High frequency signal injection method for sensorless permanent magnet synchronous motor drives

The objective of this project is to design a high frequency signal injection method for sensorless control of permanent magnet synchronous motor (PMSM) drives. Generally, the PMSM drives control requires the appearance of speed and positon sensor to measure the motor speed hence to feedback the information for variable speed drives operation. The usage of the sensor will increase the size, cost, extra hardwire and feedback devices. Therefore, there is motivation to eliminate this type of sensor by injecting high frequency signal and utilizing the electrical parameter from the motor so that the speed and positon of rotor can be estimated. The proposed position and speed sensorless control method using high frequency signal injection together with all the power electronic circuit are modelled using Simulink. PMSM sensorless driveis simulated and the results are analyzed in terms of speed, torque and stator current response without load disturbance but under the specification of varying speed, forward to reverse operation, reverse to forward operation and step change in reference speed. The results show that the signal injection method performs well during start-up and low speed operation

Comparison of pattern of disease progression and prevalence of acquired T790M mutation in Malaysia patients with EGFR mutant lung adenocarcinoma upon failure of first-line afatinib, gefitinib and erlotinib

Abstract Background Patients receiving first-line afatinib, gefitinib or erlotinib for epidermal growth factor receptor (EGFR) mutant advanced non-small cell lung cancer develop progression of disease (PD) after an average of 9-13 months. Methods A retrospective analysis of PD pattern and prevalence of acquired T790M mutation among patients failing first-line afatinib versus gefitinib or erlotinib at University Malaya Medical Centre from 1st January 2015 to 31th December 2018. Results Of 87 patients who developed PD while on first-line EGFR-tyrosine kinase inhibitor (TKI) treatment, 19 (21.8%) were on afatinib, 49 (56.3%) were on gefitinib, and 19 (21.8%) were on erlotinib. The median progression-free survival (mPFS) of these patients is as shown in the table. Of 20 patients (23.0%) who developed new symptomatic brain metastases, one (5.0%) had new leptomeningeal metastases, three (15.0%) had both new leptomeningeal metastases and solid brain metastases, and the remaining 16 (80.0%) had new solid brain metastases only. New leptomeningeal metastases occurred in one patient treated with afatinib and three patients treated with gefitinib. Forty-nine patients (56.3%) were investigated for acquired T790M mutation either by plasma biopsy or tissue biopsy or both. The prevalence of acquired T790M mutation was 61.2%. There was no difference in the pattern of PD or prevalence of acquired T790M mutation among patients treated with afatinib, gefitinib or erlotinib. Conclusions New leptomeningeal metastases were uncommon in patients receiving first-line EGFR-TKI. The choice of first-line first- or second generation EGFR-TKI did not influence the pattern of PD and prevalence of acquired T790M mutation. However, patients receiving afatinib appeared to have longer mPFS than those on gefitinib or erlotinib

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Tricetin Induces Apoptosis of Human Leukemic HL-60 Cells through a Reactive Oxygen Species-Mediated c-Jun N-Terminal Kinase Activation Pathway

Tricetin is a dietary flavonoid with cytostatic properties and antimetastatic activities in various solid tumors. The anticancer effect of tricetin in nonsolid tumors remains unclear. Herein, the molecular mechanisms by which tricetin exerts its anticancer effects on acute myeloid leukemia (AML) cells were investigated. Results showed that tricetin inhibited cell viability in various types of AML cell lines. Tricetin induced morphological features of apoptosis such as chromatin condensation and phosphatidylserine (PS) externalization, and significantly activated proapoptotic signaling including caspase-8, -9, and -3 activation and poly(ADP-ribose) polymerase (PARP) cleavage in HL-60 AML cells. Of note, tricetin-induced cell growth inhibition was dramatically reversed by a pan caspase and caspase-8- and -9-specific inhibitors, suggesting that this compound mainly acts through a caspase-dependent pathway. Moreover, treatment of HL-60 cells with tricetin induced sustained activation of extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK), and inhibition of ERK and JNK by their specific inhibitors respectively promoted and abolished tricetin-induced cell apoptosis. Dichlorofluorescein (DCF) staining showed that intracellular reactive oxygen species (ROS) levels were higher in tricetin-treated HL-60 cells compared to the control group. Moreover, an ROS scavenger, N-acetylcysteine (NAC), reversed tricetin-induced JNK activation and subsequent cell apoptosis. In conclusion, our results indicated that tricetin induced cell death of leukemic HL-60 cells through induction of intracellular oxidative stress following activation of a JNK-mediated apoptosis pathway. A combination of tricetin and an ERK inhibitor may be a better strategy to enhance the anticancer activities of tricetin in AML

Shock Wave Therapy Enhances Mitochondrial Delivery into Target Cells and Protects against Acute Respiratory Distress Syndrome

