Miracle-dz/UniFAR-FTUs huggingface dataset:
PC-1 NF suppresses high glucose-stimulated inflammation and extracellular matrix accumulation in glomerular mesangial cells via the Wnt/β-catenin signaling

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease worldwide with high morbidity and mortality. Glomerular mesangial cell (MC) proliferation, inflammatory cell infiltration and extracellular matrix (ECM) accumulation are the main pathological characteristics of DN. A previous study revealed that polycystin-1 N-terminal fragment (PC-1 NF) fusion protein could inhibit ECM accumulation in a mesangial proliferative glomerulonephritis model. However, the role of PC-1 NF fusion protein in DN remains unknown. The results of the present study indicated that PC-1 NF fusion protein significantly abolished high glucose (HG)-induced glomerular MC viability over three time points measured (24, 48 and 72 h). In addition, PC-1 NF suppressed the levels of monocyte chemotactic peptide-1 and tumor necrosis factor α, as well as the expression of fibronectin and collagen IV, in HG-stimulated MCs. Furthermore, PC-1 NF fusion protein efficiently inhibited the activation of Wnt/β-catenin signaling pathway in HG-stimulated MCs. Taken together, these data indicated that PC-1 NF fusion protein inhibited HG-induced MC proliferation, inflammation, and ECM expression via the modulation of the Wnt signaling pathway. The present study indicated that PC-1 NF fusion protein may be a potential agent in treating DN.
Discrepancies in vegetation phenology trends and shift patterns in different climatic zones in middle and eastern Eurasia between 1982 and 2015

Abstract Changes in vegetation phenology directly reflect the response of vegetation growth to climate change. In this study, using the Normalized Difference Vegetation Index dataset from 1982 to 2015, we extracted start date of vegetation growing season (SOS), end date of vegetation growing season (EOS), and length of vegetation growing season (LOS) in the middle and eastern Eurasia region and evaluated linear trends in SOS, EOS, and LOS for the entire study area, as well as for four climatic zones. The results show that the LOS has significantly increased by 0.27 days/year, mostly due to a significantly advanced SOS (−0.20 days/year) and a slightly delayed EOS (0.07 days/year) over the entire study area from 1982 to 2015. The vegetation phenology trends in the four climatic zones are not continuous throughout the 34‐year period. Furthermore, discrepancies in the shifting patterns of vegetation phenology trend existed among different climatic zones. Turning points (TP) of SOS trends in the Cold zone, Temperate zone, and Tibetan Plateau zone occurred in the mid‐ or late 1990s. The advanced trends of SOS in the Cold zone, Temperate zone, and Tibetan Plateau zone exhibited accelerated, stalled, and reversed patterns after the corresponding TP, respectively. The TP did not occurred in Cold‐Temperate zone, where the SOS showed a consistent and continuous advance. TPs of EOS trends in the Cold zone, Cold‐Temperate zone, Temperate zone, and Tibetan Plateau zone occurred in the late 1980s or mid‐1990s. The EOS in the Cold zone, Cold‐Temperate zone, Temperate zone, and Tibetan Plateau zone showed weak advanced or delayed trends after the corresponding TP, which were comparable with the delayed trends before the corresponding TP. The shift patterns of LOS trends were primarily influenced by the shift patterns of SOS trends and were also heterogeneous within climatic zones.
Rapid and Ultrasensitive Quantification of Multiplex Respiratory Tract Infection Pathogen via Lateral Flow Microarray based on SERS Nanotags

Respiratory tract infections (RTIs) are severe acute infectious diseases, which require the timely and accurate identification of the pathogens involved so that the individual treatment plan can be selected, including optimized use of antibiotics. However, high throughput and ultrasensitive quantification of multiple nucleic acids is a challenge in a point of care testing (POCT) device. Methods: Herein, we developed a 2×3 microarray on a lateral flow strip with surface enhanced Raman scattering (SERS) nanotags encoding the nucleic acids of 11 common RTI pathogens. On account of the signal magnification of encoded SERS nanotags in addition to the high surface area to volume ratio of the nitrocellulose (NC) membrane, rapid quantification of the 11 pathogens with a broad linear dynamic range (LDR) and ultra-high sensitivity was achieved on one lateral flow microarray. Results: The limit of detection (LOD) for influenza A, parainfluenza 1, parainfluenza 3, respiratory syncytial virus, coxiella burnetii, legionella pneumophila, influenza B, parainfluenza 2, adenovirus, chlamydophila pneumoniae, and mycoplasma pneumoniae were calculated to be 0.031 pM, 0.030 pM, 0.038 pM, 0.038 pM, 0.040 pM, 0.039 pM, 0.035 pM, 0.032 pM, 0.040 pM, 0.039 pM, and 0.041 pM, respectively. The LDR of measurement of the target nucleic acids of the eleven RTI pathogens were 1 pM-50 nM, which span 5 orders of magnitude. Conclusions: We anticipate this novel approach could be widely adopted in the early and precise diagnosis of RTI and other diseases.
Muscle quality index and isometric strength in older adults with hip osteoarthritis

