An effective method for the direct crystallization of xylonic acid from fermentation broth of agricultural residue hydrolysate

Xylose is the second most abundant sugar in nature and conversion of xylose to xylonic acid (XA) has become a research hotspot in recent years. Xylonic acid can be applied in the equivalent market niche of gluconic acid, due to their similar physical properties. XA bioproduction and application presents certainly a promising approach for xylose valorization in lignocellulose biorefinery, while the XA crystallization is so far still an unattainable goal. In this paper, an original method was proposed and experimentally investigated for the first time to get XA crystals from fermentation broth. In the XA crystallization, methanol was introduced as buffer-cum-solvent. The H2SO4 was dropwise added into the methanol solution dissolving potassium xylonate that is beforehand produced by fermentation. During H2SO4 blending with methanol, the strong and polar H2SO4 leads to XA diffusion and aggregation. Overall, 2.21 g of xylonic acid crystals was obtained per gram of 98% H2SO4 acidification. NMR detection showed that over 99% purity of XA crystals was finally obtained at the yields of 67.2% from xylonate. The integrated process could provide a practicable and effective technology for the high-qualify XA preparation from xylose derivations and lignocellulose biomass biorefinery

“Island-bridge”-structured nanofluidic membranes for high-performance aqueous energy conversion and storage

The attainment of carbon neutrality requires the development of aqueous energy conversion and storage devices. However, these devices exhibit limited performance due to the permeability–selectivity trade-off of permselective membranes as core components. Herein, we report the application of a synergistic approach utilizing two-dimensional nanoribbons-entangled nanosheets to rationally balance the permeability and selectivity in permselective membranes. The nanoribbons and nanosheets can be self-assembled into a nanofluidic membrane with a distinctive “island-bridge” configuration, where the nanosheets serve as isolated islands offering adequate ionic selectivity owing to their high surface charge density, meanwhile bridge-like nanoribbons with low surface charge density but high aspect ratio remarkably enhance the membrane’s permeability and water stability, as verified by molecular simulations and experimental investigations. Using this approach, we developed a high-performance graphene oxide (GO) nanosheet/GO nanoribbon (GONR) nanofluidic membrane and achieved an ultrahigh power density of 18.1 W m–2 in a natural seawater|river water osmotic power generator, along with a high Coulombic efficiency and an extended lifespan in zinc metal batteries. The validity of our island-bridge structural design is also demonstrated for other nanosheet/nanoribbon composite membranes, providing a promising path for developing reliable aqueous energy conversion and storage devices

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

Background: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. Methods: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training (n = 28,490) and testing sets (n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21–I23 and fatal I20–I25) and soft CAD (all fatal or nonfatal I20–I25) were analyzed separately. Results: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19–1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (–0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4–6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. Conclusions: In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little to no improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction