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Background: Atypical primary hyperparathyroidism (PHPT), which includes normocalcemic and normohormonal variants, can be a diagnostic challenge. We sought to create a machine learning model to predict the probability of a patient having atypical presentations of PHPT. Methods: A model was constructed using logistic regression of PHPT patients and were compared to controls. Variables included sex, body mass index (BMI), calcium, PTH, 25-hydroxyvitamin D, phosphorus, chloride, sodium, alkaline phosphatase, and creatinine. The performance of the model was evaluated using the area under the curve (AUC). Results: The study included 4987 controls and 433 patients with atypical PHPT. Calcium, PTH, vitamin D, phosphorus, BMI, and sex were found to significantly contribute to the performance of the model, achieving an AUC of 0.999. The sensitivity, specificity, positive and negative predictive values were 92.9 %, 99.7 %, 96.3 % and 99.4 %, respectively. Conclusion: Machine learning can reliably aid in the recognition of PHPT in patients with atypical variants. Clinical relevance: When evaluating patients with atypical variants of primary hyperparathyroidism, the clinician needs to be able to identify subtle relationships in the patient laboratory test to make the diagnosis. These relationships can be found with machine learning and incorporated to predictive models which can ease and improve the diagnosis.

HARES is a supportive (high G') HA filler with a low degree of water affinity (gel swelling) and modification (<1% BDDE) that has a well-established safety and efficacy profile in the literature, especially for infraorbital hollow (IOH) rejuvenation. To further support the safety of this product, a long-term review of delayed-onset adverse events of interest (DAEIs) related to HARES was conducted using reports from a global post-marketing safety surveillance database over the past 23 years. This review demonstrated low reporting frequencies of delayed-onset nodules and inflammatory events, establishing a long-term safety profile for HARES that supports its continued use in clinical practice, especially for IOH rejuvenation. [ABSTRACT FROM AUTHOR]

In temperate regions of the United States, female Anopheles mosquitoes respond to low temperatures and short photoperiods by entering an overwintering dormancy or diapause. Diapause in Anopheles results in reduced frequency of blood-feeding and reproductive arrest, indicating a period when pathogen transmission by these mosquitoes is unlikely. However, it is unclear precisely how late into the fall and how early in the spring these mosquitoes are biting, reproducing, and potentially transmitting pathogens. This is further complicated by the lack of clear markers of diapause in Anopheles (e.g., changes in egg follicle length). Our goal was to characterize the seasonal reproductive activity of female Anopheles in central Ohio, United States and evaluate egg follicle length as an indicator of Anopheles diapause. We used traditional mosquito traps and aspirators to collect Anopheles from urban woodlots and culverts, respectively, from late September 2021 through mid-May 2022 in central Ohio. By measuring their egg follicle length, reproductive status, and blood-feeding status, we found that egg follicle length is not a reliable indicator of Anopheles diapause. We also found that a small proportion of An. punctipennis (Say), An. perplexens (Ludlow), and An. quadrimaculatus (Say) continued to bite and reproduce into early November 2021 and that females of these species terminated reproductive dormancy and began biting by mid-March 2022. This period of reproductive activity extends beyond current mosquito surveillance and control in Ohio. Our findings suggest that within temperate regions of North America, Anopheles have the capacity to transmit pathogens throughout the spring, summer, and fall., (© The Author(s) 2024. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)