United States Research Articles

Rabies surveillance in the United States during 2022.

To provide comprehensive epidemiological information about the distribution and occurrence of rabies during 2022 in the US, Canada, and Mexico. The US National Rabies Surveillance System collected 2022 animal rabies data from US state and territorial public health departments and USDA Wildlife Services. Temporal and geographic analyses were conducted to evaluate trends in animal rabies cases. During 2022, 54 US jurisdictions reported 3,579 animal rabies cases, reflecting a 2.3% decline from 3,663 cases reported in 2021. Six states collectively reported > 50% of animal rabies cases: Texas (395 [11.0%]), Virginia (337 [9.4%]), Pennsylvania (329 [9.2%]), New York (267 [7.5%]), North Carolina (264 [7.4%]), and California (241 [6.7%]). Out of the total reported rabies animal cases, 3,234 (90.4%) were attributed to wildlife, with bats (1,218 [34.0%]), raccoons (1,014 [28.3%]), skunks (660 [18.4%]), and foxes (269 [7.5%]) representing the primary hosts confirmed with rabies. Rabid cats (222 [6.2%]), cattle (42 [1.2%]), and dogs (50 [1.4%]) constituted > 90% of reported domestic animal rabies cases. In 2022, there was an increase in the number of animal samples submitted for rabies testing in the US and Canada. A notable geographic expansion of gray fox rabies virus variant was detected in the US. Three human rabies deaths due to vampire bat rabies infection occurred in Mexico; none were reported from the US and Canada. Laboratory diagnosis of rabies in animals is critical to ensure judicious use of human rabies postexposure prophylaxis.

The Clinical Judgment Debriefing Structure: Integrating the Clinical Judgement Measurement Model into debriefing

The transformation of nursing education in the United States, driven by the Next Generation NCLEX (NGN), demands a focus on clinical judgment. However, a gap exists in the literature regarding debriefing structures that center on clinical judgment and integrate the Clinical Judgment Measurement Model (CJMM). This paper introduces the Clinical Judgment Debriefing Structure (CJDS) that was designed to incorporate the CJMM into debriefing to support the development of clinical judgment and enhance NGN preparedness. The CJDS provides clinical judgment practice using reflective questions and tasks by emphasizing each element in Layer 3 of the CJMM. Implementation involves faculty inputting simulation content into the CJDS by preparing answers to the standardized reflection questions and tasks. The CJDS streamlines faculty preparation and ensures standardization of each debriefing session. Presented at the 2023 International Nursing Association for Clinical Simulation and Learning (INACSL) conference, the CJDS received positive feedback, indicating its practicality and applicability in simulation practices. Findings from initial testing of the CJDS using a qualitative/quantitative design, demonstrated increased knowledge and confidence in clinical judgment. While measuring clinical judgment remains challenging, the CJDS stands as a unique tool for centering debriefing on clinical judgment and guiding students through Layer 3 of the CJMM, ultimately contributing to safer nursing practice.

Understanding the Challenges Associated with Approval of Anticancer Products to Facilitate the Regulatory Approvals: A Cross-sectional Study

Purpose: Oncological medications face a myriad of challenges, including technological, pre-clinical, clinical, and manufacturing, that lead to regulatory approval delays or failures. The present study aims to identify some challenges encountered by researchers or regulators during the development of novel cancer therapies. Methods: The present cross-sectional observational study used a mixed-method design methodology. The participants were selected via a non-random sampling method via self-selection and snowballing approach. A survey questionnaire was developed and circulated among the selected participants as a hard copy or email or a Google form. Open-ended and closed-ended questions were incorporated to identify the regulatory challenges faced during oncology drug development. The responses were collected from September 2021 to June 2022. These responses were then coded and themes were identified for the challenges. Results: A total of 87 responses were obtained for the questionnaire among the individuals contacted. Seven themes were identified from the collated responses that depicted the challenges for the regulatory approval of anticancer drug products. The majority of responders (38.2%) suggested reduced approval time whereas endpoint selection and study design were considered as a challenge by 12.0% of responders each. Furthermore, 6.0% of responders admit that timely interaction with the regulators is also a challenge that delays approval. Many challenges also exist during the product development phase; hence, 12.0% of responders reported safety issues, and 22.0% of responders reported technical issues during manufacturing as the cause of regulatory failure. Moreover, 12.0% of responders suggested the need for improvements in regulatory guidelines for oncology drug development. Conclusion: The survey indicates a lack of Indian guidelines for anticancer products, whereas limited guidance is available from other countries such as Europe or the United States. Thus, the survey points to the necessity for improvement in the regulatory guidelines and drug approval process to address the challenges unique to cancer drug development.

Article: Redefining Global Trade: The Interplay of Geopolitics, Economic Resilience, and Sustainability?

This paper explores the shifting dynamics of global trade amid rising geopolitical tensions between the United States, the European Union, and China. It traces the evolution from post-World War II American-led globalization to hyperglobalization, where China emerged as a global manufacturing powerhouse. While hyperglobalization spurred economic growth and lowered consumer prices, it also led to job losses, income inequality, and environmental degradation in developed economies.The COVID-19 pandemic and the ongoing US-China trade conflict have accelerated a shift towards economic resilience and national security. The US has responded by decoupling from China, particularly in critical sectors like technology and clean energy, viewing economic policy as integral to national security. Meanwhile, the EU, though aligned with the US in geopolitical concerns, remains economically dependent on China and has adopted a more regulatory approach. The EU seeks to balance its economic ties with China by leveraging trade regulations, such as the Carbon Border Adjustment Mechanism (CBAM) and the Corporate Sustainability Reporting Directive (CSRD), to encourage Chinese investment while promoting higher environmental and social standards.The paper also examines the increasing influence of environmental policies on trade, noting how both the US and EU are integrating sustainability into their trade frameworks. However, this trend raises concerns about the potential for environmental regulations to become trade barriers, further complicating international relations.

Impact of Artificial Intelligence-Based Autosegmentation of Organs at Risk in Low- and Middle-Income Countries

Radiation therapy (RT) processes require significant human resources and expertise, creating a barrier to rapid RT deployment in low- and middle-income countries (LMICs). Accurate segmentation of tumor targets and organs at risk (OARs) is crucial for optimal RT. This study assessed the impact of artificial intelligence (AI)-based autosegmentation of OARs in 2 LMICs. Ten patients, comprising 5 head and neck (HN) cancer patients and 5 prostate cancer patients, were randomly selected. Planning computed tomography images were subjected to autosegmentation using an Food and Drug Administration-approved AI software tool and manual segmentation by experienced radiation oncologists from 2 LMIC RT clinics. The control data, obtained from a large academic institution in the United States, consisted of contours obtained by an experienced radiation oncologist. The segmentation time, DICE similarity coefficient (DSC), Hausdorff distance, and mean surface distance were evaluated. AI significantly reduced segmentation time, averaging 2 minutes per patient, compared with 57 to 84 minutes for manual contouring in LMICs. Compared with the control data, the AI pelvic contours provided better agreement than did the LMIC manual contours (mean DSC of 0.834 vs 0.807 in LMIC1 and 0.844 vs 0.801 in LMIC2). For HN contours, AI provided better agreement for the majority of OAR contours than manual contours in LMIC1 (mean DSC: 0.823 vs 0.821) or LMIC2 (mean DSC: 0.792 vs 0.748). Neither the AI nor LMIC manual contours had good agreement with the control data (DSC < 0.600) for the optic nerves, chiasm, and cochlea. AI-based autosegmentation generates OAR contours of comparable quality to manual segmentation for both pelvic and HN cancer patients in LMICs, with substantial time savings.

