Immune-based mutation classification enables neoantigen prioritization and immune feature discovery in cancer immunotherapy.

Genetic mutations lead to the production of mutated proteins from which peptides are presented to T cells as cancer neoantigens. Evidence suggests that T cells that target neoantigens are the main mediators of effective cancer immunotherapies. Although algorithms have been used to predict neoantigens, only a minority are immunogenic. The factors that influence neoantigen immunogenicity are not completely understood. Here, we classified human neoantigen/neopeptide data into three categories based on their TCR-pMHC binding events. We observed a conservative mutant orientation of the anchor residue from immunogenic neoantigens which we termed the NP rule. By integrating this rule with an existing prediction algorithm, we found improved performance in neoantigen prioritization. To better understand this rule, we solved several neoantigen/MHC structures. These structures showed that neoantigens that follow this rule not only increase peptide-MHC binding affinity but also create new TCR-binding features. These molecular insights highlight the value of immune-based classification in neoantigen studies and may enable the design of more effective cancer immunotherapies

Principles and methods of scaling geospatial Earth science data

The properties of geographical phenomena vary with changes in the scale of measurement. The information observed at one scale often cannot be directly used as information at another scale. Scaling addresses these changes in properties in relation to the scale of measurement, and plays an important role in Earth sciences by providing information at the scale of interest, which may be required for a range of applications, and may be useful for inferring geographical patterns and processes. This paper presents a review of geospatial scaling methods for Earth science data. Based on spatial properties, we propose a methodological framework for scaling addressing upscaling, downscaling and side-scaling. This framework combines scale-independent and scale-dependent properties of geographical variables. It allows treatment of the varying spatial heterogeneity of geographical phenomena, combines spatial autocorrelation and heterogeneity, addresses scale-independent and scale-dependent factors, explores changes in information, incorporates geospatial Earth surface processes and uncertainties, and identifies the optimal scale(s) of models. This study shows that the classification of scaling methods according to various heterogeneities has great potential utility as an underpinning conceptual basis for advances in many Earth science research domains. © 2019 Elsevier B.V

Association of sleep duration and sleep quality with the risk of metabolic syndrome in adults: a systematic review and meta-analysis

Introduction: The association between sleep duration and metabolic syndrome (MetS) remains controversial, and few have considered the effects of sleep quality. We performed a meta-analysis to clarify the relationship of sleep duration and sleep quality with the risk of MetS. Material and methods: We conducted a systematic and comprehensive literature search of electronic databases from inception to 17 February 2022. The effect sizes of covariates from each study were pooled using a random or fixed model, and a restricted cubic spline random-effects meta-analysis was performed to examine the dose-response relationship between sleep duration and MetS. Results: A total of 62 studies were included in this meta-analysis. Compared to normal sleep duration, short sleep duration [odds ratio (OR) = 1.14, 95% confidence interval (CI): 1.10–1.19] and long sleep duration (OR = 1.15, 95% CI: 1.09–1.23) were associated with an increased risk of MetS. The restricted cubic spline analysis indicated that sleep durations of 8.5 h (OR = 0.95, 95% CI: 0.92–0.97) and 11 h (OR = 1.58, 95% CI: 1.31–1.91) were significantly associated with the risk of MetS. The pooled results showed that poor sleep quality (OR = 1.46, 95% CI: 1.03–2.06) and sleep complaints had significant positive associations with MetS. Conclusion: Our results demonstrated that short sleep duration increased the risk of developing MetS. Long sleep duration was also associated with MetS, especially for 11 h. 8.5 h can be considered the recommended sleep duration for MetS. Poor sleep quality and sleep complaints were also associated with MetS

A Combined Experimental and Theoretical Study on the Extraction of Uranium by Amino-Derived Metal–Organic Frameworks through Post-Synthetic Strategy

A novel carboxyl-functionalized metal–organic framework for highly efficient uranium sorption was prepared through a generic postsynthetic strategy, and this MOF’s saturation sorption capacity is found to be as high as 314 mg·g^–1. The preliminary application illustrated that the grafted free-standing carboxyl groups have notably enhanced the sorption of uranyl ions on MIL-101. In addition, we have performed molecular dynamics simulation combined with density functional theory calculations to investigate the molecular insights of uranyl ions binding on MOFs. The high selectivity and easy separation of the as-prepared material have shown tremendous potential for practical applications in the nuclear industry or radioactive water treatment, and the functionalized MOF can be extended readily upon the versatility of click chemistry. This work provides a facile and purposeful approach for developing MOFs toward a highly efficient and selective extraction of uranium­(VI) in aqueous solution, and it further facilitates the structure-based design of nanomaterials for radionuclide-containing-medium pretreatment