Ink dating using thermal desorption and gas chromatography / mass spectrometry: comparison of results obtained in two laboratories

Recent ink dating methods focused mainly on changes in solvent amounts occurring over time. A promising method was developed at the Landeskriminalamt of Munich using thermal desorption (TD) followed by gas chromatography / mass spectrometry (GC/MS) analysis. Sequential extractions of the phenoxyethanol present in ballpoint pen ink entries were carried out at two different temperatures. This method is applied in forensic practice and is currently implemented in several laboratories participating to the InCID group (International Collaboration on Ink Dating). However, harmonization of the method between the laboratories proved to be a particularly sensitive and time consuming task. The main aim of this work was therefore to implement the TD-GC/MS method at the Bundeskriminalamt (Wiesbaden, Germany) in order to evaluate if results were comparable to those obtained in Munich. At first validation criteria such as limits of reliable measurements, linearity and repeatability were determined. Samples were prepared in three different laboratories using the same inks and analyzed using two TDS-GC/MS instruments (one in Munich and one in Wiesbaden). The inter- and intra-laboratory variability of the ageing parameter was determined and ageing curves were compared. While inks stored in similar conditions yielded comparable ageing curves, it was observed that significantly different storage conditions had an influence on the resulting ageing curves. Finally, interpretation models, such as thresholds and trend tests, were evaluated and discussed in view of the obtained results. Trend tests were considered more suitable than threshold models. As both approaches showed limitations, an alternative model, based on the slopes of the ageing curves, was also proposed.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Contribution of Intronic miR-338-3p and Its Hosting Gene AATK to Compensatory β-Cell Mass Expansion.

The elucidation of the mechanisms directing β-cell mass regeneration and maintenance is of interest, because the deficit of β-cell mass contributes to diabetes onset and progression. We previously found that the level of the microRNA (miRNA) miR-338-3p is decreased in pancreatic islets from rodent models displaying insulin resistance and compensatory β-cell mass expansion, including pregnant rats, diet-induced obese mice, and db/db mice. Transfection of rat islet cells with oligonucleotides that specifically block miR-338-3p activity increased the fraction of proliferating β-cells in vitro and promoted survival under proapoptotic conditions without affecting the capacity of β-cells to release insulin in response to glucose. Here, we evaluated the role of miR-338-3p in vivo by injecting mice with an adeno-associated viral vector permitting specific sequestration of this miRNA in β-cells. We found that the adeno-associated viral construct increased the fraction of proliferating β-cells confirming the data obtained in vitro. miR-338-3p is generated from an intron of the gene coding for apoptosis-associated tyrosine kinase (AATK). Similarly to miR-338-3p, we found that AATK is down-regulated in rat and human islets and INS832/13 β-cells in the presence of the cAMP-raising agents exendin-4, estradiol, and a G-protein-coupled Receptor 30 agonist. Moreover, AATK expression is reduced in islets of insulin resistant animal models and selective silencing of AATK in INS832/13 cells by RNA interference promoted β-cell proliferation. The results point to a coordinated reduction of miR-338-3p and AATK under insulin resistance conditions and provide evidence for a cooperative action of the miRNA and its hosting gene in compensatory β-cell mass expansion.

Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models

Aim: Modelling species at the assemblage level is required to make effective forecast of global change impacts on diversity and ecosystem functioning. Community predictions may be achieved using macroecological properties of communities (MEM), or by stacking of individual species distribution models (S-SDMs). To obtain more realistic predictions of species assemblages, the SESAM framework suggests applying successive filters to the initial species source pool, by combining different modelling approaches and rules. Here we provide a first test of this framework in mountain grassland communities. Location: The western Swiss Alps. Methods: Two implementations of the SESAM framework were tested: a "Probability ranking" rule based on species richness predictions and rough probabilities from SDMs, and a "Trait range" rule that uses the predicted upper and lower bound of community-level distribution of three different functional traits (vegetative height, specific leaf area and seed mass) to constraint a pool of environmentally filtered species from binary SDMs predictions. Results: We showed that all independent constraints expectedly contributed to reduce species richness overprediction. Only the "Probability ranking" rule allowed slightly but significantly improving predictions of community composition. Main conclusion: We tested various ways to implement the SESAM framework by integrating macroecological constraints into S-SDM predictions, and report one that is able to improve compositional predictions. We discuss possible improvements, such as further improving the causality and precision of environmental predictors, using other assembly rules and testing other types of ecological or functional constraints.

