The cellular stress response network is complicated and one system may respond to more than one stress and on the other hand, more than one system may be involved in protecting the cells from a particular stress. Although the cold-shock response machinery seems to be mainly targeted towards reversing the adverse effects of temperature downshift, involvement of CspA homologues and other cold shock proteins in stresses other than cold shock suggests that, regulation and functions of these proteins are intricate. For example, CspC and CspE from E. coli regulate the expression of number of RpoS- regulated stress proteins such as OsmY, Dps, ProP and KatG, possibly thorough regulation of RpoS itself. These proteins are induced in response to osmotic stress, oxidative stress, or upon stationary phase. CspE and CspC also regulate expression of Universal protein A, UspA, a protein responding to numerous stresses. These fi ndings implicate CspA homologues in the regulation of expression of stress proteins in the complex stress response network of E. coli (Phadtare and Inouye, 2001). In addition, CspE has been implicated in number of cellular functions such as, downregulation of poly(A)-mediated 3' to 5' exonucleolytic decay by PNP (Feng et al., 2001), camphor resistance and chromosome condensation (Hu et al., 1996; Sand et al., 2003), and downregulation of λ Q-mediated transcription antitermination (Hanna and Liu, 1998). The mechanism(s) by which CspE performs these diverse functions are not defined. In addition, CspA homologues are involved in diverse phenomena such as, response to freezing conditions, stationary phase, osmotic stress, starvation, antibiotic biosynthesis, resistance to antimicrobial peptides, inhibition of replication, heat resistance of the spores, UV sensitivity etc. (Becker et al., 2000; Derzelle et al., 2003; Katzif et al., 2003; Leblanc et al., 2003; Mangoli et al., 2001; Martinez-Costa et al., 2003; Movahedi and Waites, 2002; Porankiewicz et al., 1998; Yamanaka and Inouye, 1997; Yamanaka et al., 2001).
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I cannot explain the prominence of these unusual 60, 70, 74 and 80kD proteins in some batches of oocytes and not in others. One possibility is that they are modified forms of bona fide hsp70 (for example the 70kD proteins might be phosphorylated). This seems unlikely, however, since no intermediates or unmodified hsp70 were ever seen. So the most probable explanation is that they are entirely different proteins. Their expression could be due to a polymorphism in some aspect of the control of the heat shock response, or, alternatively, to the imposition of some unidentified form of stress on the frog or the oocytes before the experiments were carried out. There is circumstantial evidence that the latter possibility is nearer the truth, since in one experiment where oocytes from the same frog were used on successive days, those used one day after ovariectomy gave the normal response, whereas those used after two days gave the abnormal response (data not shown).
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Protein inclusions are a predominant molecular pathology found in numerous neurodegenerative diseases, including amyotrophic lateral sclerosis and Huntington ’ s disease. Protein inclusions form in discrete areas of the brain characteristic to the type of neurodegenerative disease, and coincide with the death of neurons in that region (e.g. spinal cord motor neurons in amyotrophic lateral sclerosis). This suggests that the process of protein misfolding leading to inclusion formation is neurotoxic, and that cell-autonomous and non-cell autonomous mechanisms that maintain protein homeostasis (proteostasis) can, at times, be insufficient to prevent protein inclusion formation in the central nervous system. The heat shock response is a pro-survival pathway induced under conditions of cellular stress that acts to maintain proteostasis through the up-regulation of heat shock proteins, a superfamily of molecular chaperones, other co-chaperones and mitotic regulators. The kinetics and magnitude of the heat shock response varies in a stress- and cell-type dependent manner. It remains to be determined if and/or how the heat shock response is activated in the different cell-types that comprise the central nervous system (e.g. neurons and astroglia) in response to protein misfolding events that precede cellular dysfunctions in neurodegenerative diseases. This is particularly relevant considering emerging evidence demonstrating the non-cell autonomous nature of amyotrophic lateral sclerosis and Huntington ’ s disease (and other neurodegenerative diseases) and the destructive role of astroglia in disease progression. This review highlights the complexity of heat shock response activation and addresses whether neurons and glia sense and respond to protein misfolding and aggregation associated with neurodegenerative diseases, in particular Huntington ’ s disease and amyotrophic lateral sclerosis, by inducing a pro-survival heat shock response.
