Ethnomedicinal practices in the arid zone of India: A study in urban and semi-urban areas of Bhuj, Gujarat

Plants are a vital and life-sustaining natural resource as they provide many ecosystem services and supply food, fibre, fuel, medicine, etc. They are distributed heterogeneously in different ecosystems. With the increasing urbanization in all parts of the world, the vegetation overlapped with urban localities like parks, gardens, roadsides, wasteland and other human habitations. Among this vegetation, many of them are used in ethnomedicine or in ayurvedic medicine by people for a long period of time. These valuable plant resources are now under threat due to various anthropogenic activities in the urban landscape. Bhuj is a small historic city in the arid zone of India with a rich diversity of medicinal plants. With the increasing human population and associated developmental activities within the city, many of these plants are under threat of extinction. Therefore, an attempt was made to document these medicinal plants distributed in different parts of the city and their uses for ethnomedicinal purposes. The plants were intensively surveyed and documented using a questionnaire survey, discussion and cross-checked with available literature. A total of 123 species of ethnomedicinal plants were documented and analysed for their uses in curing different health problems and conservation purposes in the urban landscape

A convolutional neural network to filter artifacts in spectroscopic MRI

Purpose Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. Methods A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency‐domain spectra to detect artifacts. Results When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single‐voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole‐brain spectroscopic MRI volumes in real time. Conclusion The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning

Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy

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Dynamic and accurate assessment of acetaminophen-induced hepatotoxicity by integrated photoacoustic imaging and mechanistic biomarkers in vivo

The prediction and understanding of acetaminophen (APAP)-induced liver injury (APAP-ILI) and the response to therapeutic interventions is complex. This is due in part to sensitivity and specificity limitations of currently used assessment techniques. Here we sought to determine the utility of integrating translational non-invasive photoacoustic imaging of liver function with mechanistic circulating biomarkers of hepatotoxicity with histological assessment to facilitate the more accurate and precise characterization of APAP-ILI and the efficacy of therapeutic intervention. Perturbation of liver function and cellular viability was assessed in C57BL/6J male mice by Indocyanine green (ICG) clearance (Multispectral Optoacoustic Tomography (MSOT)) and by measurement of mechanistic (miR-122, HMGB1) and established (ALT, bilirubin) circulating biomarkers in response to the acetaminophen and its treatment with acetylcysteine (NAC) in vivo. We utilised a 60% partial hepatectomy model as a situation of defined hepatic functional mass loss to compared acetaminophen-induced changes to. Integration of these mechanistic markers correlated with histological features of APAP hepatotoxicity in a time-dependent manner. They accurately reflected the onset and recovery from hepatotoxicity compared to traditional biomarkers and also reported the efficacy of NAC with high sensitivity. ICG clearance kinetics correlated with histological scores for acute liver damage for APAP (i.e. 3h timepoint; r=0.90, P<0.0001) and elevations in both of the mechanistic biomarkers, miR-122 (e.g. 6h timepoint; r=0.70, P=0.005) and HMGB1 (e.g. 6h timepoint; r=0.56, P=0.04). For the first time we report the utility of this non-invasive longitudinal imaging approach to provide direct visualisation of the liver function coupled with mechanistic biomarkers, in the same animal, allowing the investigation of the toxicological and pharmacological aspects of APAP-ILI and hepatic regeneration