Surface defect and lattice engineering of Bi_(5)O_(7)Br ultrathin nanosheets for efficient photocatalysis

The effective separation and migration of photogenerated charge carriers in bulk and on the surface of photocatalysts will significantly promote photocatalytic efficiency.However,the synchronous regulation of photocharges on both counts is challenging.Herein,the simultaneous separation of bulk and surface photocharges is conducted to enhance photocatalytic activity by coupling the surface defects and lattice engineering of bismuth oxybromide.The depth-modulated Bi_(5)O_(7)Br ultrathin nanosheets with an abundance of bismuth in the crystal structure increased the internal electric field,which propelled the separation and migration of photocharges from bulk to the surface.Creation of oxygen vacancies(OVs)on the nanosheet surface forms local electric fields,which can stimulate the migration of charges to active sites on the catalyst surface.Therefore,the OV-assembled Bi_(5)O_(7)Br nanosheets demonstrated enhanced photocatalytic degradation efficiency under simulated solar-light illumination.This study proved the possibility of charge governing via electric field modulation based on an integrated strategy.

Presence of Rare Variants is Associated with Poorer Survival in Chinese Patients with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis(ALS)is a fatal neurodegenerative disorder with phenotypic and genetic heterogeneity.Recent studies have suggested an oligogenic basis of ALS,in which the co-occurrence of two or more genetic variants has additive or synergistic deleterious effects.To assess the contribution of possible oligogenic inheritance,we profiled a panel of 43 relevant genes in 57 sporadic ALS(sALS)patients and eight familial ALS(fALS)patients from five pedigrees in east China.We filtered rare variants using the combination of the Exome Aggregation Consortium,the 1000 Genomes and the HuaBiao Project.We analyzed patients with multiple rare variants in 43 known ALS causative genes and the genotype–phenotype cor-relation.Overall,we detected 30 rare variants in 16 different genes and found that 16 of the sALS patients and all the fALS patients examined harbored at least one variant in the investigated genes,among which two sALS and four fALS patients harbored two or more variants.Of note,the sALS patients with one or more variants in ALS genes had worse survival than the patients with no variants.Typically,in one fALS pedigree with three variants,the family member with three variants(Superoxide dismutase 1(SOD1)p.V48A,Optineurin(OPTN)p.A433V and TANK binding kinase 1(TBK1)p.R573H)exhibited much more severe disease phenotype than the member carrying one variant(TBK1 p.R573H).Our findings suggest that rare variants could exert a negative prognostic effect,thereby supporting the oligogenic inheritance of ALS.

Using Composite Phenotypes to Reveal Hidden Physiological Heterogeneity in High-Altitude Acclimatization in a Chinese Han Longitudinal Cohort

Altitude acclimatization is a human physiological process of adjusting to the decreased oxygen availability.Since several physiological processes are involved and their correlations are complicated,the analyses of single traits are insufficient in revealing the complex mechanism of high-altitude acclimatization.In this study,we examined these physiological responses as the composite phenotypes that are represented by a linear combination of physiological traits.We developed a strategy that combines both spectral clustering and partial least squares path modeling(PLSPM)to define composite phenotypes based on a cohort study of 883 Chinese Han males.In addition,we captured 14 composite phenotypes from 28 physiological traits of high-altitude acclimatization.Using these composite phenotypes,we applied k-means clustering to reveal hidden population physiological heterogeneity in high-altitude acclimatization.Furthermore,we employed multivariate linear regression to systematically model(Models 1 and 2)oxygen saturation(SpO_(2))changes in high-altitude acclimatization and evaluated model fitness performance.Composite phenotypes based on Model 2 fit better than single trait-based Model 1 in all measurement indices.This new strategy of using composite phenotypes may be potentially employed as a general strategy for complex traits research such as genetic loci discovery and analyses of phenomics.