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Survival of Halobacterium NRC-1 under heat stress In order to examine heat shock response in Halobacterium NRC-1, differential proteomic strategy was employed; first the conditions for heat shock response were optimized and growth of Halobacterium NRC-1 was tested at a wide range of temperatures from optimal (42°C) to lethal (56°C). The data presented in Fig. 2A, show that cells exhibited normal growth up to 49°C, albeit with slower growth rates as compared to the control (42°C). At higher temperatures (>50°C) growth was inhibited and cells appeared white from photobleaching. However, viability at these higher temperatures was largely maintained for several hours and growth resumed after shifting back to 42°C. To further assess the physiological significance of the sublethal but growth inhibitory temperature, we measured survival of Halobacterium NRC-1, after pretreat- ment of cells at sublethal temperature at 49°C for 1 h fol- lowed by shifting to a lethal 56°C for up to 6 hours and plating on CM + plates. A 2.5-fold increase in survival was
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Although the transcriptional activators of heat shock genes in both prokaryotes and eukaryotes are now being identified, the molecular mechanism which senses changes in temperature is presently unknown. Recent work suggests that a homeostatic mechanism involving the level of free HSPs in the cell provides a thermometer for detecting and reacting to temperature changes. Under normal growth conditions, HSPs may bind to HSF and repress its activity. These HSPs may include HSP70 and HSP90, binding of HSP90 to HSF having been recently demonstrated(Nadeau et a/., 1993).During heat shock competition with high levels of thermally damaged proteins for binding of HSPs may cause the dissociation of HSF-HSP complexes, causing either an increase in the DNA-binding affinity of the factor (Drosophila) or activation of the C-terminal domain of HSF (yeast). DNA-bound HSF may then direct increased HSP synthesis until levels are sufficiently high to result in the reassociation of HSPs with HSF and the re-establishment of the repressed state. Ensuring overproduction of HSPs will ensure a large free pool of these HSPs and may cause HSF to be inhibited in its action. Strains which synthesise low levels of HSPs might prematurely activate the heat shock response. In yeast, strains carrying deletions of two of the constitutively expressed HSP70 genes (SSAl and SSA2 ) express HSPs at high levels, even at 23°C (Craig and Jacobsen, 1984). However, it should be noted that HSP70 is essential for cell viability so reducing the levels of this protein may itself be stressful, causing activation of the heat shock response by a mechanism other than that described above. One of the early events of heat shock must be a dramatic drop in the pool of free HSPs. This is a feasible proposition given the increase in aberrant protein that will ensue, but it has only been reported for levels of free ubiquitin which decrease 75% (Rose and Warms, 1987). Recombinant Drosophila HSF produced in E.coli will bind to HSEs with high affinity in the absence of heat shock (Clos et a l, 1990). In contrast to this, the same HSF will not bind to HSEs if produced in Xenopus oocytes. This suggests that HSF may interact with one or more negative regulators found in eukaryotic cells, possibly eukaryotic HSPs. However, in this thesis (Chapter 3) it is demonstrated that the overproduction of HSP90 does not interfere with normal heat shock induction of HSP genes in S. cerevisiae.
