O. Nasib. Shawnee State University.
Within the last few years cheap 1 mg warfarin otc heart attack high 3000 miles from the south, metabolomics has developed into a technology that complements proteomics and transcriptomics buy cheap warfarin 1mg on line arrhythmia ekg strips. In combination with techniques for functional analysis of genes warfarin 1 mg fast delivery blood pressure 160 over 100, it is hoped that a holistic picture of metabolism can be formed. In addition to the genome analysis and proteome analyses, the exhaustive analysis of metabolites is important for a comprehensive understanding of cellular functions because the dynamic behavior of metabolites cannot be predicted without information regarding metabolome. In view of the chemical and physical diversity of small biological molecules, the challenge remains of developing protocols to gather the whole ‘metabolome’. No single technique is suitable for the analysis of different types of molecules, which is why a mixture of techniques has to be used. In the ﬁeld of metabolomics, the gen- eral estimations of the size and the dynamic range of a species-speciﬁc metabolome are at a preliminary stage. Metabolic ﬁngerprinting and metabonomics with high sample throughput but decreased dynamic range and the deconvolution of individ- ual components achieve a global view of the in vivo dynamics of metabolic Universal Free E-Book Store 172 7 Role of Metabolomics in Personalized Medicine networks. However, it is important to note that each type of technology exhibits a bias towards certain compound classes, mostly due to ionization techniques, chromatog- raphy and detector capabilities. Ultracomplex samples contain hundreds of co-eluting compounds that vary in abun- dance by several orders of magnitude. Urinary Proﬁling by Capillary Electrophoresis Metabolomic approaches have become particularly important for discovery of bio- markers in urine. The analytical technology for urinary proﬁling must be efﬁcient, sensitive and offer high resolution. These proﬁles have been visualized using novel advanced pattern recognition tools. The method has been applied in investigation of biomarkers characteristic of alcoholics or Down’s syndrome persons. Lipid Proﬁling Modern medicine has come to rely on a small suite of single biomarkers, such as plasma cholesterol or triglycerides, to assess the risk of certain diseases. However, such single-biomarker assessments overlook the inherent complexity of metabolic disorders involving hundreds of biochemical processes. Assessing the full breadth of lipid metabolism is what drives the ﬁeld of lipomic proﬁling. However, unlike the other “-omics” technologies, in which only a small portion of the genes or proteins is known, lipid metabolic pathways are well characterized. Another limitation of “-omics” technologies is that they produce so many false positive results that it is difﬁcult to be sure that ﬁndings are valid. Metabolomics is not immune to this prob- lem but, when practiced effectively, the technology can reliably produce knowledge to aid in decision making. Focused metabolomics platforms, which restrict their target analytes to those measured well by the technology, can produce data with properties that maximize sensitivity and minimize the false discovery problem. TrueMass® (Lipomic Technologies) analysis produces lipomic proﬁles − comprehensive and quantitative lipid metabolite proﬁles of biological samples. With TrueMass, Lipomics measures hundreds of lipid metabolites from each small quantity of tissue, plasma or serum sample. Because the resulting data are quantitative, TrueMass data can be seam- lessly integrated with pre-existing or future databases. No separation of lipids is required, and the accuracy of identiﬁcation and quantiﬁcation is not compromised, compared to conventional precursor and neutral loss scanning. Role of Metabolomics in Biomarker Identiﬁcation and Pattern Recognition Metabolomics research has increased signiﬁcantly over recent years due to advances in analytical measurement technology and the advances in pattern recognition soft- ware enabling one to visualize changes in levels of hundreds or even thousands of Universal Free E-Book Store 174 7 Role of Metabolomics in Personalized Medicine chemicals simultaneously. Multivariate metabolomic and proteomic data and time- series measurements can be combined to reveal protein-metabolite correlations. Different methods of multivariate statistical analysis can be explored for the inter- pretation of these data. Biomarkers that are responsible for these different biological characteristics can easily be classiﬁed because of the optimized separation using independent compo- nents analysis and an integrated metabolite-protein dataset. Evidently, this kind of analysis depends strongly on the comprehensiveness and accuracy of the proﬁling method, in this