The impact of statin use before intensive care unit admission on patients with acute kidney injury after cardiac surgery

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common and serious complication after cardiac surgery. The influence of statin use before surgery on the renal outcome of patients undergoing cardiac surgery is controversial. The purpose of this study was to evaluate the effect of statins on postoperative renal outcomes in patients undergoing cardiac surgery.Methods: We included CSA-AKI patients in the Medical Information Mart for Intensive Care (MIMIC)—IV database and were divided into statin group and non-statin group according to whether they used statins before entering intensive care units (ICU). The main outcomes were hospitalization and 30-day mortality, and the secondary outcomes were 60-day mortality and 90-day mortality. We used propensity score matching (PSM) to adjust for confounding factors. The 95% confidence interval (CI) and risk ratio (RO) were calculated by the COX proportional regression model. At the same time, stratified analysis was used to explore whether the relationship between the statins use before intensive care units and mortality was different in each subgroup and whether the relationship between different doses of Atorvastatin and mortality was different.Result: We identified 675 pre-ICU statin users and 2095 non-statin users. In the COX proportional regression model, pre-ICU statin use was associated with decreased in-hospital (HR = 0.407, 95%confidence interval 0.278–0.595, p < 0.001) and 30-day mortality (HR = 0.407, 95%CI 0.279–0.595, p < 0.001). The survival rate of patients who took statins before entering ICU was significantly higher than that of those who did not use statins at 30 days, 60 days and 90 days. There is a significant interaction between patients with aged>65 years (HR = 0.373, 95%CI 0.240–0.581, p < 0.001), Acute kidney injury grade I (HR = 0.244, 95%CI 0.118–0.428, p < 0.001), and without post-myocardial infarction syndrome (HR = 0.344, 95%CI 0.218–0.542, p < 0.001). The mortality in hospital and 60 days of CSA-AKI patients treated with ≥80 mg Atorvastatin before operation was significantly reduced (p < 0.05).Conclusion: The pre-ICU statin use was significantly associated with decreased risk in hospital and 30-day mortality. The preoperative use of ≥80 mg Atorvastatin may improve the prognosis of CSA-AKI

Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001

Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.Peer reviewe

A Single-Component Blue Light-Induced System Based on EL222 in Yarrowia lipolytica

Optogenetics has the advantages of a fast response time, reversibility, and high spatial and temporal resolution, which make it desirable in the metabolic engineering of chassis cells. In this study, a light-induced expression system of Yarrowia lipolytica was constructed, which successfully achieved the synthesis and functional verification of Bleomycin resistance protein (BleoR). The core of the blue light-induced system, the light-responsive element (TF), is constructed based on the blue photosensitive protein EL222 and the transcription activator VP16. The results show that the light-induced sensor based on TF, upstream activation sequence (C120)5, and minimal promoter CYC102 can respond to blue light and initiate the expression of GFPMut3 report gene. With four copies of the responsive promoter and reporter gene assembled, they can produce a 128.5-fold higher fluorescent signal than that under dark conditions after 8 h of induction. The effects of light dose and periodicity on this system were investigated, which proved that the system has good spatial and temporal controllability. On this basis, the light-controlled system was used for the synthesis of BleoR to realize the expression and verification of functional protein. These results demonstrated that this system has the potential for the transcriptional regulation of target genes, construction of large-scale synthetic networks, and overproduction of the desired product

Research on Aerodynamic Design of an End Wall Based on a Quasi-3D Optimization Method

To investigate the effects of different passage structures on the aerodynamic performance of the transonic fans, this paper develops a reliable and practical quasi-3D optimization method for the hub based on the experimental data of Stage 67. In the method, the hub profile of Stage 67 can be optimized without changing the geometrical data of the blades. The optimization results show that stream tube diffusion characteristics depend on the hub profile’s curvature in the boundary layer near the hub. In the front part of the hub, the end wall with a concave construction can enhance the expansion of the stream tubes near the root of the rotor blade, which helps control the diffusion flow of viscous fluid effectively to decrease the low-energy fluid’s energy degradation and radial secondary flow in the boundary layer. In the latter part of the hub, the end wall with a convex construction facilitates the shrinkage of stream tubes to decrease the secondary flow loss and separated flow loss by controlling the separation of the boundary layer efficiently. This construction of the hub profile is beneficial to promote the aerodynamic performance of a transonic fan

Use of gated myocardial perfusion imaging to assess clinical value of Xinmailong injection in chronic congestive heart failure

