Elevated angiotensin II induces platelet apoptosis through promoting oxidative stress in an AT1R-dependent manner during sepsis

Thrombocytopenia is independently related with increased mortality in severe septic patients. Renin-angiotensin system (RAS) is elevated in septic subjects; accumulating studies show that angiotensin II (Ang II) stimulate the intrinsic apoptosis pathway by promoting reactive oxygen species (ROS) production. However, the mechanisms underlying the relationship of platelet apoptosis and RAS system in sepsis have not been fully elucidated. The present study aimed to elucidate whether the RAS was involved in the pathogenesis of sepsis-associated thrombocytopenia and explore the underlying mechanisms. We found that elevated plasma Ang II was associated with decreased platelet count in both patients with sepsis and experimental animals exposed to lipopolysaccharide (LPS). Besides, Ang II treatment induced platelet apoptosis in a concentration-dependent manner in primary isolated platelets, which was blocked by angiotensin II type 1 receptor (AT1R) antagonist losartan, but not by angiotensin II type 2 receptor (AT2R) antagonist PD123319. Moreover, inhibiting AT1R by losartan attenuated LPS-induced platelet apoptosis and alleviated sepsis-associated thrombocytopenia. Furthermore, Ang II treatment induced oxidative stress level in a concentration-dependent manner in primary isolated platelets, which was partially reversed by the AT1R antagonist losartan. The present study demonstrated that elevated Ang II directly stimulated platelet apoptosis through promoting oxidative stress in an AT1R-dependent manner in sepsis-associated thrombocytopenia. The results would helpful for understanding the role of RAS system in sepsis-associated thrombocytopenia.     

C-terminus of Hsc70-interacting protein (CHIP) enhances stemness properties of human Wharton’s jelly mesenchymal stem cell

Mesenchymal stem cells are an attractive source of multipotent cells in part because they are easy to obtain. Several E3 ligases regulate the stability and functions of various factors in different adult stem cells through the ubiquitylation pathway. We investigated the C-terminus of Hsc70-interacting protein (CHIP) E3 ligase that regulates pluripotency of human Wharton’s jelly mesenchymal stem cells (hWJMSC). We found that CHIP increases protein kinase B (Akt) phosphorylation by decreased expression of phosphatase and tensin homolog (PTEN), which suggests improvement of the survival pathway by CHIP over-expression. We also found that increased CHIP expression induced Sox2 and NANOG, which can promote stem cell self-renewal and prevent oxidative stress-induced senescence of hWJMSC by decreased p21. We found that CHIP could be used to enhance the multiple functions of hWJMSC.     

Hopeahainol A attenuates memory deficits by targeting β‐amyloid in APP/PS1 transgenic mice

Increasing evidence demonstrates that amyloid beta (Aβ) elicits mitochondrial dysfunction and oxidative stress, which contributes to the pathogenesis of Alzheimer's disease (AD). Identification of the molecules targeting Aβ is thus of particular significance in the treatment of AD. Hopeahainol A (HopA), a polyphenol with a novel skeleton obtained from Hopea hainanensis, is potentially acetylcholinesterase‐inhibitory and anti‐oxidative in H₂O₂‐treated PC12 cells. In this study, we reported that HopA might bind to Aβ_1–42 directly and inhibit the Aβ_1–42 aggregation using a combination of molecular dynamics simulation, binding assay, transmission electron microscopic analysis and staining technique. We also demonstrated that HopA decreased the interaction between Aβ_1–42 and Aβ‐binding alcohol dehydrogenase, which in turn reduced mitochondrial dysfunction and oxidative stress in vivo and in vitro. In addition, HopA was able to rescue the long‐term potentiation induction by protecting synaptic function and attenuate memory deficits in APP/PS1 mice. Our data suggest that HopA might be a promising drug for therapeutic intervention in AD.     

Investigation on Side-Spray Fluidized Bed Granulation with Swirling Airflow

Top-spray fluidized bed granulation with axial fluidization airflow from the bottom of the granulator is well-established in the pharmaceutical industry. The application of swirling airflow for fluidized bed granulation was more recently introduced. This study examined the effects of various process parameters on the granules produced by side-spray fluidized bed with swirling airflow using the central composite and Box–Behnken design of experiment. Influence of the amount of binder solution, spray rate, and distance between spray nozzle and powder bed were initially studied to establish operationally viable values for these parameters. This was followed by an in-depth investigation on the effects of inlet airflow rate, atomizing air pressure and distance between spray nozzle and powder bed on granule properties. It was found that the amount of binder solution had a positive correlation with granule size and percentage of lumps but a negative correlation with size distribution and Hausner ratio of the granules. Binder solution spray rate was also found to affect the granules size. High drug content uniformity was observed in all the batches of granules produced. Both inlet airflow rate and atomizing air pressure were found to correlate negatively with granule size and percentage of lumps but correlate positively with the size distribution of the granule produced. Percentage of fines was found to be significantly affected by inlet airflow rate. Distance between spray nozzle and powder bed generally affected the percentage of lumps.     

