Showing papers on "Incubation published in 2020"
TL;DR: A novel low-cost and accurate method to estimate the incubation distribution of coronavirus disease 2019, where about 10% of patients with COVID-19 would not develop symptoms until 14 days after infection.
Abstract: Summary Background The current outbreak of coronavirus disease 2019 (COVID-19) has quickly spread across countries and become a global crisis. However, one of the most important clinical characteristics in epidemiology, the distribution of the incubation period, remains unclear. Different estimates of the incubation period of COVID-19 were reported in recent published studies, but all have their own limitations. In this study, we propose a novel low-cost and accurate method to estimate the incubation distribution. Methods We have conducted a cross-sectional and forward follow-up study by identifying those asymptomatic individuals at their time of departure from Wuhan and then following them until their symptoms developed. The renewal process is hence adopted by considering the incubation period as a renewal and the duration between departure and symptom onset as a forward recurrence time. Under mild assumptions, the observations of selected forward times can be used to consistently estimate the parameters in the distribution of the incubation period. Such a method enhances the accuracy of estimation by reducing recall bias and utilizing the abundant and readily available forward time data. Findings The estimated distribution of forward time fits the observations in the collected data well. The estimated median of incubation period is 8·13 days (95% confidence interval [CI]: 7·37-8·91), the mean is 8·62 days (95% CI: 8·02-9·28), the 90th percentile is 14·65 days (95% CI: 14·00-15·26), and the 99th percentile is 20·59 days (95% CI: 19·47, 21·62). Compared with results in other studies, the incubation period estimated in this study is longer. Interpretation Based on the estimated incubation distribution in this study, about 10% of patients with COVID-19 would not develop symptoms until 14 days after infection. Further study of the incubation distribution is warranted to directly estimate the proportion with long incubation periods. Funding This research is supported by National Natural Science Foundation of China grant 8204100362 and Zhejiang University special scientific research fund for COVID-19 prevention and control. Research in context Evidence before this study Before the current outbreak of coronavirus disease (COVID-19) in China, there were two other coronaviruses that have caused major global epidemics over the last two decades. Severe acute respiratory syndrome (SARS) spread to 37 countries and caused 8424 cases and 919 deaths in 2002-03, while Middle East respiratory syndrome (MERS) spread to 27 countries, causing 2494 cases and 858 deaths worldwide to date. Precise knowledge of the incubation period is crucial for the prevention and control of these diseases. We have searched PubMed and preprint archives for articles published as of February 22, 2020, which contain information about these diseases by using the key words of “COVID-19”, “SARS”, “MERS”, “2019-nCoV”, “coronavirus”, and “incubation”. We have found 15 studies that estimated the distribution of the incubation period. There are four articles focused on COVID-19, five on MERS, and six on SARS. Most of these studies had limited sample sizes and were potentially influenced by recall bias. The estimates for mean, median, and percentiles of the incubation period from these articles are summarized in Table 1. Added value of this study In the absence of complete and robust contact-tracing data, we have inferred the distribution of the incubation period of COVID-19 from the durations between departure from Wuhan and symptom onset for the confirmed cases. More than 1000 cases were collected from publicly available data. The proposed approach has a solid theoretical foundation and enhances the accuracy of estimation by reducing recall bias and utilizing a large pool of samples. Implications of all the available evidence Based on our model, about 10% of patients with COVID-19 do not develop symptoms until 14 days after infection. Further study of individuals with long incubation periods is warranted.
87 citations
TL;DR: Rival yolk weight and the total solid amount of the residual yolk at hatch seem to be decreased in the recent decades, and it is remarkable that with the genetic progress and improved management and incubation conditions over the last 88 yr, effects on yolk utilization efficiency and embryonic metabolic heat production are limited.
56 citations
01 Jun 2020
TL;DR: Any age‐related change in the incubation period of COVID‐19, specifically any difference between older (aged ≥65 years) and younger adults is explored.
