Vitamin-R 2.58 | 63.7 MB
Vitamin R 2 58 Kg To Grams
Later, Kawashima et al. Demonstrated that the pharmacological dose of vitamin K2 reduced the total-cholesterol, lipid peroxidation in plasma by treating 24 hypercholesterolemic rabbits with vitamin K2 in daily doses of 1, 10 and 100 mg/kg with a 0.5% cholesterol diet for 10 weeks. Vitamin-R 2.58 February 24, 2019 Vitamin-R creates the optimal conditions for your brain to work at its best by structuring your work into short bursts of distraction-free, highly focused activity alternating with opportunities for renewal, reflection and intuition. Spirulina is a biomass of cyanobacteria (blue-green algae) that can be consumed by humans and animals. The three species are Arthrospira platensis, A. Fusiformis, and A. Cultivated worldwide, Arthrospira is used as a dietary supplement or whole food. It is also used as a feed supplement in the aquaculture, aquarium, and poultry industries.
Vitamin-R creates the optimal conditions for your brain to work at its best by structuring your work into short bursts of distraction-free, highly focused activity alternating with opportunities for renewal, reflection and intuition. The built-in task logging and statistics features create a positive momentum towards productivity by providing visible feedback on your progress and achievements.
Recapture the Lost Art of Joyful Concentration. Overcome Procrastination. Get Motivated.
Vitamin-R creates optimal conditions for your brain by structuring your work into short bursts of distraction-free, highly-focused activity alternating with opportunities for renewal, reflection and intuition.
The built-in task logging and analysis features create positive momentum towards productivity by providing you with visible feedback on your progress and achievements.
▷ Slices Up Daunting Tasks into Manageable Chunks
Vitamin-R breaks down large, vaguely defined tasks into a series of short 'time slices' of between 10 and 30 minutes, each with a specific, easily reachable and actionable objective.
▷ Keeps You Focused
Vitamin-R features an array of highly configurable visual, audio and speech notifications that prod you back to your task as soon as your attention starts to wander.
▷ Gets You Started, Keeps You Motivated
Vitamin-R allows you to break through the resistance of procrastination and create a positive feedback loop of small achievements that get you closer to your ultimate aims.
▷ Effective Task Switching
Task switching is a big, but often unavoidable productivity killer. Vitamin-R makes it as efficient as possible and the built-in 'breadcrumbing' technique helps you pick up where you left off.
▷ Productive Breaks
Regular breaks are not for slackers. In fact, they are especially important for people who work with high focus. Vitamin-R's timed breaks make sure that your renewal break does not turn into a free afternoon and the 'priming' technique allows your intuition to work overtime before you even start on an objective.
▷ Find Your Rhythm
Each one of us is different. Find out what works best for you and unlock the key to true productivity. Vitamin-R provides the tools to gain improved awareness of your preferred work methods and rhythms. Armed with this new knowledge, you can eliminate unproductive work patterns.
▷ Get It Out of Your Head Quickly
Did you know that your short term memory can only hold 4-6 'chunks' of information? The slightest interruption and it's all gone and you have to start from scratch. That's why Vitamin-R provides you with the 'Now & Later Board', complete with FastType magic, to give you a place to quickly dump all those things that go through your head and allow you to quickly return to your task.
▷ Make It Your Own
Vitamin-R plugs into your life rather than trying to take it over. Sugar bytes cyclop 1 2 0 download free. You can use it occasionally to overcome procrastination or mental blocks or re-organize your entire working life around the concepts that it embodies.
▷ Works with OmniFocus, Things & The Hit List
Vitamin-R integrates with traditional to-do list managers rather than trying to replace them.
▷ Block Out Noise
The built-in noise machine can block out irritating coworkers and create energizing soundscapes.
▷ Eliminate Distractions
Vitamin-R helps you reduce distractions by automatically eliminating desktop clutter and hiding unrelated applications.
▷ Syncs with all your Mac OS X and iOS Devices
Vitamin-R for Mac seamlessly syncs with the iPhone version and multiple Macs via its simple Dropbox integration, so you can log your time slices wherever you are.
▷ Ideal for Pomodoro Technique Aficionados
Vitamin-R provides everything you need to implement the Pomodoro Technique: sophisticated timer, log book and analysis component.
▷ Attention Deficit Disorder
While Vitamin-R was never specifically designed with ADHD 'sufferers' in mind, many ADHD-ers have found its approach to focusing attention invaluable.
Compatibility: OS X 10.10 or later 64 bit
Abstract
Background
Warfarin inhibits vitamin K-dependent coagulation factors. Being fat-soluble, the availability of vitamin K may vary according to body fat. We hypothesized that BMI, a proxy of body fat, may interact with vitamin K intake in determining warfarin maintenance (WM) dose.
Methods
Patients with data on vitamin K intake, potential confounders and WM dose (n=172) were included in linear regression models to test whether BMI modifies the relation between vitamin K intake and WM dose.
Results
Warfarin loading dose correlated with the maintenance dose (r=0.36, P<0.0001) but was not significantly associated with WM dose in analyses adjusted for vitamin K epoxide reductase (VKORC1) and Cytochrome P450 2C9 (CYP2C9) genotypes. In fully adjusted models, BMI was associated (P=0.001) with WM dose but vitamin K was only marginally positively associated (P=0.06) with WM dose. We found no interaction (P>0.05) between BMI and vitamin K intake with regard to WM dose. Inclusion of vitamin K intake in the model only slightly improved the amount of variance (1.1%) explained by age, gender, BMI, race, physical activity, energy intake and VKORC1 and CYP2C9 genotypes.
Conclusion
Our data suggest that body fat does not affect the relation between vitamin K intake and warfarin maintenance dose.
Introduction
Response to warfarin is highly variable within and across populations []. Both genetic and environmental variables such as diet and physical activity affect response to warfarin [-]. Although, algorithms that incorporate genetic and environmental variables have been developed for clinical use in predicting response, a substantial amount of variation in warfarin response still remains unexplained [, ]. Warfarin acts by inhibiting vitamin K epoxide reductase (VKORC1) thereby inhibiting vitamin K dependent activation of coagulation factors (II, VII, IX and X). Since vitamin K is a fat-soluble, its amount and availability in tissues may vary according to body fat []. We hypothesized that obese individuals may have higher amounts of vitamin K in tissues and therefore require higher warfarin maintenance doses after adjusting for known determinants of warfarin response. Indeed in patients treated with phenprocoumon, a coumarin derivative which inhibits vitamin K reductase thereby blocking vitamin K-dependent coagulation factors, the dose and time required to attain desirable international normalized ratio (INR) is directly correlated with body mass index (BMI) in a dose-dependent manner []. Whether BMI modifies the relationship between vitamin K and warfarin response is not known.
Since BMI [] is strongly correlated with objective measures of fatness e.g., Dual Energy X-Ray Absorptiometry (correlation coefficients range from 0.55 to 0.96), BMI is a good proxy for body fat content. We investigated whether the relation between vitamin K intake and response to warfarin is modified by body fat at initiation of warfarin therapy. We also investigated whether inclusion of vitamin K intake in models improves the variance explained by established predictors of warfarin response. Tower 3 6 0 8.
Methods
Study population
The Pharmacogenetic Optimization of Anticoagulation Therapy (POAT) and the Genetic and Environmental Determinants of Warfarin (GEDWR) are ongoing prospective studies aimed at defining the influence of genetic polymorphisms on warfarin response []. Patients ≥20 years of age were considered eligible if the intended duration of anticoagulation therapy was ≥2 years. Therapy was managed at the anticoagulation clinic and the target INR range was 2 to 3. The study was approved by the Institutional Review Boards of the University of Alabama at Birmingham and Jefferson County Health System. Participants gave written informed consent.
Data collection
Detailed information including race, age, height, weight, indication for therapy, co-morbid conditions and medications was collected as detailed elsewhere []. Factors influencing warfarin response, including warfarin loading dose, INR, concurrent medications and intake of alcohol and vitamin K, were documented. Concurrent therapy with non-steroidal anti-inflammatory drugs, antiplatelet agents or drugs that alter warfarin pharmacokinetics including Cytochrome P450 2C9 (CYP2C9) inhibitors (e.g., amiodarone), CYP2C9 inducers (e.g., rifampin) or CYP2C9 substrates (e.g. losartan) were documented. In addition, we genotyped for variants in genes associated with warfarin dose [] namely: VKORC1 (-1639G>A (rs9923231)), CYP2C9 [*2 (rs1799853), *3 (rs1057910), *5 (rs28371686), *6 (rs9332131), and *11 (rs28371685)] and CYP4F2 (rs2108622).
Assessment of vitamin K intake
Intake of vitamin K and other nutrients was estimated from three 24-hour dietary recalls (DR) using Nutrition Data System for Research (NDSR)® software [10]. We had previously showed that vitamin K intake assessed from DR was similar to that measured from the food frequency questionnaire []. Estimates of vitamin K intake from DR have been used in other studies and show positive correlation with warfarin dose required to attain INR []. Available DR were averaged to obtain a stable measure of vitamin K intake.
Out of 1044 patients considered for inclusion in the current analysis, 578 were recruited as part of the POAT cohort which was established as part of a career-development award []. The funds in the POAT study were not sufficient to support a dietician for the assessment of vitamin K using 24-hr dietary recalls (NDSR). The cohort (n=466) recruited through the GEDWR project provided the funds for the assessment of dietary vitamin K intake. At the time of the analyses for this study 209 patients had completed the baseline dietary recalls.
Statistical analyses
Freemake video grabber mac. Warfarin loading dose was calculated as the total amount of warfarin a patient received divided by the total number of days taken before attaining target INR. Of the 209 patients, 11 were excluded for missing data on warfarin maintenance dose, VKORC1 or CYP2C9 genotypes and 23 for missing data on physical activity leaving 175 patients. In order to adjust for race in the models, the only patient of Asian descent was excluded from further analyses leaving 108 white and 66 black patients. Two more patients with vitamin K intakes (1,476 and 1,513 μg/d) larger than 4 standard deviations above the mean were also excluded.
Vitamin K intake was adjusted for total energy intake using standard regression approaches [, 13]. The dependent variable, average warfarin maintenance dose was square root-transformed to attain normality. Using ANOVA (SAS software version 9.2, Cary, NC) we tested whether vitamin K intake is associated with warfarin maintenance dose and whether this association is modified by BMI independent of VKORC1, CYP2C9, age, gender, physical activity and total energy intake. Additional analyses were performed adding variables such as race, education, income, CYP4F2 genotypes, alcohol use, smoking and warfarin loading dose but none of these variables were significant in any of the models. In these analyses both the main effects and interaction terms for energy-adjusted vitamin K and BMI were included.
To further investigate the effect of the interaction between BMI and vitamin K intake on warfarin response we divided the study population into obese and non-obese individuals based on the standard definition for obesity i.e., BMI ≥30 kg/m2. The relation between vitamin K and warfarin maintenance dose was then examined after stratifying by obesity status.
Next we tested whether adding vitamin K to the model that includes standard predictors of warfarin maintenance dose improves the variance explained by the model. We used linear regression with square root-transformed warfarin maintenance dose as the dependent variable and energy-adjusted vitamin K, total energy intake, age, gender, BMI, physical activity, VKORC1 and CYP2C9 genotypes as covariates. In this analysis, males were coded as 1 and females as 0, VKORC1 genotypes were coded as 1 for 'CT' and 'TT' and as 0 for 'CC' while CYP2C9 was coded as 1 for '11' genotype and 0 for all other genotypes ('12', '13', '22', '23', '33' and '111').
Results are reported as beta (± standard error), standardized beta coefficients and adjusted r2. Variables in the model were considered significant at a P≤0.05.
Results
Vitamin R 2 58 Kg Lbs
Of the 172 patients in the sample, 52% were female, 62% were white, 50% smoked cigarettes, 16% consumed alcohol, 63% had college education or higher and 41% earned ≥$50,000. Two percent of the patients were underweight (BMI<18.5 kg/m2), 24% were of normal weight (BMI 18.5-24.9 kg/m2), 33% were overweight (BMI 25-29.9%) and 43% were obese (BMI ≥30 kg/m2). BMI ranged from 16.3 kg/m2 to 58.6 kg/m2.
The median [25th, 75th percentile] vitamin K intake was 73.6 [45.9, 168.0] μg/d and ranged from 11.7 μg/d to 714.7 μg/d. The mean warfarin loading dose was 6.3±2.9 mg and ranged from 2.0 to 30.0 mg while the average maintenance dose was 5.6±2.4 mg and ranged from 0.92 to 15.6 mg. The average warfarin loading dose weakly correlated with the average maintenance dose in the study population as whole (Spearman r = 0.38, P<0.0001).
The characteristics of the study population by quartiles of warfarin maintenance dose are shown in Table 1. Age, race, warfarin loading dose, VKORC1, CYP2C9 and CYP4F2 were all significantly associated (P<0.05) with warfarin maintenance dose in univariate analyses. Patients who required a higher maintenance dose tended to be younger, received a higher initial warfarin loading dose and were more likely to be black.
