Land Use and Land Cover Change Detection Using the Random Forest Approach: The Case of The Upper Blue Nile River Basin, Ethiopia
Monitoring land use change dynamics is critical for tackling food security, climate change, and biodiversity loss on a global scale. This study is designed to classify land use and land cover in the upper Blue Nile River Basin (BNRB) using a random forest (RF) algorithm. The Landsat images for Landsat 45, Landsat 7, and Landsat 8 are used for classification purposes. The study area is classified into seven land use/land cover classes: cultivated lands, bare lands, built-ups, forests, grazing lands, shrublands, and waterbodies. The accuracy of classified images is 83%, 85%, and 91% using the Kappa index of agreements. From 1983 to 2022 periods, cultivated lands and built-up areas increased by 47541 and 1777 km2, respectively, at the expense of grazing lands, shrublands, and forests. Furthermore, the area of water bodies has increased by 662 km2 due to the construction of small and large-scale irrigation and hydroelectric power generation dams. The main factors that determine agricultural land expansion are related to population growth. Therefore, land use and land cover change detection using a random forest is an important technique for multispectral satellite data classification to understand the optimal use of natural resources, conservation practices, and decision-making for sustainable development.
Development of a morphologically realistic mouse phantom for pre-clinical photoacoustic imaging
Characterizations based on anatomically realistic phantoms are highly effective to perform accurate technical validation of imaging systems. Specifically for photoacoustic imaging (PAI), although a variety of phantom models with simplified geometries are reported, an unmet need still exists to establish morphologically realistic heterogeneous pre-clinical phantoms. So the development of a mouse-mimicking phantom can reduce the use of animals for the validation and standardization studies of pre-clinical PAI systems and thus eventually translate the PAI technology to clinical research.
A simple and robust nanosystem for photoacoustic imaging of bladder cancer based on α5β1-targeted gold nanorods
Early detection and removal of bladder cancer in patients is crucial to prevent tumor recurrence and progression. Because current imaging techniques may fail to detect small lesions of in situ carcinomas, patients with bladder cancer often relapse after initial diagnosis, thereby requiring frequent follow-up and treatments.
Near-Infrared Spectroscopy for the In Vivo Monitoring of Biodegradable Implants in Rats
Magnesium (Mg) alloys possess unique properties that make them ideal for use as biodegradable implants in clinical applications. However, reports on the in vivo assessment of these alloys are insufficient. Thus, monitoring the degradation of Mg and its alloys in vivo is challenging due to the dynamic process of implant degradation and tissue regeneration. Most current works focus on structural remodeling, but functional assessment is crucial in providing information about physiological changes in tissues, which can be used as an early indicator of healing. Here, we report continuous wave near-infrared spectroscopy (CW NIRS), a non-invasive technique that is potentially helpful in assessing the implant-tissue dynamic interface in a rodent model. The purpose of this study was to investigate the effects on hemoglobin changes and tissue oxygen saturation (StO) after the implantation of Mg-alloy (WE43) and titanium (Ti) implants in rats' femurs using a multiwavelength optical probe. Additionally, the effect of changes in the skin on these parameters was evaluated. Lastly, combining NIRS with photoacoustic (PA) imaging provides a more reliable assessment of tissue parameters, which is further correlated with principal component analysis.
Early diagnosis of bladder cancer by photoacoustic imaging of tumor-targeted gold nanorods
Detection and removal of bladder cancer lesions at an early stage is crucial for preventing tumor relapse and progression. This study aimed to develop a new technological platform for the visualization of small and flat urothelial lesions of high-grade bladder carcinoma in situ (CIS). We found that the integrin α5β1, overexpressed in bladder cancer cell lines, murine orthotopic bladder cancer and human bladder CIS, can be exploited as a receptor for targeted delivery of GNRs functionalized with the cyclic CphgisoDGRG peptide (). The GNRs@Chit- was stable in urine and selectively recognized α5β1 positive neoplastic urothelium, while low frequency ultrasound-assisted shaking of intravesically instilled GNRs@Chit- allowed the distribution of nanoparticles across the entire volume of the bladder. Photoacoustic imaging of GNRs@Chit- bound to tumor cells allowed for the detection of neoplastic lesions smaller than 0.5 mm that were undetectable by ultrasound imaging and bioluminescence.