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The cold shock response in E.coli is characterised by the increased synthesis of the cold shock proteins, the continued synthesis of the proteins involved in transcription and translation, and the downregulation of the heat shock proteins (Jones et al., 1987; Jones and Inouye, 1994). Downregulation of heat shock proteins has also been reported in B.subtilis (Graumann et al., 1996) and P.fragi (Berger et al., 1996). ID SDS-PAGE analysis of proteins from M.vaccae cold shocked to 6°C revealed that the majority of proteins continued to be synthesized. Along with the increased expression of a number of Csps and Caps, the downregulation of 2 proteins was observed by ID SDS-PAGE (Figure 5.4). Calculation of the molecular weights revealed proteins of 33.4 to 34.3kDa, and 36.7 to 38.1kDa. Moreover qualitative analysis indicated that a ~90kDa protein was downregulated on cold shock, indicating that it could be a heat shock protein. However, quantitative analysis revealed that the protein was not downregulated by 2-fold, the benchmark for changes in protein and gene expression. The downregulation of heat shock proteins and general stress proteins has been reported in B.subtilis and E.coli (Graumann et al., 1996). The -3 4 and -37kD a proteins, may be minor heat shock proteins of M.vaccae. Moreover, the downregulation of 7 proteins was noted on the 8h cold shock 2D SDS-PAGE autoradiograph (Figure 5.6). These findings indicate that M.vaccae also downregulates the synthesis of a number of proteins, including potentially some heat shock proteins, on cold shock. The heat shock and cold shock response have been reported to be antagonistic in E.coli and B.subtilis, with the expression of Hsps being repressed during cold shock and vice versa. The same situation may be true for M.vaccae.
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Previously, we found that Arabidopsis plants transformed with a construct containing the promoter of Oshsp17.3 from rice fused to the β‑glucuronidase gene (GUS), Oshsp17.3Pro::GUS (Oshsp17.3p), showed a GUS signal after heat shock (HS) or azetidine‑2‑carboxylic acid (AZC) treatment. HS and AZC trigger the heat shock response (HSR) and cytosolic protein response (CPR), respectively, in the cytosol by modulating specific heat shock factor (HSF) activity. Here we further identified that AtHSFA2 (At2g26150), AtHSFA7a (At3g51910), AtHSFB2a (At5g62020), and AtHSFB2b (At4g11660) are HS‑ and AZC‑inducible; AtHSFA4a (At4g18880) is AZC‑inducible; and AtHSFA5 (At4g13980) is less AZC‑ and HS‑ inducible. To investigate the roles of these 6 AtHSFs in the HSR or CPR, we crossed two independent Oshsp17.3p transgenic Arabidopsis plants with the AtHSF‑knockout mutants athsfa2 (SALK_008978), athsfa4a (GABI_181H12), athsfa5 (SALK_004385), athsfa7a (SALK_080138), athsfb2a (SALK_137766), and athsfb2b (SALK_047291), respectively. As compared with the wild type, loss‑of‑function mutation of AtHSFA2, AtHSFA4a, and AtHSFA7a decreased HS and AZC responsiveness, so these 3 AtHSFs are essential for the HSR and CPR. In addition, loss‑of‑function results indicated that AthsfB2b is involved in regulating the HSR in Arabidopsis. Furthermore, analysis of the relative GUS activity of two double knockout mutants, athsfA2/athsfA4a and athsfA2/athsfA7a, revealed that AtHSFA2, AtHSFA4a, and AtHSFA7a function differentially in the HSR and CPR. Transcription profiling in athsf mutants revealed positive or negative tran‑ scriptional regulation among the 6 AtHSFs in Arabidopsis plants under HS and AZC conditions. Tunicamycin treatment demonstrated that these 6 AtHSFs are not involved in the unfolded protein response.
Proteasome inhibitors such as bortezomib are highly active in multiple myeloma by affecting signaling cascades and leading to a toxic buildup of misfolded proteins. Bortezomib-treated cells activate the cytoprotective heat shock response (HSR), including upregulation of heat shock proteins (HSPs). Here we inhibited the bortezomib-induced HSR by silencing its master regulator, Heat Shock Factor 1 (HSF1). HSF1 silencing led to bortezomib sensitization. In contrast, silencing of individual and combination HSPs, except HSP40β, did not result in significant bortezomib sensitization. However, HSP40β did not entirely account for increased bortezomib sensitivity upon HSF1 silencing. To determine the mechanism of HSF1 activation, we assessed phosphorylation and observed bortezomib-inducible phosphorylation in cell lines and patient samples. We determined that this bortezomib-inducible event is phosphorylation at serine 326. Prior clinical use of HSP inhibitors in combination with bortezomib has been disappointing in multiple myeloma therapy. Our results provide a rationale for targeting HSF1 activation in combination with bortezomib to enhance multiple myeloma treatment efficacy.
