BACKGROUND Blood pressure variability(BPV)has been shown to be related to mild cognitive impairment and Alzheimer's disease in a number of studies.However,the relationship between BPV and subtle cognitive decline(...BACKGROUND Blood pressure variability(BPV)has been shown to be related to mild cognitive impairment and Alzheimer's disease in a number of studies.However,the relationship between BPV and subtle cognitive decline(SCD)has received minimal attention in this field of research to date and has rarely been reported.AIM To examine whether SCD is independently associated with changes in BPV in older adults.METHODS Participants were selected based on having participated in cognitive function evaluation and ambulatory blood pressure measurement at the Shanghai Sixth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine between June 2020 and August 2022.The participants included 182 individuals with SCD as the experimental group and 237 with normal cognitive function as the control group.The basic data,laboratory examinations,scale tests,and ambulatory blood pressure test results of the two groups were analyzed retrospectively,and the relationship between SCD and BPV was subsequently evaluated.RESULTS Significant differences were observed between the two groups of participants(P<0.05)in terms of age,education level,prevalence rate of diabetes,fasting blood glucose level,24-h systolic blood pressure standard deviation and coefficient of variation,24-h diastolic blood pressure standard deviation and coefficient of variation.The scale monitoring results showed significant differences in the scores for memory,attention,and visual space between the experimental and control groups.Logistic regression analysis indicated that age,education level,blood sugar level,and BPV were factors influencing cognitive decline.Linear regression analysis showed that there was an independent correlation between blood pressure variation and SCD,even after adjusting for related factors.Each of the above differences was still significant.CONCLUSION This study suggests that increased BPV is associated with SCD.展开更多
Key-value （KV） stores have become a backbone of large-scale applications in today＇s data centers. Write- optimized data structures like the Log-Structured Merge-tree （LSM-tree） and their variants are widely used ...Key-value （KV） stores have become a backbone of large-scale applications in today＇s data centers. Write- optimized data structures like the Log-Structured Merge-tree （LSM-tree） and their variants are widely used in KV storage systems like BigTable and RocksDB. Conventional LSM-tree organizes KV items into multiple, successively larger components, and uses compaction to push KV items from one smaller component to another adjacent larger component until the KV items reach the largest component. Unfortunately, current compaction scheme incurs significant write amplification due to repeated KV item reads and writes, and then results in poor throughput. We propose a new compaction scheme, delayed compaction （dCompaction） that decreases write amplification, dCompaction postpones some compactions and gathers them into the following compaction. In this way, it avoids KV item reads and writes during compaction, and consequently improves the throughput of LSM-tree based KV stores. We implement dCompaction on RocksDB, and conduct extensive experiments. Validation using YCSB framework shows that compared with RocksDB, dCompaction has about 40% write performance improvements and also comparable read performance.展开更多
基金Shanghai Municipal Commission of Science and Technology Program,No.19411960900.
文摘BACKGROUND Blood pressure variability(BPV)has been shown to be related to mild cognitive impairment and Alzheimer's disease in a number of studies.However,the relationship between BPV and subtle cognitive decline(SCD)has received minimal attention in this field of research to date and has rarely been reported.AIM To examine whether SCD is independently associated with changes in BPV in older adults.METHODS Participants were selected based on having participated in cognitive function evaluation and ambulatory blood pressure measurement at the Shanghai Sixth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine between June 2020 and August 2022.The participants included 182 individuals with SCD as the experimental group and 237 with normal cognitive function as the control group.The basic data,laboratory examinations,scale tests,and ambulatory blood pressure test results of the two groups were analyzed retrospectively,and the relationship between SCD and BPV was subsequently evaluated.RESULTS Significant differences were observed between the two groups of participants(P<0.05)in terms of age,education level,prevalence rate of diabetes,fasting blood glucose level,24-h systolic blood pressure standard deviation and coefficient of variation,24-h diastolic blood pressure standard deviation and coefficient of variation.The scale monitoring results showed significant differences in the scores for memory,attention,and visual space between the experimental and control groups.Logistic regression analysis indicated that age,education level,blood sugar level,and BPV were factors influencing cognitive decline.Linear regression analysis showed that there was an independent correlation between blood pressure variation and SCD,even after adjusting for related factors.Each of the above differences was still significant.CONCLUSION This study suggests that increased BPV is associated with SCD.
基金This work is supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000202 and the National Natural Science Foundation of China under Grant Nos. 61303056 and 61379042.
文摘Key-value （KV） stores have become a backbone of large-scale applications in today＇s data centers. Write- optimized data structures like the Log-Structured Merge-tree （LSM-tree） and their variants are widely used in KV storage systems like BigTable and RocksDB. Conventional LSM-tree organizes KV items into multiple, successively larger components, and uses compaction to push KV items from one smaller component to another adjacent larger component until the KV items reach the largest component. Unfortunately, current compaction scheme incurs significant write amplification due to repeated KV item reads and writes, and then results in poor throughput. We propose a new compaction scheme, delayed compaction （dCompaction） that decreases write amplification, dCompaction postpones some compactions and gathers them into the following compaction. In this way, it avoids KV item reads and writes during compaction, and consequently improves the throughput of LSM-tree based KV stores. We implement dCompaction on RocksDB, and conduct extensive experiments. Validation using YCSB framework shows that compared with RocksDB, dCompaction has about 40% write performance improvements and also comparable read performance.
