For nearly 40 years CMOS devices have been scaled down in order to achieve higher speed, performance and lower power consumption. Static Random Access Memory (SRAM) continues to be one of the most fundamental and vitally important memory technologies today. As process technology is scaled down, threshold voltage and leakage current variations are increased . In the conventional6Tcell, it is difficult to find an optimum design because the both read stability and write margin must be considered. At low supply voltage 6Tcell worsen in read stability. Leakage power is a high priority consideration due to feature scaling in high performance processor design. In today’s processors, the leakage power of cache was a major source of power dissipation because cache occupies more than 50% of the chip area . Low leakage SRAM design leakage SRAM design has been an active area of research over the past years. Low Power and high-stability have been the main themes ofSRAM designs in the last decade .
The conventional dual-port SRAMcell comprised of eight transistors (8TSRAM) is shown in Fig.8. The 8TSRAM frees a static noise margin (SNM) in a read operation because it has a separated read port. Meanwhile, a precharge circuit must be implemented on a read bitline (RBL) so that the two NMOS transistors at the read port can sink a bitline charge to the ground. Thus, a certain amount power is dissipated by pre-charging. In addition to the precharge circuit, we have to prepare a bitline keeper on the RBL which imparts negative influence on a readout time. To make the matters worse, the delay overhead becomes larger as a supply voltage (VDD) decreases because of the bitline keeper [Noguchi, etal. (2008)].
Static Random Access Memory is a type of RAM used in various electronic applications including toys, computers, digital devices and automobiles. The static RAM or SRAM only holds its contents while power is applied. An SRAMcell keeps the cell data for as long as the power is turned on since it consists of a latch and refresh operation is not required for the SRAMcell. Its difference from dynamic RAM is that DRAM must use refresh cycles to keep its contents alive. As indicated by the name, SRAM holds data/memory as a static image until written over or lost from powering down. SRAM is mainly used for the cache memory in microprocessors, mainframe computers, engineering workstations and memory in hand held devices due to high speed and low power consumption. Each bit in an SRAM is stored on four transistors that form two cross coupled inverters. Static Random Access Memories (SRAMs) are commonly embedded into system-on-chip (SoC) designs to store programs and data. Many efforts have been made to improve the efficiency of the SRAM. Improvements are reducing delay, power consumption and increasing stability. A significant increase has been there in the demand for low power and high performance digital VLSI circuits. Designers are implementing very high-order scaling of both device dimensions and supply voltage. Transistor density and functionality on a chip is improved by scaling. Scaling also helps to increase speed and frequency of the operation and hence higher performance. This paper is presented an improved 6TSRAMcell that has low power
and initiate the inflammatory process. Procoa- gulant substances are released from tumor cells with the inflammatory process (25). One in vi- tro study determined a decrease in SCUBE-1 concentrations with interleukin-1-β and TNF-α therapies, a finding implicating SCUBE-1 in the inflammatory process (10). Expression of SCU- BE-1 transcripts in prostate cancer stromal cells was encountered in a series analysisof prostate mesenchymal cell gene expressions (26). Mente- se et al. concluded that SCUBE-1 is a useful ma- rker in determining recurrences that may occur after treatment in patients with stomach cancer (27). Topcu et al. reported that SCUBE-1 can be effective in determining the risk of thrombosis and in screening patients to receive anti-throm- botic therapy as a marker of hypercoagulability in patients with breast cancer (28). In the light of these studies, SCUBE-1 may be of significant value as a biomarker in renal cancer, with wi- despread angiogenesis and thrombosis. We also determined significantly higher SCUBE-1 va- lues in patients with renal cell cancer. But the- re was no correlation between SCUBE-1 values and the pathological parameters like type, grade and stage. On the other hand, when we investi- gated the distribution of renal tumor stages in patients, there was only one patient with gra- de T3a renal tumor. Almost all of the patients were diagnosed and treated in early stages of the disease in our patient group. This could be a significant advantage for SCUBE-1 as an early cancer detection biomarker considering the dis- tribution of the patients in the group.