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The above results indicated that significant genetic variability in thermotolerance of wheat cultivars could be seen only upon exposure to an optimum induction temperature prior to severe temperature stress. Induced seedlings of temperature tolerant cultivars showed significantly higher recovery response compared to the susceptible cultivars, suggesting that this technique can be adapted to screen wheat germplasm and segregating populations. Further, the differential thermotolerance of wheat cultivars was found to be related with accumulation and expression of both HMW and LMW HSPs. Unlike the HMW HSPs which showed constitutive expression even under non stress conditions, LMW HSPs were found to be induced only under high temperature stress. The results suggest that LMW HSPs can be used as biological markers for identifying high temperature tolerant cultivars under severe heat stress conditions.
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Estrogen has pleiotropic actions, among which are its anti-apoptotic, anti-inflammatory, and vasodilatory effects. Recently, an interaction between 17 β -estradiol (E2) and the transcription factor nuclear factor κ B (NF κ B) has been identified. NF κ B has a central role in the control of genes involved in inflammation, proliferation, and apoptosis. Prolonged activation of NF κ B is as- sociated with numerous inflammatory pathological conditions. An important facet of E2 is its ability to modulate activity of NF κ B via both genomic and nongenomic actions. E2 can activate NF κ B rapidly via nongenomic pathways, increase cellular resistance to injury, and induce expression of the protective class of proteins, heat shock proteins (HSPs). HSPs can bind to many of the pro-apoptotic and pro-inflammatory targets of NF κ B and, thus, indirectly inhibit many of its deleterious effects. In addition, HSPs can block NF κ B activation and binding directly. Similarly, genomic E2 signaling can inhibit NF κ B, but does so through alternative mechanisms. This review focuses on the molecular mechanisms of cross-talk between E2, NF κ B, and HSPs, and the biological relevance of this cross-talk.
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We analyzed effect of RIM15 overexpression in the hsf1-ba1 cells on the heat shock response of HSP12, HSP26, and SSA3 (Fig. 2A). In logarithmically growing hsf1-ba1 cells, heat-in- duced accumulation of the HSP12, HSP26, and SSA3 mRNAs was reduced by ca. 60, 40, and 15% compared to HSF1 wild- type controls, respectively, and the levels were not affected by multiple copies of RIM15. We then examined the growth of hsf1-ba1 cells harboring multiple copies of MSN2, MSN4, and GIS1 and found that they are unable to rescue the growth defect (Fig. 2B). Wild-type HSF1 cells containing either msn2 ⌬ msn4 ⌬ double null mutations or a gis1 ⌬ null mutation were able to grow at 38°C (Fig. 2C). When the hsf1-ba1 mutation was combined with the null mutations of these genes, the combinations did not exacerbate the heat sensitivity of hsf1- ba1 cells. Furthermore, RIM15 rescued the temperature sen- sitivity of hsf1-ba1 msn2 ⌬ msn4 ⌬ and hsf1-ba1 gis1 ⌬ cells. Taken together, we conclude that Msn2, Msn4, and Gis1 are dispensable for suppression by Rim15 and suggest that Rim15 regulates the functions of different sets of proteins in response to distinct stressors, heat and nutrient limitation.
