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A new quantile‐based mapping method is developed for the bias correction of monthly global circulation model outputs. Compared to the widely used quantile‐based matching method that assumes stationarity and only uses the cumulative distribution functions (CDFs) of the model and observations for the baseline period, the proposed method incorporates and adjusts the model CDF for the projection period on the basis of the difference between the model and observation CDFs for the training (baseline) period. Thus, the method explicitly accounts for distribution changes for a given model between the projection and baseline periods. We demonstrate the use of the new method over northern Eurasia. We fit a four‐parameter beta distribution to monthly temperature fields and discuss the sensitivity of the results to the choice of distribution range parameters. For monthly precipitation data, a mixed gamma distribution is used that accounts for the intermittent nature of rainfall. To test the fidelity of the proposed method, we choose 1970–1999 as the baseline training period and then randomly select 30 years from 1901–1999 as the projection test period. The bootstrapping is repeated 30 times to mimic different climate conditions that may occur, and the results suggest that both methods are comparable when applied to the 20th century for both temperature and precipitation for the examined quartiles. We also discuss the dependence of the bias correction results on the choice of time period for training. This indicates that the remaining biases in the bias‐corrected time series are directly tied to the model's performance during the training period, and therefore care should be taken when using a particular training time period. When applied to the Intergovernmental Panel on Climate Change fourth assessment report (AR4) A2 climate scenario projection, the data time series after bias correction from both methods exhibit similar spatial patterns. However, over regions where the climate model shows large changes in projected variability, there are discernable differences between the methods. The proposed method is more sensitive to a reduction in variability, exemplified by wintertime temperature. Further synthetic experiments using the lower 33% and upper 33% of the full data set as the validation data suggest that the proposed equidistance quantile‐matching method is more efficient in reducing biases than the traditional CDF mapping method for changing climates, especially for the tails of the distribution. This has important consequences for the occurrence and intensity of future projected extreme events such as heat waves, floods, and droughts. As the new method is simple to implement and does not require substantial computational time, it can be used to produce auxiliary ensemble scenarios for various climate impact‐oriented applications.

To enhance the compression resistance of the existing buffer cushions, this paper developed a novel buffer cushion with an inner concave negative Poisson’s ratio (NPR) structure. The structure parameters of buffer cushion were optimized based on orthogonal experimental design and theoretical analysis. Furthermore, the finite element models of the NPR cushion and a comparable hexagonal cushion were established. Then the quasi-static compression and dynamic impact compression simulations and compression experiments using a 3D printed model were conducted to analyze the compression resistance of the NPR cushion. The results showed that the developed NPR cushion exhibited good compressive properties under a uniform load of at most 47 MPa, and its deformation was 73.49% of the deformation of the hexagonal cushion, indicating an improvement in compressive resistance. In the simulation analysis, the stresses of the two buffer cushions in the case of dynamic impact compression were much larger than those in quasi-static compression. The consistency between simulations and experiments results validated the design’s effectiveness in improving compression resistance, offering a valuable reference for the application of NPR structures in cushion design.

Background Recent studies have suggested that triglyceride-glucose (TyG) index is an independent predictor of cardiovascular disease (CVD). However, the impact of long-term visit-to-visit variability in TyG index on the risk of CVD is not known. We aimed to investigate the longitudinal association between baseline and mean TyG index as well as TyG index variability and incident CVD in a Chinese population. Methods We included 49,579 participants without previous history of CVD in the Kailuan study who underwent three health examinations (2006, 2008, and 2010) and were followed up for clinical events until 2019. TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. We measured TyG index variability as the SD of the residuals obtained from a linear regression on the three TyG index measurements for each individual. Multivariate-adjusted Cox models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) with incident CVD. Results During a median follow-up time of 9.0 years, 2404 developed CVD. The highest tertile (T3) of baseline and mean TyG index were each associated with higher CVD incidence as compared with the lowest tertile (T1): aHR, 1.25; 95% CI 1.11–1.42; and aHR 1.40; 95% CI 1.24–1.58, respectively. Tertile 3 of TyG index variability was associated with increased CVD incidence compared to T1 group (aHR, 1.12; 95% CI 1.01–1.24). Similar findings were observed in a series of sensitivity analyses. Conclusion Higher TyG index level and greater TyGindex variability were each independently associated with a higher incidence of CVD.