Context, Climate, and Red Tape: Considerations for Social-Justice Curriculum Development in Kinesiology

Curricula grounded in social justice are vital in higher education, including kinesiology programs. The United States has seen continued increases in diversity, with education consistently displaying poor representation of historically marginalized groups. The purpose of this paper is to offer three elements that kinesiology programs should consider when aiming to successfully engage in developing social-justice curricula: context, climate, and “red tape.” We define and describe each element and how it influences our approach to curriculum development and provide specific examples from our work in the University of New Mexico Physical Education Teacher Education program to illustrate practical implementation. We argue that social-justice curriculum development is required to prepare young professionals to enter the field with the knowledge, skills, and dispositions to meet the needs of diverse communities.

Use and Cost Patterns of Antihypertensive Medications in the United States From 1996 to 2021.

Antihypertensive medication use patterns have likely been influenced by changing costs and accessibility over the past 3 decades. This study examines the relationships between patent exclusivity loss, medication costs, and national health policies on antihypertensive medication use. Using 1996 to 2021 Medical Expenditure Panel Survey data of US adults with hypertension taking at least 1 antihypertensive medication, we conducted a cross-sectional analysis. We explored the associations between patent exclusivity loss, per-pill costs, and Medicare Part D enactment on medication use over time, focusing on the most commonly used medications (lisinopril, amlodipine, losartan, hydrochlorothiazide, and metoprolol). The unweighted sample comprised 50 095 US adults (mean age, 62 years; 53% female). The survey-weighted number of adults taking antihypertensive medications increased from 22 million (95% CIs, 20-23 million) to 55 million (95% CI, 51-60 million) between 1996 and 2021. Loss of patent exclusivity led to increased medication fills, notably for lisinopril, amlodipine, and losartan, which all exhibited within-class dominance. However, per-pill cost decreases coinciding with Medicare Part D did not increase the number of individuals treated or the use of specific antihypertensive medications or classes. The increase in antihypertensive medication use over the past decades highlights the significant impact of loss of patent exclusivity on the uptake in the use of specific medications. These findings underscore the complexity of factors influencing medication use, beyond cost reductions alone, and suggest that policies need to consider multiple facets to effectively improve antihypertensive medication accessibility and utilization.

Oral solid dosage form using alternate crystalline neratinib maleate anhydrous form: Pharmaceutical, bioequivalent, and clinical perspectives.

Neratinib (an active pharmaceutical ingredient [API]) is an irreversible pan-human epidermal growth factor receptor (HER) inhibitor used to treat HER2-positive breast cancer. The dosage form (marketed in the United States, China, Europe, and other regions) is a tablet for oral administration, and the brand product (NERLYNX) has patent protection for the crystalline neratinib maleate monohydrate form. This paper describes the product development using stable crystalline neratinib maleate anhydrous form, stability study, bioequivalence (BE) study of the products, and discussion of the adverse effects observed in the clinical study.

Gynecologic oncologist in cesarean hysterectomy for placenta accreta spectrum in the United States: A surgeon specialty-specific assessment

Gynecologic oncologist in cesarean hysterectomy for placenta accreta spectrum in the United States: A surgeon specialty-specific assessment

Bel Canto des Wortes— The Pedagogy of Cornelia (Cornelie) van Zanten

Abstract: The Neapolitan School is well-known for its superb pedagogues who shaped the art of bel canto singing, one of whom was Cornelia van Zanten (1855–1946). Her 1911 treatise Bel Canto des Wortes , with its many voice exercises and an overview of the history of the bel canto movement, reveals Zanten as a superb pedagogue whose work deserves more exposure. Zanten’s methods were forged by her own operatic career, which spanned both Europe and the United States, her studies with Francesco Lamperti and Julius Stockhausen, and her many years teaching in both Germany and The Netherlands.

