Cannabiscope™ was designed to be the standard in cannabis strain classification. The WHEEL categorizes cannabis strains based on Health ( cannabinoid). Over different types of terpenes have been found in cannabis, each strain having a unique composition. The full interaction of all cannabinoid & terpene. Anyone who's ever explored the surreal world of Amsterdam's cannabis cafes will tell you this: pot is complicated. There are cheesy strains.
My Dad figured he would try it. In fact, he had never felt so good in over 20 years. His friend hooked him up with a doctor specializing in medicinal cannabis.
He sought the assistance of this physician and he prescribed him Phoenix Tears. What a miracle drug! He no longer takes pain killers for his arthritis or fibro-myalgia. No need to since the Phoenix Tears! His cholesterol is substantially lower and his diabetes is under control. I believe it to be a factor of his mental state with the Phoenix Tears.
Has anyone successfully used Medical Marijuana to help with their Depression out there? If so, what strain and how was it administered and how often do you use it? Thank you Tom van Tilburg for the response. Yes, I do suffer from Chronic Depression and I am not into getting high from the Cannabis as I feel impaired and unable to function clearly.
So, I am trying the one puff rule as needed which is maybe once or twice a week in the evening. I also switched meds recently from Veraflaxine to Wellbutrin and maybe this will help. Hi Elk, I realize this comment was made two years ago. I hope all is well with your depression. As a medical user for depression and anxiety myself, I wanted to ask how you felt Wellbutrin combined with your cannabis use was going.
I used cannabis recreational while taking wellbutrin years ago and had negative affects on my body. After quitting pharmaceutical meds and focusing on indica-dominate strains for medical use, I found a type of relief that is similarly compared to that of a miracle.
Canna X is a high CND strain, we make oil from it then turn into candy bars for our cancer patients, one womad is breast cancer free now for a year. I know a lady named Corrie G. She has a resource site called Phoenix Tears. She is well versed in the treatment of most all Cancers. Your prostate type for sure. She is located around Vancouver,BC, Canada. She would d3finitely be able to answer your quwstion and get you pounted in right direction with specific Strain to use, Strength and dosage.
She is very good at following up with you if you keep her updated. So, I am going to try that to help with my depression. I just got approval from the Maryland Marijuana Commission to be notified by their list when the Maryland Medical Marijuana Dispensaries are opened up. I was able to go completely off of Cymbalta, after 20 years of trying to quit antidepressants.
I was never able to because of heroin-like withdrawal symptoms. I take cwhemp hemp oil. I went off of Cymbalta without ANY withdrawal symptoms. I created a page on facebook dedicated to posting good info for anyone who wants to learn about hemp oil.
I smoke a little super silver haze every so often like maybe once a fortnight or so? I find it inspires my creativity too. I see the world through childlike wonder, as though depression never really took hold of me. Experiences like that remind me I am capable of happiness, which -to a suicidally depressed person- is a magnificent feat. Something strong like Essex Gringo perhaps? I have depression issues and prefer a strain with the 1: I also use THC edibles an hour before bed time to keeping me asleep at night …..
It sort of depends for me at least. Girl scout cookies is a great strain that gives you a very happy and euphoric high. I also really enjoy Afghan kush flower. Good views whilst smoking is always a good idea too! It is more than 30 years since I smoked pot.
I can speak of pot without being a recreational user. Colorado has gone a little overboard on legal pot. Once we are honest about medical pot, and yes that part has been established, then we need to look honestly at recreational pot. When legalizing recreational pot we need to be open on both parts.
What are the actual limits we need, and within that question how does it compare to the effects of alcohol. Do you want your surgeon to be smoking?
The guy running an electrical plant? The guy who has to be alert? Will keep you posted. Been searching without much success. Iam new what is best strain for anxiety depression diabetic nerve pain hopefully something for menopause hot flashes. My wife used it to heal the itchy psoriasis she had between her fingers. It took a couple of weeks, but steady use, finally, made it go away.
The results of this study further support the findings of a moderate to high heritability of physical activity and add general genomic areas applicable to a large number of mouse strains that can be further mined for candidate genes associated with regulation of physical activity.
Additionally, results suggest that potential genetic mechanisms arising from traditional noncoding regions of the genome may be involved in regulation of physical activity. However, when directly measured by an accelerometer, only a low percentage of adults participate in moderate activity levels on a daily basis This paradox has led to a suggestion of a significant genetic basis for activity, and in fact a multitude of recent studies have lent support to this hypothesis e.
The heterogeneity of the human genome, the well-known limits on human experimentation, and the difficulty in directly measuring activity in the requisite thousands of subjects have made linkage and other genetic studies with humans difficult.
Thus this large core of conserved genes directly facilitates mouse to human translational efforts. Furthermore, the use of wheel running behavior in rodents as a surrogate for voluntary physical activity behavior in humans is justified by multiple correlates between humans and rodents in responses to voluntary exercise and wheel running, respectively, including similar changes in 1 cardiovascular functioning parameters e.
Furthermore, both humans and mice, when given access to means of voluntary activity, self-select similar levels of exercise intensity during autonomous exercise periods 10 , While there have been several studies that have associated genetic influence with physical activity, the animal studies often have been conducted with only one sex or a limited number of strains, thus reducing the genomic coverage and generality of the results e. For example, Festing 13 collected wheel running data from mice in 26 different strains, but the mice varied in their ages at testing and there was no indication of the sexes involved.
While we used both male and female mice in an initial study from our lab 33 , our initial strain screen only tested a limited number of strains. Since the time of our original strain screen study 33 , the use of computational methods to identify QTL from strain distribution patterns in silico analysis; see Ref.
The use of these computational methods, now generally referred to as haplotype association mapping, has also been spurred by the exponential increase in the availability of denser single-nucleotide polymorphism SNP maps.
In , Grupe et al. This poor coverage led to concerns about the power of the analysis and the potential effect of minor alleles upon the results 7. With the recent availability of a very dense SNP map containing 8. Therefore, the purpose of this project was to apply haplotype association mapping strategies to several wheel running activity traits measured in male and female mice from a large number of inbred strains of mice to expand our knowledge of the genomic locations of QTL associated with physical activity.
The expanded cohort was composed of mice, with female mice and male mice. Upon receipt, the mice were group housed and quarantined until 8 wk of age, at which time they were singly housed and given access to a running wheel. When the mice reached 9 wk of age 63 days , their wheel running data see below were collected for either 7 or 21 consecutive days. Comparison of the four strains that had both 7- and day activity data showed no difference in the average daily activity measures data not shown , and thus all data were pooled for subsequent analysis.
A similar trend toward comparable activity values within strain over the same time period weeks 10—12 in their figures was also noted by Turner et al. Body masses to the nearest 0. At 8 wk of age, a solid-surface running wheel mm in circumference and 35 mm wide interfaced with a computer Sigma Sport BC and BC, Olney, IL was placed in each cage with each individually housed mouse.
The onset of data collection varied depending on the availability of the mice. Using similar methods, we have previously shown 26 wheel running behavior to be highly repeatable in a large cohort of mice. The running wheels required an average mass of 4. Genomic data for each strain were derived from the very dense SNP database developed by Perlegen Sciences This database was subsequently expanded with an additional 40 inbred strains and the use of a hidden Markov model to impute genotypic values.
We partitioned the total variance into within- and between-strain components, and this allowed the calculation both of broad-sense heritability estimates h 2 and coefficients of genetic determination g 2 Reflecting the comparison across the inbred strains i.
There are theoretical and practical advantages of using Bayes factors rather than traditional regression-based methods for QTL determination in strain screens and genomewide association studies GWAS 43 , 48 , One advantage of this approach is that it provides a heightened discrimination of true QTL because of an elimination of the reliance on P values 43 , It is known that P value-based determination of QTL using large genome databases suffers from a statistical tendency to markedly increase the number of false-positive P values because of the effect of large sample sizes and the effect of minor allele frequencies MAF.
The basic effect, however, is that the threshold for significance decreases as the sample size increases. Conversely, Bayes factors used to determine significance thresholds do not vary with sample size, but rather with the predicted prior probability of gene association with each SNP. Previous use of Bayes factors has been limited by the requirement of an accurate prior probability of gene association, but this has been eliminated by recent advances using asymptomatic Bayes factors that do not require the prior distributions to be specified A second and perhaps more relevant advantage of the use of the Bayes factors approach is that it reduces the possible effect of alleles that exist in a few individuals or strains i.
While currently there are no data available in this area that support the general notion of rare alleles having larger effects, the use of P values tends to bias QTL discovery to those alleles existing in lower quantity. Thus the use of traditional, regression-based methods to determine an association of SNPs with a phenotype when the data contain wild-derived strains can bias QTL discovery to the MAF found in the wild-derived strains While this theory is seemingly solid 18 , it is dependent on the MAF threshold used in the analysis, which is normally set at 0.
We interpreted the calculated Bayes factors BF log10 with methods similar to those of Varona et al. A priori we determined that the criterion thresholds for Bayes factors that ranged from 2 to 3 would be considered slight i.
Table 1 shows the characteristics of the mouse cohort used in this study. However, after appropriate adjustment for multiple comparisons, the number of strains showing significant differences between sexes for any of the three activity traits was somewhat limited. Figures 1 — 3 show the strain distribution patterns of distance, duration, and speed across all of the strains, and Table 2 indicates the post hoc statistical differences between the strains in each of the activity indexes.
There was a Similarly, there was a Statistical comparisons of the strain means are in Table 2. Averages and SD for each strain in each activity index are given in Figs. The haplotype association mapping results for distance, duration, and speed are shown in the Manhattan plots in Figs. Each graph consists of four subgraphs: Distance phenotype haplotype association genome scans with full cohort A , without wild-derived strains B , and with male C and female D cohorts.
The dashed line represents a Bayes factor BF log10 of 3. BF log10 within each chromosome is plotted according to base pair location units not shown.
Speed phenotype genome association map on total A , no-wild B , male C , and female D cohorts. Surprisingly, there were virtually no QTL linked with duration in any of the cohorts Fig. Excluding the wild strains from the analysis, speed also showed no significant QTL that associated with both sexes Fig. Duration phenotype genome association map on total A , no-wild B , male C , and female D cohorts. The search for genes underlying physical activity should serve to increase our growing knowledge of the biological mechanisms that exert a significant influence on daily activity.
The present study, which makes use of the largest data set of inbred mouse wheel running activity available, adds to this knowledge base by contributing a multistrain genome map of potential chromosomal sites linked to physical activity.
Specifically, we identified 12 significant QTL linked with different activity traits that exhibit minimal overlap with QTL identified previously in both mouse e. Thus these QTL constitute additional areas to consider for potential candidate genes involved in the regulation of physical activity. A plethora of data have suggested that the heritability of physical activity is significant e. This variability probably reflects both the activity index used and the type of heritability statistic used, but the heritability estimates are generally similar between both human and animal models.
The heritability estimates for the activity traits derived from the present data set 0. While the evidence is strong that activity levels are heritable in both human and animal models, the identity and function of the genetic factors that serve to regulate activity levels are not known. Most attempts to locate such genes have relied on the association of various genetic markers with activity levels.
However, typical human studies require very large genome data sets to provide sufficient power to identify linked genomic loci; this can be observed in the recently published GWAS in 2, Dutch and American subjects using a fairly dense human SNP map 1,, common SNPs; Ref.
While De Moor and colleagues 9 identified three significant QTL associated with exercise participation, the authors suggest that one of the limitations of their study was the lower power with which to detect regions having smaller effects on physical activity. Similar issues arise when considering earlier, smaller GWAS studies in children 4 and in a family cohort of Canadians 42 that provided relatively few significant QTL linked with activity in humans. The animal linkage studies that are available to date are also not immune from lower power to detect QTL.
The present study, that by De Moor and colleagues 9 , and others using a large number of backcross and advanced intercross mice 20 , 24 , 35 have considerably more statistical power than previous studies and should add substantially to the previously identified activity-related QTL.
The QTL that we observed share some genomic localization with previously published QTL from both human and mouse models. Two of the suggestive QTL identified by Simonen and colleagues 42 associated with the amount of moderate and strenuous activity completed 4q Furthermore, an epistatic QTL from the same study Act12epi.
Thus, while our results have added to the potential QTL to be mined for candidate genes that regulate activity, there is also evidence, supported also by the colocalization of GDIST It is interesting that while the estimates of the heritability of physical activity levels fall in the moderate to high ranges, the total number of activity QTL that have been identified are still somewhat limited.
At least three possibilities could account for this phenomenon: It is possible that the three strong QTL we observed explain a large portion of the variance and thus there are relatively few QTL controlling activity traits. In fact, on the basis of on previous intercross data 34 , only four QTL were predicted to be responsible for the regulation of physical activity Thus it seems more probable that all of the models used thus far have been underpowered to detect small-effect QTL, a point that we 29 , 34 and De Moor and colleagues 9 have made previously.
While a strength of the present study was the large number of genetic markers available, unfortunately this strength also imposed a computational limitation that prevented the determination of the epistatic interactions in this data set. A large number of genes have been postulated to be involved in regulation of physical activity based primarily on their functional relevance. Similar to that found by De Moor et al.
It is probable that some of these eight QTL actually include surrounding genes, especially given the larger confidence intervals shown for the sex-specific QTL Table 3. However, none of the annotated genes that fall within the sex-specific QTL confidence intervals has other lines of evidence supporting its role in activity regulation other than speculated functional relevance. Therefore, on the basis of our mapping results alone, we are hesitant to categorize any genes within any of the confidence intervals surrounding our sex-specific QTL as potential candidate genes.
As a pseudogene, Pomc-ps1 is not thought to code for any protein; however, it has been suggested that an unknown gene in the immediate vicinity of Pomc-ps1 may be involved in the translational regulation of the dopamine transporter gene Dat since it colocalizes with a strong QTL affecting Dat expression This result was also noted by De Moor et al.
If future activity QTL localize within intergenic areas, it will further complicate future candidate gene searches by suggesting that at least some of the genetic control of physical activity arises from regulatory sequences that lie in intergenic areas. To this end, it is possible that RNA interference RNAi mechanisms may play an important role in the regulation of physical activity.
Thus whether our identified QTL actually represent direct gene influence on physical activity or mechanisms that modify the genetic process of translation, which in turn affects physical activity, remains an interesting area of inquiry.
Comparison of the activity levels of the inbred strains in this study with other published wheel running data from the same strains 13 , 31 shows that some strains exhibit fairly consistent activity patterns regardless of lab e. However, these comparisons are difficult given that Lerman et al. Furthermore, Festing 13 tested inbred strains without regard for sex of the animal, with a large range of ages 3. Additionally, in an elegant and well-controlled study, Crabbe and colleagues 6 showed that the lab environment, despite rigorous standardization, can influence mouse behavioral responses.
Thus, given the methodology differences and potential unknown environmental influences, it was not surprising that our strain distribution patterns of wheel running activity were not completely similar to previous published research.
However, it should be noted that of the strains we have tested most extensively e. Generally, it has been observed that female mice exhibit more wheel running activity overall than male mice 27 , 33 , We previously hypothesized 34 that sex hormone effects on activity occur primarily downstream of genetic mechanisms.
If so, our previous hypothesis based on a two-strain intercross cohort is not generalizable to all mice. We anticipate that the identification of potential sex-specific genetic mechanisms associated with physical activity regulation will be a fruitful line of research given the general lesser activity levels of human females compared with males in both westernized and hunter-gatherer populations 32 ,
Cannabis strains bring a colorful variety of medicinal effects, but when confronted The below wheel serves as a resource to determine which. A steering wheel is a type of steering control in vehicles and vessels (ships and boats). Steering wheels are used in most modern land vehicles, including all. Originally published in the April/May edition of mg Magazine. Before you name a strain, you need to know the strain name and the brand.