Table 1
Characteristics of the study population by quartiles of warfarin maintenance dose
Quartiles of warfarin maintenance dose | P | ||||
---|---|---|---|---|---|
1 (Lower) | 2 | 3 | 4 (Upper) | ||
n | 43 | 43 | 43 | 43 | -- |
Warfarin maintenance dose, mg | 2.91±0.84 | 4.68±0.39 | 6.10±0.49 | 8.69±1.85 | -- |
Warfarin loading dose, mg | 5.42±1.19 | 6.04±3.09 | 6.94±4.20 | 6.95±1.81 | <0.0001 |
Vitamin K adjusted for energy, μg/d | 121.39±125.47 | 100.1±70.9 | 96.29±71.32 | 160.2±177.5 | 0.68 |
Vitamin K unadjusted for energy, μg/d | 112.8±103.8 | 112.0±92.3 | 109.5±95.8 | 175.5±190.8 | 0.73 |
Total energy, kcal/d | 1748±607 | 1923±702 | 1892±716 | 1914±616 | 0.67 |
Age, y | 65.4±14.3 | 66.7±10.5 | 59.8±11.9 | 55.0±14.7 | 0.003 |
Body mass index, kg/m2 | 29.1±8.5 | 30.1±7.8 | 30.6±6.4 | 32.1±8.7 | 0.20 |
Sex, % women | 58 | 51 | 42 | 56 | 0.44 |
Race, % white | 74 | 70 | 65 | 40 | 0.04 |
Smoking, % never smokers | 49 | 54 | 49 | 49 | 0.96 |
Physical activity, % sedentary | 40 | 54 | 58 | 58 | 0.26 |
Education, % college or higher | 74 | 58 | 58 | 60 | 0.32 |
Income, $50k or higher | 44 | 39 | 49 | 33 | 0.54 |
Current alcohol user, % | 12 | 19 | 17 | 14 | 0.86 |
VKOR, % T-allele career | 70 | 65 | 37 | 14 | <0.0001 |
CYP2C9, % with ‘11' genotype | 61 | 70 | 74 | 93 | 0.01 |
CYP4F2, % G-allele career | 95 | 84 | 100 | 85 | 0.02 |
Surprisingly, BMI, smoking, income, education and current alcohol use were not significantly associated (P>0.05) with warfarin maintenance dose (Table 1). Although the association between BMI and quartiles of warfarin maintenance dose was not statistically significant, there was a tendency for the maintenance dose to increase with increasing BMI. For instance, the mean BMI for the 1st, 2nd, 3rd and 4th quartiles of the warfarin maintenance dose was 29.1±8.5, 30.1±7.8, 30.6±6.4 and 32.1±8.7 kg/m2, respectively (P>0.05) (Table 1). The spearman correlation between BMI and average warfarin loading dose was weak (r=0.28, P=0.0003) but larger than the correlation between BMI and warfarin maintenance dose (r=0.19, P=0.01).
Table 2 shows the relation between vitamin K intake and warfarin maintenance dose after adjustment for covariates. BMI was significantly associated (P=0.001) while vitamin K was marginally positively associated (P=0.06) with warfarin maintenance dose. There was no significant interaction between BMI and vitamin K (P>0.05) before and after adjustment for covariates. Inclusion of vitamin K in the model improved the variance explained by 1.1% (Table 2).
