A common mistake is to describe prevalence as incidence cheap 250 mg zithromax otc antibiotics for uti south africa, or vice versa generic zithromax 100mg overnight delivery antibiotic injection for strep, although these terms have different meanings and cannot be used interchangeably buy discount zithromax 500 mg on line virus checker. Incidence is a term used to describe the number of new cases with a condition divided by the population at risk. Prevalence is a term used to describe the total number of cases Rates and proportions 253 with a condition divided by the population at risk. The population at risk is the number of people during the specified time period who were susceptible to the condition. The prevalence of an illness in a specified period is the number of incident cases in that period plus the previous prevalent cases and minus any deaths or remissions. Both incidence and prevalence are usually calculated for a defined time period; for example, for a 1-year or 5-year period. When the number of cases of a condition is measured at a specified point in time, the term ‘point prevalence’ is used. The terms incidence and prevalence should be used only when the sample is selected randomly from a population such as in a cross-sectional or cohort study. Obviously, the larger the sample size, the more accurately the estimates of incidence and prevalence will be measured. When the sample has not been selected randomly from the population such as in some case-control or experimental studies, the terms percentage, proportion or frequency are more appropriate. Tests of chi-square are used to determine whether there is an association between two categorical variables. In health research, a test of chi-square is frequently used to assess whether disease (present/absent) is associated with exposure (yes/no). For example, a chi-square test could be used to examine whether the absence or presence of an illness is independent of whether a child was or was not immunized. Chi-square tests are appropriate for most study designs but the results are influenced by the sample size. The data for chi-square tests are summarized using crosstabulations as shown in Table 8. Tables can have larger dimensions when either the exposure or the disease has more than two levels. In a contingency table, one variable (usually the exposure) forms the rows and the other variable (usually the disease) forms the columns. For example, the exposure immunization (no, yes) would form the rows and the illness (present, absent) would form the columns. The four internal cells of the table show the counts for each of the disease/exposure groups; for example, cell ‘a’ shows the number who satisfy exposure present (immunized) and disease present (illness positive). As in all analyses, it is important to identify which variable is the outcome variable and which variable is the explanatory variable. This can be achieved by either: • entering the explanatory variable in the rows, the outcome in the columns and using row percentages, or • entering the explanatory variable in the columns, the outcome in the rows and using column percentages. A table set up in either of these ways will display the per cent of participants with the outcome of interest in each of the explanatory variable groups. In most study designs, the outcome is an illness or disease and the explanatory variable is an exposure or an experimental group. However, in case–control studies in which cases are selected on the basis of their disease status, the disease may be treated as the explanatory variable and the exposure as the outcome variable. Thus, if repeat data have been collected, for example, if data have been collected from hospital inpatients and some patients have been readmitted, a decision must be made about which data, for example, from the first admission or the last admission, are used in the analyses. The expected frequency in each cell is an important concept in determining P val- ues and deciding the validity of a chi-square test. For each cell, a certain number of participants would be expected given the frequencies of each of the characteristics in the sample. When the expected frequency of cell is less than 5, the significance tests of the Pear- son’s chi-square distribution becomes inaccurate due to the small sample size. Thus, the Pearson’s or continuity-corrected chi-square values should be used only when 80% of the expected cell frequencies exceed 5 and all expected cell frequencies exceed 1. When a chi-square test is requested, most statistics programs provide a number of chi-square values on the output. The chi-square statistic that is conventionally used depends on both the sample size and the expected cell counts as shown in Table 8. Fisher’s exact test is generally calculated for 2 × 2 tables and, depending on the program used, may also be produced for crosstabulations larger than 2 × 2. In a 2 × 2 contingency table, the Pearson’s chi-square produces smaller P values than Fisher’s exact and a type I error may occur. The linear-by-linear test is a trend test and is most appropriate in situations in which an ordered exposure variable has three or more categories and the outcome variable is binary. If the sample size is small or some cells have a low count, the ‘exact’ P values should be reported since the asymptotic P values will be unreliable. The exact calculation based on the exact distribution of the test statistics provides a reliable P value irrespective of the sample size or distribution of the data. The observed count is the actual count in the sample and is shown in each cell of the crosstabulation. The expected count is the expected value due by chance alone and is calculated for each cell as the: Row total × Column total Grand total For cell a in Table 8. The Pearson chi-square value is calculated by the following summation 256 Chapter 8 from all cells: ∑ 2 (Observed count − Expected count) Chi-squared value = Expected count The continuity corrected (Yates) chi-square is calculated in a similar way but with a cor- rection made for a smaller sample size. The null hypothesis for a chi-square test is that there is no significant difference between the observed frequencies and expected fre- quencies. Obviously, if the observed and expected values are similar, then the chi-square value will be close to zero and therefore will not be significant. The larger the observed and expected values are from one another, the larger the chi-square value becomes and the more likely the P value will be significant. This sample was not selected randomly and therefore only percentages will apply and the terms incidence and prevalence cannot be used.

