Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model

A linear multi-factor model is one of the most important tools in equity portfolio management. The linear multi-factor models are widely used because they can be easily interpreted. However, financial markets are not linear and their accuracy is limited. Recently, deep learning methods were proposed to predict stock return in terms of the multi-factor model. Although these methods perform quite well, they have significant disadvantages such as a lack of transparency and limitations in the interpretability of the prediction. It is thus difficult for institutional investors to use black-box-type machine learning techniques in actual investment practice because they should show accountability to their customers. Consequently, the solution we propose is based on LSTM with LRP. Specifically, we extend the linear multi-factor model to be non-linear and time-varying with LSTM. Then, we approximate and linearize the learned LSTM models by LRP. We call this LSTM+LRP model a deep recurrent factor model. Finally, we perform an empirical analysis of the Japanese stock market and show that our recurrent model has better predictive capability than the traditional linear model and fully-connected deep learning methods.Comment: In AAAI-19 Workshop on Network Interpretability for Deep Learnin

Unusual Protrusion of Conjunctiva in Two Neonates with Harlequin Ichthyosis

Background: We present two patients who developed severe protrusion of the conjunctiva and chemosis secondary to Harlequin ichthyosis (HI). Case Reports: Case 1 was a male infant diagnosed with HI who had parchment-like appearance and conjunctival protrusion with severe chemosis. Case 2 was a female infant on whom HI had been suspected before birth through ultrasonography. She showed thickened skin over the entire body and conjunctival protrusion with severe chemosis. For both cases, a vitamin A derivative was applied and the hyperkeratotic layer was peeled off every day. Great care was taken to sterilize and moisten the ocular surface. The conjunctival protrusion gradually improved and other systemic conditions were successfully treated. HI is a rare condition, but affected infants are surviving longer than previously and hence guidelines for ocular management are now required. Conclusions: Gentle and patient debridement of the hyperkeratotic skin and moisturizing were important in treating the unusual conjunctival protrusion

Promoter Polymorphism of RGS2 Gene Is Associated with Change of Blood Pressure in Subjects with Antihypertensive Treatment: The Azelnidipine and Temocapril in Hypertensive Patients with Type 2 Diabetes Study

We performed a prospective study to examine the genetic effect on the response to a calcium (Ca) channel blocker, azelnidipine and an ACE inhibitor, temocapril treatment in patients with hypertension, as a part of the prior clinical trial, the Azelnidipine and Temocapril in Hypertensive Patients with Type 2 Diabetes Study (ATTEST). Methods and Results. All subjects who gave informed consent for genetic research were divided into two groups: the subjects treated with azelnidipine or temocapril, for 52 weeks. We selected 18 susceptible genes for hypertension and determined their genotypes using TaqMan PCR method. RNA samples were extracted from peripheral blood, and quantitative real time PCR for all genes was performed using TaqMan method. One of the polymorphisms of the RGS2 gene was extracted as being able to influence the effect of these treatments to reduce BP. At eight weeks, BP change showed a significant interaction between the A-638G polymorphism of Regulator of G protein signaling-2 (RGS2) gene and treatment with azelnidipine or temocapril. There was no gene whose expression was associated with BP phenotypes or the polymorphisms of each gene. Conclusions. A-638G polymorphism of the RGS-2 gene could be a predictive factor for therapeutic performance of Ca channel blockers

Functional mutations in spike glycoprotein of Zaire ebolavirus associated with an increase in infection efficiency

Ebola virus (EBOV) is extremely virulent, and its glycoprotein is necessary for viral entry. EBOV may adapt to its new host humans during outbreaks by acquiring mutations especially in glycoprotein, which allows EBOV to spread more efficiently. To identify these evolutionary selected mutations and examine their effects on viral infectivity, we used experimental–phylogenetic–structural interdisciplinary approaches. In evolutionary analysis of all available Zaire ebolavirus glycoprotein sequences, we detected two codon sites under positive selection, which are located near/within the region critical for the host‐viral membrane fusion, namely alanine‐to‐valine and threonine‐to‐isoleucine mutations at 82 (A82V) and 544 (T544I), respectively. The fine‐scale transmission dynamics of EBOV Makona variants that caused the 2014–2015 outbreak showed that A82V mutant was fixed in the population, whereas T544I was not. Furthermore, pseudotype assays for the Makona glycoprotein showed that the A82V mutation caused a small increase in viral infectivity compared with the T544I mutation. These findings suggest that mutation fixation in EBOV glycoprotein may be associated with their increased infectivity levels; the mutant with a moderate increase in infectivity will fix. Our findings showed that a driving force for Ebola virus evolution via glycoprotein may be a balance between costs and benefits of its virulence