The Dual Roles of MAGE-C2 in p53 Ubiquitination and Cell Proliferation Through E3 Ligases MDM2 and TRIM28

The tumor suppressor p53 is critical for the maintenance of genome stability and protection against tumor malignant transformation, and its homeostasis is usually regulated by ubiquitination. MDM2 is a major E3 ligase of p53 ubiquitination, and its activity is enhanced by TRIM28. TRIM28 also independently ubiquitinates p53 as an E3 ligase activated by MAGE-C2. Moreover, MAGE-C2 is highly expressed in various cancers, but the detailed mechanisms of MAGE-C2 involved in MDM2/TRIM28-mediated p53 ubiquitination remain unknown. Here, we found that MAGE-C2 directly interacts with MDM2 through its conserved MHD domain to inhibit the activity of MDM2 on p53 ubiquitination. Furthermore, TRIM28 acts as an MAGE-C2 binding partner and directly competes with MAGE-C2 for MDM2 interaction, thus releasing the inhibitory role of MAGE-C2 and promoting p53 ubiquitination. MAGE-C2 suppresses cell proliferation in TRIM28-deficient cells, but the overexpression of TRIM28 antagonizes the inhibitory role of MAGE-C2 and accumulates p53 ubiquitination to promote cell proliferation. This study clarified the molecular link of MAGE-C2 in two major E3 systems MDM2 and TRIM28 on p53 ubiquitination. Our results revealed the molecular function of how MAGE-C2 and TRIM28 contribute to p53 ubiquitination and cell proliferation, in which MAGE-C2 acts as a potential inhibitor of MDM2 and TRIM28 is a vital regulator for MAGE-C2 function in p53 protein level and cell proliferation. This work would be helpful to understand the regulation mechanism of tumor suppressor p53

The safety and efficacy of carbon nanoparticle suspension injection versus indocyanine green tracer-guided lymph node dissection during radical gastrectomy (FUTURE-01): A single-center randomized controlled trial protocol

BackgroundThe use of lymph node (LN) tracers can help obtain a complete dissection of the lymph nodes and increase the detection rate of LNs and metastatic LNs. Carbon nanoparticle suspension injection (CNSI) and indocyanine green (ICG) have been widely used in radical gastrectomy in recent years. Nevertheless, the comparison of their clinical effects has not been studied.Method/designThe FUTURE-01 trial will be the first randomized, open-label, single-center trial to compare CNSI and ICG. The study started in 2021 and enrolled 96 patients according to a prior sample size calculation. The primary outcome is the number of LNs retrieved. The secondary outcomes are LN staining rate, LN metastasis rate, stained LN metastasis rate, perioperative recovery and survival.ConclusionBy comparing the safety and efficacy of CNSI and ICG tracer-guided LN dissection in patients with gastric cancer, we can determine the most appropriate LN tracer at present. With the help of LN tracers, the operation is simplified, and the prognosis of these patients is improved. Our study is a prospective exploration of the safety, efficacy, and prognosis of CNSI and ICG.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT05229874?cond=NCT05229874&draw=2&rank=1, identifier NCT05229874

Assessment of Total Suspended Sediment Distribution under Varying Tidal Conditions in Deep Bay: Initial Results from HJ-1A/1B Satellite CCD Images

Using Deep Bay in China as an example, an effective method for the retrieval of total suspended sediment (TSS) concentration using HJ-1A/1B satellite images is proposed. The factors driving the variation of the TSS spatial distribution are also discussed. Two field surveys, conducted on August 29 and October 26, 2012, showed that there was a strong linear relationship (R2 = 0.9623) between field-surveyed OBS (optical backscatter) measurements (5-31NTU) and laboratory-analyzed TSS concentrations (9.89–35.58 mg/L). The COST image-based atmospheric correction procedure and the pseudo-invariant features (PIF) method were combined to remove the atmospheric effects from the total radiance measurements obtained with different CCDs onboard the HJ-1A/1B satellites. Then, a simple and practical retrieval model was established based on the relationship between the satellite-corrected reflectance band ratio of band 3 and band 2 (Rrs3/Rrs2) and in-situ TSS measurements. The R2 of the regression relationship was 0.807, and the mean relative error (MRE) was 12.78%, as determined through in-situ data validation. Finally, the influences of tide cycles, wind factors (direction and speed) and other factors on the variation of the TSS spatial pattern observed from HJ-1A/1B satellite images from September through November of 2008 are discussed. The results show that HJ-1A/1B satellite CCD images can be used to estimate TSS concentrations under different tides in the study area over synoptic scales without using simultaneous in-situ atmospheric parameters and spectrum data. These findings provide strong informational support for numerical simulation studies on the combined influence of tide cycles and other associated hydrologic elements in Deep Bay