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It is the popular term for the construction and utilization of functional structures with at least one characteristic dimension measured in nanometers (a nanometer is one billionth of a meter i buy 500mg zithromax free shipping antibiotic for uti pseudomonas. Nanobiotechnology is the application of nanotechnology in life sciences and is the subject of a special report (Jain 2015) cheap zithromax 500mg online antibiotics for acne inversa. Role of Nanobiotechnology in Molecular Diagnostics Application of nanobiotechnology in molecular diagnostics is called nanodiagnos- tics and it will improve the sensitivity and extend the present limits of molecular diagnostics (Jain 2005 250 mg zithromax antibiotic use in livestock, 2007). Advances in nanotechnology are providing nanofabricated devices that are small, sensitive and inexpensive enough to facilitate direct observa- tion, manipulation and analysis of single biological molecule from single cell. This opens new opportunities and provides powerful tools in the fields such as genomics, proteomics, molecular diagnostics and high throughput screening. It seems quite likely that there will be numerous applications of inorganic nanostructures in biology and medicine as markers. Given the inherent nanoscale of receptors, pores, and other functional components of living cells, the detailed monitoring and analysis of these components will be made possible by the development of a new class of nanoscale probes. Biological tests measuring the presence or activity of selected substances become quicker, more sensitive and more Universal Free E-Book Store 186 8 Non-genomic Factors in the Development of Personalized Medicine flexible when certain nanoscale particles are put to work as tags or labels. Nanomaterials can be assembled into massively parallel arrays at much higher densities than is achievable with current sensor array platforms and in a format compatible with current microfluidic systems. Currently, quantum dot technology is the most widely employed nanotechnology for diagnostic developments. Cantilevers for Personalized Medical Diagnostics An innovative method for the rapid and sensitive detection of disease- and treatment- relevant genes is based on cantilevers. Short complementary nucleic acid segments (sensors) are attached to silicon cantilevers which are 450 nm thick and therefore react with extraordinary sensitivity. Binding of targeted gene transcripts to their matching counterparts on cantilevers results in mechanical bending that can be optically mea- sured. Differential gene expression of the gene 1-8U, a potential biomarker for can- cer progression or viral infections, can be observed in a complex background. The measurements provide results within minutes at the picomolar level without target amplification, and are sensitive to base mismatches. An array of different gene tran- scripts can even be measured in parallel by aligning appropriately coated cantilevers alongside each other like the teeth of a comb. It could be used as a real-time sensor for continuously monitoring various clinical parame- ters or for detecting rapidly replicating pathogens that require prompt diagnosis. These findings qualify the technology as a rapid method to validate biomarkers that reveal disease risk, disease progression or therapy response. This will have applications in genomic analysis, proteomics and molecular diagnostics. Cantilever arrays have potential as a tool to evaluate treatment response efficacy for personalized medical diagnostics. Nanobiotechnology for Therapeutics Design and Monitoring Current therapeutic design involves combinatorial chemistry and system biology- based molecular synthesis and bulk pharmacological assays. Therapeutics delivery is usually non-specific to disease targets and requires excessive dosage. Efficient therapeutic discovery and delivery would require molecular level understanding of Universal Free E-Book Store References 187 the therapeutics-effectors (e. Characterization of nanocarrier-based drug delivery can enable high efficiency of in vivo or topical administration of a small dosage of therapeutics. Multidimensional atomic force microscopy for drug discovery: a versatile tool for defining targets, designing therapeutics and monitoring their efficacy. Genomics and epigenomics: new promises of per- sonalized medicine for cancer patients. Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis. Personalized exposure assessment: promising approaches for human environmental health research. A circadian gene expression atlas in mammals: implications for biology and medicine. Universal Free E-Book Store Chapter 9 Personalized Biological Therapies Introduction Historically blood transfusion and organ transplantation were the first personalized therapies as they were matched to the individuals. Some cell therapies that use patient’s own cells are considered to be personalized medicines particularly vac- cines prepared from the individual patient’s tumor cells. More recently recombinant human proteins might provide individualization of therapy. The number of biotechnology-based therapeutics introduced in medical practice is increasing along with their use in a personalized manner (Jain 2012). Recombinant Human Proteins There are a large number of therapeutic proteins approved for clinical use and many more are undergoing preclinical studies and clinical trials in humans. Virtually all therapeutic proteins elicit some level of antibody response, which can lead to potentially serious side effects in some cases. Therefore, immunogenicity of therapeutic proteins is a con- cern for clinicians, manufacturers and regulatory agencies. In order to assess immu- nogenicity of these molecules, appropriate detection, quantitation and characterization of antibody responses are necessary. Immune response to therapeu- tic proteins in conventional animal models has not been, except in rare cases, pre- dictive of the response in humans. In recent years there has been a considerable progress in development of computational methods for prediction of epitopes in protein molecules that have the potential to induce an immune response in a recipi- ent. It is expected that computer driven prediction followed by in vitro and/or in vivo testing of any potentially immunogenic epitopes will help in avoiding, or at least minimizing, immune responses to therapeutic proteins. Another approach to protein therapy is in vivo production of proteins by geneti- cally engineered cells where the delivery of proteins can be matched to the needs of the patient and in vivo production and controlled delivery might reduce adverse effects. Therapeutic Monoclonal Antibodies Compared with small-molecule drugs, antibodies are very specific and are less likely to cause toxicity based on factors other than the mechanism of action. Orally available small molecules have many targets but they may also hepatotoxic and are involved in drug-drug interactions. From the point of view of a clean safety profile, antibodies are extremely attractive.

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Thus order zithromax 100mg online treatment for dogs with dementia, whereas simple frequency is the number of times a score occurs cheap zithromax 500mg fast delivery antibiotics for dogs australia, relative frequency is the proportion of time the score occurs 100mg zithromax with visa bacteria gif. We’ll first calculate relative frequency using a formula so that you understand its math, although later we’ll compute it using a different approach. For example, if a score occurred four times (f) in a sample of 10 scores (N), then filling in the formula gives f 4 rel. As you can see here, one reason that we compute relative frequency is simply be- cause it can be easier to interpret than simple frequency. Interpreting that a score has a frequency of 4 is difficult because we have no frame of reference—is this often or not? To transform relative frequency into simple frequency, multiply the relative frequency times N. Converting relative frequency to percent gives the percent of the time that a score occurred. Conversely, to transform percent into relative frequency, divide the percent by 100. Presenting Relative Frequency in a Table or Graph A distribution showing the relative frequency of all scores is called a relative frequency distribution. To create a relative frequency table, first create a simple frequency table, as we did previously. Then the score of 1, for example, has f 5 4, so its relative frequency is 4/20, or. We can also determine the combined relative frequency of several scores by adding their frequencies together: In Table 3. The only novelty here is that the Y axis reflects relative frequency, so it is labeled