Purpose: Obesity is being considered a "global epidemic." Surgical procedures are rendered more difficult in obese patients. We aimed to see whether any benefits were evident with use of computer navigation during total knee replacement in these cases.
Methods: A retrospective analysis of 287 TKR performed by a single surgeon was undertaken, including 133 TKR undertaken with computer navigation and 154 using standard instrumentation. Each group was further divided into subgroups depending on whether the patients were obese or nonobese.
Results: We found that TKR in obese patients took longer with standard instruments, but not with computer navigation. A chronological analysis revealed that the surgeon progressively got quicker using computer navigation to the point that there was no difference in time with either of the operative techniques in obese patients. The mid-term clinical outcomes at five years were similar. Computer navigated TKR were more consistently accurately aligned.
Conclusions: In obese patients, a dual advantage is provided by computer navigation: better alignment and no time penalty.
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http://dx.doi.org/10.1155/2014/272838 | DOI Listing |
Sci Data
January 2025
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210000, China.
Travelable area boundaries not only constrain the movement of field robots but also indicate alternative guiding routes for dynamic objects. Publicly available road boundary datasets have outlined boundaries by binary segmentation labels. However, hard post-processes have to be done to extract from detected boundaries further semantics including the shapes of the boundaries and guiding routes, which poses challenges to a real-time visual navigation system without detailed prior maps.
View Article and Find Full Text PDFNat Commun
January 2025
Neuroscience Institute, New York University Langone Health, New York, NY, 10016, USA.
Apical and basal dendrites of pyramidal neurons receive anatomically and functionally distinct inputs, implying compartment-level functional diversity during behavior. To test this, we imaged in vivo calcium signals from soma, apical dendrites, and basal dendrites in mouse hippocampal CA3 pyramidal neurons during head-fixed navigation. To capture compartment-specific population dynamics, we developed computational tools to automatically segment dendrites and extract accurate fluorescence traces from densely labeled neurons.
View Article and Find Full Text PDFInnovation (Camb)
January 2025
AIM Center, College of Life Sciences and Technology, Beijing University of Chemical Technology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Predicting free energy changes (ΔΔG) is essential for enhancing our understanding of protein evolution and plays a pivotal role in protein engineering and pharmaceutical development. While traditional methods offer valuable insights, they are often constrained by computational speed and reliance on biased training datasets. These constraints become particularly evident when aiming for accurate ΔΔG predictions across a diverse array of protein sequences.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantially. This progress inspired the development of the first genome-wide small molecule targets scanning method.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Unitat de Recerca i Innovació, Gerència d'Atenció Primària i a la Comunitat de la Catalunya Central, Institut Català de la Salut, Sant Fruitós de Bages, Spain.
Background: The COVID-19 pandemic reshaped social dynamics, fostering reliance on social media for information, connection, and collective sense-making. Understanding how citizens navigate a global health crisis in varying cultural and economic contexts is crucial for effective crisis communication.
Objective: This study examines the evolution of citizen collective sense-making during the COVID-19 pandemic by analyzing social media discourse across Italy, the United Kingdom, and Egypt, representing diverse economic and cultural contexts.
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