HSP70 (70 kDa heat shock protein) is a commonly used marker of the CSR. An increase in expression of genes encoding HSP70 isoforms may indicate an increase in intracellular macromolecular damage (Feder and Hofmann, 1999), although care must be taken with such inferences in isolation (Morris et al., 2013). Results of this study confirm that the hsp70 (form 1) gene is responsive to acute hydrostatic pressure stress. The relative fold change of the hsp70 (form 1) gene shown in this study is lower, however, than observed in previous research in response to a large temperature shock (Cottin et al., 2010; Ravaux et al., 2012). The hsp70 (form 2) gene showed no changes in expression at any time points, thus in response to pressure stress alone, the gene remains constitutively expressed. The hsp70 (form 1) gene showed significantly higher expression in the abdomen than in the head. The abdomen was also shown to exhibit higher expression in post exposure samples in comparison to unstressed baseline measurements. Muscle-rich abdominal tissue may therefore exhibit a particularly high degree of intracellular macromolecular damage. Behavioural analysis showed an increase in violent muscle contractions (tail flicking) immediately upon exposure to elevated pressure. This type of muscle contraction is likely to cause muscle cell damage which would trigger the expression of heat shock proteins. In the hierarchy of responses then, a behavioural response, such as tail flicking, is followed by the heat shock response. The expression of HSP70 isoforms has been well documented as being a vital component of the CSR (Feder and Hofmann, 1999; Sørensen and Loeschcke, 2007; Benarroch, 2011). HSP70 expression occurs not only as a response to increasing macromolecular damage during stress exposures, but predominantly post exposure as a recovery mechanism during which macromolecular damage might still be prevalent within the cell (DiDomenico et al., 1982; Tomanek and Somero, 2000). Although difficult to quantify, the heat shock response and CSR come with clear costs associated with the up-regulation of genes and production of proteins (Sørensen et al., 2003). These costs will have knock-on effects on energy budgets and distribution, and therefore metabolism. The data presented here suggest that these costs are occurring during an acute exposure to pressure, but also, and to a greater magnitude, during recovery from exposure.
The fourth shock, a “Speculative Demand” shock, is an unexpected change in the demand for natural gas due to inventories. This shock reflects the expected shortfall of future natural gas supply relative to future natural gas demand (Kilian and Murphy, 2013). Column 5 of Table (1) shows that these shocks are assumed to lead to higher natural gas production, lower demand for natural gas for use in the production of goods and services, and higher prices and inventories. As before, prices are assumed to rise because of greater demand, and increased supply follows the higher prices. The demand for natural gas for goods and services is assumed to fall because of the higher prices, which are not expected to be as short-lived as those from an “Energy Demand” shock. The final shock, an “Other” shock represents the impact of other demand or non-demand factors on the natural gas price. There are no assumptions made about the response of model variables to this shock.
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The role of exchange rate in the design of monetary policy rules is another way to study the relationship of exchange rate and monetary policy. The results from the empirical studies are quite controversial. By estimating the Taylor rule type policy rules, Mohanty & Klau (2004) show that in most of the emerging countries, the monetary policy responds to exchange rate strongly. Frömmel & Schobert (2006) estimate the simple Taylor type policy rules for six Central and Eastern European countries. They find that exchange rate plays an important role in the monetary policy during the fixed exchange rate regimes periods. However, the influence disappears after these countries have moved to the flexible regimes. On the other hand, Osawa (2006) in his study on three Asian inflation targeting countries finds no evidence of monetary policy response to the exchange rate. He argues that the reason for this difference result is because the existing studies do not consider structural breaks of data in their estimations. Besides, including the crisis period in the sample of estimation may overestimate the response of monetary policy to exchange rate.
