05. 11 ginsenosides (Rg1, Re, Rf, Rh1, Rg2, Rb1, Rc, Rb2, Rg3, Rk1, and Rg5) were analyzed by HPLC. HPLC chromatograms of REKRG and KRG are shown in Fig. 1. The amount of Rg1, Re, Rf, Rh1, Rg2, Rb1, Rc, Rb2, Rg3, Rk1, and Rg5 was 0.6, 1.9, MEK activation 12.3, 5, 4.2, 3.8, 1.2, 1,

100, 12, and 21 in REKRG and 2.9, 4.2, 0.3, 0.1, 0.2, 5.9, 2.2, 2.1, 0.3, 0.05, and 0.12 in KRG. These results show that the concentration of ginsenoside Rg3 in REKRG is ∼300 times greater than in KRG (Table 1). Because Rg3 enhances eNOS phosphorylation and NO production [20], we next examined whether REKRG has an effect on Akt and eNOS activation in endothelial cells. HUVECs were incubated with 0.1–1 μg/mL REKRG for 24 hours. Cells were then harvested and processed for Western blot analysis. REKRG concentration-dependently stimulated Ser-437 phosphorylation of Akt and Ser-1177 phosphorylation of eNOS (Fig. 2A, 2B). We also examined NO levels in the culture medium after HUVECs were exposed to 0.1–1 μg/mL REKRG for 24 hours. NO levels were increased compared with control (Fig. 2C). These results show that REKRG stimulates the Akt/eNOS signaling pathway, leading to increased MK-2206 concentration NO production in endothelial cells. It is well known that Rg3 has an anti-inflammatory effect [18]. Therefore, we next examined the effect of REKRG

on TNF-α-induced increases in ICAM-1 and COX-2 expression in HUVECs. TNF-α increased ICAM-1 and COX-2 expression at both the protein and messenger RNA (mRNA) levels in HUVECs (Fig. 3A, 3B). However, the TNF-α-induced increases in VCAM-1 and COX-2 expression at the protein and mRNA levels in HUVECs were blunted by REKRG in a concentration-dependent manner (Fig. 3A, 3B), suggesting that REKRG can inhibit inflammatory proteins and possibly the NADPH-cytochrome-c2 reductase early stage of atherosclerosis. Many studies have shown that various ginsenosides, including Rg3, have a beneficial effect on vascular function [20]. Therefore, we investigated whether REKRG affects acetylcholine-induced relaxation in rat aortic rings. Acetylcholine-induced relaxation was measured in the presence of REKRG in an

organ bath. In WKY rat aortic rings, endothelium-dependent vasorelaxation was not affected by 1 μg/mL REKRG treatment (Fig. 4A). However, compared with control rings, 1 μg/mL REKRG treatment improved impaired endothelium-dependent vasorelaxation in SHR aortic rings (Fig. 4B). REKRG (10 mg/kg) was administered to rats for 6 weeks by gastric gavage. We next examined the effect of REKRG on serum NO levels. Compared with controls, 10 mg/kg REKRG increased serum NO levels in SHRs (Fig. 5A). NO inhibits smooth muscle cell migration and proliferation [7]; therefore, we next examined the vascular structure is changed by REKRG in SHR. Digitalized microphotographs of histological sections were used to measure vessel wall thickness and cross sectional area (Fig. 5B, 5C).

They are also epistemological, in that they seem appropriate or useful to invoke in some form in order to have any chance at all for achieving knowledge. It is for these reasons that the highly respected analytical philosopher Goodman (1967, p. 93) concluded, ‘The Principle of Uniformity dissolves into a principle of SCH727965 in vivo simplicity that is not peculiar to geology but pervades all science and even daily life.” For example, one must assume UL in order to land a spacecraft at a future time at a particular spot on Mars, i.e., one assumes that the laws

of physics apply to more than just the actual time and place of this instant. Physicists also assume a kind of parsimony by invoking weak forms UM and UP when making simplifying assumptions about the systems that they choose to model, generating conclusions by deductions from these assumptions combined with physical laws. In contrast, the other forms of uniformitarianism (UK, UD, UR, and US) are all substantive, or ontological, in that they claim a priori how nature is supposed to be. As William Whewell pointed out in his 1832 critique of Lyell’s Principles, BEZ235 order it is not appropriate for the scientist to

conclude how nature is supposed to be in advance of any inquiry into the matter. Instead, it is the role of the scientist to interpret nature (Whewell is talking about geology here, not about either physics or “systems”), and science for Whewell is about getting to the correct interpretation. Many geologists continue to be confused by the terms “uniformity of nature” and “uniformitarianism.” Of course, Sclareol Whewell introduced the latter to encompass all that was being argued in Lyell’s

Principles of Geology. In that book Lyell had discussed three principles ( Camandi, 1999): (1) the “Uniformity Principle” (a strong version of UM or UP) from which Lyell held that past geological events must be explained by the same causes now in operation, (2) a Uniformity of Rate Principle (UR above), and (3) a Steady-State Principle (US above). Lyell’s version of the “Uniformity Principle” is not merely methodological. It is stipulative in that it says what must be done, not what may be done. Indeed, all of Lyell’s principles are stipulative, with number one stipulating that explanations must be done in a certain way, and numbers two and three stipulating that nature/reality is a certain way (i.e., these are ontological claims). Using Gould’s (1965) distinctions, uniformity of law and uniformity of process are methodological (so long as we do not say “one must”), and uniformity of rate and of state are both stipulative and substantive. There is also the more general view of “uniformity of nature” in science, holding uniformity to be a larger concept than what is applicable only to the inferences about the past made by geologists.

The area covered by shrubs decreased continuously between 1993 and 2014. A forest transition

could be observed in the study area as a shift from a net deforestation to a net reforestation, and it occurred at the mid of the 2000s. Fig. 3 shows the spatial pattern of land cover change between 1993 and 2014. Most of the deforestation took place in the northern and southeastern buy Pexidartinib part of the district which can be explained by the fact that forests in the southwestern part are mainly situated within the Hoang Lien National Park. According to the national law, farmland expansion is forbidden within national parks. Nevertheless, some forest loss can be observed which is probably due to forest fires and illegal logging. Fig. 4 shows the spatial pattern of the independent variables that were evaluated in this study. It is clear that Kinh people are living in click here Sa Pa town, while Hmong and Tày ethnic groups occupy the rural area. Hmong ethnic groups are

settled on higher elevations, and Tày are generally settled nearby the rivers in the valleys. The villages of the Yao are situated in the peripheral areas in the north and south of Sa Pa district. Fig. 4A shows that the household involvement in tourism is highest in Sa Pa town (>50%). Involvement in tourism in the peripheral areas is restricted to a few isolated villages. The poverty rate map shows that the town of Sa Pa and its surrounding villages are richer than the more peripheral areas. The southern

part of the district is also richer because many local households receive an additional income from cardamom cultivation under forest. Cardamom is mainly grown under trees of the Hoang Lien National Park in the southern part of the district. The population growth is positive in the whole district and highest in Sa Pa town and its immediate surroundings. Table 4 shows the results of the ANCOVA analysis for four land cover trajectories: deforestation, reforestation, land abandonment and expansion of arable land. The explanatory power of the ANCOVA models is assessed by the R2 values ( Table 4). Between 55 and 72% of the variance in land cover change is explained by the selected predictors. Land cover change is controlled by a combination of biophysical and socio-economical factors. Forests are typically better preserved in villages with poor accessibility (steep slopes, far from Cepharanthine main roads, and poor market access), and a low or negative population growth. The influence of environmental and demographic drivers on forest cover change has previously been described for other areas of frontier colonization ( Castella et al., 2005, Hietel et al., 2005, Getahun et al., 2013 and Vu et al., 2013). Table 4 shows that household involvement in tourism is negatively associated with deforestation and positively with land abandonment. When the involvement of households in tourism activities increased with 10%, deforestation is predicted to have decreased with resp. 0.

62 and 63 In particular, sarcopenia (loss of muscle mass with low strength or performance) is caused and worsened by injury, illness, and inactivity NVP-BGJ398 datasheet during hospitalization. 65, 66 and 67 Taking these malnutrition syndromes into account, the feedM.E. Group now introduces “screen, intervene,

and supervene” as a guide for delivering prompt and complete nutrition care (Figure 1). When the “screen” step shows that underlying illnesses, injuries, or symptoms are likely to cause malnutrition or its risk, we advise caregivers to consider immediate nutrition care with dietary advice to “intervene” by way of increasing energy and protein intake with dietary fortification or use of oral nutrition supplementation. Such early attention to nutrition (in patients capable of oral feeding) is expected to help prevent or lessen the impact of malnutrition. For those whose screening results suggest malnutrition or risk of malnutrition, we next advise

implementation of the complete Nutrition Care Pathway, which includes advanced strategies for diagnosis of malnutrition and its causes, in turn leading to further “intervene and supervene” steps. Screening patients for malnutrition on admission to the hospital is a new standard of care, and routine screening is likewise appropriate in rehabilitation facilities, long-term care centers, and community health care settings. To ascertain malnutrition risk, we recommend nutrition screening that pairs (1) the 2 Malnutrition selleck products Screening

Tool (MST) questions68 and 69 with (2) a quick clinical judgment about whether the patient’s illness or injury carries risk for malnutrition (Figure 1).61, 62 and 63 The 2 MSTs questions ask the patient about recent weight loss and appetite loss as a way to recognize symptoms of risk for malnutrition.68 and 69 MST is both sensitive and specific, even in older people.68, 70 and 71 Alternatively, the Simplified Nutritional Appetite Questionnaire (SNAQ) is a validated, efficient tool for use with long-term care and community populations.71, 72 and 73 Next the clinician makes triclocarban a quick judgment about the patient’s condition and its likelihood to cause or worsen malnutrition. Many chronic diseases (eg kidney disease, cancer, heart failure) and acute conditions (eg infection, surgery, burn, sepsis, or trauma) carry risk for malnutrition. This step of the screen raises awareness of potential risk for malnutrition. If nutrition screening identifies high risk of malnutrition, consider immediate intervention with nutrition advice for increasing or optimizing oral feeding, or oral nutrition supplementation. The intervention portion of the Nutrition Care Pathway includes assessment of nutrition status, malnutrition diagnosis, and implementation of treatment.

19%, 7.99%, and 6.96%, respectively. Assay batch-to-batch variability was assessed by analysing 50 serum samples with varying FLC levels (κ range 3.42–329.88 mg/L; λ range 1.09–130.51 mg/L) FK506 ic50 and the results are displayed in Fig. 7. All samples were analysed once, on separate assay days, using three consecutive batches of anti-FLC mAbs, calibrators and other appropriate assay reagents. Passing and Bablok regression analysis gave slopes between 0.93–1.01 for κ FLC and 0.86–1.05 for λ FLC. Spearman correlation coefficients for κ FLC were

≥ 0.99 and for λ FLC were ≥ 0.96. Representative assay linearity results are displayed in Fig. 8. Serum samples containing high levels of either κ (581.36, 416.37, and 256.97 mg/L) or λ (485.04, 379.41and 370.56 mg/L) FLC paraproteins were serially diluted in assay buffer. Results indicated that assay linearity was maintained on the monoclonal κ FLC samples between 7.61 mg/L and 568.01 mg/L, 1.94 mg/L and 410.36 mg/L, and, 6.32 mg/L and 260.78 mg/L, respectively. For the λ monoclonal FLC samples, linearity was maintained between 1.38 mg/L and 476.1 mg/L, 1.78 mg/L and 361.72 mg/L, and, 4.45 mg/L and 381.62 mg/L, respectively. For κ FLC, below 10 mg/L no more than 1.45 mg/L non-linearity was found, and above 10 mg/L no more than 16.37% non-linearity was observed. For λ FLC, below 10 mg/L no

more than 2.03 mg/L non-linearity was found, UK-371804 manufacturer and above 10 mg/L no more than 19.0% non-linearity was found. The assay limit of detection DOK2 for each mAb was assessed by measuring each against a κ or λ BJ protein, firstly mixed with normal serum, and then

serially diluted in assay buffer. Limit of detection for BUCIS 01 was 0.63 mg/L, BUCIS 04 was 0.86 mg/L, BUCIS 03 was 0.72 mg/L, and BUCIS 09 was 0.52 mg/L. Assay interference tests showed minimal assay cross-reactivity to alternate κ or λ FLC or intact immunoglobulins, bilirubin, haemoglobin, cholesterol or triglyceride (Fig. 9, in supplementary data). Results demonstrated that no more than a median 2.7 mg/L change was observed for the anti-κ FLC mAbs, and no more than a median 3.7 mg/L change for the anti-λ FLC mAbs. This study describes the development of four mouse anti-human κ:λ FLC mAbs and their initial validation in a multi-plex Luminex® immunoassay. Each of the anti-FLC mAbs exhibited: excellent sensitivity (< 1 mg/L); low batch variation; sustained assay linearity; specificity and minimal cross-reactivity to bound LC, or alternate FLC isotype. Each of the mAbs provided good quantitative concordance with the Freelite™ assay in the measurement of polyclonal FLC in plasma from 249 healthy donors, and FLC levels in serum from 1000 consecutive samples. Specificity and sensitivity were further illustrated in the measurement of FLC in 13,090 urine samples tested for BJ proteins.

1). For the preparation of ELISpot plates, MAIPSWU10 Multiscreen filtration plates (Millipore, Billerica, MA, USA) were pre-wetted with 70% ethanol for ≤ 1 min and washed with sterile water. Coating antigens (TTd, DT, PT, FHA and PRN) were diluted to 0.5 μg/well in sterile phosphate buffered saline (PBS) (SVA, Uppsala, Sweden) and anti-IgG coating mAbs were diluted

to 10 μg/ml in PBS and added to the plate. Wells used as blank controls were incubated with PBS only. The plates were BEZ235 ic50 then incubated overnight (ON) or ≤ 72 h at 4 °C. The plates were washed five times with PBS and blocked with RPMI-GlutaMAX™ supplemented with 10 mM HEPES and 50 μg/ml Penicillin–Streptomycin and 10% FCS (all from Gibco Invitrogen), referred to as “R10”, for at least 30 min at room temperature (RT). After the 72 hour pre-activation period cells were harvested and washed once in R10 before

counting. The cells were resuspended and added to the plates in duplicates with 100 μl cell suspension/well (for cell concentrations see paragraph 2.7). The ELISpot plates were incubated ON in humidity at 37 °C, 5% CO2. The cells were discarded and the plates were washed with PBS (5 × 200 μl/well). Biotinylated anti-IgG detection mAbs diluted to a concentration of 1 μg/ml in PBS supplemented with 0.5% FCS were added Bortezomib to the plate wells and incubated for 2 h at RT. The plates were washed with PBS (5 × 200 μl/well) before Streptavidin conjugated with Alkaline-Phosphatase (SA–ALP)

(Mabtech) diluted 1/1000 in PBS supplemented with 0.5% FCS was added and incubated for 1 h at RT. Unbound conjugate was washed away with PBS (5 × 200 μl/well). BCIP/NBT-plus substrate (Mabtech) was filtered through a 0.45 μm-filter and 100 μl/well was added to the wells and incubated for 7 min at RT. The reaction was stopped by rinsing the plates with tap water. The plates were then left to dry ON in darkness. The protocol used was Acesulfame Potassium originally described in 2009 (Buisman et al., 2009) but was later modified for a European collaboration project (Child Innovac). Antigen coating concentrations were 1.5 μg/well for PT and 0.7 μg/well for TTd, all antigens and the coating antibody were diluted in PBS. Major changes in the Child Innovac protocol were as follows; Stimulation: The cultivation medium consisted of AIM V medium (Gibco Invitrogen) supplemented with 10% FCS without β-mercaptoethanol. Also, 0.01 μg/ml of each antigen included in the assay was added to the stimulated aliquot. Coating of plate: The plates were pre-wetted with 35% ethanol and incubated with antigen ON or longer (< 5 days).

This could be analogous to the effects holding an item in working memory Torin 1 ic50 has in guiding attention to matching features (for review, see

Soto et al., 2008). Thus, setting voluntary attention to the task-relevant feature also selects the same feature in an image that is internally created in the absence of incoming visual signals, analogous to its effect on ‘normal’ perception when multiple features physically appear in a visual scene (Saenz et al., 2003). Our results also show that the relationship between pitch and synaesthetic objects follow the same rules as the subtle cross-modal mappings seen in non-synaesthetes: non-synaesthetic individuals tend to map high-pitched sounds with small, bright objects located high in space. This effect in non-synaesthetes has been documented using subjective report (Eitan and Timmers, 2010; Ward et al., 2006), speeded reaction time (Ben-Artzi and Marks, 1995; Evans and Treisman, 2010; Marks, 1987),

and preferential looking in infants (Walker et al., 2010). Although the implicit cross-modal PD-332991 correspondences in non-synaesthetes can only be measured under specific experimental settings, whereas synaesthetes have daily conscious experiences of auditorily-induced visual percepts, there are some hints in the data that controls may be subtly affected by these mappings even when we use stimuli tailored to synaesthete experiences. For example, as Fig. 5a illustrates, controls show a pattern numerically similar to that of synaesthetes across conditions, although there are no statistically significant congruency effects in their data. Ward et al. (2006) suggest that similarities between synaesthetes and non-synaesthetes in sound–colour mappings show

that synaesthesia co-opts the neural substrates for ‘normal’ cross-modality mappings and reveals the associations in a more explicit form. Another study reporting the similarity between synaesthetes and non-synaesthetes in their mapping between luminance and numerical quantity also fits the notion that synaesthesia builds on ‘normal’ mechanisms of non-synaesthetic Pyruvate dehydrogenase brain (Cohen Kadosh et al., 2007). We interpret our data similarly as implying a common neural/cognitive mechanism underlying both auditory–visual synaesthesia and ‘normal’ cross-modal mappings. The documentation of non-colour synaesthetic visual features is crucial for developing more comprehensive models to explain how synaesthesia relates to general aspects of cognition. Here we provide objective evidence showing that auditorily-induced synaesthetic objects with multiple features affect behaviour, as well as that attention modulates the component features of synaesthetic objects. Our findings suggest overt synaesthetic experiences induced by sounds reflect implicit cross-modal mechanisms we all share.

15, p=0.299. For the semantic task, there were tone×antpost, F(2, 32)=8.55, p=0.003, and tone×lat, F(2, 32)=4.67, p=0.027, interactions. High tone was more positive than low tone in frontal, F(1, 16)=12.16, p=0.003, and central, F(1, 16)=12.84, p=0.002, RoIs ( Fig. 1C). The effect size was larger over mid, F(1, 16)=15.55, p=0.001, η2=0.493, and right, F(1, 16)=11.84, p=0.003, η2=0.425, than over left electrodes, F(1, 16)=5.66, p=0.030, η2=0.261. For the lexical word boundary task, a tone×antpost

