Ideally, we would employ a psychosocial mediator such as stress, defined as “the interaction between people and their social Selleckchem Sotrastaurin environment involving psychological processes” (Egan et al.,

2008), but unfortunately such variables were not available in the study. We therefore used the General Health Questionnaire (GHQ-12) to derive a psychological factor for this study. The GHQ-12 comprises 12 self-complete questions describing mood states used to assess psychiatric morbidity, with six of the questions being positively phrased and six negatively phrased (Goldberg and Williams, 1988). Each item of the GHQ-12 has four possible response options and these were scored dichotomously using the GHQ method (all beta-catenin inhibitor items coded 0-0-1-1). Missing items were scored zero. The 12 scores were then summed and a cut-off for mental ill health derived from the mean score. For both waves 1 and 5, mean GHQ scores were approximately 2, setting a cut-off of 3 or more as

a case (‘1’) compared to not being considered a case (‘0’). Data on smoking, alcohol consumption, diet and physical activity were based on self-report. Behavioral variables created for these analyses were based, where possible, on contemporary guidelines, as well as making variables homogeneous between waves. Smoking status at both waves 1 and 5 was defined as current (1) versus ex- or non-smoker (0). Weekly alcohol consumption was used to define respondents as below (‘0’) versus above (‘1’) gender-specific recommended weekly limits (⩽21 versus 22+ units for males; ⩽14 versus 15+ units for females) (Changing Scotland’s Relationship Methocarbamol with Alcohol, 2009) Alcohol strength changed for some drinks during follow-up (Bromley et al., 2003) and we recalculated this variable in wave 5, although this change had no impact

on our results. Physical activity was based on the number of occasions per week that respondents took part in an activity “lasting more than 20 min” that made them “sweat or (be) out of breath”, reflecting guidelines at the time. Respondents were dichotomized into high physical activity (at least 20 min once a week; ‘0’) versus low physical activity (less than once a week; ‘1’). Diet, from food-frequency questionnaires, was based on the number of days per week on which participants reported eating fruit and vegetables. Respondents were classified as having a poor diet (‘1’) if they had at least one day per week with no fruit or vegetables consumed versus not having a poor diet if they consumed fruit and vegetables every day of the week (‘0’) (See Table 1). For each individual measure (e.g. smoking, income, etc.), and for the combined factors, a cumulative measure was generated using data from both waves of survey data such that each mediator could take a value of 0, 1 or 2, with higher scores representing more negative material, psychological or behavioral exposures.

52 mg/L), suggesting that the greater differential gene expression potency

and efficacy of SDD decreased as it passed from the duodenum to the jejunum. At day 91, the median rat duodenum and jejunum EC50s were comparable (49 vs. 52 mg/L SDD). Over-represented functions associated with differential gene expression were phenotypically anchored to complementary histopathology FK506 clinical trial and biochemical data (Table 1). The reduction in the GSH/GSSG ratio is suggestive of intestinal epithelium oxidative stress (Thompson et al., 2012). Nrf2 (Nfe2l2) induction (~ 2.6-fold), and subsequent expression of downstream targets (up to 2.7-fold) is consistent with an oxidative stress response. For example, ubiquitination and proteasomal degradation proteins (Vcp, Usp14 and Ube2k), chaperone and stress proteins (Stip1, Cct7, Erp29), and antioxidant proteins (Atf4, Gpx2, and Prdx1) are consistent with oxidative stress. Interestingly, EC50s of 4.2 and 14.2 mg/L SDD for Nrf2 in the duodenum and jejunum at day 8, respectively, provide further evidence that gene expression capability decreased as SDD passed from the duodenum to the jejunum. ToxResponse modeler also calculated EC50 values less than

5.0 mg/L UK-371804 SDD for Nrf2-regulated Usp14, Cct7, and Erp29 at day 8. The Nrf2-mediated oxidative stress response was also observed at day 91 and select QRT-PCR verified genes included the induction of Nrf2, Gclc and Gpx2 ( Fig. 3). Moreover, SDD induced trefoil factor 1 (Tff1), a small secreted protein involved in cell growth that stabilizes the gastrointestinal mucosa and provides a physical barrier against toxic agents. Hydrogen peroxide also induces Tff1 ( Balcer-Kubiczek et al., 2002), while oxidative stress induced by indomethacin and ROS production is reduced by TFF1 ( Chattopadhyay et al., 2006 and Marchbank et al., 1998), further suggesting

oxidative stress protection. Tff1 was induced > 10-fold in rats (EC50 Duodenum and Jejunum Day 8 = 4.2 and 35.3 mg/L SDD), and 53-fold in mice. The induction of Tff1 is consistent with oxidative stress in the rat jejunum 4-Aminobutyrate aminotransferase ( Thompson et al., 2012), and likely represents an adaptive response to SDD. Immune response genes (e.g., Acp5, Anxa5, C3, Ccl24 Cxcl12, Kitlg, Il1rl1, Il33 and C1qa) were also differentially expressed ( Table 1), consistent with the mild to marked histiocytic infiltration at days 8 and 91 ( Thompson et al., 2012). Interestingly, Il1rl1 (5- to 10.9-fold) and Il33 (4.5- to 5.9-fold) exhibited the greatest fold changes with EC50s of 6.8 and 5.4 mg/L SDD, respectively, in the duodenum at day 8. The mouse orthologs were also highly induced immune response genes, although their efficacy of induction was lower with higher EC50s ( Kopec et al., 2012). Several cell cycle, growth and proliferation genes exhibited dose-dependent induction including Myc, Tp53 and their downstream targets.

A large number of osteoprogenitor cells may be implanted at the injury site, either alone or combined with a matrix. Autologous bone marrow (BM) is rich in growth factors and osteoprogenitors as MSCs are present in the mononuclear cellular fraction of the bone marrow. Bone marrow MSCs are currently the most appropriate cells for inducing bone repair, as they have a strong osteogenic potential and are easily obtained by culturing iliac crest aspirates. Several MSC-based cell therapy modalities have been developed, i.e., with and without cell culturing, and with or without a matrix. The mononuclear cell fraction of the bone marrow,

which contains the MSCs, can be used directly by percutaneous injection of aspirated BM into the injury site. To increase the number of injected mononuclear cells and consequently of MSCs, it is possible to separate the mononuclear cells by centrifugation and Tanespimycin order concentrate them 3-fold to 6-fold [64] with good results in pseudarthrosis [65]. The healing rate increased in proportion to the injected MSC concentration. Patients whose fractures did

not heal received fewer than 1000 MSCs per mL and fewer than 30,000 MSCs in total, whereas those whose fractures healed received significantly higher MSC concentrations and counts, with a mean of 1500 MSCs per mL and 54,000 MSCs in total, in a volume of 20 mL. Concentrated or unconcentrated mononuclear cells can be mixed in the operating room Axenfeld syndrome with a synthetic or natural osteo-conducting matrix XAV-939 cell line (e.g., allogeneic bone graft or coral) before implantation. Few published studies assessed the combined use of concentrated or unconcentrated BM with a biomaterial [66], [67] and [68]. This method is a valid option for everyday practice, provided that CE-marked (that is, approved for clinical use in Europe) biomaterials are used and concentration (if used) is achieved via an approved procedure. Mononuclear cells may also be cultured in vitro to allow selection and expansion of an adherent fraction corresponding to MSC. This increases the

number of MSC to millions of cells. Expanded MSCs can be extemporaneously mixed with scaffolds during surgery (Fig. 4) so that this composite material is used in the same way as bone grafts. Quarto et al. [69] first reported the use of cultured BM MSCs combined intra-operatively with hydroxyapatite blocks to fill large bone defects (4–7 cm). They successfully treated 3 patients, with defects in the tibia, humerus, and ulna, respectively. A subsequent study confirmed healing of the defects after 6–7 years [70]. The expanded MSCs may also be injected alone percutaneously in the site of fracture or osteotomy with interesting results in two studies [71] and [72]. Tissue engineering combines bone marrow cells or mesenchymal stem cells, synthetic scaffolds and molecular signals (growth or differentiating factors) in order to form hybrid constructs.