Abstract: Objective The aim of this study was to explore any age-related change in the incubation period of COVID-19, specifically any difference between older (aged ≥65 years) and younger adults. Methods Based on online data released officially by 21 Chinese cities from January 22 to February 15, 2020, the incubation period of COVID-19 patients who had travelled to Hubei was studied according to age. Previous studies were reviewed and compared. Results The study recruited 136 COVID-19 patients who had travelled to Hubei during January 5-31, 2020, stayed for 1-2 days, and returned with symptom onset during January 10-February 6, 2020. The median age was 50.5 years (range 1-86 years), and 22 patients (16.2%) were aged ≥65 years. The age-stratified incubation period was U-shaped with higher values at extremes of age. The median COVID-19 incubation period was 8.3 (90% confidence interval [CI], 7.4-9.2) days for all patients, 7.6 (90% CI, 6.7-8.6) days for younger adults, and 11.2 (90% CI, 9.0-13.5) days for older adults. The 5th/25th/75th/90th percentiles were 2.3/5.3/11.3/14.2 days for all, 2.0/5.0/10.5/13.2 days for younger adults, and 3.1/7.8/14.4/17.0 days for older adults. There were 11 published studies on COVID-19 incubation periods up to March 30, 2020, reporting means of 1.8-7.2 days, and medians of 4-7.5 days, but there was no specific study on the effect of age on incubation period. One study showed that severe COVID-19 cases, which included more elderly patients, had longer incubation periods. Conclusion Based on 136 patients with a travel history to Hubei, the epicenter of COVID-19, the COVID-19 incubation period was found to be longer in older adults. This finding has important implications for diagnosis, prevention, and control of COVID-19.
42 citations
TL;DR: The incubation period of COVID-19 did not follow general incubation distributions such as lognormal, Weibull, and Gamma distributions and it was found that the incubation periods of the groups with age>=40 years and age<40 years demonstrated a statistically significant difference.
Abstract: Motivation: Wuhan pneumonia is an acute infectious disease caused by the 2019 novel coronavirus (COVID-19). It is being treated as a Class A infectious disease though it was classified as Class B according to the Infectious Disease Prevention Act of China. Accurate estimation of the incubation period of the coronavirus is essential to the prevention and control. However, it remains unclear about its exact incubation period though it is believed that symptoms of COVID-19 can appear in as few as 2 days or as long as 14 or even more after exposure. The accurate incubation period calculation requires original chain-of-infection data that may not be fully available in the Wuhan regions. In this study, we aim to accurately calculate the incubation period of COVID-19 by taking advantage of the chain-of-infection data, which is well-documented and epidemiologically informative, outside the Wuhan regions. Methods: We acquired and collected officially reported COVID-19 data from 10 regions in China except for Hubei province. To achieve the accurate calculation of the incubation period, we only involved the officially confirmed cases with a clear history of exposure and time of onset. We excluded those without relevant epidemiological descriptions, working or living in Wuhan for a long time, or hard to determine the possible exposure time. We proposed a Monte Caro simulation approach to estimate the incubation of COVID-19 as well as employed nonparametric ways. We also employed manifold learning and related statistical analysis to decipher the incubation relationships between different age/gender groups. Result: The incubation period of COVID-19 did not follow general incubation distributions such as lognormal, Weibull, and Gamma distributions. We estimated that the mean and median of its incubation were 5.84 and 5.0 days via bootstrap and proposed Monte Carlo simulations. We found that the incubation periods of the groups with age>=40 years and age
30 citations
TL;DR: Wang et al. as discussed by the authors showed that increases in both soil temperature and soil moisture significantly promoted the cumulative CO2 emissions from rice straw during aerobic incubation and during anaerobic incubation, the cumulative emissions of CO2 and CH4 decreased with increasing soil temperature, and the positive priming effect of rice straw on the CO2 emission duration ranged from 75.0% to 274.3%.
Abstract: Paddy soil from a site in northeast China was incubated with 13C-labeled rice straw in a laboratory study, and the effects of soil temperature and moisture on CO2 and CH4 emissions were measured using stable isotope ratio mass spectrometry. Aerobic incubation experiments were conducted at three soil temperatures (−10 °C, 0 °C, and 10 °C) and two soil moistures (60% and 100% water-filled pore space (WFPS)) in a laboratory for 24 weeks to simulate the rice-fallow season. An anaerobic incubation experiment was carried out for 16 weeks under a soil temperature of 25 °C and a 1 cm submerged layer to simulate the rice-growing season. Our results showed that increases in both soil temperature and soil moisture significantly promoted the cumulative CO2 emissions from rice straw during aerobic incubation. Furthermore, during anaerobic incubation, the cumulative emissions of CO2 and CH4 from rice straw decreased with increasing aerobic incubation soil temperature and soil moisture. The CO2 and CH4 emission ratios from rice straw throughout the incubation duration ranged from 6.6–15.7% and 0.0–3.0%, respectively. The addition of rice straw promoted a priming effect on native soil organic carbon (SOC) mineralization and produced CO2 emissions, which positively impacted priming during the aerobic (rice-fallow season) and anaerobic incubation (rice-growing season). The positive priming effect of rice straw on the CO2 emission duration ranged from 75.0% to 274.3% by the end of the 40-week incubation period. Furthermore, the aforementioned effect first increased and then decreased as the aerobic incubation soil temperature increased, with the greatest effect at 0 °C and lowest at 10 °C. These results suggest that high temperature during the rice-fallow season promotes the decomposition of rice straw C and leads to a decreased positive priming effect on native SOC during the rice-fallow and rice-growing seasons under the seasonal conditions of northeast China, and that it also leads to decreased CH4 production during the rice-growing season. These results have scientific significance for rational utilization of rice straw and mitigation of greenhouse effect in northeast China.
27 citations
TL;DR: The long, dispersive incubation period of SARS-CoV-2 contributes to the global spread of COVID-19 and a 14-day quarantine period is sufficient to trace and identify symptomatic infections, which while could be justified according to a better understanding of the crucial parameters.
Abstract: Background The incubation period of SARS-CoV-2 remains uncertain, which has important implications for estimating transmission potential, forecasting epidemic trends, and decision-making in prevention and control. Purpose To estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring. Data Sources PubMed, Embase, medRxiv, bioRxiv, and arXiv, searched up to April 26, 2020 Study Selection COVID-19 studies that described either individual-level incubation period data or summarized statistics for central tendency and dispersion measures of incubation period were recruited. Data Extraction From each recruited study, either individual-level incubation period data or summarized statistics for central tendency and dispersion measures were extracted, as well as population characteristics including sample size, average age, and male proportion. Data Synthesis Fifty-six studies encompassing 4 095 cases were included in this meta-analysis. The estimated median incubation period for general transmissions was 5.8 days [95% confidence interval (95%CI), 5.3 to 6.2 d]. Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections. Furthermore, about 20 in 10 000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10 000 for young-age infections or asymptomatic transmissions. Limitation Small sample sizes for subgroups; some data were possibly used repeatedly in different studies; limited studies for outside mainland China; non-negligible intra-study heterogeneity. Conclusion The long, dispersive incubation period of SARS-CoV-2 contributes to the global spread of COVID-19. Yet, a 14-day quarantine period is sufficient to trace and identify symptomatic infections, which while could be justified according to a better understanding of the crucial parameters.
22 citations
TL;DR: Whether patients infected by community transmission had extended incubation periods than the early generation patients who had direct exposures to Wuhan is examined to imply the decreases of virulence of the COVID-19 virus along with intergenerational transmission.
Abstract: INTRODUCTION: Current studies estimated a general incubation period distribution of COVID-19 based on early-confirmed cases in Wuhan, and have not examined whether the incubation period distribution varies across population segments with different travel histories. We aimed to examine whether patients infected by community transmission had extended incubation periods than the early generation patients who had direct exposures to Wuhan. METHODOLOGY: Based on 4741 patient case reports from municipal centers of disease control by February 21, 2020, we calculated the incubation periods of 2555 patients with clear epidemiological survey information and illness development timeline. All patients were categorized into five groups by their travel histories. Incubation period distributions were modeled for each group by the method of the posterior Weibull distribution estimation. RESULTS: Adults aged 30 to 59 years had the most substantial proportion of confirmed cases in China. The incubation period distribution varied slightly across patient groups with different travel histories. Patients who regularly lived in Wuhan and left to other locations before January 23, 2020 had the shortest posterior median value of 7.57 days for the incubation period, while the incubation periods for persons affected by local community transmission had the largest posterior median of incubation periods, 9.31 days. CONCLUSIONS: The median incubation period for all patients infected outside Wuhan was 9 days, a bit of more extended than the early estimated 5-day incubation period that was based on patients in Wuhan. Our findings may imply the decreases of virulence of the COVID-19 virus along with intergenerational transmission.
19 citations
TL;DR: A predictive model is developed that accurately estimates, solely from several virus genome features, the number of protein-coding genes and the GC content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2 and may help in establishing the appropriate quarantine durations and thus facilitate controlling future outbreaks.
Abstract: A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. At the time of the COVID-19 pandemic, optimization of quarantine regimes becomes paramount for public health, societal well-being, and global economy. However, biological factors that determine the duration of the virus incubation period remain poorly understood. We demonstrate a strong positive correlation between the length of the incubation period and disease severity for a wide range of human pathogenic viruses. Using a machine learning approach, we develop a predictive model that accurately estimates, solely from several virus genome features, in particular, the number of protein-coding genes and the GC content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2. The predictive approach described here can directly help in establishing the appropriate quarantine durations and thus facilitate controlling future outbreaks. The length of the incubation period in viral diseases strongly correlates with disease severity, emphasizing the biological and epidemiological importance of the incubation period. Perhaps, surprisingly, incubation times of pathogenic RNA viruses can be accurately predicted solely from generic features of virus genomes. Elucidation of the biological underpinnings of the connections between these features and disease progression can be expected to reveal key aspects of virus pathogenesis.
19 citations
TL;DR: Older people infected with SARS-CoV2 have longer incubation period than that of younger people, and more attention should be paid to asymptomatic elderly people who had a history of exposure.
Abstract: Background Factors associated with the incubation period of COVID-19 are not fully known. The aim of this study was to estimate the incubation period of COVID-19 using epidemiological contact tracing data, and to explore whether there were different incubation periods among different age gr1oups. Methods We collected contact tracing data in a municipality in Hubei province during the full outbreak period of COVID-19. The exposure periods were inferred from the history of travel in Wuhan and/or history of exposure to confirmed cases. The incubation periods were estimated using parametric accelerated failure time models accounting for interval censoring of exposures. Results The incubation period of COVID-19 follows a Weibull distribution and has a median of 5.8 days with a bootstrap 95% CI: 5.4-6.7 days. Of the symptomatic cases, 95% showed symptoms by 14.3 days (95% CI: 13.0-15.7), and 99% showed symptoms by 18.7 days (95% CI: 16.7-20.9). The incubation periods were not found significantly different between male and female. Elderly cases had significant longer incubation periods than young age cases (HR 1.49 with 95% CI: 1.09-2.05). The median incubation period was estimated at 4.0 days (95% CI: 3.5-4.4) for cases aged under 30, 5.8 days (95% CI: 5.6-6.0) for cases aged between 30 and 59, and 7.7 days (95% CI: 6.9-8.4) for cases aged greater than or equal to 60. Conclusion The current practice of a 14-day quarantine period in many regions is reasonable for any age. Older people infected with SARS-CoV2 have longer incubation period than that of younger people. Thus, more attention should be paid to asymptomatic elderly people who had a history of exposure.
19 citations
TL;DR: Despite some positive effects of I1 incubation on growth after starting under low ambient temperature, this study reveals the limits of such strategy concerning chicken health and welfare, demonstrating that early thermal environment is a major component of the quality and sustainability of chicken meat production.
18 citations
TL;DR: Evidences showed that biochar is best in sequestering soil C pool, followed by straw and roots, and soil microbial groups in utilization of organic substances mediated SOC mineralization, and 13C-labelled PLFA enabled the differentiation of microbial groups during substrates utilization.
TL;DR: The results show that nest moisture and temperature affect embryo mass towards the last third of development, with hatchling size positively correlated with nest moisture content, and maternal origin had a strong impact on hatching success and hatchlings size regardless of the incubation conditions.
Abstract: For reptiles, the incubation environment experienced by embryos during development plays a major role in many biological processes. The unprecedented rate of climate change makes it critical to understand the effects that the incubation environment has on developing embryos, particularly in imperiled species such as chelonians. Consequently, a number of studies have focused on the effects of different environmental conditions on several developmental processes and hatchling phenotypic traits. In addition to the incubation environment, it is also essential to understand how parental contributions can influence hatchling quality. This is the first study that investigates the effects of parental origin and incubation conditions on sea turtle embryonic development and hatchling phenotype in nests incubating in the field (rather than under controlled laboratory conditions). Here, we used the loggerhead sea turtle (Caretta caretta) to investigate the effects of parental origin (clutch), incubation temperature, and the nest hydric environment on embryonic growth, incubation durations, hatching success, and hatchling phenotype. Our results show that nest moisture and temperature affect embryo mass towards the last third of development, with hatchling size positively correlated with nest moisture content, and maternal origin had a strong impact on hatching success and hatchling size regardless of the incubation conditions. The results from this experiment identify multiple factors that affect turtle embryonic development under field incubation conditions, a fundamental consideration when interpreting the potential impacts of climate change on reptilian development.
TL;DR: Parametric and other evaluations of the incubation of food craving reveal manipulations that reduce incubation, including environmental enrichment and pharmacological manipulation of dopamine, glutamate, and endogenous opiates.
Abstract: Incubation of food craving is an abstinence-dependent increase in responding for reward-paired cues. Incubation of craving was first reported for rats responding for cocaine-paired cues, and later generalized to several drugs of abuse and for food. Incubation of drug and food craving has been reported in clinical studies as well. Incubation of food craving by rats has been reported for standard chow as well as for high fat and sucrose reinforcers. Parametric and other evaluations of the incubation of food craving reveal manipulations that reduce incubation, including environmental enrichment and pharmacological manipulation of dopamine, glutamate, and endogenous opiates. Several brain regions are likely involved in the effect, including mesolimbic terminals and the central nucleus of the amygdala. Further study of the incubation of food craving could facilitate development of treatments for cravings that precede relapse characteristic of drug and food addictions.
TL;DR: In this paper, the effects of in ovo injection of nano-selenium (Nano-Se) and nano-zinc oxide (nano-ZnO) and high eggshell temperature (EST) during late incubation on blood parameters of broiler hatchlings were evaluated.
Abstract: . This experiment was conducted to evaluate the effects of in ovo injection of nano-selenium (Nano-Se) and nano-zinc oxide (Nano-ZnO) and high eggshell temperature (EST) during late incubation on blood parameters of broiler hatchlings. A total of 750 fertile eggs, were weighed and randomly distributed among 5 treatment groups on each of 5 replicate tray levels. The injection was performed on 17 d of incubation. Treatments included of: 1) Eggs not injected and incubated at normal EST (control); 2) Eggs not injected and incubated at high EST; 3) Eggs injected NaCl solution and incubated at high EST (sham); 4) Eggs injected NaCl solution containing 40 µg Nano-Se and incubated at high EST; 5) Eggs injected NaCl solution containing 500 µg Nano-ZnO and incubated at high EST. EST of 37.8oC (normal) or 38.9oC (high) was applied from d 19 to 21 of incubation. In ovo injection of Nano-Se and Nano-ZnO significantly increased activity of GSH-Px and SOD and total protein, but decreased the levels of corticosterone, cortisol, T4 and T3 at high EST. Injection of Nano-Se and Nano-ZnO had a significant role in alleviating the negative effects of high temperature incubation and heat stress by increased antioxidant activity and reduced oxidative stress.
TL;DR: The application of transglutaminase to edible insect proteins ultimately increases its functionality and allows for the development of novel insect processing technology.
Abstract: Global concern about food supply shortage has increased interest on novel food sources. Among them, edible insects have been studied as a potential major food source. This study aimed to improve the functional properties of protein solutions extracted from Protaetia brevitarsis (PB) by use of transglutaminase (TG) as a cross-linking agent. After various incubation times (10, 20, 30, 60, and 90 min) with TG, the protein solutions were assessed with regard to their amino acid composition, protein nutritional quality, pH, color (yellowness), molecular weight distribution, thermal stability, foam ability (capacity and stability), and emulsion ability (capacity and stability). Incubation with TG changed the amino acid composition of the proteins and shifted the molecular weight distribution towards higher values, while improving the rest of the aforementioned properties. Since the incubation time for 90 min decreased the protein functionality, the optimum incubation time for cross-linking PB-derived protein with TG is 60 min. The application of TG to edible insect proteins ultimately increases its functionality and allows for the development of novel insect processing technology.
03 Aug 2020
TL;DR: In this article, the authors contribute to the literature on new market emergence by implementing a history-friendly simulation of the incubation period encompassing the decision processes that took place w...
Abstract: In this paper, we contribute to the literature on new market emergence by implementing a “history-friendly” simulation of the incubation period encompassing the decision processes that took place w...
TL;DR: Results suggest that prolactin may be associated with the regulation of parental incubation constancy and resulting heat-transfer after a disturbance, which may ultimately affect offspring development.
