Are time preference and risk preference associated with cognitive intelligence and emotional intelligence?

The authors investigated whether cognitive intelligence (intelligence quotient [IQ]) and emotional intelligence (emotional quotient [EQ]) meaningfully correlate with time preference and risk preference, finding solid evidence in support. In the realm of time preference, high-EQ individuals are less subject to present (or future) bias and more patient. Further, high-IQ subjects tend to exhibit preferences that conform to expected utility maximization. While recent research on the relationship between cognitive ability and preferences has provided important insights, the results suggest that both cognitive intelligence and emotional intelligence matter

Optical detection and modulation at 2µm-2.5µm in silicon

Recently the 2µm wavelength region has emerged as an exciting prospect for the next generation of telecommunications. In this paper we experimentally characterise silicon based plasma dispersion effect optical modulation and defect based photodetection in the 2-2.5µm wavelength range. It is shown that the effectiveness of the plasma dispersion effect is dramatically increased in this wavelength window as compared to the traditional telecommunications wavelengths of 1.3µm and 1.55µm. Experimental results from the defect based photodetectors show that detection is achieved in the 2-2.5µm wavelength range, however the responsivity is reduced as the wavelength is increased away from 1.55µm

SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty.

Detecting allelic imbalance at the isoform level requires accounting for inferential uncertainty, caused by multi-mapping of RNA-seq reads. Our proposed method, SEESAW, uses Salmon and Swish to offer analysis at various levels of resolution, including gene, isoform, and aggregating isoforms to groups by transcription start site. The aggregation strategies strengthen the signal for transcripts with high uncertainty. The SEESAW suite of methods is shown to have higher power than other allelic imbalance methods when there is isoform-level allelic imbalance. We also introduce a new test for detecting imbalance that varies across a covariate, such as time

Mouse genome-wide association and systems genetics identifies Lhfp as a regulator of bone mass.

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10-12) BMD locus on Chromosome [email protected] Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- mice displayed increased osteogenic differentiation. Lhfp-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10-5) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass

Functional Genomics Complements Quantitative Genetics in Identifying Disease-Gene Associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype

Age differences in financial decision making: The benefits of more experience and less negative emotions

The emerging literature on aging and decision making posits that decision‐making competence changes with age, as a result of age differences in various cognitive and noncognitive individual‐differences characteristics. In a national life‐span sample from the United Kingdom (N = 926), we examined age differences in financial decisions, including performance measures of sunk cost and credit card repayment decisions, and self‐report measures of money management and financial decision outcomes. Participants also completed four individual‐differences characteristics that have been proposed as relevant to financial decision making, including two cognitive ones (numeracy and experience‐based knowledge) and two noncognitive ones (negative emotions about financial decisions). First, we examined how age was related to the four financial decision‐making measures and the four individual‐differences characteristics. Older age was correlated to better scores on each of the four financial decision‐making measures, more experience‐based knowledge, less negative emotions about financial decisions, whereas numeracy and motivation were not significantly correlated with age. Second, we found that considering both the two cognitive and the two noncognitive individual‐differences characteristics increased predictions of financial decision making, as compared with considering either alone. Third, we examined how these four individual‐differences characteristics contributed to age differences in financial decision making. Older adults' higher levels of experience‐based knowledge and lower levels of negative emotions seemed to especially benefit their financial decision making. We discuss implications for theories on aging and decision making, as well as for interventions targeting financial decisions

Recent evolution of an ice‐cored moraine at the Gentianes Pass, Valais Alps, Switzerland

International audienceLateral moraines located in permafrost environments often preserve large amounts of both glacier and periglacial ice. To understand how ice‐cored moraines located in high alpine environments evolve in a context of both glacier retreat and permafrost degradation, we performed 11 terrestrial laser‐scanning measurement campaigns between 2007 and 2014 on a highly anthropogenic overprinted moraine prone to instability. Resulting comparison of the subsequent 3D models allowed to qualitatively and quantitatively analyze the morphological evolution of the moraine. The comparisons indicate a very high geomorphic activity of the moraine including large areas affected by downslope movements of blocks and 10 landslides with a volume between 24 ± 1 and 1,138 ± 47 m3. Data also indicated a very strong ice melt with a loss of ice thickness locally reaching 17.7 m at the foot of the moraine. These results, compared with resistivity and thermal measurements of the ground, suggest the combined role of ice loss at the foot of the moraine and the permafrost activity/warming in triggering these processes

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

© 2021, The Author(s). Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256, 523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing