9 to + 1.0 °C) ( Clark et check details al., 2007). This slow rate of regeneration means that if a large length of arm was lost it could take approximately 3 years to fully re-grow. In addition to its slow regeneration rate O. victoriae has an unusual and, as yet, unexplained delay in the onset of regeneration ( Clark et al., 2007). This delay in the onset of regeneration of ~ 5 months is very unusual, but a similar lag phase has also been demonstrated for another Antarctic brittle star ( Clark and Souster, in press). Hence these Antarctic species present as novel candidates for the investigation of regeneration processes, in

particular, the use of molecular analyses to provide fine-scale detail of the signalling pathways invoked and the factors determining the cold environment lag phase. In terms of publicly available sequence data for O. victoriae, recent studies

into the phylogeography and potential cryptic speciation of O. victoriae have provided DNA sequences for three mitochondrial genes ( Hunter and Halanych, 2010), represented multiple times within the Talazoparib solubility dmso 68 DNA sequence entries in NCBI Genbank for this species. With regard to sequences for the Ophiuroidea, there were only 2,805 sequences for Ophiuroidea in NCBI GenBank representing less than 30 different genes (at 23/05/2012), the vast majority, again representing mitochondrial genes. Clearly, such a paucity of DNA sequence information, particularly nuclear sequence,

limits the study of gene expression in this organism and also ophiuroidea in general. In this first study of the transcriptome of O. victoriae we used 454 pyrosequencing to increase the available cDNA sequence information and also identify putative candidate genes for use in future investigations of delayed regeneration in this circum-Antarctic locally dominant scavenger. O. victoriae used in this study were collected by SCUBA Methocarbamol divers from near the British Antarctic Survey research station at Rothera Point, Adelaide Island, West Antarctic Peninsula (67° 34.5´ S, 68° 07.0´ W) in the austral summer of 2005/2006. The material used in this study was collected as described in Clark et al. (2007). Briefly, following collection the animals were kept in flow through aquaria and one arm of each brittle star was amputated approximately 10 segments from the central disc. Regenerating animals were sampled on a monthly basis for 12 months by cutting the regenerating arm before the wound site/regenerating appendage. Additional samples were taken from fifteen animals on a weekly basis for four weeks after amputation. Each sample was placed in RNAlater (Applied Biosystems) and, after an overnight incubation at 4 °C, was placed at − 80 °C until used. RNA was extracted from selected monthly and weekly samples that represented the full range of the regenerative process in O.

In a post-mortem study of non-demented elderly (>65 years of age) obese individuals, Mrak found evidence of higher levels of hippocampal amyloid-beta peptides, amyloid prescursor protein (APP; APP processing generates amyloid-beta), and tau, compared with non-obese individuals (Mrak, 2009). Moreover, plasma levels of amyloid peptides are elevated in obese individuals and correlate with increased body fat (Balakrishnan et al., 2005 and Lee et al., 2009). Numerous experimental studies have examined markers of amyloid and

tau pathology in a variety of diet-induced obesity paradigms. In rats and wild-type mice, some but not all studies report elevations in APP, amyloid-beta, and tau phosphorylation (Thirumangalakudi et al., 2008, Jeon et al., 2012 and Puig et al., 2012). Furthermore, with the exception of a few studies (Moroz et al., 2008 and Studzinski et al., 2009), diet-induced obesity increases amyloid and tau pathology in transgenic KU-60019 mouse mouse models of AD, and exacerbates cognitive deficits (Levin-Allerhand et al., 2002, Thirumangalakudi et al., 2008, Julien et al., 2010, Maesako

et al., 2012a, Maesako et al., 2012b and Leboucher et al., 2013). Thus, while future studies are necessary, these clinical and experimental studies raise the possibility that obesity may amplify the risk of developing AD by modulating cerebral amyloid and/or tau pathology. While there is ample evidence that a relationship exists between obesity buy BEZ235 and brain health (function and structure), it is important to acknowledge that there still remains a question of causality. Indeed, the relationship between obesity and brain health may not be unidirectional. Obesity is associated with many pathophysiological changes that triclocarban have the potential to negatively impact the brain, including inflammation,

