IN VITRO EVALUATION OF PARTIALLY PURIFIED ANTIOXIDANT ENZYMES FROM LICHEN LEPTOGIUM PAPILLOSUM

ABSTRACTObjective: In this study, the enzyme activity of the partially purified six different antioxidant enzymes (AEs) of Leptogium papillosum such assuperoxide dismutase (SOD), catalase (CAT), peroxidase (POD), polyphenol oxidase (PPO), glutathione transferase (GST), and glutathione peroxidase(GPx) was carried out.Methods: Ammonium sulfate precipitation, dialysis, and DEAE-cellulose column chromatography were the three different methods performed topurify the six different AEs from L. papillosum. The antioxidant enzyme activity of the purified extracts was determined in vitro by the followingstandard procedure of SOD, CAT, POD, PPO, GST, and GPx.Results and Conclusion: The results revealed that there was a significant increase (p<0.001) in the specific activity of purified fractions of all theenzymes with a corresponding increase in the purification fold. The comparable activity of PPO and GST were determined using cluster analysis usingshort linkage distance. Principal component analysis indicated that SOD contributed primarily to the total variation in the AEs among allthe other fractions with the specific activity of 21.70 U/mg by attaining the purification fold of 5.91. Thus, our findings suggested that the purifiedAEs of L. papillosum possess potent antioxidant defense machinery by scavenging free radical population. Moreover, SOD was played a major role ofcapturing free radical by having highest enzyme activity followed by GST and CAT.DEAE-celluloseKeywords: Antioxidant enzymes, Cluster analysis, DEAE-cellulose column chromatography, Lichen, Leptogium papillosum, Principal componentanalysis

Enabling Longitudinal Respiration Monitoring Using Vapor-Coated Conducting Textiles

Wearable sensors allow for portable, long-term health monitoring in natural environments. Recently, there has been an increase in demand for technology that can reliably monitor respiration, which can be indicative of cardiac diseases, asthma, and infection by respiratory viruses. However, to date, the most reliable respiration monitoring system involves a tightly worn chest belt that is not conducive to longitudinal monitoring. Herein, we report that accurate respiration monitoring can be effected using a fabric-based humidity sensor mounted within a face mask. Our humidity sensor is created using cotton fabrics coated with a persistently p-doped conjugated polymer, poly(3,4-ethylenedioxythiophene):chloride (PEDOT-Cl), using a previously reported chemical vapor deposition process. The vapor-deposited polymer coating displays a stable, rapid, and reversible change in conductivity with an increase in local humidity, such as the humidity changes experienced within a face mask as the wearer breathes. Thus, when integrated into a face mask, the PEDOT-Cl-coated cotton humidity sensor is able to transduce breaths into an electrical signal. The humidity sensor-incorporated face mask is able to differentiate between deep and shallow breathing, as well as breathing versus talking. The sensor-incorporated face mask platform also functions both while walking and sitting, providing equally high signal quality in both indoor and outdoor contexts. Additionally, we show that the face mask can be worn for long periods of time with a negligible decline in the signal quality

Using organization knowledge to improve routing performance in wireless multi-agent networks

ABSTRACT Multi-agent systems benefit greatly from an organization design that guides agents in determining when to communicate, how often, with whom, with what priority, and so on. However, this same organization knowledge is not utilized by general-purpose wireless network routing algorithms normally used to support agent communication. We show that incorporating organization knowledge (otherwise available only to the application layer) in the network-layer routing algorithm increases bandwidth available at the application layer by as much as 35 percent. This increased bandwidth is especially important in communication-intensive application settings, such as agent-based sensor networks, where node failures and link dynamics make providing sufficient inter-agent communication especially challenging

Heteroskedastic Geospatial Tracking with Distributed Camera Networks

Visual object tracking has seen significant progress in recent years. However, the vast majority of this work focuses on tracking objects within the image plane of a single camera and ignores the uncertainty associated with predicted object locations. In this work, we focus on the geospatial object tracking problem using data from a distributed camera network. The goal is to predict an object's track in geospatial coordinates along with uncertainty over the object's location while respecting communication constraints that prohibit centralizing raw image data. We present a novel single-object geospatial tracking data set that includes high-accuracy ground truth object locations and video data from a network of four cameras. We present a modeling framework for addressing this task including a novel backbone model and explore how uncertainty calibration and fine-tuning through a differentiable tracker affect performance

Eulerian Phase-based Motion Magnification for High-Fidelity Vital Sign Estimation with Radar in Clinical Settings

Efficient and accurate detection of subtle motion generated from small objects in noisy environments, as needed for vital sign monitoring, is challenging, but can be substantially improved with magnification. We developed a complex Gabor filter-based decomposition method to amplify phases at different spatial wavelength levels to magnify motion and extract 1D motion signals for fundamental frequency estimation. The phase-based complex Gabor filter outputs are processed and then used to train machine learning models that predict respiration and heart rate with greater accuracy. We show that our proposed technique performs better than the conventional temporal FFT-based method in clinical settings, such as sleep laboratories and emergency departments, as well for a variety of human postures.Comment: Accepted in IEEE Sensors 202

Respiratory Rate Monitoring in Clinical Environments with a Contactless Ultra-Wideband Impulse Radar-based Sensor System

Respiratory rate is an extremely important but poorly monitored vital sign for medical conditions. Current modalities for respiratory monitoring are suboptimal. This paper presents a proof of concept of a new algorithm using a contactless ultra-wideband (UWB) impulse radar-based sensor to detect respiratory rate in both a laboratory setting and in a two-subject case study in the Emergency Department. This novel approach has shown correlation with manual respiratory rate in the laboratory setting and shows promise in Emergency Department subjects. In order to improve respiratory rate monitoring, the UWB technology is also able to localize subject movement throughout the room. This technology has potential for utilization both in and out of the hospital environments to improve monitoring and to prevent morbidity and mortality from a variety of medical conditions associated with changes in respiratory rate

UTILIZATION OF SAMANYA SHODHANA IN THE PURIFICATION OF EXCESS MERCURY OBTAINED FROM DENTAL OPERATORY- A PRELIMINARY STUDY

Background: Concerns about toxicity of mercury and disposal of excessive mercury has led to decreased usage of mercury in dental profession but still tooth colored restorative materials are not affordable by all the classes of any society. The disposal of excess mercury has always been a matter of concern. Thus, in the present study, we attempted to evaluate a simple procedure from Rasa Shastra using lime powder, garlic and rock salt for recycling of excess mercury obtained from dental operatory.Materials and methods: The excess mercury was recycled by the standard procedure explained in Ayurveda texts (Samanya shodhana) using Sudha churna (lime powder), Lashuna kalka (paste of Allium sativum L.) and Saindhava lavanaa (rock salt). The commercially available mercury and recycled mercury was analyzed by inductively coupled plasma mass spectrometry (ICP-MS) for the detection of elements in ppm level.Results: It was found that the excess impure mercury contained 5138 ppm, 2866.1 ppm and 0.371 ppm of Silver, Copper and Tin respectively. After Shodhana, the level of silver, tin and copper were markedly reduced. Purified mercury showed a level of 119.5ppm silver, 0.5324 ppm copper and 0.3233 ppm tin.Conclusion: Samanya shodhana is a simple promising procedure which can be used for mercury recycling. The procedure doesnot require sophisticated equipments and maneuver. Further, the materials used in the procedure are easily available and affordable at low cost