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This was a survey of the general non-healthcare-worker USA population regarding their knowledge and attitudes toward the COVID-19 pandemic. Almost everyone practiced social distancing. Women were significantly more likely to be worried about contracting the virus than men (65% vs. 43%, p = 0.0272). There was also a linear trend with age, with older Americans being more worried about contracting the virus. Women were also significantly likely to have received the influenza vaccine this past season compared to men (60% vs. 37%, p = .0167). Similarly, women were significantly more likely to get the influenza vaccine next season than men (77% vs. 46%, p = .0014.). Overall, across every age group, geographic part of the USA and gender, more (or the same) Americans plan on getting the influenza vaccine next season compared to last, but not fewer. This may reflect more awareness of preventative health brought on by the COVID-19 pandemic.

The application of small unmanned aircraft systems (sUAS)‐based high‐throughput phenotyping in plant breeding has advanced significantly over the past decade. Hyperspectral images and machine learning approaches offer potential to enhance drought resistance screening in turfgrass. However, large‐scale field applications remain limited, and the transition from controlled environments to real‐world phenotyping is not well understood. This study aimed to develop an sUAS‐based hyperspectral image workflow to monitor changes in turfgrass canopy reflectance during drought, validate previously reported indices from controlled environment studies in a large‐scale field study, and estimate visual turfgrass quality (TQ) from hyperspectral images. Images were collected from a zoysiagrass (Zoysia spp.) mapping population at three dates under varying soil moisture conditions. Vegetation indices (VIs) related to light use efficiency, leaf pigments, senescence, water status, and green vegetation were computed and compared. Top‐performing genotypes under drought exhibited greater absorption in blue and red wavelengths and higher near‐infrared reflectance than poor‐performing ones. The photochemical reflectance index and plant senescence reflectance index were highly correlated with TQ (r = 0.84 and −0.76), showed higher coefficient of variation (range 18%–37%), and had higher broad‐sense heritability (0.73–0.74) than normalized difference vegetation index (0.69), warranting their use in large‐scale field study. Machine learning models estimated TQ with a mean absolute error of 0.46. These findings highlight the importance of integrating VIs related to light use efficiency, leaf pigments, senescence, and water status to gain deeper insights into turfgrass drought response and support breeding for stress tolerance. Core Ideas A large‐scale small unmanned aircraft systems (sUAS)‐based hyperspectral imaging workflow was developed for turfgrass breeding. Spectral response to drought and the use of vegetation indices in turfgrass phenotyping was characterized. Integrating machine learning enhanced the analysis of high‐dimensional hyperspectral data. Plain Language Summary Researchers used drones equipped with hyperspectral cameras to study how different types of zoysiagrasses respond to drought in real field conditions. This camera captures detailed light signals from the grass that can reveal early signs of stress. The study identified specific vegetation indices that were strongly linked to how healthy the grass looked during drought periods. Some indices were more effective than others at detecting drought stress. The researchers also used machine learning model to predict turf quality from the measured light reflectance. Their results show that combining drone‐based imaging with data analysis can help identify grass types that handle drought better, supporting the development of more drought‐resistant turfgrass varieties.

Acute myeloid leukemia (AML) and other hematologic malignancies can be complicated by hyperleukocytosis, which leads to an increased risk for other severe complications such as tumor lysis syndrome, disseminated intravascular coagulation (DIC), and leukostasis. In this report, we present a case of a 65-year-old female with newly diagnosed AML complicated by leukostasis. We briefly review the clinical significance as well as initial diagnostic and therapeutic considerations pertaining to hyperleukocytosis and its associated complications.Acute myeloid leukemia (AML) and other hematologic malignancies can be complicated by hyperleukocytosis, which leads to an increased risk for other severe complications such as tumor lysis syndrome, disseminated intravascular coagulation (DIC), and leukostasis. In this report, we present a case of a 65-year-old female with newly diagnosed AML complicated by leukostasis. We briefly review the clinical significance as well as initial diagnostic and therapeutic considerations pertaining to hyperleukocytosis and its associated complications.

Although foreign body ingestions are less common in adults than children, when they do occur, it is often due to a fish or chicken bone. The authors present a case of a fish bone ingestion, and highlight its appearance on imaging.

Energy efficiency measures (EEMs) play an essential role in high-performance building design and retrofit, yet there is currently no consistent approach to naming and categorizing them. This makes it difficult to communicate the intent of an EEM and is a barrier to aggregating and analyzing EEM data. To address this need, the authors recently completed work on ASHRAE research project 1836-RP, \"Developing a Standardized Gategorization System for Energy Efficiency Measures.\" This article's goal is to summarize the state of the art in EEM data management by providing actionable advice for practitioners on working with EEM data.