Retinal fundus photography provides a non-invasive approach for identifying early microcirculatory alterations of chronic diseases prior to the onset of overt clinical complications. Here, we developed neural network models to predict hypertension, hyperglycemia, dyslipidemia, and a range of risk factors from retinal fundus images obtained from a cross-sectional study of chronic diseases in rural areas of Xinxiang County, Henan, in central China. 1222 high-quality retinal images and over 50 measurements of anthropometry and biochemical parameters were generated from 625 subjects. The models in this study achieved an area under the ROC curve (AUC) of 0.880 in predicting hyperglycemia, of 0.766 in predicting hypertension, and of 0.703 in predicting dyslipidemia. In addition, these models can predict with AUC>0.7 several blood test erythrocyte parameters, including hematocrit (HCT), mean corpuscular hemoglobin concentration (MCHC), and a cluster of cardiovascular disease (CVD) risk factors. Taken together, deep learning approaches are feasible for predicting hypertension, dyslipidemia, diabetes, and risks of other chronic diseases.

In transplantation immunology, the ultimate goal is always to successfully and specifically induce immune tolerance of allografts. Tolerogenic dendritic cells （toI-DCs） with immunoregulatory functions have attracted much attention as they play important roles in inducing and maintaining immune tolerance. Here, we focused on tol-DCs that have the potential to promote immune tolerance after solid-organ transplantation. We focus on their development and interactions with other regulatory cells, and we also explore various toI-DC engineering protocols. Harnessing tol-DCs represents a promising cellular therapy for promoting long-term graft functional survival in transplant recipients that will most likely be achieved in the future.

The U–Pb geochronology of 687 detrital zircons from the voluminous Upper Neoproterozoic–Ordovician succession in the Wuyishan Fold Belt of South China reveals a common dominant c. 1200–950 Ma group, indicative of an outboard provenance terrane with a Grenville-age province to the southeast during the late Neoproterozoic–Early Palaeozoic. Compared with coeval samples from the Gondwanan and eastern Laurentian margins, our data show a scarcity of distinctive Gondwanan provenances (c. 650–500 Ma) and reveal some Laurentian signatures. These results argue against the peri-Gondwanan setting for South China during the late Neoproterozoic–Ordovician, instead implying a Laurentian affinity.

The kinetic performance of different zwitterionic hydrophilic interaction liquid chromatography polymer columns is evaluated and compared in-depth. For this purpose, two lab-made monolithic columns, synthesized with different crosslinkers, and a commercial particle packed column are considered. It is found that performance evaluation techniques, such as comparing plate height curves or fitted A-, B- and C-terms, obtained by fitting experimental plate height data to a plate height model, are complicated by the determination of a reliable characteristic length. This is due to the very different morphology of these column types, and the heterogeneity of the monolithic columns. The occurrence of a convective flow through the packed particle column further complicates the interpretation of the obtained fitting parameters, as part of the C-term is wrongfully attributed to the A-term. Therefore, the use of the kinetic plot method is suggested for the comparative evaluation of these columns, as kinetic plots do not require the determination of a characteristic length, nor rely on any fitting parameters. With the kinetic plot method, it is demonstrated that the lab-made monolithic columns outperform the packed particle column for plate counts between 10,000 and 800,000. This is attributed to the higher column efficiency of these columns, due to their small domain and skeleton sizes, and their high permeability, resulting from their high external porosity and the occasional occurrence of preferential flow paths.

Background There may be evidence that COVID-19 affects illness patterns. This study aimed to assess the effects of COVID-19 epidemic on the declines in hepatitis B (HB) case notifications and to estimate the epidemiological trends of HB in Henan. Methods The Bayesian structured time series (BSTS) method was used to investigate the causal effect of COVID-19 on the decline in HB cases based on the monthly incidence of HB from January 2013 to September 2022. To assess how well the BSTS algorithm performs predictions, we split the observations into various training and testing ranges. Results The incidence of HB in Henan was generally declining with periodicity and seasonality. The seasonal index in September and February was the smallest (0.91 and 0.93), and that in March was the largest (1.19). Due to the COVID-19 pandemic, the monthly average number of notifications of HB cases decreased by 38% (95% credible intervals [ CI ]: -44% to -31%) from January to March 2020, by 24% (95% CI : -29% to -17%) from January to June 2020, by 15% (95% CI : -19% to -9.2%) from January to December 2020, by 11% (95% CI : -15% to -6.7%) from January 2020 to June 2021, and by 11% (95% CI : -15% to -7.3%) from January 2020 to December 2021. From January 2020 to September 2022, it decreased by 12% (95% CI : -16% to -8.1%). From 2021 to 2022, the impact of COVID-19 on HB was attenuated. In both training and test sets, the average absolute percentage error (10.03%) generated by the BSTS model was smaller than that generated by the ARIMA model (14.4%). It was also found that the average absolute error, root mean square error, and root mean square percentage error generated by the BSTS model were smaller than ones generated by the ARIMA model. The trend of HB cases in Henan from October 2022 to December 2023 predicted by the BSTS model remained stable, with a total number of 81,650 cases (95% CI : 47,372 to 115,391). Conclusions During the COVID-19 pandemic, the incidence of HB in Henan decreased and exhibited clear seasonal and cyclical trends. The BSTS model outperformed the ARIMA model in predicting the HB incidence trend in Henan. This information may serve as a reference and provide technical assistance for developing strategies and actions to prevent and control HB. Take additional measures to accelerate the progress of eliminating HB.

