Application of Machine Learning to Mortality Modeling and Forecasting

Estimation of future mortality rates still plays a central role among life insurers in pricing their products and managing longevity risk. In the literature on mortality modeling, a wide number of stochastic models have been proposed, most of them forecasting future mortality rates by extrapolating one or more latent factors. The abundance of proposed models shows that forecasting future mortality from historical trends is non-trivial. Following the idea proposed in Deprez et al. (2017), we use machine learning algorithms, able to catch patterns that are not commonly identifiable, to calibrate a parameter (the machine learning estimator), improving the goodness of fit of standard stochastic mortality models. The machine learning estimator is then forecasted according to the Lee-Carter framework, allowing one to obtain a higher forecasting quality of the standard stochastic models. Out-of sample forecasts are provided to verify the model accuracy

3D printable device for automated operant conditioning in the mouse

Operant conditioning is a classical paradigm and a standard technique used in experimental psychology in which animals learn to perform an action in order to achieve a reward. By using this paradigm, it is possible to extract learning curves and measure accurately reaction times. Both these measurements are proxy of cognitive capabilities and can be used to evaluate the effectiveness of therapeutic interventions in mouse models of disease. Here we describe a fully 3D printable device that is able to perform operant conditioning on freely moving mice, while performing real-time tracking of the animal position. We successfully trained 6 mice, showing stereotyped learning curves that are highly reproducible across mice and reaching more than 70% of accuracy after two days of conditioning. Different products for operant conditioning are commercially available, though most of them do not provide customizable features and are relatively expensive. This data demonstrate that this system is a valuable alternative to available state-of-the-art commercial devices, representing a good balance between performance, cost, and versatility in its use.Significance Statement 3D printing is a revolutionary technology that combines cost-effectiveness with an optimal trade off between standardization and customization. Here we show a device that performs operant conditioning in mice using largely 3D printed parts. This tool can be employed to test learning and memory in models of disease. We expect that the open design of the chamber will be useful for scientific teaching and research as well as for further improvements from the open hardware community

Increased Susceptibility to Cortical Spreading Depression in the Mouse Model of Familial Hemiplegic Migraine Type 2

Familial hemiplegic migraine type 2 (FHM2) is an autosomal dominant form of migraine with aura that is caused by mutations of the α2-subunit of the Na,K-ATPase, an isoform almost exclusively expressed in astrocytes in the adult brain. We generated the first FHM2 knock-in mouse model carrying the human W887R mutation in the Atp1a2 orthologous gene. Homozygous Atp1a2R887/R887 mutants died just after birth, while heterozygous Atp1a2+/R887 mice showed no apparent clinical phenotype. The mutant α2 Na,K-ATPase protein was barely detectable in the brain of homozygous mutants and strongly reduced in the brain of heterozygous mutants, likely as a consequence of endoplasmic reticulum retention and subsequent proteasomal degradation, as we demonstrate in transfected cells. In vivo analysis of cortical spreading depression (CSD), the phenomenon underlying migraine aura, revealed a decreased induction threshold and an increased velocity of propagation in the heterozygous FHM2 mouse. Since several lines of evidence involve a specific role of the glial α2 Na,K pump in active reuptake of glutamate from the synaptic cleft, we hypothesize that CSD facilitation in the FHM2 mouse model is sustained by inefficient glutamate clearance by astrocytes and consequent increased cortical excitatory neurotransmission. The demonstration that FHM2 and FHM1 mutations share the ability to facilitate induction and propagation of CSD in mouse models further support the role of CSD as a key migraine trigger

Parameters scored in SHIRPA primary screen.

<p>Parameters scored in SHIRPA primary screen.</p

SHIRPA results.

<p>SHIRPA primary screening was used to assess sensory-and motor function of <i>Atp1a2^+/R887</i> knock-in mice (n = 8) lines. Wild-type littermates (n = 6) were used as control. All data are expressed as mean ± S.D.. Significant Mann-Whitney non-parametric test is indicated (* = p<0.05).</p

Knock-in construct strategy.

<p>A. Genomic structure of the targeting vector and wt <i>Atp1a2</i> allele. B. Predicted structure after homologous recombination (<i>Atp1a2^R887-neo</i> allele), and after Flp-mediated deletion of the neo-cassette (<i>Atp1a2^R887</i> allele). FRT sites are indicated by green circles. Grey boxes indicate respective exons, and yellow star the R887 mutation in exon19. C. Southern blot of F1 <i>Atp1a2^+/R887</i>^-neo mutant mice. EcoRV and BamHI-digested genomic DNA from two genotypes for wild-type and <i>Atp1a2^+/R887neo</i> mutant strains probed 5′ and 3′ probe.</p

In vivo expression of mutant <i>Atp1a2</i>.

<p>Total RNA and protein samples were isolated from brain of wild type (+/+), <i>Atp1a2^+/R887</i> (+/R887) and homozygous <i>Atp1a2^R887/R887</i> (R887/R887) mice at E19.5. A. Left panel. Semi quantitative <i>Atp1a2</i> RT-PCR (254 bp fragment) on brain cDNA. The b-actin fragment (610 bp) is included as in-tube normalizer. Right panel, same <i>Atp1a2</i> RT-PCR fragments digested by MspI. B. Protein blot of microsomal fraction probed with anti-α2 Na,K-ATPase antibody and anti-neogenin as loading control; the α2 Na,K-ATPase and neogenin bands appear at the expected size of 110 kDa and 52 kDa, respectively. C. Total brain lysates from adult wild type and <i>Atp1a2^+/R887</i> mice probed with anti-α1, α2, and α3 Na,K-ATPase antibodies; anti- tubulin as loading control. Densitometric quantization shows a 50% reduction of the heterozygous mutant α2 level compared to wild type. Error bars represent ± SD; Student's <i>t test</i> p<0.05, n = 3; α1, α2, and α3 Na,K-ATPases migrate as single bands according to the expected size of 110 kDa. D. Region specific immunoblot from cortex, cerebellum and total brain of adult wild type and <i>Atp1a2^+/R887</i> mice probed with anti-α2 and anti- glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as loading control (Figure 2D). Densitometry evaluation shows significant reduction in α2 level (p<0.05) of 50%, 35% and 40% in cortex, cerebellum and total brain, respectively. Error bars represent ± SD; Student's <i>t test</i> p<0.05, n = 3.</p