in increments between 0 and 1. Finding Relative Frequency Using the Normal Curve Although relative frequency is an important component of statistics, we will not emphasize the previous formula. The X and Y axes are laid out on the ground, and the people who received a particular score are standing in line in front of the marker for their score. The lines of people are packed so tightly together that, from the air, you only see the tops of many heads in a “sea of humanity. From this perspective, the height of the curve above any score reflects the number of people standing in line at that score. The height of the curve above any score reflects the number of people standing in line at f that score. Therefore, any portion of the parking lot— any portion of the space under the curve—corresponds to that portion of the sample. Now turn this around: If 50% of the participants obtained scores below 30, then the scores below 30 occurred 50% of the time. This logic is so simple it almost sounds tricky: if you have one-half of the parking lot, then you have one-half of the participants and thus one-half of the scores, so those scores occur. Or, if you have 25% of the parking lot, then you have 25% of the participants and 25% of the scores, so those scores occur. This is how we describe what we have done using statistical terminology: The total space occupied by the everyone in the parking lot is called the total area under the nor- mal curve. We identify some particular scores and determine the area of the correspon- ding portion of the polygon above those scores. We then compare the area of this portion to the total area to determine the proportion of the total area under the curve that we have selected. Then, as we’ve seen, The proportion of the total area under the normal curve that is occupied by a group of scores corresponds to the combined relative frequency of those scores. Of course, statisticians don’t fly around in helicopters, eyeballing parking lots, so here’s a different example: Say that by using a ruler and protractor, we determine that in Figure 3. Say that the area under the curve between the scores of 30 and 35 covers 2 square inches. Therefore, the scores between 30 and 35 occupy 2 out of the 6 square inches created by all scores, so these scores constitute 2>6, or. We could obtain this answer by using the formula for relative frequency if, using N and each score’s f, we computed the rel. However, the advantage of using the area under the curve is that we can get the answer without knowing N or the simple frequencies of these scores. Scores Computing Cumulative Frequency and Percentile 51 In fact, whatever the variable might be, whatever the N might be, and whatever the ac- tual frequency of each score is, we know that the area these scores occupy is 33% of the total area, and that’s all we need to know to determine their relative frequency. This is especially useful because, as you’ll see in Chapter 6, statisticians have created a system for easily finding the area under any part of the normal curve. Therefore, we can easily determine the relative frequency for scores in any part of a normal distribu- tion. If a score occurs 23% of the time, its relative fre- ■ The area under the normal curve corresponds to quency is. They make up of the 15% of people in the parking lot are standing at these area under the normal curve. For example, it may be most informative to know that 30 people scored above 80 or that 60 people scored below 80. When we seek such information, the convention in statistics is to count the number of scores below the score, computing either cumulative frequency or percentile. To compute a score’s cumulative frequency, we fies the scores, the center col- add the simple frequencies for all scores below the score to the frequency for the score, umn contains the simple to get the frequency of scores at or below the score. We add this f to the previous cf for 10, so the cf for 11 is 3 (three people scored at 11 or below 11). Next, no one Score f cf scored at 12, but three people scored below 12, so the cf for 12 is also 3. And so on, each time adding the frequency for a score to the cumulative frequency for the score 17 1 20 16 2 19 immediately below it. Computing Percentiles We’ve seen that the proportion of time a score occurs provides a frame of reference that is easier to interpret than the number of times a score occurs.