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The standard treatment performed was wide resection. There is no clear recommendation in the literature regarding surgical margins for EP tumors. As such, we used our routine protocol for non-melanoma skin cancer, applying clear margins of at least 10 mm. In three patients, the resection was followed by a lymphadenectomy (inguinal or cervical). A single patient received palliative chemotherapy after unresectable local recurrence, while another two patients underwent adjuvant radiation therapy, one for close resection margins and the other because of lymph node macrometastasis.
Revascularization rates were higher in GC15 and GC30 when compared to BMG15 and BMG30. The importance of this formation in the provision of nutrients and cells for the graft has been attested (Stevenson et al., 1997; Bauer and Muschler, 2000). However, the BMG30 animals showed better radiographic results, which may indicate that the irrigation was more effective or that the presence of a higher number of viable cells enabled a quicker reconstruction, regardless of the irrigation. Therefore, the mechanisms of stem cell action on bone reconstruction still have to be better established. Several studies are required to determine the best way to administrate these cells, the most adequate carrier agent, site preparation for implantation and clinical situations in which they should be utilized.
Acute, blunt posterior urethral injuries, I believe, have ample data in the literature to support early endoscopic realignment over a catheter instead of suprapubic tube placement. I was surprised to see that in this series, acute realignment of significant acute blunt anterior urethral injuries was certain no better and poten- tially worse than suprapubic urinary diversion.
JEV-infected animals, are of the neuronal lineage and whether they contribute to neurogenesis. We therefore performed double staining for BrdU and DCX to determine the neuronal fate of the BrdU positive cells. A decline in the number of double positive BrdU+DCX cells was observed in the JEV-infected SVZ compared to control SVZ (Fig. 4A). In the JEV+M group however, these BrdU+DCX cells were observed in greater numbers than the infected SVZ. Furthermore, immunohisto- chemistry for DCX alone showed neurite outgrowth from the migrating neuroblasts in case of control and JEV+M group, but Figure 3. Replenishment of proliferating cells in the infected adult SVZ by minocycline administration. Cryostat sections of brains from control, control+M, JEV and JEV+M animal groups were stained for markers of proliferation- Ki-67 (A) and PCNA (B) and developed using DAB substrate. BrdU was also administered to animals for 5 days at 50 mg/kg body weight and then animals were sacrificed 6 h after the last BrdU injection. Cryostat sections from BrdU administered animals from all groups were stained using anti-BrdU antibody (C). Discrete population of cells in control SVZ show localisation of all the antigens. While reduced population of all three cell types were observed in JEV-infected SVZ, however, they were replenished in the SVZ from JEV+M animals. The graphs represent the number of Ki-67 (D), PCNA (E) and BrdU (F) positive cells in the SVZ from the different treatment groups. Cell counting was done using5 serial sections from 3 animals with Leica IM50 software. Values represent means 6 SEM from three animals in each group (* significant change from control, p,0.05; #
Telomere attrition by increasing age is a characteristic feature of peripheral blood cells as demonstrated in a large number of studies [1–5]. Regarding determinants for telomere length (TL), heredity is a well recognized major component [6–10] and for which the paternal influence seems to be of most importance [11–13]. There are also numerous studies indicating that blood cell TL is associated to various diseases, examples of which are diabetes, hypertension, arteriosclerosis and cancer [14–21]. In general, short telomeres have been coupled to increased risk of several diseases. It has been discussed whether short TL is important for disease development, if it is a biomarker for ongoing processes leading to disease or if the disease per se, or its treatment, can cause increased telomere shortening. Regarding TL and cancer risk the data is inconsistent and both short and long TL has been coupled to increased risk . It should also be noted that several published studies have been unable to show any association between TL and disease (as summarized in reference ). Furthermore, factors like life style and stress have been indicated to influence the blood cell TL attrition rate [24–25]. These data are in line with the fact that the heritable impact on TL decreases by increasing age , signifying the impact of micro- and/or macro-environmental factors in determining TL. What also must
In order to understand the all important phenomena that are connected with the dynamicstabilityof the mobile working machines, there are presented in the next part of this paper the relevant general definitions from the area of mechanics, which is describing the dynamic equilibrium of a mechanical system. The principle consists in consideration of such situation when the system is shifted from the stable position (dx) with a small speed (dv). The stability is kept in such case if the deviation from the previous position remains small.