Background Older adults with hip osteoarthritis (OA) suffer a progressive loss of muscle quality and strength, affecting their daily activities and quality of life. The purpose of this study is to compare the levels of isometric strength among older adults with and without hip OA and healthy young adults, and to determine the relationship between muscle quality index (MQI) and isometric strength. Methods Fourteen subjects with hip OA (65.6 ± 3.0 years), 18 healthy older adults (66.6 ± 6.5 years) and 32 young adults (20.7 ± 2.0 years) participated in the study. MQI, isometric muscle strength of the hip, ten time sit-to-stand tests, and body composition were measured. Results The MQI was lower in subjects with hip OA, with no significant differences between groups (p > 0.054). Subjects with OA produced significantly less isometric strength in hip extension (p < 0.001), flexion (p < 0.001), abduction (p < 0.05), adduction (p < 0.001), external (p < 0.05) and internal rotation (p < 0.05). Subjects with OA demonstrated longer time in the execution of the sit-to-stand test (p < 0.001) in comparison with healthy older and young adults. High correlations between MQI, sit-to-stand (r = − 0.76, p < 0.01) and peak force during hip abduction (r = 0.78, p < 0.01) where found in subjects with OA. Moderate correlation between MQI and peak force during hip flexion (r = 0.55, p < 0.05) and external rotation (r = 0.61, p < 0.05) were found in the OA group. Conclusions Subjects with OA have lower MQI than old and young healthy controls. In subjects with OA, there was a significant relationship between isometric strength of hip muscles and performance on the sit-to-stand test and the MQI.
Fauna of nocturnal moth species collected in a semi-natural grassland at Kanpu-zan in northern Japan

Abstract Semi-natural grasslands, which house species-rich ecosystems, have rapidly declined since the twentieth century due to land-use practices, such as agricultural intensification and abandonment. Owing to their diversity and known habitat associations, nocturnal moths are considered as one of the most suitable organisms to be studied for assessing the dynamics of species composition as a result of changes in landscape management of semi-natural grasslands. The present study provides the foremost description of nocturnal moth fauna of the semi-natural grassland at Kanpu-zan, northern Japan. Moth population data from 1987 were compared to the data collected in 2018 to evaluate the impact of decline in grasslands on species-richness. During the field sampling in 2018, a total of 226 nocturnal moth species were detected, which was nearly two-thirds of the number of species recorded in 1987, i.e. 396 species. The values obtained in 2018 were found to be nearly constant for different sites. For both periods, it was evident that moth fauna in Kanpu-zan mainly consisted of species that relied on woody plants. Amongst the species which were only recorded in 1987, 107 species were generalists that fed on plants that are commonly distributed in Kanpu-zan. No moth species were recorded that depended upon endangered or extinct plant food sources. Thus, it is unlikely that the decline in the number of moth species in Kanpu-zan was due to the loss in plant food sources. Our results suggest that environmental factors other than food plants may have caused decline and changes in nocturnal moth fauna. More studies on various organism fauna are needed for understanding the conservation of semi-natural grassland, considering that the loss of semi-natural grasslands is one of the major threats to biodiversity.
Toxicity, biodistribution and oxidative damage caused by zirconia nanoparticles after intravenous injection

Background: As a promising nanomaterial for biomedical applications, zirconia nanoparticles (ZrO2) have aroused concern recently, but the toxicity of ZrO2 in vivo has received little attention. Purpose: The aim of this study is to demonstrate the systematic single dose toxicity, biodistribution and oxidative damage of ZrO2 in vivo after intravenous injection in mice. Materials and methods: Ten ICR mice were used at the high dose of ZrO2 including 600, 500, 400 and 300mg/kg. Maximum tolerated dose (MTD) of 150 nm ZrO2 was determined as 500mg/kg. Hematology analysis and blood biochemical assay were determined for the evaluation of oxidative damage caused by ZrO2. Biodistribution of ZrO2 was investigated by ICP-OES and TEM. Results: Mice treated with higher dose (500mg/kg) showed significant spread in white blood cell counts (p<0.05). Especially, the serum ALT levels of 500mg/kg groups increased significantly (p<0.05) compared with the control group. ZrO2 particles would not induce any changes in appearance and micromorphology of liver at 100 and 350mg/kg. Spleen samples showed no significant changes in micromorphology of the lymphoid follicles and in the size of the red pulp after injection of ZrO2 at all doses. The serum of ZrO2-treated animals (350 and 500mg/kg) has reduced levels of SOD compared to the control group (p<0.05). ZrO2 persists in membrane-enclosed vesicles called lysosomes in the liver and spleen macrophages without abnormal changes of ultrastructure. Conclusion: These findings would contribute to the future development of ZrO2-based drug delivery system and other biomedical applications.
Staphyloxanthin: a potential target for antivirulence therapy