Table 2
Relation between vitamin K and warfarin maintenance dose*
Variable | Without vitamin K in the model | With vitamin K in the model | |||||||
---|---|---|---|---|---|---|---|---|---|
DF | Beta | SE | P | STB | Beta | SE | P | STB | |
Intercept | 1 | 2.28866 | 0.25920 | <.0001 | 0 | 2.25771 | 0.25759 | <.0001 | 0 |
Age, y | 1 | -0.00967 | 0.00237 | <.0001 | -0.26396 | -0.01050 | 0.00239 | <.0001 | -0.28653 |
Gender, men vs. women | 1 | 0.05395 | 0.06648 | 0.4182 | 0.05400 | 0.05851 | 0.06598 | 0.3765 | 0.05855 |
BMI, kg/m2 | 1 | 0.01353 | 0.00410 | 0.0012 | 0.21382 | 0.01391 | 0.00407 | 0.0008 | 0.21979 |
Physical activity | 1 | 0.19224 | 0.06730 | 0.0048 | 0.19230 | 0.19744 | 0.06680 | 0.0036 | 0.19750 |
VKOR | 1 | -0.31997 | 0.06511 | <.0001 | -0.31964 | -0.29956 | 0.06544 | <.0001 | -0.29925 |
CYP2C9 | 1 | 0.24312 | 0.07631 | 0.0017 | 0.21245 | 0.24597 | 0.07570 | 0.0014 | 0.21494 |
Energy, kcal/d | 1 | 0.00002598 | 0.00005104 | 0.6114 | 0.03424 | 0.00002234 | 0.00005065 | 0.6598 | 0.02944 |
Vitamin K, μg/d | -- | -- | -- | -- | -- | 0.00050834 | 0.00026368 | 0.0556 | 0.12324 |
Adjusted r2 | 33.2% | 34.3% |
To further explore the potential interaction vitamin K and BMI, we performed analyses stratified by obesity status and with warfarin maintenance dose as the dependent variable. There was no evidence for interaction in either group (P>0.05).
Discussion
Contrary to our hypothesis, we did not observe a significant interaction between vitamin K intake and BMI with regard to warfarin maintenance dose. Consistent with literature, [, ], we confirmed statistically significant associations between warfarin maintenance dose and age, BMI, physical activity and VKORC1 and CYP2C9 genotypes. Unlike other studies that reported a small but significant association between CYP4F2 and warfarin dose [], we only observed a weak association in univariate but not in analyses adjusted for CYP2C9. Furthermore, inclusion of vitamin K to a model with established predictors of warfarin response, only slightly improved the variance explained by covariates (1.1% improvement in model adjusted r2).
The association between vitamin K and warfarin maintenance dose observed in our study was only marginal (P = 0.06) and is consistent with findings from a study by Aquilante et al [] among 350 patients in which they reported a weak association (P=0.05). The relatively low mean intake of vitamin K (127±129 μg/d) in our study compared to others (~250 μg/d) [] could in part explain the weak association we observed.
Our findings are consistent with those of others in which vitamin K from diet or prescription has been associated with higher warfarin maintenance doses [], though the overall contribution of vitamin K is generally small. For instance, in a study that examined genetic factors, diet, physical activity and body weight using multivariate data-reduction techniques, genetic factors explained 52% of the variance in the warfarin maintenance dose while diet, physical activity and body weight only explained 8% []. Although there was a suggestion for a non-linear relationship between vitamin K intake and warfarin maintenance dose in univariate analyses, further analyses with vitamin K as a polynomial term did not reveal evidence for a non-linear relationship.
Our study had limitations. First, vitamin K assessed from DR is subject to measurement error. Vitamin K in plasma is not very stable and thus also subject to measurement error. We averaged multiple DR, an approach which we believe improved our estimate of vitamin K intake. Secondly, only 172 patients had complete data on major determinants of warfarin response (e.g., VKORC1 and CYP2C9). This precluded analyses stratified by more BMI categories so as to better understand the effect of body fat on the relation between vitamin K and warfarin response.
Dov ss simens workbook pdf. This study had a number of strengths including availability of data on genetic polymorphisms known to affect warfarin response e.g., VKORC1, CYP2C9 and CYP4F2. Our analyses adjusted for polymorphisms in these genes and further extended the investigation to potential contribution of the interaction between BMI and vitamin K in explaining variance in warfarin response since genetic polymorphisms only partially explain the variance in the response to warfarin []. Iffmpeg 5 4 0 – convert multimedia files between formats.
Conclusions
We found no interaction between BMI and Vitamin K intake with regard to warfarin response. Vitamin K intake was marginally associated with warfarin response and adding it to the model with standard predictors such as VKORC1 and CYP2C9 genotypes only slightly increased the variance in warfarin response that was explained by the model (change in r2=1.1%). This small improvement in variance explained is consistent with marginal improvement reported for overall diet.
Acknowledgments
This study was supported by grant R01HL092173 from the National Heart, Lung and Blood Institute, National Institutes of Health.
Footnotes
Author contributions
NAL obtained grant support and supervised data collection for this study. All authors contributed to the development of the study concept and design of the analysis plan. EKK analyzed the data and drafted the manuscript. All authors reviewed the data and contributed to the interpretation and editing of the manuscript versions.Conflict of interest
None.