Written informed consent was provided by all

subjects. The trial was designed, implemented, and overseen by the LDK378 cost PACTTE Steering Committee. An independent DSMB reviewed the safety data and study progress on an ongoing basis. Outpatient men and women with the following criteria were eligible to enroll: age ≥ 65 years with a hemoglobin concentration of ≥ 9 g/dL and < 11.5 g/dL for women or < 12.7 g/dL for men with unexplained anemia; serum ferritin between 20 and 200 ng/mL (inclusive); ability to walk without the use of a walker or motorized device, or the assistance of another person; lack of significant cognitive impairment defined by a Montreal Cognitive Assessment score of 22 or higher; and ability to understand and speak English (Table 1). The protocol initially included subjects with a serum ferritin between 20 and 100 ng/mL (inclusive) but was modified on March 26, 2012, due to poor recruitment to allow serum ferritin levels between 20 and 200 ng/mL (inclusive). The protocol was additionally modified on

August 20, 2012, at sites with Spanish-speaking study staff to include subjects who were able to speak and understand Spanish. Unexplained anemia was defined, similar to published criteria [13] and [14], as not meeting criteria for any known etiology of anemia, including vitamin B12, folate, or iron deficiency (defined as serum ferritin < 20 ng/mL); renal insufficiency (defined as glomerular filtration rate of less than 30 [16] using the four-variable Modification of Diet in Renal Disease equation [17]); thyroid dysfunction; myelodysplastic PCI32765 syndrome; anemia of inflammation; plasma cell

dyscrasia; thalassemia trait; alcohol overuse; any prior history of hematologic malignancy; unexplained splenomegaly or lymphadenopathy; or the presence of any condition reasonably assumed to be causing anemia and not corrected for 3 months (Table 2). Subjects were excluded if they had received a red blood cell transfusion, intravenous iron, or an erythropoiesis stimulating agent within 3 months prior to enrollment; had unstable angina, a myocardial infarction, a stroke, or a transient ischemic attack within 3 months prior to enrollment; had uncontrolled hypertension; had a positive fecal occult blood test during the screening period; had significant impairment in liver else function; had a documented history of anaphylactic reaction to iron sucrose infusion; had recently initiated oral iron supplementation; or if the distance walked on the 6-minute walk test (6MWT) was above the median for age and sex, to avoid a ceiling effect (Table 1; Appendix A). Subjects were randomized to start IVIS either immediately (immediate intervention group) or after a 12-week wait list period (wait list control group) at a 1:1 ratio via an interactive voice and web response system. The randomization sequence was computer-generated with random block sizes. Neither subjects nor investigators were blinded.

The

H&E slides were reviewed GSK2118436 chemical structure to confirm the diagnosis. The tissues removed were classified as cysts whenever a partial or total epithelium lining was present. The diagnosis of cysts was based mainly on radiographic and histopathologic examination. DC intensely inflamed and cysts with inadequate tissue samples were excluded. A total of 40 cysts were selected for the study (20 RC and 20 DC). Clinical and radiographic information, including age, gender, and anatomic site, were obtained from biopsy forms submitted by the clinicians. For immunohistochemical analysis, 3 μm thick paraffin embedded tissue sections were placed on 3-aminopropyltriethoxy-silane coated glass slides (Sigma Chemical Co., St Louis, MO, USA). The samples were deparaffinised

with xylene, rehydrated in graded alcohols, and washed in deionised water and phosphate-buffered saline (PBS). Samples were then incubated with 3% hydrogen peroxide and immersed in a citrate buffer, pH 6.0 for 20 min. Sections were then blocked by incubation with 3% normal goat serum at room temperature for 20 min, and slides were incubated at 4 °C, overnight, in a humidified chamber with the following primary rabbit polyclonal antibodies: anti-OPG (N-20; Santa Cruz Biotechnology, Santa Cruz, CA) diluted 1:200; anti-RANK (C-20; Santa Cruz Biotechnology, Santa Cruz, CA) diluted 1:200; and anti-RANKL (N-19; Santa Cruz Biotechnology, Santa Cruz, CA) diluted 1:200. After washing FG-4592 molecular weight in TBS (tris-buffered saline), the sections were treated with a labelled streptavidin-biotin kit (LSAB; Dako, Glostrup, Denmark). Peroxidase activity was visualised by immersing tissue sections in 3,3′-diaminobenzidine (D5637; Sigma Chemical, St. Louis, MO) and counterstained with Mayer’s haematoxylin. A central giant cell granuloma was used as positive control.9 Negative controls were obtained by the omission of primary antibodies and substitution of primary antibodies by nonimmune rabbit serum (X0902; Dako). Immunoexpression of RANK, RANKL and

OPG was evaluated in lining epithelium and fibrous capsule. The epithelial immunoexpression was semiquantitatively evaluated by Baf-A1 molecular weight two observers, using 400× magnification and classified according to the scores: 0 or no staining (<10% of positive immunostaining cells), 1 or weak (11–25%), 2 or moderate (26–75%) and 3 or strong (>76%).23 In fibrous capsule, the analysis was quantitative and the number of positive cells was counted in 10 representative and consecutive microscopic high-power fields (1000×) over totally counted cells,12 irrespectively of cell type. Digital images were loaded on the software IMAGE J® (National Institutes of Health, Bethesda, Maryland, USA) 24 to count the number of immunostained cells. Results are expressed as the mean percentage of observations per field, with the following modifications.

Coverage was assessed as a percentage of the sea bottom covered by vegetation or a certain species within the extent of the sampling site.

Along the transects, the total coverage of the macrovegetation community, coverage of individual species and character of substrate were registered visually by the diver or recorded with an underwater video camera. Observations were carried out to the deepest limit of vegetation on the transect. In the Kõiguste and CHIR-99021 concentration Sõmeri areas, 8–10 observations were made along the transects (the deepest vegetation at 10 m depth). In the Orajõe area the number of observations per transect was 7–9 (the deepest vegetation at 8.3 m depth). Paired with the sampling of seabed phytobenthic community in May, July and September, beach wrack samples were also collected in April, June, August and October (Table 1). Wrack samples were collected from three transects parallel to the shoreline in each area. The distance between the transects was about 60 m. The Tofacitinib molecular weight lengths of the transects were 5 m and five samples were collected from each transect. The samples were collected using a 20 cm × 20 cm metal frame at

a distance of 1 m from one another. Each individual frame sample served as a sampling unit in further statistical analyses. This design (3 transects and 5 samples per transect) resulted in 15 samples per area in each month. Distances from the water edge [m], thickness [cm] and coverage [%] of the wrack layer inside the sampling frame were measured.

The freshest beach wrack closest to the Non-specific serine/threonine protein kinase sea was always chosen for sampling. As a rule, older, more or less decomposed wrack strips were located higher on the shore. In April, only three samples were collectable from fresh beach cast material. As the rest of the samples included old material cast ashore during the previous autumn before the sea froze up, the April data were excluded from further quantitative analyses. The collected material was packed and kept frozen. In the laboratory, the species composition in each sample was determined. As wrack specimens were often fragmented and detailed identification was impossible, morphologically very similar species were treated as one group. The filamentous brown algae Ectocarpus siliculosus (Dillwyn) Lyngbye and Pilayella littoralis (Linnaeus) Kjellman were not separated. All characeans except Tolypella nidifica (O.F. Müller) Leonhardi were determined as Chara spp. Higher plants with similar morphology such as Zannichellia palustris L., Ruppia maritima L. and Stuckenia pectinata (L.) Börner were treated as one group. The biomasses of Fucus vesiculosus L. and Furcellaria lumbricalis (Hudson) J. V. Lamouroux and the rest of the sample were separated and weighed after drying at 60°C to constant weight. Biomass (grams dry weight) was calculated per square metre [g d.w. m−2]).

The rice populations were tested at experiment stations of the China National Rice Research Institute located either in Hangzhou, Zhejiang, check details or Lingshui, Hainan (Table 1). In all the trials, the planting density was 16.7 cm between plants and 26.7 cm between rows. For the F2-type populations in BC2F6, heading date (HD) and 1000-grain weight (TGW) were scored on a single-plant basis. For the NILs in either BC2F5 or BC2F7, a randomized complete block design with two replications was used. Each line was grown in a single row of 12 plants. HD was scored for each plant and averaged for each

replication. At maturity, the middle five plants in each row were bulk-harvested and measured for grain yield per plant (GY), number of panicles per plant (NP), number of grains per panicle (NGP) and TGW. Total DNA was extracted following the method of Zheng et http://www.selleckchem.com/products/ve-821.html al. [19]. PCR amplification was performed according to Chen et al. [20] except that the products were visualized on 6% non-denaturing polyacrylamide gels using silver staining.