Abstract Staphylococcus aureus is an important and common Gram-positive bacteria which causes clinical infections and food-poisoning cases. Therapeutic schedules for treatment of S. aureus infections are facing a challenge because of the emergence of multidrug resistance strains. It is urgent to find new antiinfective drugs to control S. aureus infection. S. aureus strains are capable of producing the golden carotenoid pigment: staphyloxanthin, which acts as an important virulence factor and a potential target for antivirulence drug design. This review is aimed at presenting an updated overview of this golden carotenoid pigment of S. aureus from the biosynthesis of staphyloxanthin, its function, and the genes involved in pigment production to staphyloxanthin: a novel target for antivirulence therapy.
The effect of preoperative respiratory physiotherapy and motor exercise in patients undergoing elective cardiac surgery: short-term results

Introduction Loss of physical activity and pulmonary dysfunction with its associated complications represent two of the most important causes of morbidity and mortality following cardiac surgery. Few studies have investigated the effects of preoperative interventions targeted at improving cardiorespiratory and musculoskeletal function in the postoperative period. Aim To evaluate whether a physiotherapy program based on respiratory training with or without musculoskeletal mobilization, started preoperatively, may provide a significant improvement in pulmonary and musculoskeletal recovery postoperatively in patients undergoing elective cardiac surgery. Material and methods Patients with similar baseline and preoperative characteristics were randomly assigned to a preoperative respiratory physiotherapy protocol (group A), a preoperative respiratory and motor physiotherapy protocol (group B), or no preoperative specific physiotherapy protocol but only a simplified perioperative standard physiotherapy protocol (control group or group C). Group A consisted of 19 patients, group B of 20, group C of 20. Data on 6-minute walking test, peak expiratory flow, and from blood gas analysis were retrospectively analyzed. Results As compared with group C, a statistically significant improvement was observed in the two preoperatively treated groups A and B in terms of longer pre- and postoperative distance traveled at the 6-minute walking test, better pre- and postoperative peak expiratory flow value, and better PaO2 and SaO2 values in postoperative blood gas measurements (p < 0.05, for all comparisons). A statistically significant reduction of the postoperative length of in-hospital stay was also observed in group B. Conclusions As compared with the control group, substantially better clinical results for respiratory and musculoskeletal function were found in the groups preoperatively treated with physiotherapeutic protocols immediately before as well as after cardiac surgery.
Validity of the iLOAD® app for resistance training monitoring

Background This study aimed (I) to assess the inter-rater agreement for measuring the mean velocity (MV) of the barbell with the iLOAD® app, and (II) to compare the magnitude of the MV and total work of a training session between the iLOAD® app and a linear encoder (reference method). Method Sixteen young healthy individuals (four women and 12 men) were tested in two sessions separated by 48 h. The 10 repetition maximum (RM) load was determined in the first testing session in the half squat exercise. The second testing session consisted of 3 sets of 10 repetitions during the half squat exercise performed against the 10RM load. Both the iLOAD® app and a linear encoder were used to calculate the MV and total work of each training set. MV was recorded with the iLOAD® app by two independent researchers to evaluate the inter-rater agreement. Results Trivial differences and nearly perfect correlations were observed between raters for the MV values collected under individual sets (effect size [ES] ≤ 0.02, r ≥ 0.987), as well as for the whole training session (ES = 0.01, r = 0.997). Trivial-small differences and nearly perfect correlations were observed between the iLOAD® app and the linear encoder (Chronojump, Barcelona, Spain) for MV (EV ≤ 0.25, r ≥ 0.903) and total work (ES ≤ 0.05, r ≥ 0.973). Bland-Altman plots did not reveal heteroscedasticity of the errors between the iLOAD® app and the linear encoder for MV (r2 = 0.010) and total work (r2 < 0.001). Conclusions iLOAD® is a valid smartphone app which can provide real-time feedback of the MV and total work completed in a set of multiple repetitions in the half squat exercise.
Overview of Data Aggregation Schemes in a Smart Grid AMI Network

