Results 61 to 70 of about 20,849 (221)

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Correlation between peripapillary retinal nerve fiber layer thickness and fundus autofluorescence in primary open-angle glaucoma

Clinical Ophthalmology, 2013
Lukas Reznicek,* Florian Seidensticker,* Thomas Mann, Irene Hübert, Alexandra Buerger, Christos Haritoglou, Aljoscha S Neubauer, Anselm Kampik, Christoph Hirneiss, Marcus Kernt Department of Ophthalmology, Ludwig-Maximilians-University, Munich ...
Reznicek L, Seidensticker F, Mann T, Hübert I, Buerger A, Haritoglou C, Neubauer AS, Kampik A, Hirneiss C, Kernt M   +9 more
doaj  

A rhesus macaque model of α‐dystroglycanopathy caused by a POMT1 splice altering variant

Animal Models and Experimental Medicine, EarlyView.
Rhesus macaques homozygous for a naturally occurring spice altering variant in the POMT1 gene develop lissencephaly, microphthalmia, and muscular contracture. The presentation models severe presentation of the human Walker‐Warburg syndrome. Abstract Background Biallelic mutations in genes associated with α‐dystroglycan glycosylation manifest in a ...
Anya Nordlund, Brian LaMendola, Nathan P. Crilly, Seth Kittle, Betsy M. Ferguson, Anne D. Lewis, Jeff Wall, Samuel M. Peterson   +7 more
wiley   +1 more source

Chrysin attenuates diabetes‐induced retinal injury by inhibiting microglial GBP3/NLRP3/GSDMD‐mediated pyroptosis

Animal Models and Experimental Medicine, EarlyView.
We investigated the therapeutic potential and mechanism of chrysin in experimental diabetic retinal disease. Using a streptozotocin (STZ)‐induced diabetic mouse model and high‐glucose‐stimulated BV2 microglia, we revealed chrysin‐responsive pyroptosis‐associated signatures and identified GBP3 as a regulated node.
Qun Liu, Song‐min Wang, Xuan Chen, Yi‐rao You, Chen‐jiao Guo, Chang‐qin Xie, Lu‐lu Wang, Qi Liu, Lan Zhang, Jun‐tao Yang   +9 more
wiley   +1 more source

Correlation between cognitive impairment and retinal neural loss assessed by swept‐source optical coherence tomography in patients with mild cognitive impairment

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 2019
Introduction We compared peripapillary retinal nerve fiber layer and macular thickness measurements in patients with mild cognitive impairment (MCI) and control subjects using swept‐source optical coherence tomography (SS‐OCT).
Ana L.M. Almeida, Leopoldo A. Pires, Evelyn A. Figueiredo, Luciana V.F. Costa‐Cunha, Leandro C. Zacharias, Rony C. Preti, Mário L.R. Monteiro, Leonardo P. Cunha   +7 more
doaj   +1 more source

Innovative PLA or PCL‐Based Ocular Implants Obtained From Tape Casting or Electrospinning for Sustained‐Release Dexamethasone

Journal of Applied Polymer Science, EarlyView.
PLA and PCL ocular implants prepared by tape casting and electrospinning provide sustained dexamethasone release with distinct release profiles governed by polymer type and processing method. The relationship between polymer structure, degradation behavior, and drug release demonstrates the potential of these fabrication techniques for controlled ...
Renata Bochanoski, Henrique Borba Modolon, Ronaldo Silveira, Januara Rodrigues, Tiago Bender Wermuth, Sabrina Arcaro, Oscar R. K. Montedo   +6 more
wiley   +1 more source

Retinal ganglion cell–inner plexiform layer thickness is nonlinearly associated with cognitive impairment in the community‐dwelling elderly

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 2019
Introduction Thinning of optical coherence tomography–measured retinal nerve fiber layer thickness and ganglion cell–inner plexiform layer (GC‐IPL) thickness has been found in patients with Alzheimer's disease.
Yao‐Lin Liu, Yi‐Ting Hsieh, Ta‐Fu Chen, Jeng‐Min Chiou, Min‐Kuang Tsai, Jen‐Hau Chen, Yen‐Ching Chen   +6 more
doaj   +1 more source

Perovskite Photodetectors at the Intelligence Frontier: From Tunable Materials to Adaptive Optoelectronic Systems

Carbon Energy, EarlyView.
This comprehensive review presents a progressive roadmap for perovskite vision detectors. Centered on perovskite‐based artificial perception, the graphic illustrates a systematic evolution: starting with fundamental material engineering and device architectures, advancing toward complex functional strategies such as flexible neuromorphic imaging ...
Chenglong Li, Wei Qu, Deepak Kumar, Naini Jain, Nur Wardina Syahirah binti Mohamad Fadil, Nur Najiha binti Ahmad Rasid, Emannuel Kymakis, Maria Vasilopoulou, Chunxiong Bao, Feng Gao, Peng Gao, Sanjeev Kumar Sharma, Mohammad Khaja Nazeeruddin, Abd. Rashid bin Mohd Yusoff, Haotong Wei   +14 more
wiley   +1 more source

Optic Nerve Head Measurements Across Optical Coherence Tomography Platforms and Incidental Optic Nerve Head Drusen in Community Screenings

Eye &ENT Research, EarlyView.
ABSTRACT Background Automated vertical cup‐to‐disc ratio (VCDR) measurements are commonly used in optic nerve assessment, but measurements may vary across optical coherence tomography (OCT) platforms, particularly in eyes with atypical optic nerve anatomy such as optic nerve head drusen (ONHD).
Sedra T. Alabed, Aretha Zhu, Bernard C. Szirth, Albert S. Khouri   +3 more
wiley   +1 more source

Artificial Intelligence in Ophthalmology: From Methodological Advances to Clinical Translation and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is reshaping ophthalmology from task‐specific image analysis toward multimodal, longitudinal, and clinically integrated decision support. This narrative review summarizes the methodological evolution of ophthalmic AI, including traditional machine learning, task‐specific deep learning, self‐supervised learning ...
Yuxin Liu, Hanruo Liu
wiley   +1 more source