ABSTRACT
Preterm birth (gestational age < 37 weeks) is a public health concern that causes fetal and maternal mortality and morbidity. When this condition is detected early, suitable treatment can be prescribed to delay labour. Uterine electromyography (uEMG) has gained a lot of attention for detecting preterm births in advance. However, analyzing uEMG is challenging due to the complexities associated with inter and intra-subject variations. This work aims to investigate the applicability of cyclostationary characteristics in uEMG signals for predicting premature delivery. The signals under term and preterm situations are considered from two online datasets. Preprocessing is carried out using a Butterworth bandpass filter, and spectral correlation density function is adapted using fast Fourier transform-based accumulation method (FAM) to compute the cyclostationary variations. The cyclic frequency spectral density (CFSD) and degree of cyclostationarity (DCS) are quantified to assess the existence of cyclostationarity. Features namely, maximum cyclic frequency, bandwidth, mean cyclic frequency (MNCF), and median cyclic frequency (MDCF) are extracted from the cyclostationary spectrum and analyzed statistically. uEMG signals exhibit cyclostationarity property, and these variations are found to distinguish preterm from term conditions. All the four extracted features are noted to decrease from term to preterm conditions. The results indicate that the cyclostationary nature of the signals can provide better characterization of uterine muscle contractions and could be helpful in detecting preterm birth. The proposed method appears to aid in detecting preterm birth, as analysis of uterine contractions under preterm conditions is imperative for timely medical intervention.
ABSTRACT
The effectiveness of aqueous extracts of various medicinal plants in detoxification of aflatoxin B1 (AFB1) was tested in vitro by thin-layer chromatography and enzyme-linked immunosorbent assay (ELISA). Among the different plant extracts, the leaf extract of Vasaka (Adhatoda vasica Nees) showed the maximum degradation of AFB1 (≥ 98%) after incubation for 24h at 37 °C. The aflatoxin detoxifying activity of the A. vasica leaf extract was significantly reduced by heating to 100 °C for 10 min or autoclaving at 121 °C for 20 min. Dialysis had no effect on aflatoxin detoxifying ability of A. vasica extract and the dialyzed extract showed similar level of detoxification of AFB1 as that of the untreated extract. A time course study of aflatoxin detoxification by A. vasica extract showed that 69% of the toxin was degraded within 6h and ≥ 95% degradation was observed after 24h of incubation. Detoxification of AFB1 by A. vasica extract was further confirmed by liquid chromatography-mass spectrometry (LC-MS) analysis. Phytochemical analysis revealed the presence of alkaloids in methanolic extract of A. vasica leaves. A partially purified alkaloid from A. vasica leaves by preparative TLC exhibited strong AFB1 detoxification activity.