Cocktail App Mac Serial Number
Garcia Miller
A cocktail is a mixed drink typically made with a distilled liquor (such as arrack, brandy, cachaça, gin, rum, tequila, vodka, or whiskey) as its base ingredient that is then mixed with other ingredients or garnishments. Sweetened liqueurs, wine, or beer may also serve as the base or be added. If beer is one of the ingredients, the drink is called a beer cocktail.
This article is organized by the primary type of alcohol (by volume) contained in the beverage. Cocktails marked with "IBA" are designated as IBA official cocktails by the International Bartenders Association, and are some of the most popular cocktails worldwide.
Some recipes call for a strawberry syrup that can be made using strawberries, vanilla extract, sugar, and water.[6] Some strawberry cocktail recipes do not call for a syrup, but rely on puréed strawberries to play that part.[7]
Carrot juice can be mixed with spirits such as agave spirits, whiskey, tequila, gin, or mezcal. Vodka is sometimes chosen because its neutral taste allows more of the carrot juice taste to shine through. Carrot juice can also be mixed with liqueurs such as amaro. ginger, orange, lemon and honey can be other ingredients in carrot juice cocktails. Turmeric infusions are also common. Examples of drinks made with carrot juice include:[22]
A smash is a casual icy julep (spirits, sugar, and herb)[31] cocktail filled with hunks of fresh fruit, so that after the liquid part of the drink has been consumed, one can also eat the alcohol-infused fruit (e.g. strawberries). The history of smashes goes back at least as far as the 1862 book How to Mix Drinks.[32] The old-style whiskey smash was an example of an early smash.[33]
The herb used in a smash is often mint, although basil is sometimes used in cocktails that go well with it, e.g. many strawberry cocktails. The name "smash" comes from the idea that on a hot day, one takes whatever fruit is on hand and smashes it all together to make a refreshing beverage.[34] Generally a smash will have crushed ice.[35]
A number of hard lemonades, such as Lynchburg lemonade (whose alcoholic ingredient is Jack Daniel's Tennessee whiskey) have been marketed. This section includes drinks that have the ingredients of lemonade (lemon juice and sugar).
Hard cider has been produced by a number of companies, e.g. Woodchuck Hard Cider. Apple-flavored malt beverage products have also been sold by companies like Redd's Apple Ale, but these do not actually contain fermented apple juice.
A ginger soda cocktail is a cocktail with ginger ale or ginger beer. Small Town Brewery produced the 5.90% ABV Not Your Father's Ginger Ale.[95] Coney Island Brewing Co. Henry's Hard Soda produced the 4.2% ABV Henry's Hard Ginger Ale. Others have included Crabbie's Original Alcoholic Ginger Beer (4.8 percent) and Spiced Orange Alcoholic Ginger Beer (4.8 percent), Fentimen's Alcoholic Ginger Beer (4 percent), and New City Ginger Beer (8 percent).[96]
Some cola cocktails are made by the brewer; for example, McAles sells a "hard cola" that is a malt beverage with kola and other natural flavors and caramel color added.[99] Jack Daniel's and Miller Brewing also introduced a hard cola, "Black Jack Cola".[100] Henry's Hard Soda introduced a hard cherry cola.
A tonic cocktail is a cocktail that contains tonic syrup or tonic water. Tonic water is usually combined with gin for a gin and tonic, or mixed with vodka. However, it can also be used in cocktails with cognac, cynar, Lillet Blanc or Lillet Rosé, rum, tequila, or white port.[102]
Drug cocktails are a promising strategy for diseases such as cancer and infections, because cocktails can be more effective than individual drugs and can overcome problems of drug resistance. However, finding the best cocktail comprising a given set of drugs is challenging because the number of experiments needed is huge and grows exponentially with the number of drugs. This problem is exacerbated when the experiments are expensive and the material for testing is rare. Here, we present a way to address this challenge using a mathematical formula, called the pairs model, that requires relatively few experimental tests in order to estimate the effects of cocktails and to predict which cocktail is most effective. The formula does well on experimental data generated in this study using combinations of between 3 and 6 anticancer drugs, as well as on existing data that use combinations of antibiotics.