case metabolite and protein detection. Assuming that the techniques will improve, more proteins and metabolites can be identiﬁed and accurately quanti- ﬁed, the integrated analysis will have great promise. Validation of Biomarkers in Large-Scale Human Metabolomics Studies A strategy for data processing and biomarker validation has been described in a large metabolomics study that was performed on 600 plasma samples taken at four time points before and after a single intake of a high fat test meal by obese and lean subjects (Bijlsma et al. Such metabolomics studies require a careful ana- lytical and statistical protocol. A method combining several well-established statis- tical methods was developed for processing this large data set in order to detect small differences in metabolic proﬁles in combination with a large biological varia- tion. The strategy included data preprocessing, data analysis, and validation of sta- tistical models. Univariate plots of potential biomarkers were used to obtain insight in up- or down-regulation. Pharmacometabonomics A major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is inﬂuenced not only by genotype but also by environ- mental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Metabolite patterns Universal Free E-Book Store Metabonomic Technologies for Toxicology Studies 175 that are characteristic of the individual can be used to diagnose diseases, predict an individual’s future illnesses, and their responses to treatments. The principle of pharmacometabonomics has been demonstrated in humans by showing a clear connection between an individual’s metabolic phenotype, in the form of a predose urinary metabolite proﬁle, and the metabolic fate of a standard dose of the widely used analgesic acetaminophen (Clayton et al. The predose spectra were statistically analyzed in relation to drug metabolite excre- tion to detect predose biomarkers of drug fate and a human-gut microbiome come- tabolite predictor was identiﬁed. Thus, the investigators found that individuals having high predose urinary levels of p-cresol sulfate had low postdose urinary ratios of acetaminophen sulfate to acetaminophen glucuronide. They conclude that, in individuals with high bacterially mediated p-cresol generation, competitive O-sulfonation of p-cresol reduces the effective systemic capacity to sulfonate acet- aminophen. Given that acetaminophen is such a widely used and seemingly well- understood drug, this ﬁnding provides a clear demonstration of the immense potential and power of the pharmacometabonomic approach. However, many other sulfonation reactions are expected to be similarly affected by competition with p-cresol and these ﬁnding also has important implications for certain diseases as well as for the variable responses induced by many different drugs and xenobiotics. It is proposed that assessing the effects of microbiome activity should be an integral part of pharmaceutical development and of personalized health care. Furthermore, gut bacterial populations might be deliberately manipulated to improve drug efﬁ- cacy and to reduce adverse drug reactions. Pharmacometabonomics could be used to preselect volunteers at key stages of the clinical trials. This would enable stratiﬁ- cation of subjects into cohorts, which could minimize the risk of adverse events, or focus on those individuals with a characteristic disease phenotype for assessment of efﬁcacy. Metabonomic Technologies for Toxicology Studies Metabonomics studies demonstrate its potential impact in the drug discovery pro- cess by enabling the incorporation of safety endpoints much earlier in the drug discovery process, reducing the likelihood (and cost) of later stage attrition. Global metabolic proﬁling (metabonomics/metabolomics) has shown particular promise in the area of toxicology and drug development. A metabolic proﬁle need not be a comprehensive survey of composition, nor need it be completely resolved and assigned, although these are all desirable attributes.
To describe the amount of prediction error we expect when predicting unknown scores buy 5mg warfarin amex blood pressure questions and answers, we first determine how well we can predict the actual Y scores in our sample: We pretend we don’t know the scores order warfarin 5 mg with visa pulse pressure formula, predict them order 1 mg warfarin visa heart attack kit, and then compare the predicted Y¿ scores to the actual Y scores. The error in a single prediction is the amount that a participant’s Y score differs from the corresponding predicted Y¿ score: In symbols this is Y 2 Y¿, and it is literally the dif- ference between the score a participant got and the score we predict he or she got. The predictions for some participants will be closer to their actual Y scores than for others, so we would like to compute something like the average error across all predictions. To