Genetic analyses of binary longitudinal health data in small low input dairy cattle herds using generalized linear mixed models

The Status of Selenium and Zinc in the Urine of Children From Endemic Areas of Kashin-Beck Disease Over Three Consecutive Years

Selenium deficiency is one of the main risk factors for Kashin-Beck disease (KBD). This study aimed to detect the status of selenium and zinc in the urine of children from endemic areas of KBD over three consecutive years and to evaluate whether selenium and zinc levels in children in Shaanxi Province remain normal after stopping selenium supplementation. The samples of urine were collected in consecutive years (2017–2019) to detect selenium content by hydride generation atomic fluorescence spectrometry (HGAFS) and to detect zinc content by atomic absorption spectrophotometry (AAS). Generalized estimation equation (GEE) analysis was integrated to assess the comprehensive nutritional status and dietary structure of children. Data were processed in duplicate and analyzed by SPSS 18.0. This study included 30 X-ray-positive KBD cases and 123 healthy children aged 7–12 years. A total of 424 urine and 137 hair samples were collected over three consecutive years for selenium determination. The mean value of urinary selenium in all subjects was 6.86 μg/l (2017), 8.26 μg/l (2018), and 4.04 μg/l (2019), and the mean value of urinary zinc in all subjects was 0.36 mg/l (2017), 0.39 mg/l (2018), and 0.31 mg/l (2019) for the three consecutive years of 2017–2019. The mean values of urinary selenium were 6.56 and 6.94 μg/l (2017), 8.69 and 8.14 μg/l (2018), and 4.57 and 3.90 μg/l (2019) in the KBD-X and normal groups, respectively; and the mean value of urinary zinc were 0.38 and 0.35 mg/l (2017), 0.41 and 0.39 mg/l (2018), and 0.43 and 0.28 mg/l (2019) in the KBD-X and normal groups, respectively. The mean value of hair selenium in 137 subjects was 275.08 μg/kg and the mean values of hair selenium were 267.48 and 276.61 μg/kg in the KBD-X group and normal group, respectively. The level of selenium/zinc showed a trend of increasing first and then decreasing during the three consecutive years. The level of selenium in all subjects from the endemic areas was lower than normal, which reminds us to monitor the state of KBD constantly and adjust selenium salt supplementation in accordance with the changes in the KBD state.

A new mixed-effects regression model for the analysis of zero-modified hierarchical count data

Count data sets are traditionally analyzed using the ordinary Poisson distribution. However, such a model has its applicability limited as it can be somewhat restrictive to handle specific data structures. In this case, it arises the need for obtaining alternative models that accommodate, for example, (a) zero-modification (inflation or deflation at the frequency of zeros), (b) overdispersion, and (c) individual heterogeneity arising from clustering or repeated (correlated) measurements made on the same subject. Cases (a)-(b) and (b)-(c) are often treated together in the statistical literature with several practical applications, but models supporting all at once are less common. Hence, this paper's primary goal was to jointly address these issues by deriving a mixed-effects regression model based on the hurdle version of the Poisson-Lindley distribution. In this framework, the zero-modification is incorporated by assuming that a binary probability model determines which outcomes are zero-valued, and a zero-truncated process is responsible for generating positive observations. Approximate posterior inferences for the model parameters were obtained from a fully Bayesian approach based on the Adaptive Metropolis algorithm. Intensive Monte Carlo simulation studies were performed to assess the empirical properties of the Bayesian estimators. The proposed model was considered for the analysis of a real data set, and its competitiveness regarding some well-established mixed-effects models for count data was evaluated. A sensitivity analysis to detect observations that may impact parameter estimates was performed based on standard divergence measures. The Bayesian p -value and the randomized quantile residuals were considered for model diagnostics.

Analysis of potential associations of JUUL flavours with health symptoms based on user-generated data from Reddit

BACKGROUND

The rise of the popular e-cigarette, JUUL, has been partly attributed to various teen-friendly e-liquid flavours offered. However, the possible health risks associated with each e-liquid flavour still remain unclear. This research focuses on the possible associations between JUUL flavours and health symptoms using social media data from Reddit.

METHODS

Keyword filtering was used to obtain 5,746 JUUL flavour-related posts and 7927 health symptom-related posts from June 2015 to April 2019 from Reddit. Posts from September 2016 to April 2019 were used to conduct temporal analysis for nine health symptom categories and the 8 JUUL flavours. Finally, associations between the JUUL flavours and health symptom categories were examined on the user level using generalised estimating equation models.

RESULTS

According to our temporal analysis, Mango and Mint were the most discussed JUUL flavours on Reddit. Respiratory and throat symptoms were the most discussed health issues together with JUUL on Reddit over time. Respiratory symptoms had potential associations with the Mango, Mint and Fruit JUUL flavours. Digestive symptoms had a potential association with the Crème flavour, psychological symptoms had a potential association with the Cucumber flavour, and cardiovascular symptoms had a potential association with the tobacco flavours.

CONCLUSIONS

Mango and Mint were the two most mentioned JUUL flavours on Reddit. Certain JUUL flavours were more likely to be mentioned together with certain categories of health symptoms by the same Reddit users. Our findings could prompt further medical research into the health symptoms associated with different e-liquid flavours.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.