Almost all creatinine is excreted by the kidney in individuals. Serum creatinine concentration, a widely used renal function index in clinical practice, can be affected by both genetic and environmental factors, as evidenced by current research exploring the relationship between these factors and kidney function. However, few studies have explored the heritability of serum creatinine in Asian populations. Therefore, we explored the genetic and environmental factors that affect the serum creatinine level in Asian populations. Participants in this study came from the Qingdao Twin Registry in China, and 374 pairs of twins were included, of which 139 pairs were dizygotic twins, whose ages ranged from 40 to 80 years old, and the serum creatinine level ranged from 10 to 126 μmol/L. Structural equation models were constructed using Mx software to calculate heritability, with adjusted covariates being age, sex, and body mass index. The results of heritability analysis showed that ACE was the best fit model. Serum creatinine level is influenced by genetic and environmental factors. The result of heritability was 35.44%, and the influence of shared environmental factors accounted for 52.13%. This study provided the relevant basis for future research on genetic and environmental factors affecting serum creatinine levels in Asian populations.

An abnormal alanine aminotransferase (ALT) level is predictive of disease and all-cause mortality and may indicate liver injury. Using twin modeling, the genetic and environmental factors that affect human serum ALT levels have been well studied for the populations in the different countries, and the results showed moderate-to-high heritability. However, the heritability of ALT level has not been explored in Chinese population. Thus, we recruited 369 pairs of twins (233 monozygotic and 136 dizygotic) from the Qingdao Twin Registry in China with a median age of 50 years (40−80 years). Correlation analysis and a structural equation model (SEM) were conducted to evaluate the heritability of ALT level. The data for age, gender, body mass index and alcohol consumption were set as covariates. Intrapair correlation in monozygotic twins was 0.64 (95%CI [.56, .71]) and 0.42 (95% CI [.28, .55]) in dizygotic twins. The SEM analysis indicated that 65% (95% CI [57%, 71%]) of the variation in ALT levels can be explained by additive genetics and 35% (95% CI [29%, 44%]) of the variation is attributed to unique environmental factors or residuals. Shared environmental influences were not significant. In conclusion, serum ALT variations exhibited strong genetic effects. The variation could also be explained by unique environmental factors. However, shared environmental factors have a minor impact on the serum ALT level.

A theoretical model is established to describe the thermal dynamics and laser kinetics in a static pulsed exciplex pumped Cs–Ar laser (XPAL). The temporal behaviors of both the laser output power and temperature rise in XPALs with a long-time pulse and multi-pulse operation modes are calculated and analyzed. In the case of long-time pulse pumping, the results show that the initial laser power increases with a rise in the initial operating temperature, but the laser power decreases quickly due to heat accumulation. In the case of multi-pulse operation, simulation results show that the optimal laser output power can be obtained by appropriately increasing the initial temperature and reducing the thermal relaxation time.

The genetic and environmental impacts on correlations between hearing and cognitive functions have not been well studied. Cognitive function was evaluated by the Montreal Cognitive Assessment (MoCA). Hearing function was assessed by audiometric pure-tone hearing thresholds at different frequencies, including 0.5 kHz, 1 kHz, 2 kHz, 4 kHz, 8 kHz, and 12.5 kHz, with the lower hearing thresholds indicating better hearing function. Cognitive and hearing functions were measured on 379 complete twin pairs (240 monozygotic and 139 dizygotic pairs) with a median age of 50 years (range: 40–80 years). Bivariate twin models were fitted to quantify the genetic and environmental components of the correlations between hearing and cognitive functions. The analysis showed significantly high genetic correlation between 2 kHz of hearing and cognition (rG = −1.00, 95% CI [−1.00, −0.46]) and moderate genetic correlation between 4 kHz of hearing and cognition (rG = −0.62, 95% CI [−1.00, −0.14]). We found no significant genetic correlations between low as well as high frequencies of hearing and cognition. Low to moderate common and unique environmental correlations were shown between low frequencies of hearing and cognition (−0.13 to −0.39) and the common environmental correlation between 8 kHz, one of the high frequencies of hearing, and cognition (−0.22). The middle frequencies of hearing and cognitive functions may have a shared genetic basis. Low frequencies of hearing and cognition may share similar common and unique environmental factors. At 8 kHz, the high frequency of hearing and cognition may share similar common environment. This twin study detected a significant genetic and environmental basis in the phenotype correlation between cognition and hearing, which differed across frequencies.