TL;DR: It was found that the incubation period of patients with no travel history to Hubei was longer and more volatile and it is recommended that the duration of quarantine should be extended to at least 3 weeks.
Abstract: Objectives Amid the continuing spread of the novel coronavirus (COVID-19), the incubation period of COVID-19 should be regularly re-assessed as more information is available upon the increase in reported cases. The present work estimated the distribution of incubation periods of patients infected in and outside Hubei province of China. Methods Clinical data were collected from the individual cases reported by the media as they were not fully available on the official pages of the Chinese health authorities. MLE was used to estimate the distributions of the incubation period. Results It was found that the incubation period of patients with no travel history to Hubei was longer and more volatile. Conclusion It is recommended that the duration of quarantine should be extended to at least 3 weeks.
TL;DR: The results demonstrate that incubation behaviour as mediated by incubation strategy has important consequences for sandpipers’ reproductive success.
Abstract: Most birds incubate their eggs to allow embryo development. This behaviour limits the ability of adults to perform other activities. Hence, incubating adults trade off incubation and nest protection with foraging to meet their own needs. Parents can either cooperate to sustain this tradeoff or incubate alone. The main cause of reproductive failure at this reproductive stage is predation and adults reduce this risk by keeping the nest location secret. Arctic sandpipers are interesting biological models to investigate parental care evolution as they may use several parental care strategies. The three main incubation strategies include both parents sharing incubation duties (‘biparental’), one parent incubating alone (‘uniparental’), or a flexible strategy with both uniparental and biparental incubation within a population (‘mixed’). By monitoring the incubation behaviour in 714 nests of seven sandpiper species across 12 arctic sites, we studied the relationship between incubation strategy and nest predation. First, we described how the frequency of incubation recesses (NR), their mean duration (MDR), and the daily total duration of recesses (TDR) vary among strategies. Then, we examined how the relationship between the daily predation rate and these components of incubation behaviour varies across strategies using two complementary survival analysis. For uniparental and biparental species, the daily predation rate increased with the daily total duration of recesses and with the mean duration of recesses. In contrast, daily predation rate increased with the daily number of recesses for biparental species only. These patterns may be attributed to two independent mechanisms: cryptic incubating adults are more difficult to locate than unattended nests and adults departing the nest or feeding close to the nest can draw predators’ attention. Our results demonstrate that incubation behaviour as mediated by incubation strategy has important consequences for sandpipers’ reproductive success.
TL;DR: A higher EST in week 2 had minor effects at hatching and during rearing, whereas a lower EST in weeks 3 seemed to result in better organ development, but resulted in lower grow-out performance.
TL;DR: The established primary cell cultures derived from chicken proved to be proper models to study the specific molecular effects caused by T-2 toxin, and showed different levels of H2O2, HSP70, and IL-8 concentrations independently of T- 2 toxin supplementation.
Abstract: Trichothecene mycotoxins such as T-2 toxin cause severe problems for agriculture, as well as for veterinary medicine. As liver is one of the key organs in metabolism, the main aim of our study was to investigate the immunomodulatory and cytotoxic effects of T-2 toxin, using primary hepatocyte mono-culture and hepatocyte—nonparenchymal cell (predominantly Kupffer cell) co-culture models of chicken. Cultures were exposed to 10 (T10 group), 100 (T100 group) and 1000 (T1000 group) nmol/L T-2 toxin treatment for 8 or 24 h. Alterations of cellular metabolic activity, the production of reactive oxygen species (extracellular H2O2), heat shock protein 70 (HSP70), and the concentration of different inflammatory cytokines such as interleukin (IL-)6 and IL-8 were investigated. Metabolic activity was intensely decreased by T-2 toxin administration in all of the cell culture models, in every applied concentration and incubation time. Concentrations of HSP70 and IL-8 were significantly increased in hepatocyte mono-cultures exposed to higher T-2 toxin levels (both in T100 and T1000 groups for HSP70 and in T1000 group for IL-8, respectively) compared to controls after 24 h incubation. Similarly, IL-6 levels were also significantly elevated in the T100 and T1000 groups in both of mono- and co-cultures, but only after 8 h of incubation time. In spite of the general harmful effects of T-2 toxin treatment, no significant differences were observed on reactive oxygen species production. Furthermore, the two cell culture models showed different levels of H2O2, HSP70, and IL-8 concentrations independently of T-2 toxin supplementation. In conclusion, the established primary cell cultures derived from chicken proved to be proper models to study the specific molecular effects caused by T-2 toxin. Metabolic activity and immune status of the different examined cell cultures were intensively affected; however, no changes were found in H2O2 levels.