Polymorphic markers located in the target region included 17 SSR markers (Fig. 2), all of which were selected from the Gramene database (http://www.gramene.org/). For the F2-type populations in BC2F6, linkage maps were constructed with MAPMAKER/EXP 3.0 [21], and genetic distances in centiMorgans (cM) were derived using the Kosambi function. QTL analysis was performed with composite interval mapping implemented in Windows QTL Cartographer 2.5 [22]. Using 1000 permutation test, the critical LOD values at P = 0.05 were determined,

ranging from 1.75 to 2.03. Putative QTL were claimed at a LOD threshold of 2.1. For the NIL populations in BC2F5 and BC2F7, two-way analyses of variance (ANOVA) were performed to test phenotypic differences between the two homozygous genotypic groups in each NIL set, with a mixed model using SAS procedure GLM [23] as previously described [24]. When significant differences (P < 0.05) were detected, the same model was applied to estimate the genetic effects of the QTL, including additive effect and the proportions of phenotypic variance explained. Since QTL for TGW on the long arm of chromosome 1 showed significant QTL × QTL interaction but no significant main effect in the ZS97/MY46 RIL population [17], it remained unknown whether the QTL effect could be detected in the genetic background Cell press of ZS97. To avoid the risk of wasted effort in population development, marker analysis and field trials, it was necessary to test the effect using NILs at an early generation stage. Therefore, when NILs with sequential segregating regions in the target region became available in BC2F5, they were grown at two locations for primary validation of the QTL effect. Two-way ANOVA for testing phenotypic differences between two homozygous genotypic groups in each of the three NIL sets are shown in Table 2. In populations I and II, no significant effect was detected for any traits.

Several studies have investigated the vulnerability of coastal and marine resource-dependent communities and nations to climatic change [3], [4] and [24]. However, until recently, the implications of climate variability on the lives and livelihoods of marine resource-users at local scales have been less well explored [13] and [25]. Investigations of individual perceptions of environmental change have commonly used a livelihoods approach see [13] and [23]. This approach focuses on local-scale assets Akt inhibition (land, stock, savings etc.), capabilities and activities of resource-dependent

people, and assesses how different livelihood strategies can affect the ability of people or groups to withstand disturbance or change [23]. Here a livelihoods approach is used to assess the resilience of marine check details and coastal resource-users to

environmental change on the Caribbean island of Anguilla, a country highly dependent on marine and coastal resources, with no other significant economic industries [26] and [27]. This study focuses on the effects of hurricanes to examine the resilience of communities to environmental change, as the islands of the Caribbean are particularly at risk from these extreme events [28] and [29]. The impacts from North Atlantic hurricane activity are expected to increase in the Caribbean region in response to changing global climate conditions [2] and [30], although specific changes in hurricane risk for the Caribbean are not yet fully understood e.g. see [31] and [32]. Nevertheless, hurricanes have considerable impacts on Caribbean islands and the increasing prevalence of these extreme events is a major concern for the region [28], [33] and [34]. The aim of this study is to explore the social-resilience of marine resource-dependent livelihoods on the Caribbean island of Anguilla to environmental stressors by (1) identifying the characteristics

of marine and coastal resource-dependent users and livelihoods, (2) assessing the impacts of previous hurricane events on these resource-dependent livelihoods, and (3) investigating resource-user perceptions of future environmental change on the Forskolin resource and livelihood security. The study was undertaken in Anguilla, a small island in the Lesser Antilles chain in the Caribbean Sea (Fig. 1). Like many islands in the Caribbean, the island of Anguilla depends heavily on its marine and coastal resources for fisheries and tourism [34] and [35]. Fishing in Anguilla is largely artisanal, and there are approximately 300 outboard-powered open-top fishing vessels, most of which are between 5 and 10 m in length. The majority of fishers operate close to shore, but due to low inshore catch rates, many vessels have expanded their range to within approximately 65 km radius of the island [27]. The inshore coral reef fishery principally targets reef fish (e.g.