A Fast Workflow for Identification and Quantification of Proteomes

The current in-depth proteomics makes use of long chromatography gradient to get access to more peptides for protein identification, resulting in covering of as many as 8000 mammalian gene products in 3 days of mass spectrometer running time. Here we report a fast sequencing (Fast-seq) workflow of the use of dual reverse phase high performance liquid chromatography - mass spectrometry (HPLC-MS) with a short gradient to achieve the same proteome coverage in 0.5 day. We adapted this workflow to a quantitative version (Fast quantification, Fast-quan) that was compatible to large-scale protein quantification. We subjected two identical samples to the Fast-quan workflow, which allowed us to systematically evaluate different parameters that impact the sensitivity and accuracy of the workflow. Using the statistics of significant test, we unraveled the existence of substantial falsely quantified differential proteins and estimated correlation of false quantification rate and parameters that are applied in label-free quantification. We optimized the setting of parameters that may substantially minimize the rate of falsely quantified differential proteins, and further applied them on a real biological process. With improved efficiency and throughput, we expect that the Fast-seq/Fast-quan workflow, allowing pair wise comparison of two proteomes in 1 day may make MS available to the masses and impact biomedical research in a positive way.The performance of mass spectrometry has been improved tremendously over the last few years (1–3), making mass spectrometry-based proteomics a viable approach for large-scale protein analysis in biological research. Scientists around the world are striving to fulfill the promise of identifying and quantifying almost all gene products expressed in a cell line or tissue. This would make mass spectrometry-based protein analysis an approach that is compatible to the second-generation mRNA deep-seq technique (4, 5).Two liquid chromatography (LC)-MS strategies have been employed to achieve deep proteome coverage. One is a single run with a long chromatography column and gradient to take advantage of the resolving power of HPLC to reduce the complexity of peptide mixtures; the other is a sequential run with two-dimensional separation (typically ion-exchange and reverse phase) to reduce peptide complexity. It was reported by two laboratories that 2761 and 4500 proteins were identified with a 10 h chromatography gradient on a dual pressure linear ion-trap orbitrap mass spectrometer (LTQ Orbitrap Velos)(6–8). Similarly, 3734 proteins were identified using a 8 h gradient on a 2 m long column with a hybrid triple quadrupole - time of flight (Q-TOF, AB sciex 5600 Q-TOF)(9) mass spectrometer. The two-dimensional approach has yielded more identification with longer time. For example, 10,006 proteins (representing over 9000 gene products, GPs)¹ were identified in U2OS cell (10), and 10,255 proteins (representing 9207 GPs) from HeLa cells (11). It took weeks (for example, 2–3 weeks) of machine running time to achieve such proteome coverage, pushing proteome analysis to the level that is comparable to mRNA-seq. With the introduction of faster machines, human proteome coverage now has reached the level of 7000–8500 proteins (representing 7000–8000 GPs) in 3 days (12). Notwithstanding the impressive improvement, the current approach using long column and long gradient suffers from inherent limitations: it takes long machine running time and it is challenging to keep reproducibility among repeated runs. Thus, current throughput and reproducibility have hindered the application of in-depth proteomics to traditional biological researches. A timesaving approach is in urgent need.In this study, we used the first-dimension (1D) short pH 10 RP prefractionation to reduce the complexity of the proteome (13), followed by sequential 30 min second-dimension (2D) short pH 3 reverse phase-(RP)-LC-MS/MS runs for protein identification (14). The results demonstrated that it is possible to identify 8000 gene products from mammalian cells within 12 h of total MS measurement time by applying this dual-short 2D-RPLC-MS/MS strategy (Fast sequencing, Fast-seq). The robustness of the strategy was revealed by parallel testing on different MS systems including quadrupole orbitrap mass spectrometer (Q-Exactive), hybrid Q-TOF (Triple-TOF 5600), and dual pressure linear ion-trap orbitrap mass spectrometer (LTQ-Orbitrap Velos), indicating the inherent strength of the approach as to merely taking advantage of the better MS instruments. This strategy increases the efficiency of MS sequencing in unit time for the identification of proteins. We achieved identification of 2200 proteins/30 mins on LTQ-Orbitrap Velos, 2800 proteins/30 mins on Q-Exactive and Triple-TOF 5600 respectively. We further optimized Fast-seq and worked out a quantitative-version of the Fast-seq workflow: Fast-quantification (Fast-quan) and applied it for protein abundance quantification in HUVEC cell that was treated with a drug candidate MLN4924 (a drug in phase III clinical trial). We were able to quantify > 6700 GPs in 1 day of MS running time and found 99 proteins were up-regulated with high confidence. We expect this efficient alternative approach for in-depth proteome analysis will make the application of MS-based proteomics more accessible to biological applications.