An Imperfect List of Eminent Sport and Exercise Psychology Researchers

The purpose of the present study was to identify eminent sport and exercise psychology researchers, based on citation count, and their most highly cited papers. Men (n = 121) and women (n = 32) from 17 different countries (e.g., the United States n = 47 to Ireland n = 1) were identified. Researchers were selected if their h-index was 60 or greater for Google Scholar and Web of Science combined. This criterion reflects Hirsch’s (2005) characterization as follows based on h-index: a successful scientist (20), an outstanding scientist (40), and truly unique (60), for one database. Our criteria of 60 for two databases are equivalent to a designation halfway between successful and outstanding. The results indicate an h-index mean of 103, median of 94, mode of 105, and range of 60–346. Top-cited publications leaned toward more sport psychology than exercise psychology topics. Prominent journals included the Journal of Sport and Exercise Psychology (n = 24) and Psychology of Sport and Exercise (n = 15). Other publications were in related fields (e.g., Psychology and Health). In summary, we have identified the most highly cited researchers in sport and exercise psychology and their single most-cited papers. We hope this information is of both heuristic and practical value to readers.

Ensemble Predictability of Week 3/4 Precipitation and Temperature over the United States via Cluster Analysis of the Large-Scale Circulation

Abstract Forecasting the week 3/4 period presents many challenges, resulting in a need for improvements to forecast skill. At this distance from initial conditions, numerical models struggle to present skillful forecasts of temperature, precipitation, and associated extremes. One approach to address this is to utilize more predictable large-scale circulation regimes to make forecasts of temperature and precipitation anomalies, using the association between the regimes and surface weather obtained from reanalysis products. This study explores the utility of k-means cluster analysis on geopotential heights and their ability to make skillful regime predictions in the week 3/4 period. Using 14-day running means of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) 500-hPa geopotential heights for the wintertime December–February (DJF) period, circulation regimes are identified using k-means clustering. Each period is assigned a cluster number, allowing the compositing of any reanalysis or observation variable to form cluster maps. Maps of 500-hPa height, 2-m temperature, precipitation, and storm-track anomalies are some of the variables composited. The utility of these relationships in a dynamical forecast setting is tested via Global Ensemble Forecast System v12 (GEFSv12) hindcasts and real-time ensemble suite forecasts. Week 3/4 deterministic and probabilistic experimental forecasts are then derived from cluster assignments using several methods. We find, via a conditional skill analysis, forecasts strongly correlated with a cluster exhibit greater skill for both dynamical model and cluster-derived forecasts. Our preliminary results represent a step forward to aid forecasters make more skillful assessments of the circulation regime and its associated surface weather for this challenging forecast time scale. Significance Statement Our paper links the local statistics of 14-day precipitation and temperature within the United States to very broad preferred patterns of winds and pressure over the wide Pacific–North American region. Such patterns, known as “circulation regimes,” provide the background that heavily influences local surface conditions. We find that forecasts for which midatmospheric anomalies are closely aligned with one or more circulation regimes are better at predicting the U.S. weather probabilities than other week 3–4 forecasts. A tool based on this finding identifies forecasts for which confidence is higher. Future work will be designed to further exploit the links between circulation regimes and weather to improve the accuracy of week 3–4 forecasts.

Mindfulness, crashes, and risky driving behaviors among adolescents and young adults in the United States

PurposeThe purpose of this study was to examine the association between individual-level mindfulness and a range of risky driving behaviors among U.S. adolescents. MethodsWe conducted a survey of a nationally representative sample of 16–19-year-olds, recruited from the National Opinion Research Center AmeriSpeak panel, a probability-based sample. Participants completed the Mindful Attention Awareness Scale. Risky driving measures were adapted from the Youth Risk Behavior Survey. Spline regression analysis was performed to identify the threshold where mindfulness scores significantly changed driving behaviors. ResultsAfter adjusting for age, gender, and race, adolescents reporting higher mindfulness scores were significantly less likely to engage on all risky driving behaviors and significantly less likely to have been involved in a crash. Spline regression analysis indicated that a mindfulness score of 75 corresponded to the minimum marginal probability change averaged across the outcomes of interest. DiscussionThis paper describes a previously unknown association between mindfulness and risky driving in a vulnerable population which is at higher risk of injury and death from motor vehicle crashes. The strength of the associations across a range of behaviors suggests mindfulness could be a general protective factor for adolescents’ driving behaviors and suggests that mindfulness training may be a promising safety intervention for adolescents. A mindfulness score of 75 could be a potential target for mindfulness training interventions aiming to reduce risky driving behaviors and crashes among teenage drivers.Abbreviations: ADHD, Attention Deficit Hyperactivity Disorder; CI, Confidence Interval; MAAS, Mindful Attention Awareness Scale; NORC, University of Chicago’s National Opinion Research Center; YRBS, Youth Risk Behavior Survey.