TL;DR: Higher EST in week 2 during incubation may benefit embryonic immune organ development and posthatch broiler immunocompetence, while lower EST in weeks 3 showed opposite indications.
TL;DR: In this paper, the authors used three parametric forms with Hamiltonian Monte Carlo method for Bayesian Inference to estimate the incubation period of Vietnamese confirmed COVID-19 cases.
Abstract: Objective: To estimate the incubation period of Vietnamese confirmed COVID-19 cases. Methods: Only confirmed COVID-19 cases who are Vietnamese and locally infected with available data on date of symptom onset and clearly defined window of possible SARS-CoV-2 exposure were included. We used three parametric forms with Hamiltonian Monte Carlo method for Bayesian Inference to estimate incubation period for Vietnamese COVID-19 cases. Leave-one-out Information Criterion was used to assess the performance of three models. Results: A total of 19 cases identified from 23 Jan 2020 to 13 April 2020 was included in our analysis. Average incubation periods estimated using different distribution model ranged from 6.0 days to 6.4 days with the Weibull distribution demonstrated the best fit to the data. The estimated mean of incubation period using Weibull distribution model was 6.4 days (95% credible interval (CrI): 4.89-8.5), standard deviation (SD) was 3.05 (95%CrI 3.05-5.30), median was 5.6, ranges from 1.35 to 13.04 days (2.5th to 97.5th percentiles). Extreme estimation of incubation periods is within 14 days from possible infection. Conclusion: This analysis provides evidence for an average incubation period for COVID-19 of approximately 6.4 days. Our findings support existing guidelines for 14 days of quarantine of persons potentially exposed to SARS-CoV-2. Although for extreme cases, the quarantine period should be extended up to three weeks.
TL;DR: If reasonable methods of disinfection, SPF detection and pathogen isolation and utilize optimal egg densities and incubation systems are implemented, large-scale production of SPF seedlings of Cherax quadricarinatus is possible.
TL;DR: Behavioral decisions made during incubation represent life‐history trade‐offs between predation risk and reproductive success on an unpredictable landscape, and are suggested to represent trade-offs between nest and female survival.
Abstract: Females must balance physiological and behavioral demands of producing offspring with associated expenditures, such as resource acquisition and predator avoidance. Nest success is an important parameter underlying avian population dynamics. Galliforms are particularly susceptible to low nest success due to exposure of ground nests to multiple predator guilds, lengthy incubation periods, and substantive reliance on crypsis for survival. Hence, it is plausible that nesting individuals prioritize productivity and survival differently, resulting in a gradient of reproductive strategies. Fine-scale movement patterns during incubation are not well documented in ground-nesting birds, and the influence of reproductive movements on survival is largely unknown. Using GPS data collected from female wild turkeys (n = 278) across the southeastern United States, we evaluated the influence of incubation recess behaviors on trade-offs between nest and female survival. We quantified daily recess behaviors including recess duration, recess frequency, total distance traveled, and incubation range size for each nest attempt as well as covariates for nest concealment, nest attempt, and nest age. Of 374 nests, 91 (24%) hatched and 39 (14%) females were depredated during incubation. Average nest survival during the incubation period was 0.19, whereas average female survival was 0.78. On average, females took 1.6 daily unique recesses (SD = 1.2), spent 2.1 hr off the nest each day (SD = 1.8), and traveled 357.6 m during recesses (SD = 396.6). Average nest concealment was 92.5 cm (SD = 47). We found that females who took longer recess bouts had higher individual survival, but had increased nest loss. Females who recessed more frequently had lower individual survival. Our findings suggest behavioral decisions made during incubation represent life-history trade-offs between predation risk and reproductive success on an unpredictable landscape.
21 Sep 2020
TL;DR: The findings from analysis of the confirmed CO VID-19 cases indicate that age could be associated with the incubation period, and an age-specific quarantine policy might be more efficient than a unified one in confining COVID-19.
