Development of a method for screening short-lived proteins using green fluorescent protein.

We have developed a screening technology for the identification of short-lived proteins. A green fluorescent protein (GFP)-fusion cDNA library was generated for monitoring degradation kinetics. Cells expressing a subset of the GFP-cDNA expression library were screened to recover those in which the fluorescence signal diminished rapidly when protein synthesis was inhibited. Thirty clones that met the screening criteria were characterized individually. Twenty-three (73%) proved to have a half-life of 4 hours or less

Use of an array technology for profiling and comparing transcription factors activated by TNFα and PMA in HeLa cells

AbstractMultiple signal transduction pathways are generally triggered simultaneously by a single extracellular stimulus. As a result, multiple transcription factors (TFs) can be activated downstream to mediate the inducible expression of target genes. Profiling the activation of all TFs will aid in the dissection of the numerous pathways of signal transduction. Tumor necrosis factor alpha (TNFα) and phorbol 12-myristate 13-acetate (PMA) mediate many biological functions, including cell proliferation and apoptosis, by stimulating signaling pathways. Two TFs, nuclear factor kappaB (NFκB) and activating factor 1 (AP1), have been identified as targets of both TNFα and PMA activation. Here, we describe the use of a protein/DNA array system to identify additional TFs activated by TNFα and PMA in HeLa cells. From a total of 150 targeted TFs, six—CREB, E2F, CETP/CRE, c-Rel, MSP1, and Pax6—were identified whose activities, like NFκB and AP1, were regulated by both TNFα- and PMA-induced pathways. Interestingly, the TF E47 was shown to be specifically activated by TNFα but was not affected by treatment with PMA. In addition, GATA, NF-E1, and ISRE were shown to be specifically activated by PMA but not TNFα. These findings suggest that TNFα and PMA both stimulate unique signaling pathways while mediating transcriptional activation through common pathways

(E)-N′-[1-(4-Chloro­phen­yl)ethyl­idene]-2-hydroxy­benzohydrazide

In the title compound, C15H13ClN2O2, the dihedral angle between the two benzene rings is 7.0 (1)°. An intra­molecular N—H⋯O hydrogen bond is present and inter­molecular O—H⋯O hydrogen bonds link the mol­ecules into chains along [001]

Low CO_2 levels of the entire Pleistocene epoch

Quantifying ancient atmospheric pCO_2 provides valuable insights into the interplay between greenhouse gases and global climate. Beyond the 800-ky history uncovered by ice cores, discrepancies in both the trend and magnitude of pCO_2 changes remain among different proxy-derived results. The traditional paleosol pCO_2 paleobarometer suffers from largely unconstrained soil-respired CO_2 concentration (S(z)). Using finely disseminated carbonates precipitated in paleosols from the Chinese Loess Plateau, here we identified that their S(z) can be quantitatively constrained by soil magnetic susceptibility. Based on this approach, we reconstructed pCO_2 during 2.6–0.9 Ma, which documents overall low pCO_2 levels (<300 ppm) comparable with ice core records, indicating that the Earth system has operated under late Pleistocene pCO_2 levels for an extended period. The pCO_2 levels do not show statistically significant differences across the mid-Pleistocene Transition (ca. 1.2–0.8 Ma), suggesting that CO_2 is probably not the driver of this important climate change event

A new merged dataset of global ocean chlorophyll-a concentration for better trend detection

Chlorophyll-a concentration (Chla) is recognized as an essential climate variable and is one of the primary parameters of ocean-color satellite products. Ocean-color missions have accumulated continuous Chla data for over two decades since the launch of SeaWiFS (Sea-viewing Wide Field-of-view Sensor) in 1997. However, the on-orbit life of a single mission is about five to ten years. To build a dataset with a time span long enough to serve climate change related studies, it is necessary to merge the Chla data from multiple sensors. The European Space Agency has developed two sets of merged Chla products, namely GlobColour and OC-CCI (Ocean Colour Climate Change Initiative), which have been widely used. Nonetheless, issues remain in the long-term trend analysis of these two datasets because the inter-mission differences in Chla have not been completely corrected. To obtain more accurate Chla trends in the global and various oceans, we produced a new dataset by merging Chla records from the SeaWiFS, MODIS (Medium-spectral Resolution Imaging Spectrometer), MERIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), and OLCI (Ocean and Land Colour Instrument) with inter-mission differences corrected in this work. The fitness of the dataset on long-term Chla trend study was validated by using in situ Chla and comparing the trend estimates to the multi-annual variability of different satellite Chla records. The results suggest that our dataset can be used for long-term series analysis and trend detection. We also provide the global trend map in Chla over 23 years (1998–2020) and present a significant positive global trend with 0.67% ± 0.37%/yr

Low CO_2 levels of the entire Pleistocene epoch

Quantifying ancient atmospheric pCO_2 provides valuable insights into the interplay between greenhouse gases and global climate. Beyond the 800-ky history uncovered by ice cores, discrepancies in both the trend and magnitude of pCO_2 changes remain among different proxy-derived results. The traditional paleosol pCO_2 paleobarometer suffers from largely unconstrained soil-respired CO_2 concentration (S(z)). Using finely disseminated carbonates precipitated in paleosols from the Chinese Loess Plateau, here we identified that their S(z) can be quantitatively constrained by soil magnetic susceptibility. Based on this approach, we reconstructed pCO_2 during 2.6–0.9 Ma, which documents overall low pCO_2 levels (<300 ppm) comparable with ice core records, indicating that the Earth system has operated under late Pleistocene pCO_2 levels for an extended period. The pCO_2 levels do not show statistically significant differences across the mid-Pleistocene Transition (ca. 1.2–0.8 Ma), suggesting that CO_2 is probably not the driver of this important climate change event

Identification of the shared gene signature and biological mechanism between type 2 diabetes and colorectal cancer

Background: The correlation of type 2 diabetes mellitus (T2DM) with colorectal cancer (CRC) has garnered considerable attention in the scientific community. Despite this, the molecular mechanisms underlying the interaction between these two diseases are yet to be elucidated. Hence, the present investigation aims to explore the shared gene signatures, immune profiles, and drug sensitivity patterns that exist between CRC and T2DM.Methods: RNA sequences and characteristics of patients with CRC and T2DM were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. These were investigated using weighted gene co-expression network analysis (WGCNA) to determine the co-expression networks linked to the conditions. Genes shared between CRC and T2DM were analyzed by univariate regression, followed by risk prognosis assessment using the LASSO regression model. Various parameters were assessed through different software such as the ESTIMATE, CIBERSORT, AND SSGSEA utilized for tumor immune infiltration assessment in the high- and low-risk groups. Additionally, pRRophetic was utilized to assess the sensitivity to chemotherapeutic agents in both groups. This was followed by diagnostic modeling using logistic modeling and clinical prediction modeling using the nomogram.Results: WGCNA recognized four and five modules that displayed a high correlation with T2DM and CRC, respectively. In total, 868 genes were shared between CRC and T2DM, with 14 key shared genes being identified in the follow-up analysis. The overall survival (OS) of patients in the low-risk group was better than that of patients in the high-risk group. In contrast, the high-risk group exhibited higher expression levels of immune checkpoints The Cox regression analyses established that the risk-score model possessed independent prognostic value in predicting OS. To facilitate the prediction of OS and cause-specific survival, the nomogram was established utilizing the Cox regression model.Conclusion: The T2DM + CRC risk-score model enabled independent prediction of OS in individuals with CRC. Moreover, these findings revealed novel genes that hold promise as therapeutic targets or biomarkers in clinical settings