Effects of Electronic Cigarettes on Indoor Air Quality and Health.

With the rapid increase in electronic cigarette (e-cig) users worldwide, secondhand exposure to e-cig aerosols has become a serious public health concern. We summarize the evidence on the effects of e-cigs on indoor air quality, chemical compositions of mainstream and secondhand e-cig aerosols, and associated respiratory and cardiovascular effects. The use of e-cigs in indoor environments leads to high levels of fine and ultrafine particles similar to tobacco cigarettes (t-cigs). Concentrations of chemical compounds in e-cig aerosols are generally lower than those in t-cig smoke, but a substantial amount of vaporized propylene glycol, vegetable glycerin, nicotine, and toxic substances, such as aldehydes and heavy metals, has been reported. Exposures to mainstream e-cig aerosols have biologic effects but only limited evidence shows adverse respiratory and cardiovascular effects in humans. Long-term studies are needed to better understand the dosimetry and health effects of exposures to secondhand e-cig aerosols

Human Induced Turbidity Changes in Poyang Lake Between 2000 and 2010: Observations from MODIS

A robust retrieval algorithm to estimate concentrations of total suspended sediments (TSS) in Poyang Lake (the largest freshwater lake in China) was developed using Moderate Resolution Imaging Spectroradiometer (MODIS) medium-resolution (250 m) data from 2000 to 2010 and in situ data collected during two cruise surveys. The algorithm was based on atmospherically corrected surface reflectance at 645 nm, with 1240 nm data serving as a reference for aerosols and a nearest-neighbor method was used to avoid land adjacency effect. The algorithm showed an uncertainty of 30–40% for TSS ranging between 3 and 200 mg L−1. Long-term TSS distribution maps derived from MODIS data and the customized TSS algorithm showed significant variations in both space and time, with low TSS (\u3c10 mg L−1) in wet seasons and much higher TSS (\u3e15–20 mg L−1) in dry seasons for the south lake, and generally higher TSS in the north lake. The TSS difference between the north and the south increased significantly after 2002, with mean TSS often reaching \u3e40 mg L−1in the north. While the TSS seasonality was attributed to the seasonal changes of the lake\u27s circulation, the inter-annual variations were primarily driven by sand dredging activities, regulated by management policies. The case study here provides baseline water quality information for future restoration efforts in Poyang Lake, and more generally, an approach to assess water quality changes in similar water bodies, which have resulted from either climate variability or human activities

Radiometric Cross-Calibration of Tiangong-2 MWI Visible/NIR Channels over Aquatic Environments using MODIS

The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions

Human Induced Turbidity Changes in Poyang Lake Between 2000 and 2010: Observations from MODIS

A robust retrieval algorithm to estimate concentrations of total suspended sediments (TSS) in Poyang Lake (the largest freshwater lake in China) was developed using Moderate Resolution Imaging Spectroradiometer (MODIS) medium-resolution (250 m) data from 2000 to 2010 and in situ data collected during two cruise surveys. The algorithm was based on atmospherically corrected surface reflectance at 645 nm, with 1240 nm data serving as a reference for aerosols and a nearest-neighbor method was used to avoid land adjacency effect. The algorithm showed an uncertainty of 30–40% for TSS ranging between 3 and 200 mg L−1. Long-term TSS distribution maps derived from MODIS data and the customized TSS algorithm showed significant variations in both space and time, with low TSS (\u3c10 mg L−1) in wet seasons and much higher TSS (\u3e15–20 mg L−1) in dry seasons for the south lake, and generally higher TSS in the north lake. The TSS difference between the north and the south increased significantly after 2002, with mean TSS often reaching \u3e40 mg L−1in the north. While the TSS seasonality was attributed to the seasonal changes of the lake\u27s circulation, the inter-annual variations were primarily driven by sand dredging activities, regulated by management policies. The case study here provides baseline water quality information for future restoration efforts in Poyang Lake, and more generally, an approach to assess water quality changes in similar water bodies, which have resulted from either climate variability or human activities