interaction was seen, F(2, 32)=5.98, p=0.010. High tones produced more positivity at frontal, F(1, 16)=6.34, p=0.023, and central, F(1, 16)=22.59, p<0.001, leads ( Fig. 1D). There was no significant effect for delexicalized speech, F(1, 16)=1.55, p=.231. In the semantic task ERPs, there was a tone×suffix interaction between 400 and 550 ms following suffix onset, F(1, 16)=4.63, SB431542 ic50 p=0.047. High tone-inducing suffixes produced increased positivity as compared to low tone-inducing suffixes following low stem tones ( Fig. 1E), F(1, 16)=5.84, p=0.028, but not following high stems, F(1, 16)=0.01, p=0.921. There were no significant effects for the lexical or delexicalized word boundary check details tasks. The negativities

for high tone-inducing suffixes preceding and following the positivity were not significant. It has been hypothesized that the early stages of prosodic processing are reflected in variations in the N1 and P2 components. N1 increase is thought to show detection of salient auditory features that might be relevant for speech processing, whereas a P2 increase would index allocation of anticipatory attention to upcoming grammatical information cued by the prosodic features. The present study tested the ERP effects of high and low word-stem tones in Central Swedish. As previously found, high stem tones increased the P2 amplitude as compared to low

tones. Crucially, however, this was not the case for the delexicalized EGFR antibody inhibitor versions of the same stimuli. This finding supports the hypothesis that the P2 effect indexes allocation of attention to upcoming grammatical information – in this case, high stem tone-associated suffixes – which was not available in the delexicalized stimuli. The fact that the P2 effect was also present in the lexical boundary task blocks, where the stem tone was irrelevant for the task, might suggest that the P2 in fact indexes “passive” anticipatory attention. It should be noted that native speakers are often unconscious of the existence of high and low stem tones in Swedish. This is similar to the case of left-edge boundary tones, where the P2 has been argued to show passive anticipatory attention to upcoming main clause structures. The P2 onset was further found to be rather early, around 160 ms rather than the 200 ms onset previously reported. This is most likely due to the more exact tone onset and thereby earlier tone processing in the present study.

The incorporation of radiolabelled 7 or 8 in Salix or Populous leave tissues can readily be transformed stereospecifically to 3-hydroxy-3-phenylpropanoic acid 11 or 3-hydroxy-3-(2-hydroxyphenyl)-propanoic acid 12via CoA-dependent β-oxidation [7] and [20]. Subsequently, 3-hydroxy propanoate side chain of compounds, 13 or

14, undergo C2 unit elimination to yield 9 or 10via retro Claisen condensation ( Scheme 2). The mechanism of biotransformation, in the last two steps, is analogous to the metabolism of fatty acids in humans [16], [20] and [21]. selleckchem The elimination of the C2 unit involves the formation of β-oxophenyl propionyl-CoA 13 or β-oxo-orthohydroxyphenyl propionyl-CoA 14 which is followed by the nucleophilic attack by thiolase at β-carbonyl group, forming an enzyme-substrate complex 15 or 16, respectively. These two complexes, 15 and 16, subsequently, undergoes α-β-C–C cleavage, resulting in the formation of the following intermediates: 17, 18, 19. Protonation of 17 gives acetyl CoA 20 while the intermediate 18 and 19 undergo nucleophilic attack by acetyl S-CoA to release the enzyme and form benzoyl-SCoA 9 and salicyloyl-SCoA 10, respectively ( Scheme 2). Plants modulate the phenylpropanoide pathways by interconverting