This study tested the hypothesis that shock wave therapy (SW) enhances mitochondrial uptake into the lung epithelial and parenchymal cells to attenuate lung injury from acute respiratory distress syndrome (ARDS). ARDS was induced in rats through continuous inhalation of 100% oxygen for 48 h, while SW entailed application 0.15 mJ/mm2 for 200 impulses at 6 Hz per left/right lung field. In vitro and ex vivo studies showed that SW enhances mitochondrial uptake into lung epithelial and parenchyma cells (all p<0.001). Flow cytometry demonstrated that albumin levels and numbers of inflammatory cells (Ly6G+/CD14+/CD68+/CD11b/c+) in bronchoalveolar lavage fluid were the highest in untreated ARDS, were progressively reduced across SW, Mito, and SW + Mito (all p<0.0001), and were the lowest in sham controls. The same profile was also seen for fibrosis/collagen deposition, levels of biomarkers of oxidative stress (NOX-1/NOX-2/oxidized protein), inflammation (MMP-9/TNF-α/NF-κB/IL-1β/ICAM-1), apoptosis (cleaved caspase 3/PARP), fibrosis (Smad3/TGF-β), mitochondrial damage (cytosolic cytochrome c) (all p<0.0001), and DNA damage (γ-H2AX+), and numbers of parenchymal inflammatory cells (CD11+/CD14+/CD40L+/F4/80+) (p<0.0001). These results suggest that SW-assisted Mito therapy effectively protects the lung parenchyma from ARDS-induced injury

Pterostilbene Simultaneously Induced G0/G1-Phase Arrest and MAPK-Mediated Mitochondrial-Derived Apoptosis in Human Acute Myeloid Leukemia Cell Lines

<div><p>Background</p><p>Pterostilbene (PTER) is a dimethylated analog of the phenolic phytoalexin, resveratrol, with higher anticancer activity in various tumors. Herein, the molecular mechanisms by which PTER exerts its anticancer effects against acute myeloid leukemia (AML) cells were investigated.</p><p>Methodology and Principal Findings</p><p>Results showed that PTER suppressed cell proliferation in various AML cell lines. PTER-induced G0/G1-phase arrest occurred when expressions of cyclin D3 and cyclin-dependent kinase (CDK)2/6 were inhibited. PTER-induced cell apoptosis occurred through activation of caspases-8-9/-3, and a mitochondrial membrane permeabilization (MMP)-dependent pathway. Moreover, treatment of HL-60 cells with PTER induced sustained activation of extracellular signal-regulated kinase (ERK)1/2 and c-Jun N-terminal kinase (JNK)1/2, and inhibition of both MAPKs by their specific inhibitors significantly abolished the PTER-induced activation of caspases-8/-9/-3. Of note, PTER-induced cell growth inhibition was only partially reversed by the caspase-3-specific inhibitor, Z-DEVE-FMK, suggesting that this compound may also act through a caspase-independent pathway. Interestingly, we also found that PTER promoted disruption of lysosomal membrane permeabilization (LMP) and release of activated cathepsin B.</p><p>Conclusion</p><p>Taken together, our results suggest that PTER induced HL-60 cell death via MAPKs-mediated mitochondria apoptosis pathway and loss of LMP might be another cause for cell apoptosis induced by PTER.</p></div

Effect of pterostilbene (PTER) on alterations of cell-cycle regulatory proteins in HL-60 cells.

<p>Proteins were extracted from cultured HL-60 cells at 24 h after PTER treatment and probed with proper dilutions of specific antibodies. (A and B) PTER at a concentration of 100 µM induced significant decreases in protein levels of cyclin D3, CDK2, and CDK6. Upper panels: Representative results of cyclins and cyclin-dependent kinase (CDK) protein levels as determined by a Western blot analysis. Lower panels: Quantitative results of cyclin and CDK protein levels, which were adjusted to the β-actin protein level and expressed as multiples of induction beyond its own control. Values are presented as the mean ± SE of three independent experiments. *<i>p</i><0.05, compared to the vehicle control group. (C) There were no significant differences in protein levels of p15 INK4B, p21 Cip1, or p27 Kip1 between control and PTER-treated HL-60 cells. Upper panel: Representative results of p15, p21, and p27 protein levels as determined by a Western blot analysis. Lower panel: Quantitative results of p15, p21, and p27 protein levels, which were adjusted with the β-actin protein level and expressed as multiples of induction beyond its own control. (D) Cyclin D3, CDK2, and CDK6 peotein expression were downregulated in a concentration-dependent fashion after PTER treatment in HL-60 cells. Left panel: Representative results of cyclin D3, CDK2, and CDK6 protein levels as determined by a Western blot analysis. Right panel: Quantitative results of cyclin D3, CDK2, and CDK6 protein levels, which were adjusted with the β-actin protein level and expressed as multiples of induction beyond its own control. *<i>p</i><0.05, compared to the vehicle control group.</p

Effect of pterostilbene (PTER) on the cell proliferation of acute myeoloid leukemia (AML) cell lines.

<p>(A) The chemical structure of PTER. (B) Five AML cell lines were treated with the vehicle (DMSO) or PTER (12.5∼150 µM) in serum-containing medium for 24 h. Cell proliferation was determined by an MTS assay. Results are expressed as multiples of cell proliferation rate. Values represent the mean ± SE of 3 independent experiments. *^{, #, &, @, ∧}<i>p</i><0.05, compared to the vehicle groups. (C) HL-60 cells were treated with different concentrations of PTER (0∼150 µM) for 24 and 48 h and analyzed by a trypan blue exclusion assay. Quantitative assessment of the mean number of cells is expressed as the mean ± SE.</p