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The resulting graph is shown in Figure 3. A contractionary monetary policy shock leads to unfavourable financial conditions (a decline in FCI below zero) one quarter after the shock. This deterioration in financial conditions persists until the end of the second quarter. Financial conditions improve (FCI rises above zero) for nearly three quarters before declining. We track the robustness of the FCI response to contractionary monetary policy by obtaining IRFs from an alternative ordering strategy. In this case, STR is ordered second but last. This identification is motivated by previous studies (e.g., Christiano, Eichenbaum, and Evans, 1999; Uhlig, 2005), which argue that monetary policy has an immediate effect only on the policy rate (short-term rate). Because monetary policy has a delayed effect on the economy (Christiano, Eichenbaum, and Evans, 1999), we order FCI first. Stated formally, our ordering strategy is
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20. Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, Sevransky JE, Sprung CL, Douglas IS, Jaeschke R, Osborn TM, Nunnally ME, Townsend SR, Reinhart K, Kleinpell RM, Angus DC, Deutschman CS, Machado FR, Rubenfeld GD, Webb SA, Beale RJ, Vincent JL, Moreno R, Surviving Sepsis Campaign Guidelines Committee including the Pediatric Subgroup: Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med 2013, 41:580 ? 637. 21. McLuckie A: Shock - an overview. In Oh ? s Intensive Care Manual. 6th edition.
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surface. h is data is chosen as it displays the clearest distinction between peaks. Only strains within elastically compressed portions of the sample are considered, permitting comparison with the purely elastically response observed in di f raction. A summation of these strain pro i les over a 1 ns window, assuming that the backlighter has spectrally l at response over the (300 eV) range of interest, and no signi i cant energy dependence to sample re l ectivity, allows us to create a simulated di f raction signal, as shown in 3b. h is simulation clearly shows the for- mation of both HSE, LSE and tensile responses. Best i t to the experimental data is found for a lag time for phase transition of 1.2 ns. It should be noted that due the assumptions on spectral response discussed above, and the stochastic nature of the lag time between shots, this value should be taken as being representative. However, this signi i cant kinetic lag is consistent with considerable predicted enthalpy barrier (of around 500 meV) between the cd and β-Sn phases 31 .
Aside from answering some of the experimental criti- cisms raised, the model additionally addresses a long-held conceptual problem with avoidance models of phobia. Whereas human phobias are viewed as maladaptive, interfer- ing with healthy daily functioning, traditional active avoid- ance responding is an adaptive response. Animals trained to lever press to prevent the shock are behaving in an adaptive way. In this very basic conceptual way, avoidance models are doomed to fail in representing phobias. Animals trained under the DCP paradigm are potentially prevented from an adaptive behavior (food reinforcement) as a result of their conditioned fear. In human phobias, it is the fear-induced failure to respond, (eg, leave the house for work, fly to visit family, cross a bridge to go on vacation) that interferes with the pursuit of reinforcement in aspects of one’s life. As noted previously, Costello 6 argued that a phobia model
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Last, co-integrated test is conducted to find whether the non- stationary variables co-integrated or not. The integration concept was stated by Engle and Granger (1987) as the linear combination from two or more non stationary variables would produce stationer variable. It is known as co-integrated equation and can be interpreted as long run equilibrium connection among variables. The co-integrated test using Johansen approach compares the trace statistic and used critical value (which is 5%). If trace statistic > critical value, the variable is co-integrated. VECM can be preceded after the number of co-integrated equation is known. Estimating innovation accounting IRF and FEVD are conducted after doing the pre-test estimating. IRF is a model which is used to determine the response of an endogenous variable to a certain fluctuation variable (Amisano and Carlo, 1997). IRF is also used to see the effect of a certain fluctuation variable to another variable and how long (period) the effect lasts. It is due to the shock
The original DSGE models are actually the extension of real business cycle (RBC) models. Kydland and Prescott (1982) laid the foundation of DSGE modeling in the spirit of RBC theory. Real Business Cycle theory, assuming price ‡exibility and rationality of optimizing agents facing some constraints, investigates quarterly ‡uctuations when economy is hit by a real shock (the most common one being a technology shock). The earlier RBC models were criticized because economic policies had no role to play in these models. Fur- thermore these models failed to replicate some of the empirical regularities such as liquidity e¤ects, co-movement of productivity and employment or the co-movement of real wages and output (Kremer et al., 2006). However, over time, there has been extensive work done that has helped in making these models theoretically parsimonious and empirically sound.
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