Clinical significance of very high IgE levels (≥1000 IU/mL): Population-based study of 118,211 adults by Shay Nemet, MD, Daniel Elbirt, MD, Ramon Cohen, MD, Keren Mahlab-Guri, MD, Shira Bezalel-Rosenberg, MD, Ilan Asher, MD, Aviv Talmon, MD, Limor Rubin, MD, Yaarit Ribak, MD, Ruslan Sergienko, MHA, Udi Nussinovitch, MD, PhD, Yuval Tal, MD, PhD, Oded Shamriz, MD

“…Outcomes included eosinophilic, autoimmune, autoinflammatory, and cardiovascular disorders (CVD), cancer, and inborn errors of immunity (IEI). A multivariable Cox regression model determined statistical significance (P < .05). …”
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Assessing effective mask use by the public in two countries: an observational study by Peter C Austin, Bory Kea, Bin Chen, Arshia P Javidan, Huong Nguyen, Alex Chang, Allen Li, Clare L Atzema, Ivona Mostarac, Dana Button, Lauren Wintraub, Raumil V Patel, Daniel Dongjoo Lee, Nathaniel P Latham, Eric A Latham, Patrick C M Brown, Rita D Somogyi, Sara Buerk, Tristen Zimmerman, Trevor Funari, Cameron Colbert

“…Mandatory mask-use settings were associated with lower adjusted odds of mask error (OR 0.30; 95% CI 0.14 to 0.73), along with female sex and Portland subjects. …”
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Dietary exposure to nitrites and nitrates in association with type 2 diabetes risk: Results from the NutriNet-Santé population-based cohort study. by Bernard Srour, Eloi Chazelas, Nathalie Druesne-Pecollo, Younes Esseddik, Fabien Szabo de Edelenyi, Cédric Agaësse, Alexandre De Sa, Rebecca Lutchia, Charlotte Debras, Laury Sellem, Inge Huybrechts, Chantal Julia, Emmanuelle Kesse-Guyot, Benjamin Allès, Pilar Galan, Serge Hercberg, Fabrice Pierre, Mélanie Deschasaux-Tanguy, Mathilde Touvier

“…<h4>Conclusions</h4>The findings of this large prospective cohort did not support any potential benefits for dietary nitrites and nitrates. …”
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Specific features of cognitive skill development in athletes of situational sports by Vyacheslav Romanenko, Yrui Tropin, Leonid Podrigalo, Natalya Boychenko, Anatoly Abdula, Nataliia Sereda, Yaroslav Yatsiv

“…Model testing confirmed high accuracy in classifying respondents according to their respective sports profiles: judo (0.88 ± 0.11) and football (0.98 ± 0.03). Conclusions. Situational sports, including team sports and martial arts, require athletes to demonstrate a high level of executive functions. …”
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Procedure Type and Preoperative Patient-Reported Outcome Metrics Predict Variation in the Value of Hip Arthroscopy for Femoroacetabular Impingement by Michael C. Dean, B.A., Nathan J. Cherian, M.D., Ana Paula Beck da Silva Etges, Ph.D., Zachary L. LaPorte, B.A., Kieran S. Dowley, B.A., Kaveh A. Torabian, M.S., Ryan E. Dean, M.D., Scott D. Martin, M.D.

“…The exclusion criteria were hip dysplasia, advanced hip osteoarthritis (TÖnnis grade >1), or unreconcilable documenting errors. Value was calculated by dividing 2-year postoperative International Hip Outcome Tool 33 scores by time-driven activity-based costs. …”
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Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification by Jose Manuel Martí, Car Reen Kok, James B. Thissen, Nisha J. Mulakken, Aram Avila-Herrera, Crystal J. Jaing, Jonathan E. Allen, Nicholas A. Be

“…This new resource demonstrably reduces errors and improves the reliability of microbial identification across diverse taxonomic groups. …”
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Comparison of treatment planning for stereotactic radiosurgery and stereotactic body radiation therapy techniques with 2.5mm and 5mm multileaf collimator (MLC): A pilot study [vers... by Senthil Manikandan, Krishna Sharan, Shirley Lewis, Suresh Sukumar, Umesh V, Srinidhi G Chandraguthi, Shreekripa Rao, Rechal Nisha Dsouza, Sneha Ravichandran

“…GI was superior in the 2.5mm mMLC compared to the 5mm MLC giving a steep falloff in the dose distributions (p = 0.158). Conclusions The TC, CI, HI, and OAR doses were similar in both 2.5mm and 5mm based VMAT plans. …”
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Estresse e inovação tecnológica em unidade de terapia intensiva de cardiologia: tecnologia dura [Stress and technological innovation in a cardiac intensive care unit: hard technolo... by Elias Barbosa de Oliveira, Natalia Victor Madeira de Souza

“…Intervening factors, such as lack of training and preventive maintenance of apparatus and machines, result in occupational stress in face of possible errors and adverse effects on patients. Conclusions show that hospital risk management is required to safeguard quality of care, safety, wellbeing, and team satisfaction. …”
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Associations between nighttime or weekend deliveries and adverse maternal, birth, and neonatal outcomes: secondary analysis of the MANGO study in western Kenya by Maneet K. Virk, Jenine Shafi, Pooja Maheria, Garoma Basha, Harold E. Kooreman, John Humphrey, James G. Carlucci, Audrey Chepkemoi, Caitlin Bernard, Megan S. McHenry, Beverly Musick, Caroline Kerich, Winnie Matelong, Constantin T. Yiannoutsos, Wycliffe Kosgei, Julia Songok, Kara Wools-Kaloustian, Edwin Were, Rena C. Patel