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The first interpretation is mainly based upon the remark ‘these things are divine’ (taÓta d’–stª qe±a cheap 250mg zithromax with mastercard xefo antibiotics, 18 buy zithromax 100mg without prescription infection tooth. The author derives the divinity of the disease from the divinity of its causes buy zithromax 250mg with mastercard antibiotic xan, the climatic factors whose influence has been discussed in 10. And since these factors are – as the author claims – the causes of all diseases, all diseases are equally divine, so that none of them should be distinguished from the others as being more divine. It is not stated explicitly in either of these passages in what sense they are human,17 but it has been suggested that diseases are caused (or at least determined in their development) by human factors as well. For these reasons, for instance, the brain (¾ –gk”f- alov) is not mentioned in chapter 18, although the writer had stated ear- lier (3. But in the author’s view all diseases are both divine and human: the explanandum is not that all diseases are human, but in what sense all diseases are divine as well. Among the ‘human’ factors determining the disease we should probably also reckon the individual’s constitution (phlegmatic or choleric: 2. A difficulty of this view is that not all of these factors seem to be accessible to human control or even influence, so that this connotation of anthropinos¯ seems hardly applicable here. Yet perhaps another association of the opposition theios– anthropinos¯ has prompted the author to use it here, namely the contrast ‘universal–particular’, which also seems to govern the use of theios in the Hippocratic treatise On the Nature of the Woman. Firstly, the meaning of the word phusis and the reason for mentioning it in all three passages remains unclear. If, as is generally supposed,20 phusis and prophasis are related to each other in that phusis is the abstract concept and prophasis the concrete causing factor (prophasies being the concrete constituents of the phusis of a disease), then the mention of the word phusis does not suffice to explain the sense in which the disease is to be taken as divine, for the nature of a disease is constituted by human factors as well. It is the fact that some of the constituents of the nature of the disease are themselves divine which determines the divine character of the disease. Secondly, in the sentence ‘it derives its divinity from the same source from which all the others do’ (2. I refrain from a systematic discussion of the concept of the divine in other Hippocratic writings, partly for reasons of space but also because such a discussion would have to be based on close analysis of each of these writings rather than a superficial comparison with other texts. Besides, it is unnecessary or even undesirable to strive to harmonise the doctrines of the various treatises in the heterogeneous collection which the Hippocratic Corpus represents, and it is dangerous to use the theological doctrine of one treatise (e. For general discussions see Thivel (1975); Kudlien (1974); and Norenberg (¨ 1968) 77–86. On the Sacred Disease 53 Âtou kaª t‡ Šlla p†nta), we have to suppose, on this interpretation, that when writing ‘the same source’ (toÓ aÉtoÓ) the author means the climatic factors, whose influence is explained later on in the text (see above) and whose divine character is not stated before the final chapter. Now if a writer says: ‘this disease owes its divine character to the same thing to which all other diseases owe their divine character’, it is rather unsatisfactory to suppose that the reader has to wait for an answer to the question of what this ‘same thing’ is until the end of the treatise. This need not be a serious objection against this interpretation, but it would no doubt be preferable to be able to find the referent of toÓ aÉtoÓ in the immediate context. Thirdly, this interpretation requires that in the sentence ‘from the things that come and go away, and from cold and sun and winds that change and never rest’ (18. In a sequence of four occurrences of kai this is a little awkward, since there is no textual indication for taking the second kai in a different sense from the others. Yet perhaps one could argue that this is indicated by the shift from plural to singular without article, and by the fact that the expression ‘the things that come and those that go away’ is itself quite general: it may denote everything which approaches the human body and everything which leaves it, such as food, water or air, as well as everything the body excretes. Il caracterise d’une part ce qui entre` ´ dans le corps et ce qui en sort, c’est a dire l’air et les aliments, d’autre part le froid, le soleil, les vents,` bref, les conditions climatiques et atmospheriques; c’est donc la nature entiere, consideree comme´ ` ´ ´ une realite materielle qui est proclamee divine. Lloyd reminds me, it could be argued that the divinity of air, water and food need not be surprising in the light of the associations of bread with Demeter, and wine with Dionysus (cf. But even if these associations apply here (which is not confirmed