find the average error, we first compute Y¿ for everyone in the sample and sub- tract their Y¿ from their actual Y score. Statisticians equate errors with deviations, so Describing Errors in Prediction 169 Y 2 Y¿ equals the amount that Y deviates from Y¿. To get the average error, we would like to simply sum these deviations and then find the average, but we cannot. Therefore, the Ys are equally spread out around their Y¿ scores, in the same way that previously we saw that Xs are spread out around their X. Because of this, like with the mean, the positive and nega- tive deviations with Y will cancel out, always producing a sum equal to zero. The sum of the squared deviations of Y 2 Y¿ is not necessarily zero, so neither is the average squared deviation. Computing the Variance of the Y Scores Around Y9 The variance of the Y scores around Y¿ is the average squared difference between the actual Y scores and their corresponding predicted Y¿ scores. The S2 indicates sample variance or error, and the subscript Y¿ indi- Y¿ cates that it is the error associated with using Y¿ to predict Y scores. The formula that defines the variance of the Y scores around Y¿ is ©1Y 2 Y¿ 22 S2 5 Y¿ N Like other definitional formulas we’ve seen, this formula is important because it shows the core calculation involved: We subtract the Y¿ predicted for each participant from his or her actual Y score giving us a measure of our error. The answer is one way to measure roughly the “average” amount of error we have when we use linear regression to predict Y scores. Note: Among the approaches we might use, the regression procedures described in this chapter produce the smallest error in predictions possible, thereby producing the smallest sum of squared deviations possible. In the defining formula, we can replace Y¿ with the formulas for finding Y¿ (for finding a, b, and so on). Among all of these formulas we’ll find the com- ponents for the following computational formula. The computational formula for the variance of the Y scores around Y9 is S2 5 S2 11 2 r22 Y¿ Y Much better! Therefore, finish the computations of S2 using the formula at the begin- Y ning of this chapter. Although this variance is a legitimate way to compute the error in our predictions, it is only somewhat like the “average” error, because of the usual problems when interpreting variance. First, squaring each difference between Y and Y¿ produces an unrealistically large number, inflating our error. Second, squaring produces error that is measured in squared units, so our predictions above are off by 2. To distinguish the standard deviation found in regression, we call it the standard error of the estimate. Computing the Standard Error of the Estimate The standard error of the estimate is similar to a standard deviation of the Y scores around their Y¿ scores. It is the clearest way to describe the “average error” when using Y¿ to predict Y scores. By computing the square root, the answer is a more realistic number and we are no longer dealing with a squared variable. The core calcu- lation, however, is still to find the error between participants’ actual Y scores and their predicted Y¿ scores, and this is as close as we will come to computing the “average error” in our predictions. Then we find the square root of the quantity 1 2 r2 and then multiply it times the standard deviation of all Y scores. Therefore, we conclude that when using the regression equation to predict the number of widgets produced per hour based on a per- son’s widget test score, when we are wrong, we will be wrong by an “average” of about 1. It is appropriate to compute the standard error of the estimate anytime you compute a correlation coefficient, even if you do not perform regression—it’s still important to know the average prediction error that your relationship would produce. The symbol for the variance of the Y scores around errors in prediction when using regression, which Y¿ is ______. Y¿ Y¿ Interpreting the Standard Error of the Estimate In order for S (and S 2) to accurately describe our prediction error, and for r to accu- Y¿ Y¿ rately describe the relationship, you should be able to assume that your data generally meet two requirements. Homoscedasticity occurs when the Y scores are spread out to the same degree at every X. Because the vertical spread of the Y scores is constant at every X, the strength of the relationship is relatively constant at both low Xs and at high Xs, so r will accurately describe the relationship for all Xs. Further, the vertical distance sepa- rating a data point above or below the regression line on the scatterplot is a way to visualize the difference between someone’s Y and the Y¿ we predict. Heteroscedasticity occurs when the spread in Y is not equal throughout the relationship. Now part of the relationship is very strong (forming a nar- row ellipse) while part is