Diagnostic Tests and their Application in the Management of Soil- and Water-borne Oomycete Pathogen Species

Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness

History of Premenstrual Mood Change and Postpartum Episodes are Associated with Perimenopausal Episodes in Women with Bipolar Disorder

Background and Aims: Reproductive life events are potential triggers of mood episodes in women with bipolar disorder. We aimed to establish whether a history of premenstrual mood change and postpartum episodes are associated with perimenopausal episodes in women who have bipolar disorder. Methods: Participants were 339 post-menopausal women with DSM-IV bipolar disorder recruited into the Bipolar Disorder Research Network (www.bdrn.org). Women self-reported presence (N = 200) or absence (N = 139) of an illness episode during the perimenopausal period. History of premenstrual mood change was measured using the self-report Premenstrual Symptoms Screening Tool (PSST), and history of postpartum episodes was measured via semi-structured interview (Schedules for Clinical Assessment in Neuropsychiatry, SCAN) and inspection of case-notes. Results: History of a postpartum episode within 6 months of delivery (OR = 2.13, p = 0.03) and history of moderate/severe premenstrual syndrome (OR = 6.33, p < 0.001) were significant predictors of the presence of a perimenopausal episode, even after controlling for demographic factors. When we narrowed the definition of premenstrual mood change to premenstrual dysphoric disorder, it remained significant (OR = 2.68, p = 0.007). Conclusions: Some women who have bipolar disorder may be particularly sensitive to reproductive life events. Previous mood episodes in relation to the female reproductive lifecycle may help clinicians predict individual risk for women with bipolar disorder approaching the menopause. There is a need for prospective longitudinal studies of women with bipolar disorder providing frequent contemporaneous ratings of their mood to overcome the limitations of retrospective self-report data.