No abstract

No abstract

Background Gut microbiota affects lipid metabolism interactively with diet. Equol, a metabolite of isoflavones produced by gut bacteria, may contribute substantially in beneficial lipid-lowering effects. This study aimed to examine equol production-related gut microbiota differences among humans and its consequent association with blood lipid levels. Results Characterization of the gut microbiota by deep shotgun sequencing and serum lipid profiles were compared between equol producers and non-producers. Gut microbiota differed significantly at the community level between equol producers and non-producers (P = 0.0062). At the individual level, 32 species associated with equol production were identified. Previously reported equol-producing related species Adlercreutzia equolifaciens and Bifidobacterium bifidum showed relatively higher abundance in this study in equol producers compared to non-producers (77.5% vs. 22.5%; 72.0% vs. 28.0%, respectively). Metabolic pathways also showed significant dissimilarity between equol producers and non-producers (P = 0.001), and seven metabolic pathways were identified to be associated with the equol concentration in urine. Previously reported equol production-related gene sequences in A. equolifaciens 19450T showed higher relative abundance in equol producers than in non-producers. Additionally, we found that equol production was significantly associated with the prevalence of dyslipidemia, including a marginal increase in serum lipids (27.1% vs. 50.0%, P = 0.02). Furthermore, equol production was not determined by intake of soy isoflavones, which suggested that gut microbiota is critical in the equol production process. Conclusion Both content and functioning of the microbial gut community significantly differed between equol producers and non-producers. Further, equol producers showed lower prevalences of dyslipidemia, which suggests the important role that equol might play in lipid metabolism by gut microbiota. Electronic supplementary material The online version of this article (10.1186/s13099-019-0297-6) contains supplementary material, which is available to authorized users.

No abstract

Sinogram-affirmed iterative reconstruction can significantly improve image quality of low-dose lung CT screening compared with FBP, and SAFIRE with reconstruction strength 3 was a pertinent choice for low-dose lung CT.

Background The purpose of the present study is to evaluate the prevalence of temporomandibular disorders (TMD) and their associated biological and psychological factors in Chinese university students. Methods A total of 754 students were included from Zunyi Medical University, each participant completed questionnaires and clinical examinations according to the Diagnostic Criteria for Temporomandibular Disorders. Results The overall prevalence of TMD was 31.7% among medical students. Subjects with TMD had a high prevalence of bruxism, empty chewing, unilateral chewing, chewing gum, anterior teeth overbite, anterior teeth overjet, depression, anxiety, and sleep disturbance. Moreover, sleep bruxism, empty chewing, unilateral chewing, anterior teeth overbite, depression, and anxiety were the strongest risk factors for TMD. Conclusions Individuals with TMD have a high prevalence of psychological distress and oral parafunctional habits. Except for the psychological factors associated with TMD, bruxism, abnormal chewing, and malocclusion also shared similar risks for TMD.

No abstract

Code reuse brings vulnerabilities in third-party library to many Internet of Things (IoT) devices, opening them to attacks such as distributed denial of service. Program-wide binary diffing technology can help detect these vulnerabilities in IoT devices whose source codes are not public. Considering the architectures of IoT devices may vary, we propose a data-aware program-wide diffing method across architectures and optimization levels. We rely on the defined anchor functions and call relationship to expand the comparison scope within the target file, reducing the impact of different architectures on the diffing result. To make the diffing result more accurate, we extract the semantic features that can represent the code by data flow dependence analysis. Earth mover distance is used to calculate the similarity of functions in two files based on semantic features. We implemented a proof-of-concept DAPDiff and compared it with baseline BinDiff, TurboDiff and Asm2vec. Experiments showed the availability and effectiveness of our method across optimization levels and architectures. DAPDiff outperformed BinDiff in recall and precision by 41.4% and 9.2% on average when making diffing between standard third-party library and the real-world firmware files. This proves that DAPDiff can be applicable for the vulnerability detection in IoT devices.