Background: Quantitative evaluation of antibiotic spectrum is an important, underutilized metric in measuring antibiotic use (AU) and may assist antimicrobial stewards in identifying targets and strategy for intervention. We evaluated the spectrum of initial antibiotic choices by hospital location, day of the week, and time of day to determine whether these factors may be associated with broad-spectrum antibiotic choices. Methods: We identified all admissions with antibiotic exposure in medical and surgical wards and critical care units in a tertiary academic medical center between July 1, 2014, and July 1, 2019. The antibiotic spectrum index (ASI), proposed by Gerber et al, is a numeric score based on the number of pathogens covered by a particular agent. We defined ASI for initial antibiotic choice as follows: ASI for each unique antibiotic administered within 24 hours of the first antibiotic administration was summed and assigned to the administration time of the first dose. We categorized time into 4 distinct categories: weekday days (Monday–Friday, 7 a.m.–7 p.m.), weekday nights, weekend days, and weekend nights. Weekend time began 7 p.m. Friday and ended 7 a.m. Monday. We constructed heatmaps stratified by hospital location. Mann-Whitney U tests were applied to evaluate differences in the distributions of ASI using weekday days as a reference. Results: Data included 90,455 unique antibiotic admissions with initial antibiotic starts in medical and surgical wards and critical care units. Patterns of ASI for initial antibiotic choice varied between unit locations and time (Figs. 1 and 2). Mean and median ASIs for initial antibiotic choices were higher for medical ward and medical ICUs than for surgical wards and surgical ICUs. Initial antibiotic choices had higher ASIs during overnight hours for all units except the surgical ICU. Notable differences in ASIs were identified between weekday and weekend prescribing for surgical units, whereas medical units demonstrated less extreme differences. Conclusion: We observed a “weekend effect” across hospital units; the most extreme occurred in surgical wards. This observation may be due to differences in patient volume and rounding patterns. For example, hospitalist and critical care units have 7-day schedules, whereas surgical wards are highly influenced by operating room schedules. Antimicrobial stewardship teams may use these data to identify strategies targeting the most opportune time and place to intervene on the spectrum of initial antibiotic choice.

Funding: None

Disclosures: None

Heyes’ book is an important contribution that rightly integrates cognitive development and cultural evolution. However, understanding the cultural evolution of cognitive gadgets requires a deeper appreciation of complexity, feedback, and self-organization than her book exhibits.

All herbicides will move off-target to sensitive crops when not applied correctly. Therefore, low-dose applications of flumioxazin and metribuzin were evaluated in soybean at the unifoliate, V2, and V4 growth stages. Rates evaluated were 12.5%, 25%, and 50% of the labeled use rates of 72 and 316 g ai ha−1 of flumioxazin and metribuzin, respectively. Flumioxazin injury was characterized by necrosis and visible height and width reduction. Injury increased with rate 3 d after treatment (DAT), with unifoliate, V2, and V4 soybean injured 15% to 30%, 18% to 27%, and 5% to 8%, respectively. Unifoliate and V4 soybean were injured more than V4 soybean 3 to 14 DAT, but injury decreased to <5% by 42 DAT. Soybean yields in the flumioxazin study were 92% to 96% of the nontreated, resulting in a yield loss of 196 to 393 kg ha−1 and a revenue loss of 71 to 141 US$ ha−1. Metribuzin injury was primarily chlorosis with necrosis and a visible reduction in soybean height and width. Soybean at the V2 growth stage was injured 14% more than V4 soybean 3 DAT, regardless of metribuzin rate. Injury to V2 and V4 soybean was similar 14 DAT, with injury of 21% to 40% across rates. Soybean injury when treated at the V2 and V4 growth stages was 6% to 29% 42 DAT compared to unifoliate soybean at 0 to 17%. Soybean yields in the metribuzin study yields were 96% to 98% of the nontreated. However, a 2% to 4% reduction equates to a loss of 90 to 180 kg ha−1 and a revenue loss of 32 to 65 US$ ha−1. Unifoliate and V2 soybean are more sensitive to a low dose of flumioxazin POST, and V2 and V4 soybean are more sensitive to a low dose of metribuzin POST. Injury and the impact on soybean growth could potentially cause economic loss for a soybean producer.

The main question that Firestone & Scholl (F&S) pose is whether “what and how we see is functionally independent from what and how we think, know, desire, act, and so forth” (sect. 2, para. 1). We synthesize a collection of concerns from an interdisciplinary set of coauthors regarding F&S's assumptions and appeals to intuition, resulting in their treatment of visual perception as context-free.

Many long-standing predominant theories of cognition have viewed higher levels of processing, such as language and cognition, as free from the influence of lower levels of processing, such as action and perception. However, many recent experiments have found evidence that the delineation between traditional modules is not so clean or precise, with motor output and language comprehension interacting much more fluidly than traditional theories predict. Evidence for this account includes findings of systematic activation of motor cortex while processing action words, as well as functional consequences of language on action and of action on language. It is worth noting that this recent spate of interest in the embodiment of cognition is not without historical precedence. Here, we will review such evidence coming from previous decades of research on the interaction between language and action, in addition to exploring the empirical results of these more recent experiments and methodologies. It seems to be the case, as evidenced from research in cognitive neuroscience and modeling, that motor representations and actions can influence language processing in predictable ways. Not only is there continuous competition between simultaneously active representations in language processing, with multiple sources of information interacting immediately, this competition is apparent in the motor output produced as a response to language.

Many variations upon the theme of parser combinators have been proposed, too many to list here, but the main idea is simple: A parser for phrases of type α is a function that takes an input string and produces results (x, rest), where x is a value of type α, and rest is the remainder of the input after the phrase with value x has been consumed. The results are often arranged into a list, because this allows a parser to signal failure with the empty list of results, an unambiguous success with one result, or multiple possibilities with a longer ‘list of successes’.