Language disorders, which are still very poorly detected, are often present in abused children. While the consequences are well known and long-lasting, little is known about the development and specific characteristics of these children, depending on where they were placed, the type of abuse they suffered and the age at which they were placed. This finding led to a review of the literature aimed at better defining the state of knowledge on the subject, for the benefit of better detection and treatment.
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http://dx.doi.org/10.1016/j.spp.2024.05.009 | DOI Listing |
JAMA Netw Open
January 2025
Office of Global and Population Health, Boston University Henry M. Goldman School of Dental Medicine, Boston, Massachusetts.
Importance: Caries is the most common chronic childhood disease, with substantial health disparities.
Objective: To test whether parent-targeted oral health text (OHT) messages outperform child wellness text (CWT) messages on pediatric caries increment and oral health behaviors among underserved children attending pediatric well-child visits.
Design, Setting, And Participants: The parallel randomized clinical trial, Interactive Parent-Targeted Text Messaging in Pediatric Clinics to Reduce Caries Among Urban Children (iSmile), included participants who were recruited during pediatric medical clinic visits at 4 sites in Boston, Massachusetts, that serve low-income and racially and ethnically diverse (herein, underserved) populations.
Zhonghua Kou Qiang Yi Xue Za Zhi
January 2025
Department of Stomatology, The second affiliated hospital of Nanchang University,Nanchang330006, China.
Artificial intelligence (AI) technology is a scientific and technological field that focuses on the research and development of systems that simulate, extend, and expand human intelligence activities. This field encompasses various applications such as image recognition, language processing, expert systems, and robotics. The advancement of AI has greatly improved the quality and efficiency of medical work, particularly in areas like medical imaging, clinical decision support, precision medicine, and healthcare management.
View Article and Find Full Text PDFOcul Surf
December 2024
Centre for Ocular Research and Education (CORE), School of Optometry and Vision Science, University of Waterloo, Canada; Optometry and Vision Science Research Group, College of Health and Life Sciences, Aston University, Birmingham, United Kingdom; Department of Ophthalmology, Aotearoa New Zealand National Eye Centre, The University of Auckland, New Zealand.
Aims: To understand current clinical management of dry eye disease (DED), based on its perceived severity and subtype by practitioners across the world.
Methods: The content of the anonymous survey was chosen to reflect the DED management strategies reported by the Tear Film and Ocular Surface Society (TFOS) 2 Dry Eye Workshop (DEWS II). Questions were designed to ascertain practitioner treatment choice, depending on the subtype and severity of DED.
PLoS One
December 2024
Department of Spanish Philology, University of Málaga, Málaga, Spain.
Nasalance is a valuable clinical biomarker for hypernasality. It is computed as the ratio of acoustic energy emitted through the nose to the total energy emitted through the mouth and nose (eNasalance). A new approach is proposed to compute nasalance using Convolutional Neural Networks (CNNs) trained with Mel-Frequency Cepstrum Coefficients (mfccNasalance).
View Article and Find Full Text PDFBioact Mater
April 2025
Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China.
Angiogenesis is imperative for bone regeneration, yet the conventional cytokine therapies have been constrained by prohibitive costs and safety apprehensions. It is urgent to develop a safer and more efficient therapeutic alternative. Herein, utilizing the methodologies of Deep Learning (DL) and Natural Language Processing (NLP), we proposed a paradigm algorithm that amalgamates with a variant, , to deftly discern potential pro-angiogenic peptides from intrinsically disordered regions (IDRs) of 262 related proteins, where are fertile grounds for developing safer and highly promising bioactive peptides.
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