Food neophobia and its association with sociodemographic factors and food preferences among bangladeshi university students: evidence from a cross-sectional study

Food neophobia, described as a reluctance to eat and or avoid new food, is a personality trait that affects food choice. Despite its potential influence on an individual's food intake, food neophobia has been poorly investigated in Bangladesh. This cross-sectional study was designed to evaluate food neophobia and its association with sociodemographic factors and food preferences in a sample of Bangladeshi university students. Five hundred students from five public universities completed the structured surveys. Food neophobia was assessed by a 10-item validated food neophobia scale with some minor modifications based on study settings. A multiple linear regression model was used to observe the factors associated with food neophobia. The mean food neophobia score among study participants was 37.45 (SD: 13.39, Range: 13-67). According to the adjusted statistical model, being female (regression coefficient, β = 2.73), having higher monthly family income (β = -6.64), being underweight (β = 4.68), being overweight (β = -4.63), having any food allergy (β = 9.09), and a history of sickness after eating a new food item (β = 5.16) were significantly associated with food neophobia amongst the participants. The participants' liking of various food items such as vegetables were significantly correlated with food neophobia scores. Nutrition education policies and programs are of importance to address the students' food neophobia during their tertiary education so that they maintain lifelong healthy dietary habits and consume a variety of foods to improve their physical health and well-being

Silencing Agrobacterium oncogenes in transgenic grapevine results in strain-specific crown gall resistance

Crown gall disease of grapevine induced by Agrobacterium vitis or Agrobacterium tumefaciens causes serious economic losses in viticulture. To establish crown gall-resistant lines, somatic proembryos of Vitis berlandieri × V. rupestris cv. 'Richter 110' rootstock were transformed with an oncogene-silencing transgene based on iaaM and ipt oncogene sequences from octopine-type, tumor-inducing (Ti) plasmid pTiA6. Twentyone transgenic lines were selected, and their transgenic nature was confirmed by polymerase chain reaction (PCR). These lines were inoculated with two A. tumefaciens and three A. vitis strains. Eight lines showed resistance to octopine-type A. tumefaciens A348. Resistance correlated with the expression of the silencing genes. However, oncogene silencing was mostly sequence specific because these lines did not abolish tumorigenesis by A. vitis strains or nopaline-type A. tumefaciens C58

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Temporal Analysis of the Honey Bee Microbiome Reveals Four Novel Viruses and Seasonal Prevalence of Known Viruses, Nosema, and Crithidia

Honey bees (Apis mellifera) play a critical role in global food production as pollinators of numerous crops. Recently, honey bee populations in the United States, Canada, and Europe have suffered an unexplained increase in annual losses due to a phenomenon known as Colony Collapse Disorder (CCD). Epidemiological analysis of CCD is confounded by a relative dearth of bee pathogen field studies. To identify what constitutes an abnormal pathophysiological condition in a honey bee colony, it is critical to have characterized the spectrum of exogenous infectious agents in healthy hives over time. We conducted a prospective study of a large scale migratory bee keeping operation using high-frequency sampling paired with comprehensive molecular detection methods, including a custom microarray, qPCR, and ultra deep sequencing. We established seasonal incidence and abundance of known viruses, Nosema sp., Crithidia mellificae, and bacteria. Ultra deep sequence analysis further identified four novel RNA viruses, two of which were the most abundant observed components of the honey bee microbiome (∼1011 viruses per honey bee). Our results demonstrate episodic viral incidence and distinct pathogen patterns between summer and winter time-points. Peak infection of common honey bee viruses and Nosema occurred in the summer, whereas levels of the trypanosomatid Crithidia mellificae and Lake Sinai virus 2, a novel virus, peaked in January

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

The effect of β-aminobutyric acid (BABA) on root knot nematode and soft rot pathogen disease complexes in Solanum tuberosum plants

The efficacy of three elicitors, DL-β-aminobutyric acid (BABA), Acibenzolar-S-methyl (Bion) and Messenger (Harpin) on potato plants inoculated with Meloidogyne incognita second stage juveniles (J2s) was investigated in this study. The efficacy of each elicitor was evaluated based on galling index, egg numbers, total root knot nematode (RKN) population numbers, number of juveniles and the percentage of females in respective extracted populations per treatment at 28 and 56 dpi. There was a significant decrease in galling indices of all treated compared to untreated control plants. The highest percentage reduction was observed for 20 mM BABA-treated plants (33%) followed by 5mM BABA (23%), 50mg/L Bion (18%), 100mg/L Bion (15%) and Messenger (8%). The number of eggs extracted from plants treated with 20mM BABA was significantly lower (66%) compared to untreated controls. Furthermore, treating plants with 20mM BABA decreased the total RKN population numbers by 55% whilst the decrease observed for Bion and Messenger was between 24-39%. Of the three tested elicitors, 20mM BABA was found to be the most effective elicitor at both 28 and 56 dpi. Hence, it was selected for further testing against RKN and Pectobacterium carotovorum subsp. brasiliense (Pcb) disease complex. Efficacy was tested by comparing the colony forming units (cfu) of Pcb from treated and untreated control plants inoculated with M. incongita and Pcb simultaneously. The concentration of Pcb from untreated plants inoculated with both pathogens was significantly higher (3.3 × 103cfu/ml) compared to their treated counterparts (8.71 × 102cfu/ml). This suggests that BABA has the potential to decrease soft rot bacterial infections in RKN disease complexes by decreasing the rate of RKN infection. This is the first report where BABA is shown to decrease the infection rate of RKN as a primary causal agent in combination with a secondary pathogen.National Research Foundation, South Africa. AM received NRF Innovative and Potatoes South Africa Development Fund bursaries.http://link.springer.com/journal/106582016-05-21hb201