Detecting patterns of species diversification in the presence of both rate shifts and mass extinctions.

BACKGROUND: Recent methodological advances allow better examination of speciation and extinction processes and patterns. A major open question is the origin of large discrepancies in species number between groups of the same age. Existing frameworks to model this diversity either focus on changes between lineages, neglecting global effects such as mass extinctions, or focus on changes over time which would affect all lineages. Yet it seems probable that both lineages differences and mass extinctions affect the same groups. RESULTS: Here we used simulations to test the performance of two widely used methods under complex scenarios of diversification. We report good performances, although with a tendency to over-predict events with increasing complexity of the scenario. CONCLUSION: Overall, we find that lineage shifts are better detected than mass extinctions. This work has significance to assess the methods currently used to estimate changes in diversification using phylogenetic trees. Our results also point toward the need to develop new models of diversification to expand our capabilities to analyse realistic and complex evolutionary scenarios.

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.

Bidirectional relationship between the Body Mass Index and Substance Use in Young Men

BACKGROUND: Obesity and substance use are major concern in young people. This study explored the bidirectional longitudinal relationships between the body mass index (BMI) of young men and their use of: 1) four classes of non-medical prescription drugs; 2) alcohol; 3) tobacco; and 4) cannabis. METHODS: Baseline and follow-up data from the Cohort Study on Substance Use Risk Factors were used (n=5,007). A cross-lagged panel model, complemented by probit models as sensitivity analysis, was run to determine the bidirectional relationships between BMI and substance use. Alcohol was assessed using risky single-occasion drinking (RSOD); tobacco, using daily smoking; and cannabis, using hazardous cannabis use (defined as twice-weekly or more cannabis use). Non-medical prescription drugs use (NMPDU) included opioid analgesics, sedatives/sleeping pills, anxiolytics and stimulants. RESULTS: Different associations were found between BMI and substance use. Only RSOD (β= -.053, p=.005) and NMPDU of anxiolytics (β=.040, p=.020) at baseline significantly predicted BMI at follow-up. Baseline RSOD predicted a lower BMI at follow-up while baseline NMPDU of anxiolytics predicted higher BMI at follow-up. Furthermore, BMI at baseline significantly predicted daily smoking (β=.050, p=.007) and hazardous cannabis use (β=.058, p=.030). CONCLUSIONS: Our results suggest different associations between BMI and the use of various substances by young men. However, only RSOD and NMPDU of anxiolytics predicted BMI, whereas BMI predicted daily smoking and hazardous cannabis use.

Reciprocal Effects on Neurocognitive and Metabolic Phenotypes in Mouse Models of 16p11.2 Deletion and Duplication Syndromes.

The 16p11.2 600 kb BP4-BP5 deletion and duplication syndromes have been associated with developmental delay; autism spectrum disorders; and reciprocal effects on the body mass index, head circumference and brain volumes. Here, we explored these relationships using novel engineered mouse models carrying a deletion (Del/+) or a duplication (Dup/+) of the Sult1a1-Spn region homologous to the human 16p11.2 BP4-BP5 locus. On a C57BL/6N inbred genetic background, Del/+ mice exhibited reduced weight and impaired adipogenesis, hyperactivity, repetitive behaviors, and recognition memory deficits. In contrast, Dup/+ mice showed largely opposite phenotypes. On a F1 C57BL/6N × C3B hybrid genetic background, we also observed alterations in social interaction in the Del/+ and the Dup/+ animals, with other robust phenotypes affecting recognition memory and weight. To explore the dosage effect of the 16p11.2 genes on metabolism, Del/+ and Dup/+ models were challenged with high fat and high sugar diet, which revealed opposite energy imbalance. Transcriptomic analysis revealed that the majority of the genes located in the Sult1a1-Spn region were sensitive to dosage with a major effect on several pathways associated with neurocognitive and metabolic phenotypes. Whereas the behavioral consequence of the 16p11 region genetic dosage was similar in mice and humans with activity and memory alterations, the metabolic defects were opposite: adult Del/+ mice are lean in comparison to the human obese phenotype and the Dup/+ mice are overweight in comparison to the human underweight phenotype. Together, these data indicate that the dosage imbalance at the 16p11.2 locus perturbs the expression of modifiers outside the CNV that can modulate the penetrance, expressivity and direction of effects in both humans and mice.