AbstractObjectiveThis study used gated myocardial perfusion imaging (G-MPI) to assess the clinical value of Xinmailong injection in chronic congestive heart failure (CHF).MethodsA total of 102 CHF patients were randomly divided into the control group (n=51) and the Xinmailong group (n=51). Patients in the control group were routinely treated. Patients in the Xinmailong group were additionally treated with Xinmailong injection in addition to routine treatment. Before and 3 months after treatment, G-MPI was used to determine changes in the left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV) and left ventricular end-systolic volume (LVESV). Fourteen days after treatment, changes in plasma brain natriuretic peptide (BNP) levels were determined.ResultsBefore treatment, there were no significant differences in LVEF, LVEDV, LVESV, and BNP levels between the two groups (all P>0.05). After treatment, LVEDV, LVESV, and BNP levels were significantly lower, and LVEF was significantly higher in the Xinmailong group than in the control group (all P<0.05).ConclusionAdditional use of Xinmailong injection in addition to routine treatment improves cardiac function of CHF patients. Because of the safety and effectiveness of Xinmailong injection, this therapy should be promoted

Weak Fault Feature Extraction Method Based on Improved Stochastic Resonance

Aiming at the problems of early weak fault feature extraction of bearings in rotating machinery, an improved stochastic resonance (SR) is proposed combined with the advantage of SR to enhance weak characteristic signals with noise energy. Firstly, according to the characteristics of the large parameters of the actual fault signal, the amplitude transform coefficient and frequency transform coefficient are introduced to convert the large parameter signal into small parameter signal which can be processed by SR, and the relationship of second-order parameters are introduced. Secondly, a comprehensive evaluation index (CEI) consisted of power spectrum kurtosis, correlation coefficient, structural similarity, root mean square error, and approximate entropy, is constructed through BP neural network. Moreover, this CEI is adopted as fitness function to search the optimal damping coefficient and amplitude transform coefficient with adaptive weight particle swarm optimization (PSO). Finally, according to the improved optimal SR system, the weak fault feature can be extracted. The simulation and experiment verify the effectiveness of the proposed method compared with traditional second-order general scale transform adaptive SR

A Fast Sparse Decomposition Based on the Teager Energy Operator in Extraction of Weak Fault Signals

In order to diagnose an incipient fault in rotating machinery under complicated conditions, a fast sparse decomposition based on the Teager energy operator (TEO) is proposed in this paper. In this proposed method, firstly, the TEO is employed to enhance the envelope of the impulses, which is more sensitive to frequency and can eliminate the low-frequency harmonic component and noise; secondly, a smoothing filtering algorithm was adopted to suppress the noise in the TEO envelope; thirdly, the fault signal was reconstructed by multiplication of the filtered TEO envelope and the original fault signal; finally, sparse decomposition was used based on a generalized S-transform (GST) to obtain the sparse representation of the signal. The proposed preprocessing method using the filtered TEO can overcome the interference of high-frequency noise while maintaining the structure of fault impulses, which helps the processed signal perform better on sparse decomposition; sparse decomposition based on GST was used to represent the fault signal more quickly and more accurately. Simulation and application prove that the proposed method has good accuracy and efficiency, especially in conditions of very low SNR, such as impulses with anSNR of −8.75 dB that are submerged by noise of the same amplitude

Evolution and expression analysis reveal the potential role of the HD-Zip gene family in regulation of embryo abortion in grapes (Vitis vinifera L.)

Abstract Background The HD-Zip family has a diversity of functions during plant development. In this study, we identify 33 HD-Zip transcription factors in grape and detect their expressions in ovules and somatic embryos, as well as in various vegetative organs. Results A genome-wide survey for HD-Zip transcription factors in Vitis was conducted based on the 12 X grape genome (V. vinifera L.). A total of 33 members were identified and classified into four subfamilies (I-IV) based on phylogeny analysis with Arabidopsis, rice and maize. VvHDZs in the same subfamily have similar protein motifs and intron/exon structures. An evaluation of duplication events suggests several HD-Zip genes arose before the divergence of the grape and Arabidopsis lineages. The 33 members of HD-Zip were differentially expressed in ovules of the stenospermic grape, Thompson Seedless and of the seeded grape, Pinot noir. Most have higher expressions during ovule abortion in Thompson Seedless. In addition, transcripts of the HD-Zip family were also detected in somatic embryogenesis of Thompson Seedless and in different vegetative organs of Thompson Seedless at varying levels. Additionally, VvHDZ28 is located in the nucleus and had transcriptional activity consistent with the typical features of the HD-Zip family. Our results provide a foundation for future grape HD-Zip gene function research. Conclusions The identification and expression profiles of the HD-Zip transcription factors in grape, reveal their diverse roles during ovule abortion and organ development. Our results lay a foundation for functional analysis of grape HDZ genes