Results 171 to 180 of about 122,919 (308)

Body Mass Index and Vaccine-induced Immune Responses in Children Living With HIV. [PDF]

Pediatr Infect Dis J
Massa JD, Giganti MJ, Lindsey JC, Levin MJ, Nachman S.   +4 more
europepmc   +1 more source

Risk Factors for Small‐for‐Size Syndrome Grade B/C After Simultaneous Splenectomy in Adult Living‐Donor Liver Transplantation

Annals of Gastroenterological Surgery, EarlyView.
In a single‐center cohort of 577 adult LDLT recipients who underwent simultaneous splenectomy, clinically significant SFSS grade B/C (ILTS‐iLDLT‐LTSI 2023) occurred in 18.2% and was associated with inferior graft survival. Multivariate analysis identified MELD ≥ 30, NLR ≥ 4.5, and donor age ≥ 50 years as independent risk factors, which risk rising ...
Kyohei Yugawa, Takeo Toshima, Shinji Itoh, Takashi Motomura, Shohei Yoshiya, Norifumi Iseda, Tomoharu Yoshizumi   +6 more
wiley   +1 more source

Effective communication and public engagement strategies to counter misinformation about infectious diseases. [PDF]

Immunol Cell Biol
Cruickshank S, McKee M, Pagel C.
europepmc   +1 more source

Visionary Leadership in Cancer Care: An Interview With Professor Timothy J. Eberlein

Annals of Gastroenterological Surgery, EarlyView.
Professor Timothy J. Eberlein and Professor Ken Shirabe, President of the Japanese Society of Gastroenterological Surgery, during their interview discussing the vision, strategic framework, and leadership that shaped the development of the Siteman Cancer Center into a world‐class institution. ABSTRACT This is a short interview with Professor Timothy J.
Ken Shirabe, Koshi Mimori, Masaki Mori, Yuko Kitagawa   +3 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Integration Models for Delivering COVID-19 Vaccines Through HIV Services in Low-and Middle-Income Countries: A Scoping Review. [PDF]

Infect Dis Rep
Mbeye NM, Chipojola R, Banda S, Kaude P, Mdolo A, Nwosisi C, Mounier-Jack S.   +6 more
europepmc   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

"Make America Healthy Again" will make the world sicker : The public health policies of the US administration will have dire results for national and global health. [PDF]

EMBO Rep
Grimes DR.
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source