which in turn may be a cause and a consequence of obesity. It is also possible that reduced cognitive function, in particular executive functioning, could predispose individuals to obesity. Indeed, executive dysfunction is associated with obesity-related behaviours, such as increased food intake, dis-inhibited eating, and less physical activity (Reinert et al., 2013). This may prove to be more relevant for obesity in childhood and adolescence, a period characterized by relative immaturity of executive cognitive domains coupled with the relative maturity of reward processing (Reinert et al., 2013). It is now well accepted that obesity is associated with chronic low-grade systemic inflammation (Gregor and Hotamisligil, 2011 and Spencer, 2013). This pro-inflammatory profile appears to be both a cause and a consequence of obesity. Dietary factors such as fatty acids lead to stimulation of the free fatty acid and lipopolysaccharide (LPS) receptor, toll like receptor 4 (TLR4), on immune cells, and initiation of an inflammatory cascade (Shu et al., 2012).

This hypothesis has first

been proposed after observing that fetal mesencephalic cells grafted into the brain of PD patients 11–22 years earlier contained classical LB inclusions [54], [55] and [56]. This suggested that α-SYN could be transmitted from the affected host neurons to healthy transplanted neurons, where it recruited normal α-SYN to misfold. Other findings derived from tissue culture and transgenic animals demonstrated cell-to-cell transfer of α-SYN inducing pathological changes and cell death in the recipient [48] and [57]. Recently, Luk and co-workers demonstrated the widespread propagation of pathological α-SYN aggregates throughout anatomically connected regions of the CNS following brain injection of synthetic α-SYN fibrils into α-SYN transgenic or wild type ABT-888 in vitro nontransgenic mice [58]. They suggested a mechanistic link between α-SYN transmission and PD hallmarks as α- SYN

pathology resulted in the progressive loss of DA nigral neurons and a consecutive striatal dopamine depletion of sufficient magnitude to induce detectable motor deficits [59]. Accumulating evidence suggests that PD may indeed be a prion-like disorder and AZD0530 chemical structure that α-SYN behaves like the protein prion (PrP), which underlies disorders such as Creutzfeld–Jakob disease or bovine spongiform encephalopathy. Both proteins share many similarities: (i) they can undergo an aberrant conformational change from a

native α-helix to a β-sheet conformation which C59 molecular weight promotes their self-aggregation, (ii) their protein aggregates can act as “seeds” to recruit and promote the misfolding of wild-type proteins, (iii) their misfolded protein form is recognized to be toxic and induce neurodegeneration [60]. The transmission of LB pathology following a prion-like mechanism through anatomically linked neuronal network might explain the sequential and predictable topographical progression of PD observed by Braak and co-workers. The mechanisms by which intracellular protein aggregates can reach neighboring cells in the CNS are not clear, and may involve neuronal transmission by exocytosis and endocytosis as well as spreading throughout the nervous system via anterograde and retrograde transport. Among the many hypotheses surrounding PD etiology, environmental toxin exposure has been the most studied. The awareness of a relationship with PD was raised during the 1980s, when young individuals developed PD signs after an intake of designer drugs contaminated with 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP), a substance similar to the herbicide paraquat [61]. MPTP was then demonstrated to selectively damage nigral neurons by blocking mitochondrial complex I [62]. Since then, many pesticides (i.e., rotenone), herbicides (i.e., paraquat) or insecticides were positively associated to PD risk [63].

9% saline (w/v). After centrifugation at 14,000×g for 10 min at 4 °C, the supernatant was used for the assays. The assays were performed by mixing 10 μL of a sample containing 0.5 midgut equivalents

with 30 μL of 0.1 M HEPES buffer containing 20 mM NaCl and 20 μL of 4.5% starch. After incubation for 1 h, the reaction was stopped in boiling water (2 min). Ethanol (1140 μL) was added to each tube, and the mixture was incubated at −20 °C for 1 h. The precipitated material was separated from the soluble material by centrifugation (14,000×g for 10 min), and the supernatant containing the soluble material was transferred to other tubes. All of the materials were completely dried in an evaporator centrifuge at 76 °C, and the selleck kinase inhibitor reducing carbohydrates were evaluated using the DNS method, as described in Section 2.2.1, after solubilization with 300 μL of distilled water (sonication was used when necessary). The processivity was calculated