To investigate the genetic relationship between end stage renal disease (ESRD) and human leukocyte antigen (HLA) alleles in the Guangxi Zhuang population. We performed polymerase chain reaction reversed sequence-specific oligonucleotide (PCR-rSSO) in 325 patients with ESRD and genotyped the HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 loci. The direct counting method was used to determine the frequencies of HLA alleles, and Arlequin software (version 3.5.2.2) was used for haplotypic frequency analyses to compare the included ESRD patients with 350 healthy donors from the Guangxi Zhuang population. In our study, 120 HLA alleles, 284 HLA-A-B-DRB1 haplotypes, and 332 HLA-A-C-B-DRB1-DQB1 haplotypes were detected. We found that only A*11:01-B*15:02-DRB1*12:02 had a positive association with ESRD ( P  = 0.001, P c  = 0.020, OR = 3.106, 95% CI = 1.497–6.446) after Bonferroni correction; thus, individuals with this haplotype may be susceptible to ESRD. A*11:01-B*15:02-DRB1*12:02 is a potentially valuable haplotype for evaluating the risk of ESRD in the Guangxi Zhuang population.

Background Arterial stiffening and hypertension are interrelated, age-associated risk factors for cardiovascular disease (CVD). This study used estimated pulse wave velocity (ePWV), a recognized but non-standardized arterial stiffness measure, to investigate the temporal sequence of arterial stiffening and hypertension, and their mediating pathway and combined effects on CVD. Methods Data were drawn from the 2011–2018 China Health and Retirement Longitudinal Study. CVD was defined as self-reported physician-diagnosed heart disease and/or stroke. Elevated arterial stiffness was identified as ePWV ≥ the wave-specific median value, and hypertension as blood pressure ≥ 140/90 mmHg, current antihypertensive medication use, or a self-reported history. Cross-lagged panel analysis and mediation analysis, and modified Poisson regression were conducted on 6868 and 10,812 participants, respectively. Results The cross-lagged path coefficient from 2011 hypertension to 2015 elevated ePWV (β = 0.19, 95% CI = 0.15–0.22) was significantly greater than that from 2011 elevated ePWV to 2015 hypertension (β = 0.15, 95% CI = 0.11–0.20; P for difference = 0.007). Mediation analysis revealed an indirect association between 2011 hypertension and 2018 CVD through 2015 elevated ePWV (proportion mediated = 26.2%). Compared to normotension and normal ePWV, CVD risk was higher in those with elevated ePWV alone (RR = 1.28, 95% CI = 1.09–1.50), hypertension alone (RR = 1.39, 95% CI = 1.16–1.67), and both conditions (RR = 1.59, 95% CI = 1.39–1.82). Conclusions Hypertension likely precedes elevated ePWV, and this temporal relationship contributes to CVD progression. Individuals with hypertension and elevated ePWV had higher risks than those with either condition alone. Managing both hypertension and arterial stiffening may effectively reduce CVD risk, and ePWV could be a promising marker of arterial stiffness, especially in resource-limited settings. Graphical abstract Hypertension appeared to precede elevated estimated pulse wave velocity (ePWV), and elevated ePWV partially mediated the longitudinal hypertension-CVD association. Individuals with both hypertension and elevated ePWV had the highest CVD risk. CHARLS, China Health and Retirement Longitudinal Study; ePWV, estimated pulse wave velocity; CVD, cardiovascular diseases.