Non-intrusive RF sensing for early diagnosis of spinal curvature syndrome disorders.

The recent developments in communication and information ease people's lives to sit in one place and access any information from anywhere. However, the longevity of sitting and sitting in different postures raises the issues of spinal curvature. It necessitates a physical examination to identify the spinal illness in its early stages. This article aims to develop an intelligent monitoring framework for detecting and monitoring spinal curvature syndrome problems based on Software Defined Radio Frequency (SDRF) sensing and verify its feasibility for diagnosing actual patients. The proposed SDRF-based system identifies irregular spinal curvature syndrome and offers feedback signals when an incorrect posture is identified. We design the system using wireless university software-defined radio peripheral (USRP) kits to transmit and receive RF signals and record the wireless channel state information (WCSI) for kyphosis, Lordosis, and scoliosis spinal disorders. The statistical measures are extracted from the WCSI and apply machine learning algorithms to identify and classify the type of disorders. We record and test the system using 11 subjects with the spinal disorders kyphosis, Lordosis, and scoliosis. We acquire the WCSI, extract various statistical measures in terms of time and frequency domain features, and evaluate machine learning classifiers to identify and classify the spinal disorder. The performance comparison of the machine learning algorithms showed overall and each spinal curvature disorder recognition accuracy of more than 99%.

Three new anthraquinone derivatives isolated from Symplocos racemosa and their antibiofilm activity / 中国天然药物

Three new alkyl substituted anthraquinone derivatives, trivially named as symploquinones A-C (Compounds 1-3) were isolated from Symplocos racemosa. The structures of these compounds were determined on the basis of extensive spectroscopic analyses (UV, IR, Mass, H- and C-NMR, and two-dimensional (2D) NMR techniques). The resulting data were also compared with the reported literature. These compounds were then subjected to antibacterial or antibiofilm testing. Compounds 1 and 3 exhibited good antibacterial activity in the concentration range of 160-83 μg·mL against Streptococcus mutans, methicillin resistant Staphylococcus aureus and Proteus mirabilis. Both compounds were further screened for anti-biofilm activity, which revealed promising activities at sub-MIC concentrations. None of the compounds were found to be active against Klebsiella pneumoniae.

In vitro-in vivo correlation study on nimesulide loaded hydroxypropylmethylcellulose microparticles / 药学学报

This study involves mathematical simulation model such as in vitro-in vivo correlation (IVIVC) development for various extended release formulations of nimesulide loaded hydroxypropylmethylcellulose (HPMC) microparticles (M1, M2 and M3 containing 1, 2, and 3 g HPMC, respectively and 1 g drug in each) having variable release characteristics. In vitro dissolution data of these formulations were correlated to their relevant in vivo absorption profiles followed by predictability worth analysis of these Level A IVIVC. Nimaran was used as control formulation to validate developed formulations and their respective models. The regression coefficients of IVIVC plots for M1, M2, M3 and Nimaran were 0.834 9, 0.831 2, 0.927 2 and 0.898 1, respectively. The internal prediction error for all formulations was within limits, i.e., < 10%. A good IVIVC was found for controlled release nimesulide loaded HPMC floating M3 microparticles. In other words, this mathematical simulation model is best fit for biowaiver studies which involves study parameters as those adopted for M3 because the value of its IVIVC regression coefficient is the closest to 1 as compared to M1 and M2.