Genetic and environmental influences on predictors of decline in daily functioning, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), handgrip, and five-times-sit-to-stand test (FTSST), have not been addressed in the aging Chinese population. We performed classical twin modeling on FEV1, FVC, handgrip, and FTSST in 379 twin pairs (240 MZ and 139 DZ) with median age of 50 years (40–80 years). Data were analyzed by fitting univariate and bivariate twin models to estimate the genetic and environmental influences on these measures of physical function. Heritability was moderate for FEV1, handgrip, and FTSST (55–60%) but insignificant for FVC. Only FVC showed moderate control, with shared environmental factors accounting for about 50% of the total variance. In contrast, all measures of pulmonary function and muscle strength showed modest influences from the unique environment (40–50%). Bivariate analysis showed highly positive genetic correlations between FEV1 and FVC (rG = 1.00), and moderately negative genetic correlations between FTSST and FEV1 (rG = −0.33) and FVC (rG = −0.42). FEV1 and FVC, as well as FEV1 and handgrip, displayed high common environmental correlations (rC = 1.00), and there were moderate correlations between FVC and handgrip (rC = 0.44). FEV1 and FVC showed high unique environmental correlations (rE = 0.76) and low correlations between handgrip and FEV1 (rE = 0.17), FVC (rE = 0.14), and FTSST (rE = −0.13) with positive or negative direction. We conclude that genetic factors contribute significantly to the individual differences in common indicators of daily functioning (FEV1, handgrip, and FTSST). FEV1 and FVC were genetically and environmentally correlated. Pulmonary function and FTSST may share similar sets of genes but in the negative direction. Pulmonary function and muscle strength may have a shared environmental background.

Although the correlation between cognition and physical function has been well studied in the general population, the genetic and environmental nature of the correlation has been rarely investigated. We conducted a classical twin analysis on cognitive and physical function, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), handgrip strength, five-times-sit-to-stand test (FTSST), near visual acuity, and number of teeth lost in 379 complete twin pairs. Bivariate twin models were fitted to estimate the genetic and environmental correlation between physical and cognitive function. Bivariate analysis showed mildly positively genetic correlations between cognition and FEV1, rG = 0.23 [95% CI: 0.03, 0.62], as well as FVC, rG = 0.35 [95% CI: 0.06, 1.00]. We found that FTSST and cognition presented very high common environmental correlation, rC = -1.00 [95% CI: -1.00, -0.57], and low but significant unique environmental correlation, rE = -0.11 [95% CI: -0.22, -0.01], all in the negative direction. Meanwhile, near visual acuity and cognition also showed unique environmental correlation, rE = 0.16 [95% CI: 0.03, 0.27]. We found no significantly genetic correlation for cognition with handgrip strength, FTSST, near visual acuity, and number of teeth lost. Cognitive function was genetically related to pulmonary function. The FTSST and cognition shared almost the same common environmental factors but only part of the unique environmental factors, both with negative correlation. In contrast, near visual acuity and cognition may positively share part of the unique environmental factors.

The genetic influences on aging-related phenotypes, including cognition and depression, have been well confirmed in the Western populations. We performed the first twin-based analysis on cognitive performance, memory and depression status in middle-aged and elderly Chinese twins, representing the world's largest and most rapidly aging population. The sample consisted of 384 twin pairs with a median age of 50 years. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) scale; memory was assessed using the revised Wechsler Adult Intelligence scale; depression symptomatology was evaluated by the self-reported 30-item Geriatric Depression (GDS-30)scale. Both univariate and multivariate twin models were fitted to the three phenotypes with full and nested models and compared to select the best fitting models. Univariate analysis showed moderate-to-high genetic influences with heritability 0.44 for cognition and 0.56 for memory. Multivariate analysis by the reduced Cholesky model estimated significant genetic (rG = 0.69) and unique environmental (rE = 0.25) correlation between cognitive ability and memory. The model also estimated weak but significant inverse genetic correlation for depression with cognition (-0.31) and memory (-0.28). No significant unique environmental correlation was found for depression with other two phenotypes. In conclusion, there can be a common genetic architecture for cognitive ability and memory that weakly correlates with depression symptomatology, but in the opposite direction.

The geometric multigrid method (GMG) is one of the most efficient solving techniques for discrete algebraic systems arising from elliptic partial differential equations. GMG utilizes a hierarchy of grids or discretizations and reduces the error at a number of frequencies simultaneously. Graphics processing units (GPUs) have recently burst onto the scientific computing scene as a technology that has yielded substantial performance and energy-efficiency improvements. A central challenge in implementing GMG on GPUs, though, is that computational work on coarse levels cannot fully utilize the capacity of a GPU. In this work, we perform numerical studies of GMG on CPU-GPU heterogeneous computers. Furthermore, we compare our implementation with an efficient CPU implementation of GMG and with the most popular fast Poisson solver, Fast Fourier Transform, in the cuFFT library developed by NVIDIA.