“…We utilized multivariable Poisson regression models, with log link, robust standard errors, and adjusted for several covariates, to assess the association between nighttime/weekend deliveries and adverse composite maternal, birth, or neonatal outcomes. …”
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Bridging the Gap in Carbohydrate Counting With a Mobile App: Needs Assessment Survey by Asmaa Housni, Alexandra Katz, Lucien Junior Bergeron, Alain Simard, Ashley Finkel, Amélie Roy-Fleming, Meranda Nakhla, Anne-Sophie Brazeau

“…ConclusionsCC mobile apps currently used do not meet the needs of people with T1D. …”
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Surface morphology segmentation and evaluation of diamond lapping pad based on improved Mask R-CNN by Wenlong SUO, Yanfen LIN, Congfu FANG

“…ConclusionsThe dilated convolution method can effectively expand the receptive field and improve the ability to extract deep semantic features of targets at different scales. …”
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Impact evaluation of a digital health platform empowering Kenyan women across the pregnancy-postpartum care continuum: A cluster randomized controlled trial. by Rajet Vatsa, Wei Chang, Sharon Akinyi, Sarah Little, Catherine Gakii, John Mungai, Cynthia Kahumbura, Anneka Wickramanayake, Sathyanath Rajasekharan, Jessica Cohen, Margaret McConnell

“…A limitation of our study was that outcomes were self-reported, and the study was not powered to detect effects on health outcomes.<h4>Conclusions</h4>Digital health tools indicate promise in addressing shortcomings in pregnant and postpartum women's health care, amidst systems that do not reliably deliver a minimally adequate standard of care. …”
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Skin conditions associated with dermal exposure to oil spill chemicals among Deepwater Horizon disaster response and cleanup workers by Dazhe Chen, Kaitlyn G. Lawrence, Patricia A. Stewart, Melanie Gorman Ng, Mark R. Stenzel, John W. Cherrie, Kate E. Christenbury, W. Braxton Jackson II, Lawrence S. Engel, Dale P. Sandler

“…We used Poisson regression with robust standard errors to evaluate associations of exposures with prevalent skin conditions during spill cleanup and at enrollment (1–3 years later) and incident eczema diagnoses after the start of OSRC work. …”
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ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis by Weihong Huang, Wudi Wei, Xiaotao He, Baili Zhan, Xiaoting Xie, Meng Zhang, Shiyi Lai, Zongxiang Yuan, Jingzhen Lai, Rongfeng Chen, Junjun Jiang, Li Ye, Hao Liang

“…Performance was evaluated using mean squared error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). …”
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Deep Learning–Based Prediction of Glaucoma Severity and Progression Using Imo/TEMPO Screening Program by Kei Sano, MD, PhD, Euido Nishijima, MD, PhD, Shunsuke Sumi, MD, PhD, Takahiko Noro, MD, PhD, Shumpei Ogawa, MD, PhD, Yuka Igari, MD, Aiko Iwase, MD, PhD, Tadashi Nakano, MD, PhD

“…Main Outcome Measures: Mean absolute error for mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI). …”
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Feasibility of automating the determination of changes in forest areas using satellite images (Case Study: Central Alborz protected area) by Amir Satari Rad, Behzad Rayegani, Ali Jahani, Hamid Goshtasb Meigooni

“…The 16-day NDVI images were converted to monthly images with the maximum value algorithm and the PCA algorithm with 25 components was applied to them to eliminate errors and noise. Using the Google Earth system, 5 random polygons were selected on virgin forest areas, in order to estimate the value of the pixels and finally determine the thresholds. …”
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A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…Additionally, the root mean square error (RMSE) decreased from 0.531 to 0.426, suggesting a reduction of 19.8%. …”
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Characterization of RAP Signal Patterns, Temporal Relationships, and Artifact Profiles Derived from Intracranial Pressure Sensors in Acute Traumatic Neural Injury by Abrar Islam, Amanjyot Singh Sainbhi, Kevin Y. Stein, Nuray Vakitbilir, Alwyn Gomez, Noah Silvaggio, Tobias Bergmann, Mansoor Hayat, Logan Froese, Frederick A. Zeiler

“…Goal: Current methodologies for assessing cerebral compliance using pressure sensor technologies are prone to errors and issues with inter- and intra-observer consistency. …”
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Machine learning model for predicting corneal stiffness and identifying keratoconus based on ocular structures by Longhui Li, Yifan Xiang, Xi Chen, Duoru Lin, Lanqin Zhao, Jun Xiao, Zhenzhe Lin, Jianyu Pang, Xiaotong Han, Lixue Liu, Yuxuan Wu, Zhenzhen Liu, Jingjing Chen, Jing Zhuang, Keming Yu, Haotian Lin

“…The addition of the predicted SP-A1 and cCBI significantly improved model performance in diagnosing keratoconus, with NRI of 0.607 (95% CI 0.367-0.812) and 0.188 (95% CI −0.022-0.398), and IDI of 0.028 (95% CI 0.006-0.048) and 0.045 (95% CI 0.018-0.072), respectively. Conclusion: Our models predicted SP-A1 and cCBI relatively accurately in keratoconus and normal corneas. …”
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Evaluating and Forecasting the Probability of Lightning Occurrence in Rasht City by Afsaneh Ghasemi, Jamil Amanollahi

“…CHAID tree with a specificity rate of 0.794 and a minimum false positive rate of 0.205 and the SVM model with a correct prediction of 0.773 and an error rate of 0.475 and precision of 0.855 have optimum performance compared with other models. …”
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