subject and to provide evidence on the diagnostic accuracy of ONSD ultrasonography in detecting raised ICP. METHODS: This IPDMA will be conducted in different phases. First, we will systematically search for eligible studies. To be eligible, studies must have compared ONSD ultrasonography to invasive intracranial devices, the current reference standard for diagnosing raised ICP. Subsequently, we will assess the quality of studies included based on the QUADAS-2 tool, and then collect and validate individual patient data. The objectives of the primary analyses will be to assess the diagnostic accuracy of ONSD ultrasonography and to determine a precise cutoff value for detecting raised ICP. Secondly, we will construct a logistic regression model to assess whether patient and study characteristics influence diagnostic accuracy. DISCUSSION: We believe that this IPD MA will provide the most reliable basis for the assessment of diagnostic accuracy of ONSD ultrasonography for detecting raised ICP and to provide a cutoff value. We also hope that the creation of the ONSD research group will encourage further study. TRIAL REGISTRATION: PROSPERO registration number: CRD42012003072.

Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Endovascular aortic repair versus open surgical repair for descending thoracic aortic disease a systematic review and meta-analysis of comparative studies.

OBJECTIVES: The purpose of this study was to determine whether thoracic endovascular aortic repair (TEVAR) reduces death and morbidity compared with open surgical repair for descending thoracic aortic disease. BACKGROUND: The role of TEVAR versus open surgery remains unclear. Metaregression can be used to maximally inform adoption of new technologies by utilizing evidence from existing trials. METHODS: Data from comparative studies of TEVAR versus open repair of the descending aorta were combined through meta-analysis. Metaregression was performed to account for baseline risk factor imbalances, study design, and thoracic pathology. Due to significant heterogeneity, registry data were analyzed separately from comparative studies. RESULTS: Forty-two nonrandomized studies involving 5,888 patients were included (38 comparative studies, 4 registries). Patient characteristics were balanced except for age, as TEVAR patients were usually older than open surgery patients (p = 0.001). Registry data suggested overall perioperative complications were reduced. In comparative studies, all-cause mortality at 30 days (odds ratio [OR]: 0.44, 95% confidence interval [CI]: 0.33 to 0.59) and paraplegia (OR: 0.42, 95% CI: 0.28 to 0.63) were reduced for TEVAR versus open surgery. In addition, cardiac complications, transfusions, reoperation for bleeding, renal dysfunction, pneumonia, and length of stay were reduced. There was no significant difference in stroke, myocardial infarction, aortic reintervention, and mortality beyond 1 year. Metaregression to adjust for age imbalance, study design, and pathology did not materially change the results. CONCLUSIONS: Current data from nonrandomized studies suggest that TEVAR may reduce early death, paraplegia, renal insufficiency, transfusions, reoperation for bleeding, cardiac complications, pneumonia, and length of stay compared with open surgery. Sustained benefits on survival have not been proven.

Phylogeographic patterning of mtDNA in the widely distributed harvest mouse (Micromys minutus) suggests dramatic cycles of range contraction and expansion during the mid- to late Pleistocene

We examined sequence variation in the mitochondrial cytochrome b gene (1140 bp, n = 73) and control region (842-851 bp, n = 74) in the Eurasian harvest mouse (Micromys minutus (Pallas, 1771)), with samples drawn from across its range, from Western Europe to Japan. Phylogeographic analyses revealed region-specific haplotype groupings combined with overall low levels of inter-regional genetic divergence. Despite the enormous intervening distance, European and East Asian samples showed a net nucleotide divergence of only 0.36%. Based on an evolutionary rate for the cytochrome b gene of 2.4%(.)(site(.)lineage(.)million years)(-1), the initial divergence time of these populations is estimated at around 80 000 years before present. Our findings are consistent with available fossil evidence that has recorded repeated cycles of extinction and recolonization of Europe by M. minutus through the Quaternary. The molecular data further suggest that recolonization occurred from refugia in the Central to East Asian region. Japanese haplotypes of M. minutus, with the exception of those from Tsushima Is., show limited nucleotide diversity (0.15%) compared with those found on the adjacent Korean Peninsula. This finding suggests recent colonization of the Japanese Archipelago, probably around the last glacial period, followed by rapid population growth.

The effect of cognitive behavioral treatment on the positive symptoms of schizophrenia spectrum disorders: a meta-analysis

(from the journal abstract) Background: Despite the effectiveness of anti-psychotic pharmacotherapy, residual hallucinations and delusions do not completely resolve in some medicated patients. Additional cognitive behavioral therapy (CBT) seems to improve the management of positive symptoms. Despite promising results, the efficacy of CBT is still unclear. The present study addresses this issue taking into account a number of newly published controlled studies. Method: Fourteen studies including 1484 patients, published between 1990 and 2004 were identified and a meta-analysis of their results performed. Results: Compared to other adjunctive measures, CBT showed significant reduction in positive symptoms and there was a higher benefit of CBT for patients suffering an acute psychotic episode versus the chronic condition (effect size of 0.57 vs. 0.27). Discussion: CBT is a promising adjunctive treatment for positive symptoms in schizophrenia spectrum disorders. However, a number of potentially modifying variables have not yet been examined, such as therapeutic alliance and neuropsychological deficits. (PsycINFO Database Record (c) 2005 APA, all rights reserved)

Diagnostic performance of Fluorine-18-Fluorodeoxyglucose positron emission tomography in the assessment of pleural abnormalities in cancer patients: A systematic review and a meta-analysis.

OBJECTIVE: To systematically review and meta-analyze published data about the diagnostic performance of Fluorine-18-Fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) and PET/computed tomography (PET/CT) in the assessment of pleural abnormalities in cancer patients. METHODS: A comprehensive literature search of studies published through June 2013 regarding the role of (18)F-FDG-PET and PET/CT in evaluating pleural abnormalities in cancer patients was performed. All retrieved studies were reviewed and qualitatively analyzed. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR+ and LR-) and diagnostic odd ratio (DOR) of (18)F-FDG-PET or PET/CT on a per patient-based analysis were calculated. The area under the summary ROC curve (AUC) was calculated to measure the accuracy of these methods in the assessment of pleural abnormalities. Sub-analyses considering (18)F-FDG-PET/CT and patients with lung cancer only were carried out. RESULTS: Eight studies comprising 360 cancer patients (323 with lung cancer) were included. The meta-analysis of these selected studies provided the following results: sensitivity 86% [95% confidence interval (95%CI): 80-91%], specificity 80% [95%CI: 73-85%], LR+ 3.7 [95%CI: 2.8-4.9], LR- 0.18 [95%CI: 0.09-0.34], DOR 27 [95%CI: 13-56]. The AUC was 0.907. No significant improvement considering PET/CT studies only and patients with lung cancer was found. CONCLUSIONS: (18)F-FDG-PET and PET/CT demonstrated to be useful diagnostic imaging methods in the assessment of pleural abnormalities in cancer patients, nevertheless possible sources of false-negative and false-positive results should be kept in mind. The literature focusing on the use of (18)F-FDG-PET and PET/CT in this setting remains still limited and prospective studies are needed.