from the ratio between the absorbance measured for the low-molecular-mass carbohydrates (which are soluble in see more ethanol) and that measured for the higher molecular-mass carbohydrates (which are insoluble in ethanol). A plot of reducing sugars versus time was constructed using data obtained by incubating starch with the total midgut homogenate containing the intestinal amylase. The incubations were performed by mixing 100 μL of a 1.5% (w/v) aqueous starch solution with 150 μL of 0.1 M HEPES/NaOH buffer (pH 8.5) and 50 μL of a sample containing the equivalent of 1 midgut in a centrifuge tube. The NaCl concentration in the final mixture was 50 mM. The assays were performed by incubating the sample with starch (or glycogen) for 10, 20, 30, 40 and 60 min at 30 °C. The reducing carbohydrates released from the

substrate were quantified using the dinitrosalicylic acid method as described (Section 2.2.1). The blanks were prepared by substituting the sample with distilled water. The activity of the α-amylases extracted from the mycelia of the fungi BCKDHA collected from the larval rearing pots was measured at pH 6.5 and 8.5. This extract was prepared by homogenization of 4 mg of mycelium in 200 μL of aqueous 1% Triton-X100 followed by sonication for 1 min. The homogenate was centrifuged for 10 min at 4 °C. The supernatant was collected and used in the assays. The assays were performed by mixing 100 μL of 1.5% (w/v) starch (Sigma n° S9765) (dissolved in water) with 150 μL of 0.1 M buffer (MES/NaOH, pH 6.5, or HEPES/NaOH, pH 8.5) containing 0.1 M NaCl in a micro centrifuge tube. The reaction was started by the addition of 50 μL of the sample. This mixture was incubated at 30 °C for 1 h. The reducing carbohydrates released from the substrate by the action of the amylase were quantified using the DNS method, as described in Section 2.2.1. The supernatant of the extract prepared from 10 larval midguts in 500 μL of a 0.9% (w/v) saline solution containing 1% Triton-X100 was also assayed using a similar protocol.

The toxicity of pentavalent inorganic arsenic occurs via its reduction to trivalent arsenic (Ferrario et al., 2008). Pentavalent arsenic resembles to inorganic phosphate and substitutes for phosphate in glycolytic and cellular respiration pathways. Uncoupling

of oxidative phosphorylation occurs because of the loss of the high-energy ATP phosphate bonds due to the preferential formation Alpelisib price of ADP-arsenate. As mentioned above, methylated organic arsenicals are usually viewed as being less toxic than the inorganics (Mandal and Suzuki, 2002). This is substantiated by the majority of studies supposing that the acute toxicity of inorganic arsenic was greater than organic arsenic. Thus, the methylation of inorganic arsenic was considered to be a detoxication process. However, CAL-101 chemical structure the results presented in the past decade show that human

cells are more sensitive to the cytotoxic effects of MMAIII than arsenite (Petrick et al., 2000 and Styblo et al., 2001) and that DMAIII is at least as cytotoxic as arsenite in several human cell types (Styblo et al., 2000). Thus the process of methylation of arsenic does not have to be a detoxication mechanism. Further detailed studies dealing with the possible toxic effects of organic arsenic are awaited. Several organic arsenicals are found to accumulate in fish and shellfish. These include arsenobetaine and arsenocholine, both referred to as “fish arsenic” that have been found to be essentially nontoxic (Hindmarsh, 2000). Many studies confirmed the generation of various types of ROS during arsenic metabolism in cells (reviewed in Valko et al., 2005). Oxidative stress has been linked with the development of arsenic related diseases including Methisazone cancers. In addition to ROS, reactive nitrogen species (RNS) are also thought to be directly involved in oxidative damage to lipids, proteins and DNA in cells exposed to arsenic. Many recent studies have provided experimental evidence that arsenic-induced generation of free radicals can cause cell damage and death through activation of oxidative sensitive signalling pathways (Roy et al., 2009). Arsenic-mediates formation of the superoxide anion radical (O2−

), singlet oxygen (1O2), the peroxyl radical (ROO ), nitric oxide (NO ), hydrogen peroxide (H2O2), dimethylarsinic peroxyl radicals ([(CH3)2AsOO ]) and also the dimethylarsinic radical [(CH3)2As ] (Yamanaka and Okada, 1994). The exact mechanism responsible for the generation of all these reactive species is not yet clear, but some studies proposed the formation of intermediary arsine species. Recent studies on the arsenite toxicity in the brain reported that some of its effects have been connected to the generation of the damaging hydroxyl radical (Mishra and Flora, 2008). The time-evolution of the formation of the hydroxyl radical in the striatum of both female and male rats who underwent a direct infusion of different concentrations of arsenite was investigated.

