The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.
Read More...Varying levels of disinfectant resistance among invasive Klebsiella pneumoniae isolates
The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.
Read More...The Clinical Accuracy of Non-Invasive Glucose Monitoring for ex vivo Artificial Pancreas
Diabetes is a serious worldwide epidemic that affects a growing portion of the population. While the most common method for testing blood glucose levels involves finger pricking, it is painful and inconvenient for patients. The authors test a non-invasive method to measure glucose levels from diabetic patients, and investigate whether the method is clinically accurate and universally applicable.
Read More...Comparing neural networks with a traditional method for identifying the vanishing points of surgical tools
Robot-assisted minimally invasive surgery (RMIS) benefits from increased precision and faster recovery, with force feedback from the surgical tool being critical for control. Researchers tested the use of neural networks for detecting the vanishing point of the tool, a key element for force feedback.
Read More...Assessing Materials’ Short-term Effectiveness on Controlling Zebra Mussel (Dreissena polymorpha) Attachment
Zebra mussels are an aquatic invasive species. They attach to essential industrial structures and harm the native ecosystem, costing millions of dollars each year to control. This study explored the effectiveness of two nontoxic materials (Sharklet & Netminder) in combating zebra mussel attachment.
Read More...The peroxidase-like activity of papain colorimetrically detects H2O2 and glucose with high sensitivity
Many diabetics agree that the current glucometer methods are invasive, inefficient, and unsustainable for measuring blood glucose. These authors investigate the possibility of using a non-invasive glucometer patch that predicts blood glucose from patient sweat, with high accuracy.
Read More...Near-infrared activation of environmentally-friendly gold and silver nanoparticles for unclogging arteries
Coronary artery disease, the leading cause of death worldwide, results from cholesterol build-up in coronary arteries, limiting blood and oxygen flow to the heart. This study investigated the use of gold and silver nanoparticles coated with aspirin and activated by near-infrared light to improve blood flow in a clogged artery model. The nanoparticles increased simulated blood flow rates, demonstrating potential as a less invasive and more targeted treatment for cardiovascular disease.
Read More...QuitPuff: A Simple Method Using Saliva to Assess the Risk of Oral Pre-Cancerous Lesions and Oral Squamous Cell Carcinoma in Chronic Smokers
Smoking generates free radicals and reactive oxygen species which induce cell damage and lipid peroxidation. This is linked to the development of oral cancer in chronic smokers. The authors of this study developed Quitpuff, simple colorimetric test to measure the extent of lipid peroxidation in saliva samples. This test detected salivary lipid peroxidation with 96% accuracy in test subjects and could serve as an inexpensive, non-invasive test for smokers to measure degree of salivary lipid peroxidation and potential risk of oral cancer.
Read More...Optimizing an eDNA assay and field deployment to detect decapod species in Oʻahu streams
This study explored the use of environmental DNA (eDNA) methods to detect native Hawaiian decapod species (‘opae), which are difficult to observe manually due to their low density.
Read More...Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.
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