—In a fully evolved smart grid advanced metering infrastructure network, grid operators, energy suppliers and other third-party operators can be granted access to end users consumption data for purposes such as billing and other grid control operations. This will help to optimize smart grid operations and maximize energy consumer’s benefits. However, uncontrolled or unauthorized access to consumption data may put energy consumer’s privacy at risk. This is because end user’s energy consumption data can be profiled when collected at a high frequency and then subsequently used to make reasonable inferences about the private life of energy consumers. Aggregation of energy consumption data has been a popular research approach towards preserving the privacy of energy consumers. In this paper, we present a survey of different schemes using data aggregation approach for preserving the privacy of energy consumers in a smart grid AMI network. At the end, open research issues are highlighted and discussed.
A Microstrip Patch Antenna with Defected Ground Structure for Triple Band Wireless Communications

—In this article, a triple band microstrip antenna is designed and developed. The rectangular patch is loaded with slots and the ground is made defective for achieving triple band operation. The proposed design is optimized and simulated using CST microwave studio simulator. The optimized structure of the proposed design for triple mode operates at 1.2 GHz, 2.45 GHz and 5.6372 GHz. The prototype of the proposed antenna is developed and measured. The simulated and measured results are presented. Various antenna patterns such as reflection coefficient, E-plane and H-plane radiation patterns, gain, directivity etc are presented and discussed. The reflection coefficient plot of the proposed antenna both in simulation and in measurement confirms the triple band characteristics. The maximum gain and maximum directivity of the antenna are 6.307 dB and 7.279 dBi, respectively. The proposed antenna is suitable for wireless video transmission, wireless security systems, industry, scientific and medical (ISM) radio, and wireless local area networks (WLANs) applications.
Investigation of Asymmetrically Clipped Optical Wavelet Based OFDM System

The main advantage of Orthogonal Frequency Division Multiplexing (OFDM) is its robustness against channel dispersion. This feature makes OFDM a strong modulation technique for high speed communication systems in dispersive environments. OFDM has been proposed for dispersion compensation in optical communication systems [1]. The fundamental challenge to implement optical OFDM is converting the bipolar electrical OFDM signal to a unipolar optical signal. To this end, optical structures such as DC biased Optical (DCO) structure and Asymmetrically Clipped Optical (ACO) structure have been proposed for OFDM transmission over multimode optical fibers and free space optical channels [2]-[10]. In these structures, optical modulation format is intensity modulation in which the electrical OFDM signal is represented as the intensity of light. The strategy of OFDM to overcome channel dispersion is simultaneous transmission of long duration symbols. To this end, the Fourier transform modulates data symbols on the amplitudes of orthogonal subcarriers, i.e. orthogonal complex exponentials, using rectangular windowing. This process generates windowed complex exponentials that each have sinc shapes with considerable side lobes in the frequency domain. This causes Inter Carrier Interference (ICI). In WOFDM, subcarriers are the scaled and shifted versions of wavelets. Wavelets are designed in such a way to have finite length in both time and frequency domain. Wavelets have pulse shaping nature, so spectrums of wavelets contain lower side lobes
A Cross-Platform Malware Variant Classification based on Image Representation

Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.
A Classification Algorithm Based on Data Clustering and Data Reduction for Intrusion Detection System over Big Data

With the rapid development of network, Intrusion Detection System(IDS) plays a more and more important role in network applications. Many data mining algorithms are used to build IDS. However, due to the advent of big data era, massive data are generated. When dealing with large-scale data sets, most data mining algorithms suffer from a high computational burden which makes IDS much less efficient. To build an efficient IDS over big data, we propose a classification algorithm based on data clustering and data reduction. In the training stage, the training data are divided into clusters with similar size by Mini Batch K-Means algorithm, meanwhile, the center of each cluster is used as its index. Then, we select representative instances for each cluster to perform the task of data reduction and use the clusters that consist of representative instances to build a K-Nearest Neighbor(KNN) detection model. In the detection stage, we sort clusters according to the distances between the test sample and cluster indexes, and obtain k nearest clusters where we find k nearest neighbors. Experimental results show that searching neighbors by cluster indexes reduces the computational complexity significantly, and classification with reduced data of representative instances not only improves the efficiency, but also maintains high accuracy.
Joint Optimization of Mobile Charging and Data Gathering for Wireless Rechargeable Sensor Networks

Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes’ energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV’s velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.