However, SANS has a clear advantage over SAXS when applied to RNP complexes. In SANS, hydrogen

(or deuterons) nuclei are responsible for the scattering of the neutrons, as opposed to electrons that scatter X-ray radiation in SAXS. The biological particle under investigation is usually dissolved in aqueous solvent; this has its own scattering density in dependence of the percentage of D2O contained in the H2O-based buffer. Similarly, proteins have on average a different scattering density from nucleic acids and 2H-labelled RNAs or proteins scatter at higher density than their 1H-counterparts (Fig. 5). Thus, if the SANS scattering curve is recorded for an RNP complex in 42% D2O buffer, the average scattering Selleckchem Bafetinib density of the proteins is matched by the solvent, and therefore subtracted with the measurement of the reference buffer, while the scattering density of the RNA component of the complex dominates the curve. In this experiment it is possible to gain selective information on the shape of the RNA molecule(s) in the context of the complete RNP complex. Similarly if the SANS scattering curve is recorded in 70% D2O,

the average scattering density of the RNA is matched by the solvent while the proteins dominate the (negative) scattering density. This technique, called “contrast matching”, allows investigating the shape of single components of a complex in the context of the complete assembled particle [56]. The protein and RNA components can be further separated from each other using selective 2H-labelling of one protein www.selleckchem.com/products/ch5424802.html or RNA species. In multi-component complexes a number of samples can be prepared with different labeling schemes, for each of which SANS data report on the shape of single components in the complex or on the relative position of two components. In early years, the SANS

contrast matching approach was used to study the ribosome particle and to generate a model of the complex, including the position of the tRNA [57], [58] and [59]; this model has been proven largely correct on the basis of crystal structures obtained years later. Others [60] Aurora Kinase and we find it very useful to complement NMR data with SANS data in the calculation of the structure of RNP complexes. The SANS data can be used to derive distances between multiple domains or molecules in the complex (Fig. 5), which can then be imposed as restraints in structure calculation. In alternative, a pool of computer-generated structures can be selected on the basis of their agreement with several SANS curves measured with varied contrast for different 2H-labelled samples. In Fig. 6 we propose a possible workflow to determine the structure of high-molecular-weight RNP complexes by the combined use of NMR data and distance or shape information generated by complementary structure biology techniques.

5 μl of SuperScript III RT/Platinum Taq Mix (SuperScript III Platinum SYBR Green One-Step Quantitative RT-PCR

Kit, Invitrogen, Carlsbad, CA, USA). The amplification conditions consisted of reverse transcription at 50 °C for 30 min, 95 °C for 5 min for Taq inhibitor inactivation, followed by 45 cycles of 95 °C for 10 s, 54 °C for 30 s and 72 °C for 30 s. Melting curve analysis was used to confirm the specificity of the amplicons. Positive (extracted RNA from control strains of DENV1-4) and negative controls were included in each PCR run and the run only accepted if all controls gave appropriate results. The serotype of dengue virus was sought from the acute plasma specimen in all patients with serologically confirmed dengue infection using a nested RT-PCR assay,12 modified by the Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok, Thailand.19 The Panbio Dengue Early ELISA (cat. no. E-DEN01P, lot. no. 08140; Panbio, Brisbane, Queensland, Ribociclib cell line Australia) was used to detect NS-1 antigen

in the acute plasma specimens only, following the manufacturer’s instructions. A positive specimen was defined as having >11 Panbio units; <9 Panbio units was defined as negative; and 9–11 Panbio units was equivocal and the specimen retested to confirm the result. Panbio units were calculated by first determining the assay cut-off value: the lot specific RGFP966 cell line calibration factor was multiplied by the average absorbance result of the kit calibrator of (internal control, run in triplicate). Subsequently, an index value was calculated for each patient specimen by dividing the specimen absorbance result by the cut-off value. Finally the Panbio units were determined by multiplying the index value by 10. We used the dengue IgM (Panbio: cat. no. E-DEN01 M, lot. no. 08316) and IgG (Panbio: cat. no. E-DEN02G, lot. no. 09080) antibody capture ELISAs to detect IgM and IgG antibodies in both the acute and convalescent plasma specimens, following

