THE EFFECT OF RESISTANCE AND ENDURANCE EXERCISE TRAINING ON MUSCLE PROTEOME EXPRESSION IN HUMAN SKELETAL MUSCLE

To investigate the effect of resistance and endurance training on muscle proteome expression, samples of vastus lateralis from 10 physically active young men were analysed by 2-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Differential patterns of protein expression were determined after 4 weeks of endurance or resistance exercise training. Following endurance exercise training, carbonic anhydrase III immunoglobulin heavy chain, myosin heavy chain 1, titin, chromosome 12, and fructose-1,6-bisphosphatase 2 were up-regulated while pyruvate kinase 3 isoform, ubiquitin carboxyl-terminal hydrolase, and phosphoglucomutase were down-regulated. After the 4 weeks of resistance exercise training, five proteins, apolipoprotein A-IV precursor, microtubule-actin cross linking factor 1, myosin light chain, growth hormone inducible transmembrane protein, and an unknown protein were up-regulated and pyruvate kinase 3 isoform, human albumin, and enolase 3 were down-regulated. We conclude that endurance and resistance exercise training differently alter the expression of individual muscle proteins, and that the response of muscle protein expression may be associated with specific myofibre adaptations to exercise training. Proteomic studies represent one of the developing techniques of metabolism which may substantially contribute to new insights into muscle and exercise physiology

Breaking Temporal Consistency: Generating Video Universal Adversarial Perturbations Using Image Models

As video analysis using deep learning models becomes more widespread, the vulnerability of such models to adversarial attacks is becoming a pressing concern. In particular, Universal Adversarial Perturbation (UAP) poses a significant threat, as a single perturbation can mislead deep learning models on entire datasets. We propose a novel video UAP using image data and image model. This enables us to take advantage of the rich image data and image model-based studies available for video applications. However, there is a challenge that image models are limited in their ability to analyze the temporal aspects of videos, which is crucial for a successful video attack. To address this challenge, we introduce the Breaking Temporal Consistency (BTC) method, which is the first attempt to incorporate temporal information into video attacks using image models. We aim to generate adversarial videos that have opposite patterns to the original. Specifically, BTC-UAP minimizes the feature similarity between neighboring frames in videos. Our approach is simple but effective at attacking unseen video models. Additionally, it is applicable to videos of varying lengths and invariant to temporal shifts. Our approach surpasses existing methods in terms of effectiveness on various datasets, including ImageNet, UCF-101, and Kinetics-400.Comment: ICCV 202

Investigating Factors Affecting Electronic Word-Of-Mouth In The Open Market Context: A Mixed Methods Approach

Electronic Word-of-Mouth (eWOM) has been identified as one of key factors affecting online sales. There has been, however, lack of understanding about the factors leading to eWOM in the open market context. As many Internet vendors have adopted the open market business, it is essential to understand the factors leading to eWOM for the success of open market business. This study investigates factors affecting eWOM in the open market context based on a sequential combination of qualitative and quantitative research methods. The exploratory findings in the qualitative study become the basis for the quantitative study, survey research. The findings from the mixed methods explain the significance of three new factors (information sharing desire, self-presentation desire, and open market reward) and two other factors (open market satisfaction and open market loyalty) affecting eWOM directly and indirectly. This study contributes to research by adding to the broader literature on eWOM. The findings also can inform open market providers on how to promote and manage eWOM for their online business success

Estimating Live Fuel Moisture Using SMAP L-Band Radiometer Soil Moisture for Southern California, USA

Live fuel moisture (LFM) is a field-measured indicator of vegetation water content and a crucial observation of vegetation flammability. This study presents a new multi-variant regression model to estimate LFM in the Mediterranean ecosystem of Southern California, USA, using the Soil Moisture Active Passive (SMAP) L-band radiometer soil moisture (SMAP SM) from April 2015 to December 2018 over 12 chamise (Adenostoma fasciculatum) LFM sites. The two-month lag between SMAP SM and LFM was utilized either as steps to synchronize the SMAP SM to the LFM series or as the leading time window to calculate the accumulative SMAP SM. Cumulative growing degree days (CGDDs) were also employed to address the impact from heat. Models were constructed separately for the green-up and brown-down periods. An inverse exponential weight function was applied in the calculation of accumulative SMAP SM to address the different contribution to the LFM between the earlier and present SMAP SM. The model using the weighted accumulative SMAP SM and CGDDs yielded the best results and outperformed the reference model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Visible Atmospherically Resistance Index. Our study provides a new way to empirically estimate the LFM in chaparral areas and extends the application of SMAP SM in the study of wildfire risk

17β-Estradiol strongly inhibits azoxymethane/dextran sulfate sodium-induced colorectal cancer development in Nrf2 knockout male mice

© 2020 The Author(s)Nuclear factor erythroid 2-related factor 2 (Nrf2) has dual effects on inflammation and cancer progression depending on the microenvironment. Estrogens have a protective effect on colorectal cancer (CRC) development. The aim of this study was to investigate CRC development in Nrf2 knockout (KO) mice. Azoxymethane (AOM) and dextran sulfate sodium (DSS)-treated wild-type (WT) and Nrf2 KO male mice were sacrificed at weeks 2 and 16 after AOM injection with/without 17β-estradiol (E2) treatment during week 1. Disease activity index and colon tissue damage at week 2 showed strong attenuation following E2 administration in WT mice but to a lesser extent in Nrf2 KO male mice. At week 16, E2 significantly diminished AOM/DSS-induced adenoma/cancer incidence at distal colon in the Nrf2 KO group, but not in the WT. Furthermore, mRNA or protein levels of NF-κB-related mediators (i.e., iNOS, TNF-α, and IL-1β) and Nrf2-related antioxidants (i.e., NQO1 and HO-1) were significantly lower in the Nrf2 KO group regardless of E2 treatment compared to the WT. The expression of estrogen receptor beta (ERβ) was higher in the Nrf2 KO group than in the WT. In conclusion, estrogen further inhibits CRC by upregulating ERβ-related alternate pathways in the absence of Nrf2.