One metric especially stands out —positive predictive value for D. melanogaster was nearly 95% . In other words, given that an 11-day egg-laying segment of this species is classified as terminal, there is nearly a 95% chance that this classification is correct. The value of this performance metric in this fruit fly species contrasts to that for the values from data on the tephritid species where it ranged between around 66% to just under 75% depending on species and whether the database was complete or censored.We believe that there were a number of important results from this study. The first was the revelation that daily egg-laying patterns in fruit flies can be used to distinguish periods in a female fly’s life that end in death from those that do not . Most of the previous analyses and models concerned with individual-level egg laying in fruit flies at or near the end of life focused primarily on classification of end-of-life stage such as senescent, terminal or retired stage. Our approach differed in that we made specific predictions that could be quantified according to performance metrics. A second important result was that the overall performance metrics such as precision, container raspberries accuracy and false positives and negatives were heavily species-dependent. This was because of between-species differences in the consistency of egg laying patterns in both the midlife and terminal segments.
Among the three species the best performing metrics including accuracy and precision were those produced using data on D. melanogaster. A third important outcome of our study was that it shed important light on the challenges inherent in predicting the timing of death. As we noted earlier, one reason for some of the low-performing metrics was that the egg-laying patterns indicative of flies that are at the end of their lives are also present in midlife. Consequently the segments in which these occur are misclassified as terminal rather than midlife. Another problem of misclassification occurred when flies either died at the height of their egg laying or very old flies produced larger numbers of eggs close to their day of death. In other words, patterns of egg laying that were more common in midlife than at or near the end of life. These types of misclassifications were rare in D. melanogaster but occurred around one third of the time in the Mexfly as was reflected in the much higher rates of false negatives for this species relative to the other two. A fourth important and what we consider to be the overarching outcome of our study was “proof-of-principle”—patterns of reproduction at the individual level contain information that can be used to predict impending death in fruit flies. This general finding is important since it suggests that there are likely identifiable individual-level age-specific life history data ranging from information on respiratory, metabolic and locomotor activity to sleep, circadian, and mating patterns that can be used singly or in various combinations to predict the timing of death, not only in fruit flies, but in a range of other organisms including in humans.
Indeed, the egg laying patterns we used to identify impending death may be the rudimentary equivalents of clinical prediction rules in humans used to calibrate the timing of deaths across age groups and between sexes. A unique strength of our study was in its multi-level comparisons involving two different fruit fly families , two different genera within one of these families and three different species overall . Our results demonstrated that the same independent variables could be used across families, genera and species to classify egg-laying segments ; but that the performance metrics such as accuracy and precision were family-, genus- and species-dependent. A caveat that applies to all studies like ours involving contingency tables is that performance metrics including PPV and NPV depend upon the relative numbers of positive and negative cases. Because the proportion of negatives influences the number of both false positives and true negatives, as the proportion of negatives increases, PPV decreases and NPV increases. For example, in disease epidemiology the if the prevalence of infection were low, the PPV might be very small but will be much larger in a population with moderate or high prevalence. So the fraction of true positives relative to false positives will be lower in the former hypothetical scenario than in the latter but in both cases the TPR remains the same.
This sample size-dependent relationship for some performance metrics in the contingency table was one of the primary reasons we used equal numbers of mid life and terminal segments for each fruit fly species rather than the number of mid-life segments possible for each species. For example, after a 10-day maturation period, flies that live 25, 50 and 100 days each have only a single 11-day terminal segment but 4, 29 and 68 possible mid-life 11- day segments, respectively. Because both the cohort sizes and life expectancies differed among the three fly species, the relative numbers of possible mid-life versus terminal 11-day segments also differed. Thus using different relative numbers of mid-life versus terminal segments for each species rather than equal numbers would have confounded comparisons. This perspective underscores the caution required in the interpretation of contingency table performance metrics such as sensitivity and specificity where one is much higher than theother. Indeed, this is the case for the Medfly and Mexfly in which sensitivity ranges from 40 to 60% for both but specificity is substantially higher for both species—i.e., 90 and 70%, respectively. This we conclude that our findings are robust but that the specific values of the performance metrics are subject aspects of the sample including size and details such as segment length. An entirely different aspect of this large concept and one we don’t address in this study is that of distinguishing between mid-life and terminal segments when, for example, age-specific reproductive patterns are altered by changing food quality modifying availability . We believe that research on the classification and timing of death in non-human species has the potential to provide important insights into approaches on similar research in humans. This includes research in contexts ranging from estimations of time to death after withdrawal of life-sustaining treatment in patients including for organ transplants , in nursing homes where 50% die within 3 years and over 30% need palliative care within a year , in hospice end-of-life care where one of the key criteria for entry and Medicare eligibility is that the patient has 6 months or less to live if the disease takes its natural course , and for physicians and their patients who are considering euthanasia for what is referred to as “dying on time” for dementia patients who may not wish to continuing living in advanced stages of any number of dementia-related diseases, but the symptoms conflict with the due care criteria . Lowbush “wild” blueberries are considered a nutrient-rich healthy food, due in large part to their exceptional phenolic content and antioxidant activity. Lowbush blueberries are particularly rich in anthocyanins and the anthocyanin profile is complex compared with other fruits. They contain five of the six anthocyanidins commonly found in nature , which can have three different sugar moieties attached as well as acyl groups such as acetyl-, malonyl-, or coumaryl- also attached to the sugar moieties. Blueberries are also rich in proanthocyanidins, chlorogenic acid, and flavonols. Diets rich in blueberries or their polyphenolic-rich extracts have been associated with lower cardiovascular risk, weight gain and metabolic syndrome, draining pots and neurological diseases . In addition, studies involving blueberries have identified polyphenolic-derived phenolic acids that improve cell differentiation and proliferation of osteoblasts in vitro and promote bone growth and limit bone loss in rodents. These health-promoting effects are due to a myriad of mechanisms associated with blueberry polyphenolics, including prevention of oxidative stress and inflammation, and vaso- and lipid modulation.
