Waist-to-calf circumstance ratio and cognitive function among Chinese older adults: Mediating roles of physical performance and social activity

BackgroundIn light of the potentially detrimental effects of central fat and decreased muscle mass on cognitive function, it would be beneficial to learn more about the mediating mechanisms underpinning the association between the two. The purpose of this study is to determine the association between waist-to-calf circumstance ratio (WCR) and cognitive function, as well as to investigate whether physical performance and social activity mediate the relationship between WCR and cognitive function among older Chinese adults.MethodsAn analysis of 9,652 older Chinese adults was conducted during the 2018 wave of the Chinese Longitudinal Health Longevity Survey (CLHLS). The Mini-Mental State Examination (MMSE) and a self-reported scale were used to measure cognitive function, physical performance, and social activity, respectively. Multiple linear regression and mediation analyses were conducted.ResultsThe findings suggest that a high WCR had a significant negative association with cognitive function (B = −0.535, 95% CI: −0.754, −0.317). Mediation analysis revealed that a high WCR influenced old adults' cognitive function in three ways: first, through the partial mediating effect of physical performance (B = −0.270; 95% CI: −0.340, −0.203); second, through the partial mediating effect of social activity (B = −0.035; 95% CI: −0.055, −0.017); and third, through the serial mediating effects of physical performance and social activity (B = −0.021, 95% CI: −0.029, −0.015).ConclusionThe study results suggest the adverse impact of a high WCR on older adults' cognitive function, and the possible mechanisms of physical performance and social activity by which the association takes place. Multidimensional health and social interventions aimed at improving physical, social, and cognitive functioning among older adults with sarcopenic obesity are recommended

The experience of long-stay patients in a forensic psychiatric hospital in China: a qualitative study

open access articleBackground Long stay in forensic psychiatric hospitals is common in patients who are defined as “not criminally responsible on account of mental disorder”. However, little is known about how these patients experience and perceive the long stay within these settings. The aim of this study is to explore the perception and needs of long-stay patients in forensic psychiatric hospitals in China. Methods In-depth semi-structured interviews were conducted with 21 participants who had lived in the forensic psychiatry hospital for more than 8 years. We used thematic analysis strategies to analyse the qualitative data. Results Participants’ perceptions clustered seven themes: hopelessness, loneliness, worthlessness, low mood, sleep disturbances, lack of freedom, and lack of mental health intervention. Conclusions The views and opinions expressed by long-stay patients showed that psychological distress is prevailing in forensic psychiatric hospitals. Adequate and effective care and mental health interventions are recommended to be tailored for their special needs

MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions

Deep neural networks are widely used in personalized recommendation systems. Unlike regular DNN inference workloads, recommendation inference is memory-bound due to the many random memory accesses needed to lookup the embedding tables. The inference is also heavily constrained in terms of latency because producing a recommendation for a user must be done in about tens of milliseconds. In this paper, we propose MicroRec, a high-performance inference engine for recommendation systems. MicroRec accelerates recommendation inference by (1) redesigning the data structures involved in the embeddings to reduce the number of lookups needed and (2) taking advantage of the availability of High-Bandwidth Memory (HBM) in FPGA accelerators to tackle the latency by enabling parallel lookups. We have implemented the resulting design on an FPGA board including the embedding lookup step as well as the complete inference process. Compared to the optimized CPU baseline (16 vCPU, AVX2-enabled), MicroRec achieves 13.8~14.7x speedup on embedding lookup alone and 2.5$~5.4x speedup for the entire recommendation inference in terms of throughput. As for latency, CPU-based engines needs milliseconds for inferring a recommendation while MicroRec only takes microseconds, a significant advantage in real-time recommendation systems.Comment: Accepted by MLSys'21 (the 4th Conference on Machine Learning and Systems

A Recalibrated Molecular Clock and Independent Origins for the Cholera Pandemic Clones

Cholera, caused by Vibrio cholerae, erupted globally from South Asia in 7 pandemics, but there were also local outbreaks between the 6th (1899–1923) and 7th (1961–present) pandemics. All the above are serotype O1, whereas environmental or invertebrate isolates are antigenically diverse. The pre 7th pandemic isolates mentioned above, and other minor pathogenic clones, are related to the 7th pandemic clone, while the 6th pandemic clone is in the same lineage but more distantly related, and non-pathogenic isolates show no clonal structure. To understand the origins and relationships of the pandemic clones, we sequenced the genomes of a 1937 prepandemic strain and a 6th pandemic isolate, and compared them with the published 7th pandemic genome. We distinguished mutational and recombinational events, and allocated these and other events, to specific branches in the evolutionary tree. There were more mutational than recombinational events, but more genes, and 44 times more base pairs, changed by recombination. We used the mutational single-nucleotide polymorphisms and known isolation dates of the prepandemic and 7th pandemic isolates to estimate the mutation rate, and found it to be 100 fold higher than usually assumed. We then used this to estimate the divergence date of the 6th and 7th pandemic clones to be about 1880. While there is a large margin of error, this is far more realistic than the 10,000–50,000 years ago estimated using the usual assumptions. We conclude that the 2 pandemic clones gained pandemic potential independently, and overall there were 29 insertions or deletions of one or more genes. There were also substantial changes in the major integron, attributed to gain of individual cassettes including copying from within, or loss of blocks of cassettes. The approaches used open up new avenues for analysing the origin and history of other important pathogens

