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Abstract Background It has not been clarified whether physical frailty symptoms predict social. frailty. The purpose of this study was to elucidate the effect of physical frailty on social frailty, and to determine which domains of physical frailty predict the development of social frailty. Methods We employed a two-year prospective cohort study. A total of 342 socially robust community-dwelling older adults were recruited. We used a modified social frailty screening index consisting of four social domains including financial difficulties, living alone, social activity, and contact with neighbors. Physical frailty status was also assessed at baseline. At the two-year follow-up, we assessed the development of social frailty. Social status was assessed using four social subdomains for the primary analysis. Social status was assessed using the two social subdomains of social activity and contact with neighbors, which would be affected by the physical frailty component, for the secondary analysis. The risk ratios (RR) of physical frailty for the development of social frailty were estimated. Results Although physical frailty symptoms were not a significant risk factor for future development of social frailty as assessed by four social subdomains (adjusted RR 1.39, 95% CI 0.95–2.15), it became significant when development of social frailty was assessed by the two social subdomains (adjusted RR 1.78, 95% CI 1.10–2.88). An analysis using the physical frailty subdomain showed that slow gait speed (adjusted RR 3.41, 95% CI 1.10–10.53) and weakness (adjusted RR 1.06, 95% CI 1.01–1.12) were independent risk factors for development of social frailty as assessed by two social subdomains. Conclusions Physical frailty symptoms predict the development of social frailty. Among physical frailty subdomains, gait speed and muscle strength are critical independent risk factors for future decline in the social aspect. The prevention of physical frailty, especially by maintaining gait ability and muscle strength, may be effective for avoiding social frailty.

Recently, ultra high definition television (UHDTV) services have become popular using satellites and the Internet. However, there are expansive volumes of high definition television (HDTV) and standard definition television (SDTV) contents held by broadcasting companies and in storage devices. Herein we propose two color space conversion (also known as gamut mapping) methods from BT.709 (used for current HDTV broadcast) to BT.2020 (used for UHDTV broadcast) that restore or estimate lost color information. One of our methods anisotropically diffuses the BT.709 chromaticities with regard to the direction of the original chromaticities in the BT.2020 color space, generating chromaticities out of BT.709 gamut. The other learns an end-to-end conversion method from a BT.709 image to a BT.2020 image and restores lost color information using convolutional neural network (CNN). Using these methods along with BT.709 images, we obtain BT.2020 images with chromaticities from the BT.709 color gamut.

The models and parameters related to the generated curing heat in the molding simulation of composite materials are dependent on the type of resin used and the experimental conditions. Therefore, in this study, we estimated the generated curing heat that changes with time by a data assimilation method, which combines the observation values with simulation values, so that the heat curing simulation of carbon fiber reinforced polymers (CFRPs) becomes closer to the experimental conditions. In the data assimilation method, the temperature distribution on the surface of the composite material was used as an observation value, and the generated curing heat was estimated using an ensemble Kalman filter. By optimizing the data assimilation parameters in advance using the response surface method and estimating the generated curing heat by numerical experiments, the generated curing heat could be estimated with an accuracy represented by the time mean error of less than 6%.

Survival motor neuron protein (SMN), which is linked to spinal muscular atrophy, is a key component of the Gemin complex, which is essential for the assembly of small nuclear RNA-protein complexes (snRNPs). After initial snRNP assembly in the cytoplasm, both snRNPs and SMN migrate to the nucleus and associate with Cajal bodies, where final snRNP maturation occurs. It is assumed that SMN must be free from the Cajal bodies for continuous snRNP biogenesis. Previous observation of the SMN granules docked in the Cajal bodies suggests the existence of a separation mechanism. However, the precise processes that regulate the spatial separation of SMN complexes from Cajal bodies remain unclear. Here, we have employed a super-resolution microscope alongside the β-carboline alkaloid harmine, which disrupts the Cajal body in a reversible manner. Upon removal of harmine, SMN and Coilin first appear as small interconnected condensates. The SMN condensates mature into spheroidal structures encircled by Coilin, eventually segregating into distinct condensates. Expression of a multimerization-deficient SMN mutant leads to enlarged, atypical Cajal bodies in which SMN is unable to segregate into separate condensates. These findings underscore the importance of multimerization in facilitating the segregation of SMN from Coilin within Cajal bodies. [ABSTRACT FROM AUTHOR]