much weaker (forming a fat ellipse). Therefore, r will not accurately describe the strength of the relationship for all Xs. Second, we assume that the Y scores at each X form an approximately normal distri- bution. That is, if we constructed a frequency polygon of the Y scores at each X, we should have a normal distribution centered around Y¿. Recall that in a normal distribution approximately 68% of the scores fall between ;1 standard deviation from the mean. The Strength of a Relationship and Prediction Error Finally, although the standard error of the estimate is the way to quantify our “average” prediction error, be sure you understand why this error is communicated by the size of r. A larger r indicates a stronger relationship and the strength of a relationship determines the amount of prediction error that occurs. This is because the strength of a relationship is the amount of variability—spread—in the Y scores at each X. Thus, there is small vertical spread in the Ys at each X, so the data points are close to the regression line. When the data points are close to the regression line it means that participants’ actual Y scores are relatively close to their corresponding Y¿ scores. Therefore, we will find relatively small differences between the participants’ Y scores and the Y¿ we predict for them, so we will have small error, and S and S2 Y¿ Y¿ will be small. This indicates that the Y scores are more spread out vertically around the regression line. Therefore, more often, participants’ actual Y scores are farther from their Y¿ scores, so we will have greater error, and S and S2 will be larger. This is why, as we Y¿ Y¿ saw in the previous chapter, the size of r allows us to describe the X variable as a good or poor “predictor” for predicting Y scores. When r is large, our prediction error, as measured by S or S2 is small, and so the X variable is a good predictor. However, Y¿ Y¿ when r is smaller, our error and S or S2 will be larger, so the X variable is a poorer Y¿ Y¿ predictor.
Shiel who discovered it or who was the first to Erection is reversed when muscles in the penis con- describe and clearly delineate it order warfarin in india blood pressure medication helps ed. It is a particular danger to anatomy safe warfarin 2mg hypertensive retinopathy, mechanics buy discount warfarin 2 mg on-line blood pressure medication depression side effects, physiology, and psychology to people with compromised immune systems, includ- utilize human energy most effectively. Treatment is with antiviral med- is ergonomic is designed for safe, comfortable, and ication and rest. A injury, drug side effects, or a disorder that impairs form of ergot was also the original basis for the the nerve supply or the blood flow to the penis. Other forms of impotence include lack of sexual desire and problems with ejaculation and orgasm. Erotomania can be a symptom of schizophrenia or other psychiatric erection, penile The state of the penis when it is disorders that are characterized by delusional filled with blood and becomes rigid. Impulses from the brain errors of metabolism, inborn See metabolic and local nerves cause the muscles of the corpora disease. Treatment methods include observation, topical ointments, and surgical erythema chronicum migrans The classic ini- techniques including laser surgery. In the early phase of ery- thema chronicum migrans, within hours to weeks of erythropoietin A hormone that is produced by the tick bite, the local skin develops an expanding the kidney and promotes the formation of red blood ring of unraised redness. Erythema nodosum may duced for use in persons with anemia due to kidney be self-limited. It has been misused as ing condition is treated, and treatment is simultane- a performance-enhancing drug in endurance ath- ously directed toward the erythema nodosum itself. The risk of cancer of the esophagus is throleukemia, the body produces large numbers of increased by long-term irritation of the esophagus, abnormal, immature red blood cells. Very small tumors in the esoph- erythromycin An antibiotic that is commonly agus usually do not cause symptoms. Erythromycin grows, the most common symptom is difficulty in prevents bacteria from producing proteins and swallowing. There may be a feeling of fullness, pres- interferes with bacterial growth and multiplication. Cancer of the esophagus can also cause indigestion, heartburn, vomiting, and frequent choking on food. Treatment includes chemother- esophagogastroduodenoscopy See endoscopy, apy and sometimes surgery. In an adult, the esophagus obstruction of the esophagus occurs when food is about 25 centimeters (10 inches) long. Attempts to relieve the obstruction by induc- Glands in the lining of the esophagus produce ing vomiting at home are usually unsuccessful. Endoscopy is usually used to retrieve the obstruc- esotropia A condition in which a