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Boosting Supramolecular Gelation Efficiency and Properties: Ionic Strength as a Key to Superior Hydrogels.
Langmuir
December 2024
Organic & Bioorganic Chemistry Laboratory, Council of Scientific and Industrial Research (CSIR) - Central Leather Research Institute (CLRI), Adyar, Chennai 600020, India.
Controlling the minimum gelation concentration (MGC) of low molecular weight (LMW) hydrogelators is a key for modulating gel properties, such as mechanical strength, viscoelasticity, and stability, which are crucial for applications ranging from drug delivery to tissue engineering. However, tweaking the MGC under specific conditions, such as pH and/or temperature, poses a considerable challenge. Herein, we varied the ionic strength of buffer solutions using NaCl for several LMW hydrogelators, including Fmoc-Phe, Fmoc-Tyr, Fmoc-Trp, Fmoc-Met, and Fmoc-Cha, and assessed their gelation efficiency at pH 7.
View Article and Find Full Text PDFExploring the adhesion properties of extracellular vesicles for functional assays.
bioRxiv
October 2024
Department of Molecular and Comparative Pathobiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
The "stickiness" of extracellular vesicles (EVs) can pose challenges for EV processing and storage, but adhesive properties may also be exploited to immobilize EVs directly on surfaces for various measurement techniques, including super-resolution microscopy. Direct adhesion to surfaces may allow examination of broader populations of EVs than molecular affinity approaches, which can also involve specialized, expensive affinity reagents. Here, we report on the interaction of EVs with borosilicate glass and quartz coverslips and on the effects of pre-coating coverslips with poly-L-lysine (PLL), a reagent commonly used to facilitate interactions between negatively charged surfaces of cells and amorphous surfaces.
View Article and Find Full Text PDFA whole genome sequencing-based assay to investigate antibiotic susceptibility and strain lineage of Helicobacter pylori.
Microb Pathog
December 2024
State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and KLMDASR of Tianjin, Nankai University, Tongyan Road, Haihe Education Park, Tianjin, 300350, China. Electronic address:
Article Synopsis
- Helicobacter pylori (H. pylori) is increasingly resistant to antibiotics globally, complicating treatment efforts for infections.
- A new whole genome sequencing (WGS) assay was developed to analyze 73 H. pylori strains from patients in Tianjin, China, linking specific genetic mutations to antibiotic resistance.
- Four super-resistant strains were identified that formed biofilms, indicating that biofilm formation is another mechanism of resistance, suggesting that biofilm-related genes could be valuable for resistance screening.
Monitoring and management of the Nearctic leafhopper Scaphoideus titanus (Hemiptera: Cicadellidae) in Italian vineyards.
J Econ Entomol
December 2024
Department of Agriculture, Food and Environment (DISAAA-a), University of Pisa, Pisa, Italy.
Article Synopsis
- The study focused on the effectiveness of various insecticides in managing *Scaphoideus titanus*, the main vector for grapevine flavescence dorée in European vineyards.
- It involved a three-year evaluation of different spray strategies and monitoring tools to better target and control leafhopper populations.
- Results indicated that certain insecticides like etofenprox and deltamethrin were most effective, and that yellow and green sticky traps significantly outperformed others for capturing the insects.
SRNet-YOLO: A model for detecting tiny and very tiny pests in cotton fields based on super-resolution reconstruction.
Front Plant Sci
August 2024
School of Computer Science and Technology, Xinjiang University, Urumqi, China.
Article Synopsis
- - The study introduces a new pest detection framework, called SRNet-YOLO, designed to improve the identification of tiny and very tiny pests in cotton fields, which are challenging for existing object detection models due to their small sizes.
- - SRNet-YOLO integrates advanced features such as a super-resolution reconstruction module (FM-SR) to enhance feature detail and a fusion mechanism (BiFormerAF) to combine these features with existing data, resulting in better detection accuracy.
- - Experimental results indicate that SRNet-YOLO significantly outperforms previous models, achieving 78.2% mean Average Precision (mAP) for tiny pests and 57% mAP for very tiny pests, showing considerable improvements over models like YOLO
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