Multidimensional structural racism and estimated cancer risk from traffic-related air pollution.

Traffic-related air pollutants have been associated with a variety of adverse human health impacts, including cancers. In the United States, numerous studies have documented racial inequities in neighborhood exposures to traffic-related air pollution. Emerging evidence suggests that structural racism may influence neighborhood exposures to air pollutants. However, existing research has largely focused on residential racial segregation, one indicator of structural racism. This study developed a multidimensional measure of structural racism to examine the relationship between structural racism and estimated cancer risk from air pollutants in Georgia. Carcinogenic air toxics data were obtained from the US Environmental Protection Agency's 2019 Air Toxics Screening Assessment and sociodemographic data from the American Community Survey. Guided by stakeholder input, county-level data on residential segregation, education, employment, incarceration, economic status, political participation, and homeownership were used to create a multidimensional county-level structural racism index. Relative risks (RRs) were estimated for associations between structural racism and elevated (top 10% in Georgia) estimated cancer risk from air toxics. Multilevel analyses revealed a significant association between multidimensional structural racism and exposure to carcinogenic traffic-related air pollutants. Neighborhoods in the highest quartile of structural racism exhibited an elevated cancer risk from traffic-related air pollutants (RR,7.84; 95% CI,5.11-12.05) compared to neighborhoods with lower levels of structural racism. Multidimensional structural racism was associated with estimated cancer risk from traffic-related air pollution in Georgia. Findings can inform future studies and policy interventions that address racial inequalities in exposure to traffic-related air pollution.

Evaluation of Yield, Fruit Chemistry, and Firmness of Seven Strawberry (Fragaria ×ananassa) Cultivars in an Eastern North Carolina Greenhouse

The combination of increasing costs, climate change, and disease- and pest-related issues present large challenges for the strawberry (Fragaria ×ananassa) industry in the United States. This is especially true for the Southeast, where rain, frost, and a range of foliar, fruit, and soil-borne diseases are prevalent, leading to significant losses every year. Simultaneously, niche winter markets open the opportunity to extend the harvest season, leading to an industry push to use protected culture strawberry production. Tabletop soilless strawberry greenhouse production has the advantage of avoiding soilborne issues while at the same time mitigating weather-related impacts on strawberry yield and quality. The use of long-day cultivars, originally bred for the Central Coast region of California, is currently the industry standard because of desired winter yields. However, short-day cultivars bred for Florida production might also have the potential to produce in winter. In this study, we evaluated the growth, yield, fruit chemistry, and fruit firmness of seven strawberry cultivars that are commonly grown in protected culture in North Carolina: Albion, Brilliance, Camino Real, Fronteras, Monterey, Florida Sensation, and Sweet Charlie. Experiments were conducted in a randomized complete block design in a commercial tabletop greenhouse in eastern North Carolina over two growing seasons (2022–23 and 2023–24). Our results showed that Florida cultivars Brilliance and Florida Sensation produced more consistently yields in winter compared with long-day cultivars Albion and Monterey and produced similar yields over the entire season. ‘Brilliance’ especially showed high fruit firmness across both years, and high sweetness in one of the two years. Additionally, the short-day cultivar Fronteras showed high yields in early spring and could serve as a late-season crop for direct-to-consumer producers. Our study showed that ‘Brilliance’ and ‘Florida Sensation’ could be alternatives to ‘Albion’, and that ‘Monterey’ can be used to produce a winter crop in a soilless tabletop production system in the Southeast.

Regulatory Landscape of Cannabis Warning Labels in US States with Legal Retail Nonmedical Cannabis, 2024.

