Background: Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. Categorizing CDI based on location of onset and potential exposure is critical in understanding transmission patterns and prevention strategies. While claims data are well-suited for identifying prior healthcare utilization exposures, they lack specimen collection and diagnosis dates to assign likely location of onset. Algorithms to classify CDI onset and healthcare association using claims data have been published, but the degree of misclassification is unknown. Methods: We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016-2020 to Medicare beneficiaries using residence, birth date, sex, and hospitalization and/or healthcare exposure dates. Uniquely linked patients with fee-for-service Medicare A/B coverage and complete EIP case report forms were included. Patients with a claims CDI diagnosis code within ±28 days of a positive CDI test reported to EIP were categorized as hospital-onset (HO), long-term care facility onset (LTCFO), or community-onset (CO, either healthcare facility-associated [COHCFA] or community-associated [CA]) using a previously published algorithm based on claim type, ICD-10-CM code position, and duration of hospitalization (if applicable). EIP classifies CDI into these categories using positive specimen collection date and other information from chart review (e.g. admit/discharge dates). We assessed concordance of EIP and claims case classifications using Cohen’s kappa. Results: Of 10,002 eligible EIP-identified CDI cases, 7,064 were linked to a unique beneficiary; 3,451 met Medicare A/B fee-for-service coverage inclusion criteria. Of these, 650 (19%) did not have a claims diagnosis code ±28 days of the EIP specimen collection date (Table); 48% (313/650) of those without a claims diagnosis code were categorized by EIP as CA CDI. Among those with a CDI diagnosis code, concurrence of claims-based and EIP CDI classification was 68% (κ=0.56). Concurrence was highest for HO and lowest for COHCFA CDI. A substantial number of EIP-classified CO CDIs (30%, Figure) were misclassified as HO using the claims-based algorithm; half of these had a primary ICD-10 diagnosis code of sepsis (226/454; 50%). Conclusions: Evidence of CDI in claims data was found for 81% of EIP-reported CDI cases. Medicare classification algorithms concurred with the EIP classification in 68% of cases. Discordance was most common for community-onset CDI patients, many of whom were hospitalized with a primary diagnosis of sepsis. Misclassification of CO-CDI as HO may bias findings of claims-based CDI studies.

Quasi-periodic plasmoid formation at the tip of magnetic streamer structures is observed to occur in experiments on the Big Red Ball as well as in simulations of these experiments performed with the extended magnetohydrodynamics code, NIMROD. This plasmoid formation is found to occur on a characteristic time scale dependent on pressure gradients and magnetic curvature in both experiment and simulation. Single mode, or laminar, plasmoids exist when the pressure gradient is modest, but give way to turbulent plasmoid ejection when the system drive is higher, which produces plasmoids of many sizes. However, a critical pressure gradient is also observed, below which plasmoids are never formed. A simple heuristic model of this plasmoid formation process is presented and suggested to be a consequence of a dynamic loss of equilibrium in the high-$\beta$ region of the helmet streamer. This model is capable of explaining the periodicity of plasmoids observed in the experiment and simulations, and produces plasmoid periods of 90 minutes when applied to two-dimensional models of solar streamers with a height of $3R_\odot$. This is consistent with the location and frequency at which periodic plasma blobs have been observed to form by Large Angle and Spectrometric Coronograph and Sun Earth Connection Coronal and Heliospheric Investigation instruments.

Magnetic reconnection is explored on the Terrestrial Reconnection Experiment (TREX) for asymmetric inflow conditions and in a configuration where the absolute rate of reconnection is set by an external drive. Magnetic pileup enhances the upstream magnetic field of the high-density inflow, leading to an increased upstream Alfvén speed and helping to lower the normalized reconnection rate to values expected from theoretical consideration. In addition, a shock interface between the far upstream supersonic plasma inflow and the region of magnetic flux pileup is observed, important to the overall force balance of the system, thereby demonstrating the role of shock formation for configurations including a supersonically driven inflow. Despite the specialized geometry where a strong reconnection drive is applied from only one side of the reconnection layer, previous numerical and theoretical results remain robust and are shown to accurately predict the normalized rate of reconnection for the range of system sizes considered. This experimental rate of reconnection is dependent on system size, reaching values as high as 0.8 at the smallest normalized system size applied.

Contamination, when members of a comparison or control condition are exposed to the event or intervention under scientific investigation, is a methodological phenomenon that downwardly biases the magnitude of effect size estimates. This study tested a novel approach for controlling contamination in observational child maltreatment research. Data from The Longitudinal Studies of Child Abuse and Neglect (LONGSCAN; N = 1354) were obtained to estimate the risk of confirmed child maltreatment on trajectories of internalizing and externalizing behaviors before and after controlling contamination. Baseline models, where contamination was uncontrolled, demonstrated a risk for greater internalizing (b = .29, p < .001, d = .40) and externalizing (b = .14, p = .040, d = .19) behavior trajectories. Final models, where contamination was controlled by separating the comparison condition into subgroups that did or did not self-report maltreatment, also demonstrated risks for greater internalizing (b = .37, p < .001, d = .51) and externalizing (b = .22, p = .028, d = .29) behavior trajectories. However, effect size estimates in final models were 27.5%–52.6% larger compared to baseline models. Controlling contamination in child maltreatment research can strengthen effect size estimates for child behavior problems, aiding future child maltreatment research design and analysis.

Carrot weevil, Listronotus oregonensis (LeConte) (Coleoptera: Curculionidae), is a pest of carrot (Daucus carota var. sativus Hoffmann; Apiaceae) throughout eastern Canada. Carrot weevil emergence and oviposition were monitored in commercial carrot fields in Nova Scotia. Cumulative degree days were calculated using a base temperature of 7 °C (DD7), and models were developed to predict cumulative emergence and oviposition using nonlinear regression. Cumulative emergence and oviposition were adequately explained as functions of DD7 by a three-parameter sigmoidal Hill equation. Our emergence model predicted initial and peak adult emergence at 35 and 387 DD7, respectively, with oviposition on carrot baits occurring as early as 42 DD7. Models were then validated to evaluate how well they performed. Oviposition on carrot plants began at the fourth true-leaf stage (342 DD7) and continued until eleventh true-leaf stage. Growers using these models can identify their window of opportunity to manage their carrot weevil populations targeting the majority of emerged adults before oviposition begins in the field.