Energy efficiency measures (EEMs) are the fundamental unit of building performance improvement and play an essential role in both energy modeling and energy auditing. However, there is currently no standard approach for naming EEMs, and practitioners often take a custom approach on a project-by-project basis. This makes it difficult to communicate the intent and scope of an EEM clearly and consistently, and to compare EEM effectiveness across projects and programs. This study builds on work from ASHRAE 1836-RP: Developing a standardized categorization system for energy efficiency measures, which identified common problems and desirable features in EEM names. The goal of this study is to develop a set of best practices for naming EEMs and to demonstrate a methodology for applying them to any set of measures. First, the results from 1836-RP were synthesized into four best practices and eight common errors. Then, a methodology for evaluating measures according to these best practices was developed and applied to a set of water conservation measures (WCMs). The results showed that while many WCMs followed at least one of the best practices, most also made at least one common error. Key recommendations include reducing the variety of verbs used, incorporating a building element into each WCM, minimizing wordiness, and ensuring that measures are actionable. The results from this study provide guidance for practicing energy auditors, energy modelers, and software and data tool developers about developing measure names for effective communication and data exchange.

Medical educators in recent years have been using social media for more penetrance to technologically-savvy learners. The utility of using Twitter for curriculum content delivery has not been studied. We sought to determine if participation in a social media-based educational supplement would improve student performance on a test of clinical images at the end of the semester. 116 second-year medical students were enrolled in a lecture-based clinical medicine course, in which images of common clinical exam findings were presented. An additional, optional assessment was performed on Twitter. Each week, a clinical presentation and physical exam image (not covered in course lectures) were distributed via Twitter, and students were invited to guess the exam finding or diagnosis. After the completion of the course, students were asked to participate in a slideshow \"quiz\" with 24 clinical images, half from lecture and half from Twitter. We conducted a one-way analysis of variance to determine the effect Twitter participation had on total, Twitter-only, and lecture-only scores. Twitter participation data was collected from the end-of-course survey and was defined as submitting answers to the Twitter-only questions \"all or most of the time\", \"about half of the time\", and \"little or none of the time.\" We found a significant difference in overall scores (p<0.001) and in Twitter-only scores (p<0.001). There was not enough evidence to conclude a significant difference in lecture-only scores (p=0.124). Students who submitted answers to Twitter \"all or most of the time\" or \"about half the time\" had significantly higher overall scores and Twitter-only scores (p<0.001 and p<0.001, respectively) than those students who only submitted answers \"little or none of the time.\" While students retained less information from Twitter than from traditional classroom lecture, some retention was noted. Future research on social media in medical education would benefit from clear control and experimental groups in settings where quantitative use of social media could be measured. Ultimately, it is unlikely for social media to replace lecture in medical curriculum; however, there is a reasonable role for social media as an adjunct to traditional medical education.

Aneurysmal ruptures are a life-threatening pathology, and while the aorta is the principal location, any aneurysmal rupture can be fatal. Most result from chronic diseases, such as hypertension, diabetes, and vasculitis. Nevertheless, a rupture can result in acute decompensation and must be recognized and addressed quickly to limit morbidity and mortality. The authors describe a case of a 66-year-old female who presented to the emergency department (ED) for abdominal pain and syncope. Even though imaging did not explicitly show the specific site of rupture of the hepatic artery, the positive Rapid Ultrasound for Shock and Hypotension (RUSH) exam and aortic dissection on computed tomography angiography along with her clinical picture (hypotension, abdominal pain, decreased capillary refill, grey skin) raised our suspicions for critical pathology. Exploratory laparotomy revealed a ruptured hepatic artery aneurysm. Her hospital course was complicated by ischemic necrosis of the gallbladder, spleen, and liver, requiring cholecystectomy, splenectomy, and partial hepatectomy, but she was discharged to rehabilitation and expected to make a recovery. This case displays the importance of using ultrasonography early to aid in expedited diagnosis and treatment as well as maintaining a high suspicion for vascular pathology in the setting of hemorrhagic shock.

The novel coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that originated in China in late 2019, has caused significant morbidity and mortality worldwide. Although fever, cough, and shortness of breath have been recognized as hallmark symptoms, other lesser known complications continue to be described. We report a series of three patients who presented to the emergency department, who tested positive for COVID-19, and were found to have or subsequently developed thromboembolic complications.