The LDBC Financial Benchmark

The Linked Data Benchmark Council's Financial Benchmark (LDBC FinBench) is a new effort that defines a graph database benchmark targeting financial scenarios such as anti-fraud and risk control. The benchmark has one workload, the Transaction Workload, currently. It captures OLTP scenario with complex, simple read queries and write queries that continuously insert or delete data in the graph. Compared to the LDBC SNB, the LDBC FinBench differs in application scenarios, data patterns, and query patterns. This document contains a detailed explanation of the data used in the LDBC FinBench, the definition of transaction workload, a detailed description for all queries, and instructions on how to use the benchmark suite.Comment: For the source code of this specification, see the ldbc_finbench_docs repository on Githu

Room-Temperature Pressure Synthesis of Layered Black Phosphorus–Graphene Composite for Sodium-Ion Battery Anodes

Sodium-ion batteries offer an attractive option for grid-level energy storage due to the high natural abundance of sodium and low material cost of sodium compounds. Phosphorus (P) is a promising anode material for sodium-ion batteries, with a theoretical capacity of 2596 mAh/g. The red phosphorus (RP) form has worse electronic conductivity and lower initial Coulombic efficiency than black phosphorus (BP), but high material cost and limited production capacity have slowed the development of BP anodes. To address these challenges, we have developed a simple and scalable method to synthesize layered BP/graphene composite (BP/rGO) by pressurization at room temperature. A carbon-black-free and binder-free BP/rGO anode prepared with this method achieved specific charge capacities of 1460.1, 1401.2, 1377.6, 1339.7, 1277.8, 1123.78, and 720.8 mAh/g in a rate capability test at charge and discharge current densities of 0.1, 0.5, 1, 5, 10, 20, and 40 A/g, respectively. In a cycling performance test, after 500 deep cycles, the capacity of BP/rGO anodes stabilized at 1250 and 640 mAh/g at 1 and 40 A/g, respectively, which marks a significant performance improvement for sodium-ion battery anodes

In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine

Backgrounds and AimsRecently, a growing number of hepatotoxicity cases aroused by Traditional Chinese Medicine (TCM) have been reported, causing increasing concern. To date, the reported predictive models for drug induced liver injury show low prediction accuracy and there are still no related reports for hepatotoxicity evaluation of TCM systematically. Additionally, the mechanism of herb induced liver injury (HILI) still remains unknown. The aim of the study was to identify potential hepatotoxic ingredients in TCM and explore the molecular mechanism of TCM against HILI.Materials and MethodsIn this study, we developed consensus models for HILI prediction by integrating the best single classifiers. The consensus model with best performance was applied to identify the potential hepatotoxic ingredients from the Traditional Chinese Medicine Systems Pharmacology database (TCMSP). Systems pharmacology analyses, including multiple network construction and KEGG pathway enrichment, were performed to further explore the hepatotoxicity mechanism of TCM.Results16 single classifiers were built by combining four machine learning methods with four different sets of fingerprints. After systematic evaluation, the best four single classifiers were selected, which achieved a Matthews correlation coefficient (MCC) value of 0.702, 0.691, 0.659, and 0.717, respectively. To improve the predictive capacity of single models, consensus prediction method was used to integrate the best four single classifiers. Results showed that the consensus model C-3 (MCC = 0.78) outperformed the four single classifiers and other consensus models. Subsequently, 5,666 potential hepatotoxic compounds were identified by C-3 model. We integrated the top 10 hepatotoxic herbs and discussed the hepatotoxicity mechanism of TCM via systems pharmacology approach. Finally, Chaihu was selected as the case study for exploring the molecular mechanism of hepatotoxicity.ConclusionOverall, this study provides a high accurate approach to predict HILI and an in silico perspective into understanding the hepatotoxicity mechanism of TCM, which might facilitate the discovery and development of new drugs

My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype

Massive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces (“edgetic”) and 311,022 functional sites (“nodetic”), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org

Influence of academic stress and school bullying on self-harm behaviors among Chinese middle school students: The mediation effect of depression and anxiety

ObjectiveThe purpose of this study was to explore the relationship between academic stress, school bullying and self-harm behaviors among Chinese middle school students and to further explore the impact of anxiety and depression on this relationship.MethodsThe students (aged 12–16 years) in a middle school in Changsha city were invited to respond to a questionnaire through an online platform. The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to assess the severity of anxiety and depressive symptoms, respectively. The experience of being bullied, academic stress, and self-harm behaviors were assessed using several questions on the basis of previous studies.ResultsA total of 1,313 middle school students completed the study, and 3.40% and 4.10% of them reported suicide attempts (SAs) and non-suicidal self-injury (NSSI), respectively. Univariate logistic regression analysis revealed that anxiety symptoms (OR = 1.23, 95% CI: 1.18–1.28; OR = 1.25, 95% CI: 1.19–1.31), depressive symptoms (OR = 1.20, 95% CI: 1.16–1.25; OR = 1.26, 95% CI: 1.20–1.31), school bullying (OR = 3.8, 95% CI: 2.11–6.89; OR = 2.76, 95% CI: 1.39–5.47), and academic stress (OR = 2.20, 95% CI: 1.27–3.80; OR = 3.80, 95% CI: 1.20–7.25) were common factors of NSSI and SAs. In addition, depressive symptoms showed a mediating effect on the association of school bullying and academic stress with SAs or NSSI, and anxiety symptoms showed a mediating effect on the association of school bullying and academic stress with NSSI only.ConclusionAppropriate strategies are needed to reduce academic pressure and prevent school bullying. Meanwhile, negative emotions such as depression and anxiety should be evaluated and intervened in to prevent self-harm behaviors among middle school students