the manufacturer’s instructions. A positive specimen was defined as having >11 Panbio units for IgM and >22 for IgG antibodies; <9 and <18 Panbio units was defined as negative for IgM and IgG antibodies, respectively; 9–11 Panbio units was equivocal for IgM and 18–22 Panbio units was equivocal for IgG antibodies and the specimen retested to confirm the result. Panbio units were calculated as described above. Dengue infection was classified using the above described commercial serological assays as ‘confirmed’ acute dengue infection based on WHO dengue diagnostic criteria as defined in Table 1. ‘Confirmed’ acute dengue cases were those that demonstrated an IgM or IgG antibody sero-conversion based on paired serum collections.16 Patients with static IgM positivity (i.e., positive in both acute and convalescent specimens, but with no rise in Panbio units) were considered to have evidence of recent dengue infection. All statistical analyses were performed by using STATA/SE for Macintosh, version 10.

05) and 100 μg (p < 0.001) presenting greater activity than the PBS control. The amount of 100 μg Batroxase completely dissolved the clot ( Fig. 2B). The fibrinolysis assay consisted of incubation of Batroxase in a gel containing fibrin. Batroxase was able to induce fibrin hydrolysis at all concentrations tested, and there was no significant difference from the hydrolysis induced by

plasmin. This activity was concentration-dependent up to 8 μg of Batroxase; higher concentrations did not induce additional fibrin hydrolysis (Fig. 2C). The fibrinogen digestion by Batroxase was monitored by SDS-PAGE under reducing conditions. The concentrations used for the experiment induced substrate digestion (Fig. 3A). From 0.5 μg of the proteinase, hydrolysis of the α and β chain of fibrinogen, but not the γ chain, was observed (Fig. 3A). GSKJ4 Bioactive Compound Library cost After the critical concentration of Batroxase was determined, digestions performed for different periods of incubation showed that fibrinogen was digested at all time periods tested, and 30 min of incubation was determined as optimal for this activity (Fig. 3B, lane 7). The optimal temperature and pH for fibrinogen proteolysis by Batroxase were 37 °C and pH 5.0 (data not shown). Ion-chelating agents such

as EDTA and EGTA, as well as the reducing agent β-mercaptoethanol, were able to completely inhibit the substrate digestion (data not shown). These results confirm that Batroxase is able to digest the fibrinogen molecule as a metalloproteinase. At amounts of 8 μg and higher, Batroxase was able to induce the partial digestion of the α 1 and α 2 chains of type IV collagen, and the substrate was completely degraded

with 10 μg of Batroxase (Fig. 4A, lane 6 and 7, respectively). Batroxase was able to cleave fibronectin subunits A and B after 60 min of incubation, presenting a complete substrate digestion at 240 min (Fig. 4B, lane 3–6) and was not able to digest laminin, even with long periods of incubation (data not shown). As illustrated in Fig. 4C, Palmatine Batroxase was able to digest the fibrin, preferentially the β chain. After 15 min of incubation, a decrease of the β chain could be noted, with complete hydrolysis occurring after 60 min. The α and γ chains of fibrin remained intact, but the γ-γ dimer was gradually digested (Fig. 4C, lane 5). Fig. 4D shows the SDS-PAGE analysis of the proteolytic fragmentation of plasminogen by Batroxase. The band with a molecular mass of 83 kDa is represents plasminogen (Fig. 4D, lane 1). The incubation of plasminogen with urokinase generated proteolytic fragments with an apparent molecular mass of 66 kDa, which corresponded to the heavy chain of plasmin (compared with the plasmin control band: Fig. 4D, lanes 2 and 3). This pattern was not observed when the substrate was incubated with Batroxase, which generated fragments ranging from 20 to 38 kDa, independent of the time of incubation (Fig. 4D, lanes 5–8).