by any textual evidence), the unlikelihood of the divinity of the ‘things that go out of the body’ (t‡ ˆpi»nta) remains. First, in the sentence ‘these things are divine’, it indicates an essential characteristic of the things mentioned, but in the following sentence it is attributed to the disease in virtue of the disease’s being related to divine factors. This need not be a problem, since theios in itself can be used in both ways; but it seems unlikely that in this text, in which the sense in which epilepsy may be called ‘divine’ is one of the central issues, the author permits himself such a shift without explicitly marking it. The point of this ‘derived divinity’ becomes even more striking as the role assigned to the factors mentioned here is, to be sure, not negligible but not very dominant either. Admittedly, the influence of winds is noted repeatedly and discussed at length (cf. This may also help us to understand the use of the word prophasis here; for if the writer of On the Sacred Disease adheres to a distinction between prophasis and aitios, with prophasis playing only the part of an external catalyst producing change within the body (in this case particularly in the brain),24 this usage corresponds to the subordinated part which these factors play in this disease. Then the statement about the divine character of the disease acquires an almost depreciatory note: the disease is divine only to the extent that climatic factors play a certain, if a modest part in 23 13. But the whole question, especially the meaning of prophasis, is highly controversial. Norenberg (¨ 1968), discussing the views of Deichgraber (¨ 1933c) and Weidauer (1954), rejects this distinction on the ground that, if prophasis had this restricted meaning, then ‘durfte der Verfasser bei seiner aufklarerischen Ab-¨ ¨ sicht und wissenschaftlichen Systematik gerade nicht so viel Gewicht auf die prophasies legen, sondern er musste¨ vielmehr von den “eigentlichen” aitiai sprechen’ (67). However, I think that the use of prophasis here (apart from other considerations which follow below) strongly suggests that there are good reasons for questioning this ‘aufklarerische¨ Absicht’. If this is true, it becomes difficult to read this statement as the propagation of a new theological doctrine. Of the three factors mentioned, the sun is least problematic, since the divinity of the celestial bodies was hardly ever questioned throughout the classical period, even in intellectual circles27 – although the focus of the text is not on the sun as a celestial body but rather on the heat it produces (see 10. The divinity of cold ( psuchos) seems completely unprecedented, and the divinity of the winds could only be explained as the persistence of a mythological idea. This is, of course, not impossible, since the author has been shown to have adopted other ‘primitive’ notions as well. Miller (1953) 6–7: ‘The basic question is why these forces or elements of Nature are described as divine. One objection, however, to this interpretation is the fact that this belief in the divinity of winds was frequently connected with magical claims and practices which the author of On the Sacred Disease explicitly rejects as blasphemous in 1. Moreover I am not sure whether the text of Prognostic can bear this interpretation. In the passage in question 56 Hippocratic Corpus and Diocles of Carystus the statement sounds too strange to be accepted as a self-evident idea not needing explanation. Finally, as was already noted by Nestle,31 the restricted interpretation of ‘the divine’ as the climatic factors is absent (and out of the question) in the parallel discussion of the divine character of diseases in chapter 22 of Airs, Waters, Places. Although the writer of Airs, Waters, Places, in accordance with the overall purpose of his treatise, generally assigns to climatic factors a fundamental role in his explanation of health and disease, he does not say anything about their allegedly divine character and surprisingly does not, in his discussion of the divinity of diseases in chapter 22, explain this with an appeal to climatic factors. In the case discussed there (the frequent occurrence of impotence among the Scythians) the prophasies of the disease are purely ‘human’ factors,32 and no influence of climatic factors (gn»nta oÔn crŸ tän paq”wn tän toioÅtwn t‡v fÅsiav, Âkoson Ëp•r tŸn dÅnamin e«sin tän swm†twn, Œma d• kaª e­ ti qe±on ›nesti –n t¦€si noÅsoisin, kaª toÅtwn tŸn pr»noian –kman- q†nein), the distribution of p†qov (or n»shma, which is the varia lectio) and noÓsov suggests that in the author’s opinion the first thing for the physician to do is to identify the nature of the patho- logical situation (which consists in diagnosis and, as the text says, in determining the extent to which the disease exceeds the strength of the patient’s body) and at the same time to see whether ‘something divine’ is present in the disease in question. As the structure of the sentence (the use of the participle gn»nta and of the infinitive –kmanq†nein) indicates, it cannot be maintained (as Kudlien believes) that a distinction is made here between diseases which result in death and diseases of divine, i.