For all hourly based data sets the information content in re- sidual data was equal 1. It means that both statistical tests explic- itly indicated that the residual data may include important infor- mation and therefore it is advisable to apply a regression model for finding desired predictions. By contrast, for most of the daily based data sets the information content in residual data was below 0,5, (in almost half of the cases it was equal to zero). Taking into account that the residual data are important fraction of the whole variability in those sets (an example is shown in Fig. 1), these results indicate that the time-series analysis can give prediction results with relatively large errors.
The original copyright did not indicate that the article is part of the public domain; the correct copyright statement is: This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
From a qualitative perspective, SAM maintenance is a question of developing and maintaining a patterning of a tissue with respect to distinct domains with specific gene expression profiles. A popular approach in developmental biology to capture pattern formation are reaction diffusion systems developed by Turing in the 1950s [22,32]. Relying on diffusion, these systems are capable of producing spatially heterogeneous patterns of somewhat antagonistic reactions initiated by an initial small perturbation. Here we employ a similar mechanism: Eqs. (0.1)–(0.2) are a variant of the activator-substrate model  - a system that is known to produce circular domains that remain mobile and thereby allow an OC that is forming in the meristem tip to move down after initiation of the SCD. Eqs. (0.3)-(0.5) are derived guided by the law of mass action. Still, parameters like the Hill coefficients in Eq. (0.4) have been further tuned, e.g. large Hill coefficients are used in Eq. (0.4) in order to produce a sharper transition between cells showing a high level of stemness and neighbouring cells with low levels of stemness. In turn, such parameter choices reflect possible underlying biological reactions like the formation of homodi- mers or other forms of cooperativity.
Homocysteine Inhibits Proliferation in Hepatocytes In this study, we found that homocysteine (0.1–2 mM) did not cause a significant lactate dehydrogenase leakage (an index ofcell injury) for the 24 h treatment in both cultured primary hepatocytes and HepG2 cells (data not shown). The effect of homocysteine on cell proliferation was assessed by [ 3 H]-thymidine incorporation into DNA. As shown in Fig. 1A, treatment of homocysteine markedly inhibited this incorporation in a dose- dependent manner in primary cultured hepatocytes and HepG2 cells. Concentrations of 0.1, 0.25, 0.5, and 1 mM homocysteine Figure 2. Homocysteine upregulates the expression of genes involved in transition ofcell cycle. (A) Primary cultured hepatocytes were incubated with 1 mM of homocysteine (Hcy) for 8 h. The mRNA levels were detected by real-time PCR. All results are standardized to the levels of actin and are the means 6 SD of five experiments. *P,0.05 versus control (without Hcy). (B) The proteins from hepatocytes were detected by Western blotting. The blot is representative of three independent experiments. The upper part shows quantification of immunoreactivity levels. The data are expressed as percent change from control. *P,0.05 versus control (without Hcy).
In this report we present a concise review concerning the use of flow cytometric methods to charac- terize and differentiate between two different mechanisms ofcell death, apoptosis and necrosis. The applications of these techniques to clinical and basic research are also considered. The following cell features are useful to characterize the mode ofcell death: (1) activation of an endonuclease in apoptotic cells results in extraction of the low molecular weight DNA following cell permeabilization, which, in turn, leads to their decreased stainability with DNA-specific fluorochromes. Measurements of DNA content make it possible to identify apoptotic cells and to recognize the cell cycle phase specificity of apoptotic process; (2) plasma membrane integrity, which is lost in necrotic but not in apoptotic cells; (3) the decrease in forward light scatter, paralleled either by no change or an increase in side scatter, represent early changes during apoptosis. The data presented indicate that flow cytometry can be ap- plied to basic research of the molecular and biochemical mechanisms of apoptosis, as well as in the clinical situations, where the ability to monitor early signs of apoptosis in some systems may be predic- tive for the outcome of some treatment protocols.