Objectives. To characterize regulatory practices related to nonmedical cannabis warning labels in states across the United States that have legalized retail nonmedical cannabis. Methods. In March 2024, we conducted a content analysis of regulations for nonmedical cannabis warning labels required on product packages in 20 states where, as of March 2024, adults could legally purchase nonmedical cannabis in retail environments. For each state, we examined requirements related to warning label content and characteristics. Results. Required warning label content and characteristics varied widely across states. Only 2 states required a warning about mental health risks (10%) and 2 states required a warning for high potency products on risk of psychosis (10%). No states required front-of-package warning placement, only 2 states required rotating warnings (10%), and 4 states required contrasting colors (20%). Warnings were often verbose (mean = 57 words), vague, and had small or no minimum font size. Conclusions. Opportunities exist for states to improve the alignment of their nonmedical cannabis warning label regulations with evidence that has been generated so far in cannabis effects, cannabis warning efficacy, and warning label design. (Am J Public Health. 2024;114(S8):S681-S684. https://doi.org/10.2105/AJPH.2024.307722).

Interconnected influence: Unraveling purdue pharmaceutical's role in the global response to the opioid crisis

BackgroundThe global pharmaceutical industry has a long history of prioritizing profits over public health through widespread practices such as price gouging, deceptive marketing, and fraud. A prominent example of this issue is the mislabeling and mass-marketing of OxyContin by Purdue Pharmaceuticals (Purdue) that catalyzed the opioid crises in and beyond the United States. MethodsGuided by Actor-Network Theory, this case study employs Visual Network Analysis to map the actors-networks involved in responding to the harms caused by Purdue. Data was generated from peer-reviewed and grey literature published between 2007 and 2022 (n = 40) and imported into Gephi visualization software where centrality metrics were applied. ResultsA total of 39 actors and 99 relationships were visualized based on the relational thinking that actors who are heavily interconnected with others are rendered important. Centrality measures identified the socio-technical centrality of Purdue in influencing the response to the harms it caused. Purdue exerted influence through various avenues, most prominently through the creation and cooptation of pain advocacy groups, their close ties with United States elected officials, and through embedding pro-opioid messaging in international guidance documents. In doing so, Purdue was able to extend the reach and impact of their opioid promotion, while simultaneously limiting the capacity of regulatory bodies to pursue accountability and implement policies to mitigate opioid-related harms. ConclusionThis study advances understandings of the complex interplay between transnational pharmaceutical companies, global health systems, regulatory bodies, and public health. In doing so, we underscore the need for stronger regulation and increased transparency surrounding the interactions between pharma, patient groups, governments, and international organizations to better address and prevent future harms.

Changing demographics cervical cancer in the United States: An update (2000−2022)

Changing demographics cervical cancer in the United States: An update (2000−2022)

Capsular attention Conv-LSTM network (CACN): A deep learning structure for crop yield estimation based on multispectral imagery

Precise prediction of agricultural production output is crucial for farmers, policymakers, and the Farming-related industry. This article introduces a novel methodology to crop yield forecasting using a capsular neural network equipped with Conv-LSTM and attention mechanism. Our model combines the strengths of 3DCNN, and Conv-LSTM, which can capture the temporal dependencies and 3D features of crop yield data, and attention mechanism, which Can prioritize the most significant characteristics for making predictions. We evaluated CACN on a sizable collection of data of soybean crop yield in the United States from 2003 to 2019 and evaluated against various cutting-edge deep learning models. The outcomes indicate that our suggested approach surpasses other models in performance in terms of RMSE, correlation coefficient, and prediction error map. Specifically, our model achieved approximately 14 % improvement in terms of RMSE, compared to the state-of-the-art model Deep-Yield. Our model also demonstrated the ability to extract more meaningful features and capture the complex relationships between crop yield data and meteorological variables. Overall, our proposed method shows great potential for accurate and efficient crop yield forecasting and can be applied to other crops and regions.

The decline in complex ovarian cancer procedures performed by surgeons in the United States: 2004–2020

The decline in complex ovarian cancer procedures performed by surgeons in the United States: 2004–2020