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Intra-Mesopore Immunoassay Based on Core-Shell Structured Magnetic Hierarchically Porous ZIFs.
ACS Sens
January 2025
Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
It is crucial yet challenging to sensitively quantify low-abundance biomarkers in blood for early screening and diagnosis of various diseases. Herein, an analytical model of intra-mesopore immunoassay (IMIA) was proposed, which was competent to examine various biomarkers at the femtomolar level. The success is rooted in the design of an innovative superparamagnetic core-shell structure with FeO nanoparticles (NPs) at the core and hierarchically porous zeolitic imidazolate frameworks as a shell (FeO@HPZIF-8), achieved through a soft-template directed self-assembly coupled with confinement growth mechanism.
View Article and Find Full Text PDFAdvanced low-power filter architecture for biomedical signals with adaptive tuning.
PLoS One
January 2025
Computer Engineering, CCSIT, King Faisal University, Al Hufuf, Kingdom of Saudi Arabia.
This paper presents a low-power, second-order composite source-follower-based filter architecture optimized for biomedical signal processing, particularly ECG and EEG applications. Source-follower-based filters are recommended in the literature for high-frequency applications due to their lower power consumption when compared to filters with alternative topologies. However, they are not suitable for biomedical applications requiring low cutoff frequencies as they are designed to operate in the saturation region.
View Article and Find Full Text PDFsp. nov., a bacterium isolated from the air of the Icelandic volcanic island Surtsey.
Int J Syst Evol Microbiol
January 2025
Department of Research and Innovation, MATIS, Reykjavk, Iceland.
A novel bacterium, designated 19SA41, was isolated from the air of the Icelandic volcanic island Surtsey. Cells of strain 19SA41 are Gram-stain-negative, strictly aerobic, non-motile rods and form pale yellow-pigmented colonies. The strain grows at 4-30 °C (optimum, 22 °C), at pH 6-10 (optimum, pH 7.
View Article and Find Full Text PDFNoninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.
Transl Vis Sci Technol
January 2025
School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.
Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.
Deep Learning Enabled Scoring of Pancreatic Neuroendocrine Tumors Based on Cancer Infiltration Patterns.
Endocr Pathol
January 2025
Department of Computer Engineering, Koc University, Istanbul, Turkey.
Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms that include tumors with different histomorphologic characteristics that can be correlated to sub-categories with different prognoses. In addition to the WHO grading scheme based on tumor proliferative activity, a new parameter based on the scoring of infiltration patterns at the interface of tumor and non-neoplastic parenchyma (tumor-NNP interface) has recently been proposed for PanNET categorization. Despite the known correlations, these categorizations can still be problematic due to the need for human judgment, which may involve intra- and inter-observer variability.
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