“
“The number, diversity and complexity of synthetic chemicals produced

and released to the environment are overwhelming. As a consequence, we are rarely exposed to only one single contaminant, but typically to mixtures of numerous man-made-chemicals with varying constituents in varying concentrations and concentration ratios (Faust et al., 2003). However, in contrast to this exposure scenario, the present toxicological approach devotes 95% of its resources to the study of single chemicals (Groten, 2000) and provides threshold doses or concentrations of regulatory concern (such as acceptable daily intakes or predicted no effect concentrations) for individual chemicals, implying that exposures below these levels are to be considered safe. In addition, with a few exceptions, chemical risk Enzalutamide datasheet assessment considers the effects of single Apoptosis inhibitor substances in isolation, an approach that is only justified if the exposure to mixtures does not bear the risk of an increased toxicity. In fact, the behavior of chemicals in a mixture may not correspond to the one predicted from data obtained with the pure compounds (Altenburger et al., 2004). From the practical point of view, though, the

direct testing of all the potential combinations of contaminants is unfeasible, and thus we are confronted with the task of deriving valid predictions of multiple mixture toxicity from toxicity data on individual compounds (Faust et al., 2003). In a recent review on the state of the art on mixture toxicity (Kortenkamp et al., 2009) it was concluded that there is a deficit on mixtures studies in the area, amongst others, of neurotoxicity and that it is difficult to assess, based on experimentally published data, the type of combination effect. Furthermore, at present toxicity testing for hazard identification relies mostly on the use of animal models. This approach is costly and time-consuming, and is not practical for hazard identification of this website the thousands of chemicals such as under the REACH directive or in the

high production volume program. Thus, even in the context of mixture toxicity, alternative approaches that have higher throughput capability and are predictive of in vivo effects are needed ( Coecke et al., 2007 and Lilienblum et al., 2008). From a toxicological point of view, in a mixture, chemicals may basically behave in two ways: they can have a joint action or they can interact (Plackett and Hewlett, 1952). In the first case they may act through concentration addition (CA) and independent action (IA) mechanisms also referred to as Loewe additivity and Bliss independence. CA is thought to be valid for mixtures where the components have similar sites and modes of action, while IA is currently held appropriate for mixtures where the components have different sites and dissimilar modes of action ( Greco et al., 1995 and McCarty and Borgert, 2006).

The first two maps in Figure 8 illustrate the distributions of parameters generally characterizing the photosynthetic predispositions of the Baltic basins. Figure 8a shows the range of BYL719 cell line the euphotic zone in which photo-synthesis takes place, calculated according to the optical criterion (the depth to which 1% of the irradiance PAR(z = 0) penetrates) with respect to the irradiance crossing the sea

surface (see e.g. Woźniak & Dera 2007). Figure 8b shows the distributions of the photosynthetic index in the Baltic, i.e. the parameter defining the part of the solar radiation PAR entering the water that is consumed in the photosynthesis of organic matter. It is thus the ratio of the radiant energy flux consumed in primary production under unit surface area of the water column PSR to the radiant energy flux PAR(0) entering the water. The next three maps in Figure 8 show the

distributions of parameters characterizing in a way the condition of phytoplankton resulting from their physiological state, in particular those parameters describing their potential photosynthetic abilities. Figure 8c selleck chemicals llc shows the distributions of the maximum quantum yield of carbon fixation characteristic of a basin. They define the maximum possible ratios of the number of atoms (or moles) of photosynthetically assimilated carbon to the number (or moles) of quanta of solar radiation absorbed under given conditions by phytoplankton pigments (Ficek 2001, Ficek et al. 2000). These maximum values are attained at very low irradiances in the sea and are recorded at great depths. The

second magnitude characterizing the condition of phytoplankton is the phytoplankton assimilation number – see Figure 8d. This defines the maximum possible rate of photosynthesis in waters of a given trophic type (for a fixed amount of nutrients in those waters and Clomifene a particular sea water temperature) expressed in numbers of atoms or moles of carbon assimilated in unit time by phytoplankton of unit chlorophyll content. Such maximum rates of photosynthesis are usually recorded at intermediate (photosynthetically optimal) depths, at which irradiance levels are still sufficiently high not to limit the rate of light reactions, yet not so high that destructive photoinhibition of the photosynthetic apparatus comes into play (Majchrowski 2001, Ficek 2001, Woźniak & Dera 2007). In the Baltic such optimal conditions usually (in ca 66% of cases) prevail at depths from 1 to 5 m (see Woźniak et al. 1989). The last of these maps (Figure 8e) shows the distribution of the non-photosynthetic pigment factor, determined for plant communities in Baltic surface waters, that is, in the water layer most exposed to photoinhibitory processes (Woźniak et al. 2007a). Usually ranging in value from 0.5 to 1.