benzoate secondary metabolites in response to the plant’s physiological Linsitinib concentration requirement. Therefore, the exact mechanism of β-d-salicin 1 biosynthesis may seem difficult to justify. Using Salix and Populous leaf tissue indicated that the downstream of β-d-salicin 1 biosynthesis involves inter conversion of different simple phenolic molecules, including benzaldehyde 21, benzoic acid 22 and benzoyl-SCoA 9 compounds in plants [7], [16], [22] and [23]. The biotic transformation of cinnamic acid 7, for example, can undergo direct ortho hydroxylation to give 2-hydroxycinnamic acid 8 or Carnitine palmitoyltransferase II C2 elimination to give benzaldehyde 21 ( Scheme 3). Benzaldehyde 21 can also be hydroxylated at ortho position to give 2-hydroxybenzaldehyde 23. Feeding the leave tissue of S. purpurea

with radiolabelled benzoic acid 22 or benzyl alcohol 24 gave benzaldehyde 21via reduction or oxidation reaction, respectively [7] and [16]. Further biotic transformation of compounds 22 and 24 gave salicyl alcohol 5, the precursor of β-d-salicin 1 ( Scheme 3). In addition, benzoyl-SCoA 9 undergoes a reduction reaction to give benzyl alcohol 24 or benzoic acid 22 ( Scheme 3). In addition, there are other benzoate secondary metabolites that have been found in Populous, which contribute to the biosynthesis of phenolic glycosides. These benzoates are 1-hydroxy-6-oxo-2-cyclohexene-1-carboxylic acid 26, benzyl 6-hydroxy-2-cyclohexen-on-oyl 27 and salicyl 6-hydroxy-2-cyclohexen-on-oyl 28 [7], [22] and [23]. The final step, in the biosynthesis of 1, involves glucosylation of salicyl alcohol 5 at the phenyl hydroxyl group. In S.

Briefly, the four types of knowledge dimension are organized from more “concrete” to

more “abstract” knowledge. Factual knowledge corresponds to the basic elements (terminology and specific details) students must know “to be acquainted with a discipline or to solve problems in it”. Conceptual knowledge corresponds to classifications and categories, principles and generalizations, theories, models and structures. Procedural knowledge relates to “how to do something” (techniques, methods, criteria for determining when to use appropriate procedures). Finally, Metacognitive knowledge involves cognition in general as well as awareness on its own cognition. The cognitive processes are organized as a continuum of increasing cognitive complexity: I-BET-762 clinical trial Understand is believed to be more cognitively complex than Remember; Analyze more cognitively complex than Apply, and so. As mentioned ( Anderson et al., 2001), Remember consists in “retrieving relevant knowledge from long term memory”. Understand

corresponds to cognitive efforts made to “elaborate meaning from oral, written or graphic educational messages”. Understanding can be observed through activities like exemplifying (illustrating), classifying (subsuming), inferring, comparing (mapping, matching), or explaining (constructing models). Apply consists in “executing a procedure to a familiar task (executing) or to an unfamiliar task” (implementing). Analyzing consists in “breaking material into its constituent parts and determine how the parts relate to each one another and to

an overall structure Veliparib research buy or purpose”. It can be further divided into 3 sub-categories: discriminating (focusing, selecting); organizing (finding coherence, integrating, outlining, parsing, and structuring); attributing (deconstructing). Evaluate concerns “the ability to make judgments based on criteria and standards” (checking, judging). And finally Create consists in “organizing elements together to form a coherent or functional whole” SPTLC1 or in “reorganizing elements into a new pattern or structure”. Creation appears while generating hypothesis, planning (designing a procedure to accomplish a task) and producing (constructing). This taxonomy allows to categorize the skills exercised during the construction of sCM and to propose the sCM matrix. To answer a given focus question in a sCM, learners must go through the following steps (see Table 1). (1) Recognizing and recalling: actively retrieve the appropriate terminology used to specify details, elements, and concepts. (2) Remembering: remember principles, generalizations, theories or models. (3a) Remember and (3b) understand the strategic skills for organizing knowledge in maps. (4) Illustrating/explaining: find appropriates examples, figures or pictures to illustrate their map. (5) Subsuming/mapping/constructing models: connect elements together.