First, as indicated, other than in a crude fashion, active ingredients were generally not identified. At best, hours of treatment dedicated to a listed deficit (gait, attention, etc) were captured GSK458 molecular weight and, even where the active ingredient was identified and isolated, it was not quantified other than indirectly, using the assumption that hours dedicated to a particular treatment correspond very closely to the units of the ingredient delivered.82 If we consider that the essential

or other ingredients may include goal setting, providing feedback, and transferring of factual knowledge, it should be clear that the claim that time corresponds with quantity of ingredients is a tenuous one. Once we have solved the problem of how to fruitfully classify rehabilitation treatments, Galunisertib purchase the next predicament will be how to operationalize the quantity of those treatments and to develop systems of measurement that, in practice, maybe feasible only for the most well-funded research projects. The efforts described in the preceding sections are far from offering an integrated, complete, and useful taxonomy of rehabilitation interventions; however, they may contribute building

blocks to such an effort. Whether a rehabilitation taxonomy is created predominantly deductively or inductively, it needs to specify interventions (treatments, techniques, technologies, practices, approaches) because these are the links between patient diagnoses (in medical terminology) or client problems and goals (in

behavioral terminology) and patient/client outcomes.57 and 102 In contrast Phosphatidylethanolamine N-methyltransferase with the “bottom-up,” inductive approach to rehabilitation treatment classifications used by PBE and similar studies, a “top-down,” deductive approach would start with a well-developed and validated treatment theory (or a set of midrange treatment theories18) and might use expert opinion to identify those treatments that fit in this theory, that is, interventions that offer or include the active ingredient(s) the theory specifies as a necessary and potentially sufficient treatment for the deficits or problems experienced by categories of patients.10, 18 and 25 Although no systematic approach to such a theory-driven taxonomy has been published, we have put forth what we consider to be the essential elements of treatment theories: the outcomes that may be expected to be affected by treatments that are based on a specific theory, the essential and other ingredients that are contained in those treatments, and the mechanism(s) of action that connect ingredients to outcomes.13 and 61 Characteristics of the patients/clients involved may be moderators of the causal pathway leading from treatment to outcome.25 The series of articles in the current supplement specifies further characteristics of a theory-driven system for classifying rehabilitation interventions.

33 and 34 Moreover, these groups may have different expectations concerning RTW, which could lead to a higher dropout rate from rehabilitative interventions.35 In this study, they represented 50% of patients. Although, studies about the role of the mother language are scarce, 1 study36 reported that the mother language, among others, was a predictor for non-RTW. Additionally, a non-Swiss mother language is related to a low health literacy, which may cause a substantial burden to society and the injured person.37 Understanding the role of language in the development of chronic WADs may be crucial for developing effective work disability

prevention programs for patients with WADs. Predicting RTW in patients with chronic pain is difficult. Lifting tests explain 10% to 20% of the variance in RTW in patients with musculoskeletal disorders.38 Some authors reported an explained variance up to 27%,39 while others suggested that adding FCE tests buy Entinostat to self-reported data would increase the explained variance from 9% to 16%.40 However, others reported a 10% explained variance, questioning the predictive value of FCE tests for RTW in patients with chronic musculoskeletal pain.41 and 42 These differences may be explained by differences in study design (eg, cross-sectional vs prospective) or sample size ranging from 5 to 20 events per prognostic association tested. Follow-up times may range from 1 to 12 months, statistical

models may use uni- or multivariate analysis that corrects for confounders.8 Moreover, buy Dabrafenib results between studies may this website differ based on the definition of RTW used, which can be measured by self-report or insurance data. Also social security systems between different countries may lead to different results. This study shows that the strength of the correlation between WC and FCE tests is related to the time point after the whiplash injury. Most of the patients in this study reached full WC within the 12-month follow-up period. This is in contrast to other studies1 and 2 showing that a substantial proportion of patients with WADs (40%–60%) still have varying levels of pain and self-reported disability after 1 year.

We hypothesized that WC over 12 months may not be indicative of perceived disability. In a post hoc analysis, we evaluated the correlation between WC and the available NDI scores at 3 and 12 months (50% of the study sample). The correlations were low (r<0.3; WC accounts for 9% of the explained variance of NDI), indicating that disability and WC are related but distinct constructs. While it may be methodologically correct to study FCE tests separately, in clinical work, FCE tests are used in conjunction with medical records, patient interviews, musculoskeletal evaluation, and job-specific observations.11 One may argue that predictive values would be higher if RTW can be predicted based on the full clinical package, including FCE tests. Results of this strategy are indeed positive.