Grouping-Based Time-Series Model for Monitoring of Fall Peak Coloration Dates Using Satellite Remote Sensing Data

Accurate monitoring of plant phenology is vital to effective understanding and prediction of the response of vegetation ecosystems to climate change. Satellite remote sensing is extensively employed to monitor vegetation phenology. However, fall phenology, such as peak foliage coloration, is less well understood compared with spring phenological events, and is mainly determined using the vegetation index (VI) time-series. Each VI only emphasizes a single vegetation property. Thus, selecting suitable VIs and taking advantage of multiple spectral signatures to detect phenological events is challenging. In this study, a novel grouping-based time-series approach for satellite remote sensing was proposed, and a wide range of spectral wavelengths was considered to monitor the complex fall foliage coloration process with simultaneous changes in multiple vegetation properties. The spatial and temporal scale effects of satellite data were reduced to form a reliable remote sensing time-series, which was then divided into groups, namely pre-transition, transition and post-transition groups, to represent vegetation dynamics. The transition period of leaf coloration was correspondingly determined to divisions with the smallest intra-group and largest inter-group distances. Preliminary results using a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2002 to 2013 at the Harvard Forest (spatial scale: ~3500 m; temporal scale: ~8 days) demonstrated that the method can accurately determine the coloration period (correlation coefficient: 0.88; mean absolute difference: 3.38 days), and that the peak coloration periods displayed a shifting trend to earlier dates. The grouping-based approach shows considerable potential in phenological monitoring using satellite time-series

Sampling Uncertainties of Long-Term Remote-Sensing Suspended Sediments Monitoring over China's Seas: Impacts of Cloud Coverage and Sediment Variations

Satellite-based ocean color sensors have provided an unprecedentedly large amount of information on ocean, coastal and inland waters at varied spatial and temporal scales. However, observations are often adversely affected by cloud coverage and other poor weather conditions, like sun glint, and this influences the accuracy associated with long-term monitoring of water quality parameters. This study uses long-term (2013-2017) and high-frequency (eight observations per day) datasets from the Geostationary Ocean Color Imager (GOCI), the first geostationary ocean color satellite sensor, to quantify the cloud coverage over China&#39;s seas, the resultant interrupted observations in remote sensing, and their impacts on the retrieval of total suspended sediments (TSS). The monthly mean cloud coverage for the East China Sea (ECS), Bohai Sea (BS) and Yellow Sea (YS) were 62.6%, 67.3% and 69.9%, respectively. Uncertainties regarding the long-term retrieved TSS were affected by a combination of the effects of cloud coverage and TSS variations. The effects of the cloud coverage dominated at the monthly scale, with the mean normalized bias (P-bias) at 14.1% (+/- 2.6%), 7.6% (+/- 2.3%) and 12.2% (+/- 4.3%) for TSS of the ECS, BS and YS, respectively. Cloud coverage-interfering observations with the Terra/Aqua MODIS systems were also estimated, with monthly P(bias)ranging from 6.5% (+/- 7.4%) to 20% (+/- 13.1%) for TSS products, and resulted in a smaller data range and lower maximum to minimum ratio compared to the eight GOCI observations. Furthermore, with approximately 16.7% monthly variations being missed during the periods, significant &quot;missing trends&quot; effects were revealed in monthly TSS variations from Terra/Aqua MODIS. For the entire region and the Bohai Sea, the most appropriate timeframe for sampling ranges from 12:30 to 15:30, while this timeframe was narrowed to from 13:30 to 15:30 for observations in the East China Sea and the Yellow Sea. This research project evaluated the effects of cloud coverage and times for sampling on the remote sensing monitoring of ocean color constituents, which would suggest the most appropriate timeframe for ocean color sensor scans, as well as in situ data collection, and can provide design specification guidance for future satellite sensor systems.</p