Abstract: The incubation period of coronavirus disease 2019 (COVID-19) is not always observed exactly due to uncertain onset times of infection and disease symptoms. In this paper, we demonstrate how to estimate the distribution of incubation and its association with patient demographic factors when the exact dates of infection and symptoms’ onset may not be observed. The findings from analysis of the confirmed COVID-19 cases indicate that age could be associated with the incubation period, and an age-specific quarantine policy might be more efficient than a unified one in confining COVID-19.
TL;DR: The first deep learning model which automated analysis of nest camera video recordings from eight purple martin (Progne subis) nests over the entire incubation period at a 1-s resolution found that attentiveness was mainly affected by ambient temperature, with incubating adults reducing their efforts as ambient temperature reaches the minimum threshold for egg development.
Abstract: Incubation is a key life history stage for birds, and incubation attentiveness can have significant fitness consequences for both parents and offspring. Incubation is, however, a challenging phenomenon to observe and studies generally either measure some proxy of the target behavior, or risk disturbing birds through direct observation. More recently, nest cameras have provided a non-intrusive way to directly observe incubation, but analysis of these data is time-consuming. Here, we use the results of the first deep learning model which automated analysis of nest camera video recordings from eight purple martin (Progne subis) nests over the entire incubation period at a 1-s resolution. We mathematically define the initiation of incubation, characterize the change in nest attentiveness during incubation, and analyze the factors determining nest attentiveness and on- and off-bout duration during the incubation process. A random forest regression model identified the most important predictors of nest attentiveness. Attentiveness decreased with increasing temperature, but the strength of this response increased above the presumed physiological zero egg temperature, below which egg development ceases. This implies that the purple martins are able to adjust their incubation behavior in a complex, multiple-state manner to an extrinsic stimulus. Our study highlights the value of high-resolution datasets created using artificial intelligence for the analysis of nest camera video recordings of animal behavior. The use of artificial intelligence for image classification tasks is becoming commonplace in society. This technology is beginning to be used to automate the analysis of video recordings of wildlife behavior. Here, we use the results of the first such classification from nest camera video recordings of the purple martin (Progne subis) to determine the factors affecting incubation attentiveness (the proportion of time that the adults spend in contact with eggs). Incubation attentiveness is important because it can affect hatch rate and have carry-over effects both for the condition of the incubating adults and the quality of the resulting offspring. Our analysis found that attentiveness was mainly affected by ambient temperature, with incubating adults reducing their efforts as ambient temperature reaches the minimum threshold for egg development.
TL;DR: Findings are the first to show that ITs change the expression of key YST genes, leading to variations in yolk utilization by the embryo, an important parameter for hatchling quality.
TL;DR: An egg turning frequency of 24 times per day during incubation provided high hatchability rates, and in contrast, the turning frequencies of 12, 6, and 3 timesper day showed significant losses in hatchability.
TL;DR: It is suggested that moisture in the nest environment during incubation may influence hatchling performance via their initial hydration levels, although upon entering the ocean hatchlings have the opportunity to rehydrate by drinking and thus, differences in locomotor performance associated with moisture treatments cease.
Abstract: Incubation conditions are critical in determining numerous traits in reptilian neonates. This is particularly significant in species with low offspring survival such as sea turtle species, because of the extremely high predation rates that hatchlings face during their initial dispersal from nesting beaches. Hatchlings that develop in suboptimal nest environments are likely to be smaller, slower and more susceptible to predation than hatchlings from optimal nest environments. Previous studies have focused on the effects of temperature on hatchling traits, but few have investigated the effects of moisture concentrations, despite moisture levels in nests influencing hatchling size, sex, incubation duration, and hatching success. Here, we incubated eggs of three sea turtle species at various moisture levels and tested the terrestrial and aquatic locomotor performance of the resultant hatchlings during the frenzy and post-frenzy period. We also compared and evaluated the ontogeny of early locomotor performance for each species over the first months of life. Drier incubation conditions produced hatchlings that crawled more slowly and took longer to self-right than hatchlings from wetter incubation conditions. There was no difference in swimming performance associated with moisture treatments. We suggest that moisture in the nest environment during incubation may influence hatchling performance via their initial hydration levels. Thus, nest moisture influences terrestrial performance (i.e., escaping from the nest and dispersing across the beach), although upon entering the ocean hatchlings have the opportunity to rehydrate by drinking and thus, differences in locomotor performance associated with moisture treatments cease.