person is tion and relieve the condition. When linoleic acid is loon is then inflated, thereby opening the narrowing obtained in the diet, it can be converted to both caused by the stricture. Linoleic acid is inserting tapered dilators of different sizes through the commonly found in cold-pressed oils, especially mouth and into the esophagus to dilate the stricture. However, arachnoidic acid may lower the digestive juices secreted by the stomach cells. Ulcer pain may not correlate with the presence or essential oil An oil derived from a natural sub- severity of ulceration. Diagnosis is made through bar- stance, usually either for its healing properties or as ium X-ray or endoscopy. Treatment includes the-counter or “holistic” remedies, are based on or using antibiotics to eradicate H. Eugenics is from a helps control and guide sexual development, includ- Greek word meaning “normal genes. It Albert Einstein’s sperm to conceive a child by artifi- also influences the course of ovulation in the monthly cial insemination would represent an attempt at menstrual cycle, lactation after pregnancy, aspects of positive eugenics. It is changes naturally over the female lifespan, reaching important to note that no experiment in eugenics adult levels with the onset of puberty (menarche) and has ever been shown to result in measurable decreasing in middle age until the onset of improvements in human health. Estrogen deficiency can lead to lack of menstruation (amenorrhea), persistent difficulties eukaryote An organism that consists of one or associated with menopause (such as mood swings more cells with a nucleus and other well-developed and vaginal dryness), and osteoporosis in older age. Eukaryotes include all organisms In cases of estrogen deficiency, natural and synthetic except bacteria, viruses, and blue-green algae, estrogen preparations may be prescribed. In humans, the euploid number of chromosomes is 46; with the notable exception of estrogen-associated blood clots See estro- the unfertilized egg and sperm, in which it is 23. Eustachian tube The tube that runs from the estrogen-associated hypercoagulability middle ear to the pharynx. The function of the Hyper-coagulable blood (a supranormal tendency Eustachian tube is to protect, aerate, and drain the for blood to clot) occurs as an occasional but seri- middle ear and mastoid. The blood clots mits the gas pressure in the middle ear cavity to in this situation are dose-related; that is, they occur adjust to external air pressure. All descending in an airplane, the Eustachian tube estrogen therapy preparations carry this risk. Eustachian tube can lead to the development of mid- dle ear infection (otitis media). The Eustachian tube measures only 17 to 18 mm, and it is horizontal at etiology The study of causes, as in the causes of a birth. In medicine, exacer- opening in an adult is significantly below the tym- bation may refer to an increase in the severity of a panic opening, found in the middle ear near the disease or its signs and symptoms. The shorter length and the horizontal ori- exacerbation of asthma might occur as a serious entation of the Eustachian tube in infancy protects effect of air pollution, leading to shortness of breath. The Eustachian tube in the adult is opened by two muscles, the tensor palati exam, rectal See digital rectal exam. Also known contrast, a rash on the inside of the body (for exam- as otopharyngeal tube because it connects the ear to ple, inside the mouth) is called enanthem. For example, a scalpel evening primrose oil A natural source of essen- or laser beam may be used to excise a tumor. Exclamation grate clinical expertise with the research evidence point hair is a key diagnostic finding in a disorder and patient values. An exercise treadmill permits the detection of unique and essential: There is not an extra copy of abnormal heart rhythms (arrhythmias) and pro- that gene with which evolution can tinker, and vides a screening test for the presence of narrowed changes in the gene are likely to be lethal. Narrowing of these arteries can limit the supply of oxygenated evolutionarily conserved sequence A base blood to the heart muscle during exercise. For example, Marfan syndrome shows vari- soles in psoriasis, Kawasaki disease, and Reiter syn- able expressivity. In the latter case, the most common expulsion, stage of The second stage of labor, exfoliating methods are sanding and chemical peels. The exocrine extension The process of straightening or the glands include the salivary glands, sweat glands, and state of being straight. For example, insulin taken by a diabetic is from the head, brain, face, and neck and convey exogenous insulin. An exon is the the sternocleidomastoid muscle, passes down the protein-coding part of a gene. Also known as exter- extrapyramidal side effects Physical symp- nal strabismus and, pejoratively, walleye.