The colloidal stability is strongly influenced by the interactions between nanoparticles and be- tween NPs and its surrounding medium. The particle surface charges are balanced by an equal but oppositely charged region of counter-ions. Each particle has electrical charge that is respon- sible by the mutual electrostatic repulsion/attraction force between adjacent particles. The coun- ter-ions form a double layer at the interface of the NPs with the medium. The double layer theory (Figure 3.4 A) describes the formation and the extension of the ionic neighborhood of a charged colloid [39, 40]. If one considers a negative charged particle in an aqueous medium, this particle would be surrounded by a layer of positive ions (counter-ions) also known as the Stern layer. Surrounding the Stern layer are positive ions that form a second layer called diffuse layer. The Stern layer together with the charged region of the diffuse layer is the so-called double layer. The presence of the double layer not only neutralizes the charged particle, but also creates an electro- kinetic potential between the surface of the colloid and any point in the mass of the solution, called surface potential (Figure 3.4 B). On the other hand, the diffuse layer, or part of it, can move under the influence of tangential stress. Therefore, a slipping plane is introduced to separate the mobile fluid from fluid that remains attached to the surface. The electric potential at this plane is called the zeta potential (ζ). A value of 25-30 mV (in modulus) can be taken as a reference of the minimum potential to form a stable colloid, since it separates low charged surfaces from highly charged surfaces [39, 40].
For solving cell formation problem, Hachicha et al. (2008) used a multivariate approach based correlation analysis to get an original similarity coefficient matrix in the first phase of the procedure, and in the second phase, the PCA was applied to find the eigenvalues and eigenvectors on the correlation similarity matrix. They also used a ‘scatter plot’ as a cluster analysis which was applied to form machine groups, and the comparative results on multiple performance criteria duly establishes the effectiveness, efficiency and practical suitability of their approach. Seifoddini (1987); Gupta (1991) developed software packages to verify the suitability of the usage of similarity coefficient obtained using production data for machine-component grouping decisions in the design of a cellular manufacturing system. Some researchers, in the recent past, developed similarity coefficient algorithms for solution and presented them with illustrated numerical problems and computational results (Waghodekar & Sahu, 1984; Kusiak & Cho, 1992).
Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabili- zation of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progres- sion. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled sam- ples 1551 proteins were identified, of which 290 were differentially abundant, while 783 pro- teins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further exami- nation revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysisof complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin- 1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified a11111
S1 Fig. In-depth profiles of every colony studied at the single cell level. Top left: phase con- trast image of the colony at after four days of growth. Cells in images were color-coded post hoc to match the progeny they belong to (see figure key). Top center: phase contrast image of the colony at Day 4, with cells color-coded by their generation. Top right: glyph representing cell area, generation, relative location in colony, and proliferative capacity of the progeny/ progenies that formed the colony (see Fig 4). Filled circles represent individual cells at Day 4, with the size of the circles representing the relative cell spread area and their color representing the generation they belong to. The outer rings represent the number and proliferative capacity of the originating progeny; solid line (–) = fast proliferator, dotted line (. . .) = moderate prolif- erator, dashed line (- -) = slow proliferator. Cells that didn’t divide by Day 7 are marked (/). Glyphs were enlarged from Fig 4 for added detail; scale bar is relative only to other glyphs and does not represent an absolute length. Middle: lineage trees of colony-originating cells for the first four days of development. Width of lineage lines represents cell spread area at each 15-minute time point. Cells that did not divide by Day 7 and cells whose lifetime differed from their twin more than one standard deviation from the pooled average of all 1384 cells (0.27 days) are indicated (see key). Bottom: phase contrast images of the colony at Days 4, 7, and 10. Images underwent a process of background flattening and brightness/contrast adjustment (see Methods). Transparent red dots were placed on the Day 7 phase contrast images for single- cell-derived colonies and mark cells that do not belong to the originating progeny. Scale bars = 250 μm.