We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure [email protected]
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Tiafenacil is a new nonselective protoporphyrinogen IX oxidase (PPO)–inhibiting herbicide with both grass and broadleaf activity labeled for preplant application to corn, cotton, soybean, and wheat. Early-season corn emergence and growth often coincides in the mid-South with preplant herbicide application in cotton and soybean, thereby increasing opportunity for off-target herbicide movement from adjacent fields. Field studies were conducted in 2022 to identify the impacts of reduced rates of tiafenacil (12.5% to 0.4% of the lowest labeled application rate of 24.64 g ai ha–1) applied to two- or four-leaf corn. Corn injury 1 wk after treatment (WAT) for the two- and four-leaf growth stages ranged from 31% to 6% and 37% to 9%, respectively, whereas at 2 WAT these respective ranges were 21.7% to 4% and 22.5% to 7.2%. By 4 WAT, visible injury following the two- and four-leaf exposure timing was no greater than 8% in all instances except the highest tiafenacil rate applied at the four-leaf growth stage (13%). Tiafenacil had no negative season-long impact, as the early-season injury observed was not manifested in a reduction in corn height 2 WAT or yield. Application of tiafenacil directly adjacent to corn in early vegetative stages of growth should be avoided. In cases where off-target movement does occur, however, affected corn should be expected to fully recover with no impact on growth and yield, assuming adequate growing conditions and agronomic/pest management practices are provided.
Tiafenacil is a new non-selective protoporphyrinogen IX oxidase (PPO)-inhibiting herbicide with both grass and broadleaf activity labeled for preplant application to corn (Zea mays L.), cotton (Gossypium hirsutum L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.). Early-season soybean emergence and growth often coincide in the U.S. Midsouth with preplant herbicide application in later-planted cotton and soybean, thereby increasing opportunity for off-target herbicide movement from adjacent fields. Field studies were conducted in 2022 to identify any deleterious impacts of reduced rates of tiafenacil (12.5% to 0.4% of the lowest labeled application rate of 24.64 g ai ha−1) applied to 1- to 2-leaf soybean. Visual injury at 1 wk after treatment (WAT) with 1/8×, 1/16×, 1/32×, and 1/64× rate of tiafenacil was 80%, 61%, 39%, and 21%, while at 4 WAT, these respective rates resulted in visual injury of 67%, 33%, 14%, and 4%. Tiafenacil at these respective rates reduced soybean height 55% to 2% and 53% to 5% at 1 and 4 WAT and soybean yield 53%, 24%, 5%, and 1%. Application of tiafenacil directly adjacent to soybean in early vegetative growth should be avoided, as severe visual injury will occur. In cases where off-target movement does occur, impacted soybean should not be expected to fully recover, and negative impact on growth and yield will be observed.
To characterise the association between risk of poor glycaemic control and self-reported and area-level food insecurity among adult patients with type 2 diabetes.
Design:
We performed a retrospective, observational analysis of cross-sectional data routinely collected within a health system. Logistic regressions estimated the association between glycaemic control and the dual effect of self-reported and area-level measures of food insecurity.
Setting:
The health system included a network of ambulatory primary and speciality care sites and hospitals in Bronx County, NY.
Participants:
Patients diagnosed with type 2 diabetes who completed a health-related social need (HRSN) assessment between April 2018 and December 2019.
Results:
5500 patients with type 2 diabetes were assessed for HRSN with 7·1 % reporting an unmet food need. Patients with self-reported food needs demonstrated higher odds of having poor glycaemic control compared with those without food needs (adjusted OR (aOR): 1·59, 95 % CI: 1·26, 2·00). However, there was no conclusive evidence that area-level food insecurity alone was a significant predictor of glycaemic control (aOR: 1·15, 95 % CI: 0·96, 1·39). Patients with self-reported food needs residing in food-secure (aOR: 1·83, 95 % CI: 1·22, 2·74) and food-insecure (aOR: 1·72, 95 % CI: 1·25, 2·37) areas showed higher odds of poor glycaemic control than those without self-reported food needs residing in food-secure areas.
Conclusions:
These findings highlight the importance of utilising patient- and area-level social needs data to identify individuals for targeted interventions with increased risk of adverse health outcomes.
While prior literature has largely focused on marriage effects during young adulthood, it is less clear whether these effects are as strong in middle adulthood. Thus, we investigated age differences in marriage effects on problem-drinking reduction. We employed parallel analyses with two independent samples (analytic-sample Ns of 577 and 441, respectively). Both are high-risk samples by design, with about 50% of participants having a parent with lifetime alcohol use disorder. Both samples have been assessed longitudinally from early young adulthood to the mid-to-late 30s. Separate parallel analyses with these two samples allowed evaluation of the reproducibility of results. Growth models of problem drinking tested marriage as a time-varying predictor and thereby assessed age differences in marriage effects. For both samples, results consistently showed marriage effects to be strongest in early young adulthood and to decrease somewhat monotonically thereafter with age, reaching very small (and nonsignificant) magnitudes by the 30s. Results may reflect that role transitions like marriage have more impact on problem drinking in earlier versus later adulthood, thereby highlighting the importance of life span developmental research for understanding problem-drinking desistance. Our findings can inform intervention strategies aimed at reducing problem drinking by jumpstarting or amplifying natural processes of adult role adaptation.