Many human studies reporting positive health outcomes have used freeze-dried wild blueberry powder, which is a natural source of concentrated polyphenolics. However, the freeze-dried WBB powder may be tart or astringent and not always palatable to consume. This can be problematic in feeding trials in children and adults. In our previous work, we developed five food products prepared with freeze-dried WBB powder that were evaluated for children’s acceptability and desire to eat . These results are useful in designing food products as well as menu items that could be used in clinical trials of WBB-rich diets. In addition to evaluating sensory properties, it is important to validate the storage stability of polyphenolics in these products, before use in clinical trials, to ensure that a consistent dose of polyphenolics can be maintained. Blueberry polyphenolics, especially anthocyanins, are unstable in various processed forms such as juices, jams, purees, and canned berries when stored at ambient temperature. Additionally, anthocyanins in freeze-dried WBB powder are susceptible to degradation when stored at ambient temperature with a reported half-life of 139 days at 25 ◦C. The mechanism responsible for loss of anthocyanins during storage is unknown, but anthocyanin losses are commonly accompanied by increased polymeric color values, suggesting that anthocyanins form polymers with proanthocyanidins. In addition to polymerization, many other factors can affect the stability of anthocyanins including exposure to elevated temperatures, light, oxygen, metals, sugars, and ascorbic acid. At present, refrigeration of blueberry products such as jam and juices is the best approach to mitigate polyphenolic losses during storage. This study was undertaken to determine the stability of anthocyanins, flavonols, chlorogenic acid, and percent polymeric color in five blueberry products prepared with freeze-dried WBB powder. Gummy, oatmeal bar, graham cracker cookie, and juice were stored at 21 ◦C and 4.4 ◦C and evaluated for anthocyanin, flavonol, and chlorogenic acid content and percent polymeric color over eight weeks of storage. An ice pop product stored at −20 ◦C was evaluated for its anthocyanin and chlorogenic acid content over eight weeks of storage.Samples of juice, ice pop, gummy, oatmeal bar, and graham cracker cookie, each containing 15 g of WBB powder per serving, were prepared and packaged as previously described. One serving of oatmeal bar, ice pop, and graham cracker cookie was equivalent to one piece each , a juice serving was 135 g, and a gummy serving was 7 pieces, or 113 g. The amount of 15 g of WBB powder used in product formulations was calculated and converted from previous animal studies to humans. This involved only the use of brief microwave heating to solubilize the ingredients in order to avoid thermal loss of phenolic compounds, but still obtain a ready-to-consume non-baked product. The blueberry juice and ice pop were prepared with an anthocyanin concentrate, previously extracted from the WBB powder. This procedure was used to produce juice and ice pop products with no particulates. The formulation was adjusted with water so the anthocyanin content ofthe products was equivalent to that found in 15 g of WBB powder per serving. The preparation and processing of the samples for the storage study were performed in two separate experiments, using the same sample of wild freeze-dried blueberries obtained from FutureCeuticals Inc. . The WBB powder was stored at 15.5 ◦C for four months between the two experiments. The samples from Experiment 1 were stored at 21 ◦C and the samples from Experiment 2 were stored at 4.4 ◦C. The ice pop products prepared in Experiment 1 were stored at −20 ◦C. Three samples of each packaged product were evaluated at time 0 and after 2, 4, 6, and 8 weeks of storage.Polyphenolics were extracted by homogenizing 5 g of WBB-containing food product or 1 g of WBB powder in 25 mL of extraction solution containing methanol/water/formic acid , to the smallest particle size using a Euro Turrax T18 Tissuemizer for 1 min. Homogenates were centrifuged for 5 min at 10,864 × g. The pellet was re-extracted two additional times with 25 mL of extraction solution and centrifuged for 5 min at 10,864 × g. The filtrates were pooled and adjusted to 100 mL with extraction solvent in a volumetric flask. Prior to HPLC analysis, 5 mL of extract were dried in a Thermo Savant Speed Vac Plus SC210A and reconstituted in 1 mL 5% formic acid in water. All samples were passed through 0.45 µm nylon syringe filters into 1 mL HPLC vials prior to HPLC analysis.