Funding: European Research Council Executive Agency (grant number 693436) received by UA. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Minerva foundation (grant number 7125960101) received by UA. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Abisch-Frenkel Professorial Chair received by UA. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Israel Science foundation www.ISF.org.il (grant number 1349/15) received by UA. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Currently, there are approximately 1,000 available compounds to treat cancer [14,15]. Testing all combinations at all doses is impossible, because the number of experiments grows exponentially with the number of drugs and doses. Hence, very effective cocktails may be hidden in this vast space of possible combinations [1,6,16,17], as recently demonstrated by Horn et al. in an extensive study of colorectal cancer [5].
Recently, Zimmer and Katzir et al. suggested a model that accurately predicted the multidose response of triplets and quadruplets of antibiotics and cancer drugs [29]. This model requires measurements of each pair of drugs at a few dose combinations. It uses this multidose information to fit a smooth drug response curve for all doses, in which each drug changes the effective dose of the other drugs. This model greatly reduces the number of experiments needed in order to scan the space of drug cocktails at multiple doses.
To address this, we tested all combinations of 6 chemotherapy drugs at a single dose on 2 cell lines (a fully factorial design). We find that synergy and antagonism are cell-line dependent and are usually consistent with the synergy/antagonism of the pairs that make up each combination. We developed a simple model for cocktails that is insensitive to experimental noise and that uses only measurements on drug pairs at a single dose. In addition to the 6-drug combinations, we further tested the model on previous fully-factorial datasets of 3 chemotherapy drugs at 8 doses [29] and of 3 or 4 antibiotics [28], totaling 1,392 additional triplets and 248 quadruplets. The pairs model predicts well the effect of these cocktails, with the limitation that it can only predict effects at the same dose at which the pairs were measured.
We compared the synergy/antagonism of each combination between the 2 cell lines. Fig 1 (and S1 Table) shows each combination plotted by its interaction in HeLa versus H1299. Overall, there is only a moderate correspondence between the interactions in the 2 cell lines (R = 0.16). The higher the combination order, the smaller the correlation between the two cell lines: Two-drug interactions (circles) tend to be more similar between the 2 cell lines (R = 0.5) than triplets (triangles, R = 0.1) and quadruplets (squares, R = 0.08). This indicates that cell-line-specific predictions are needed, especially for the high-order cocktails in this sample, although care is needed with this interpretation due to small number effects and noise.
Circles stand for cocktails of pairs of drugs, triangles for triplets, squares for quadruplets, and stars for cocktails of 5 drugs. The error bars are 95% confidence intervals of the measurements. The number in each shape identifies the cocktail according to the list on the right. CbPt, Carboplatin; CisPt, Cisplatin; CPT, Camptothecin; Etopo, Etoposide; NCZ, Nocodazole.
To address the possibility of using pairs to model the cocktails, we asked whether the synergy/antagonism sign of pairs in a combination is informative with regards to the overall synergy/antagonism sign of the cocktail in a given cell line. For this purpose, we compared the interaction (I) values of each combination of drugs to the interaction of its constituent pairs. The results for triplets are shown in Fig 2 (and S1 Table).
Thus, for triplets, the pairs model is the square root of the product of the 3 pair effects. One feature of the pairs model is that it is less sensitive to experimental noise than most other models in this class, because it uses only data for pairs; other models use both pair and single drug data, increasing the number of variables and hence the sensitivity to noise. Assuming independent multiplicative experimental noise for each measurement with standard deviation σ, the Bliss formula has total experimental noise of , the regression formula has larger noise of , and the pairs formula has noise of only . For triplets (M = 3), for example, these noise terms are , , and times σ for Bliss, regression, and pairs, respectively. The pairs model is expected to be most useful when data is noisy.
This antibiotic data are extensive enough to ask how well the models can rank the combinations in terms of efficacy. Efficacy ranking is of interest if one needs to prioritize potential cocktails based on measuring the pairs. We find that the pairs model shows 85% accuracy in identifying the top 10% most effective triplets (that is, triplets with lowest bacterial growth rate), compared to 75% accuracy in the Isserlis model, 22% for Bliss, and 10% for random (S6 Fig). The regression model shows worse accuracy than random.
In addition to the 6 cancer drug combinations measured here, we also tested the pairs model on an additional 1,640 combinations form previous studies: 280 cocktails of 3 cancer drugs at 8 doses [29], 1,112 cocktails of 3 antibiotics, and 248 quadruplets of antibiotics [28]. The model predicts these combinations reasonably well. The model only works at the measured doses and is not able to predict effects of combinations at doses in which the pairs were not measured.
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