Quorum-quenching activity of the AHL-lactonase from <i>Bacillus licheniformis</i> DAHB1 inhibits vibrio biofilm formation in vitro and reduces shrimp intestinal colonisation and mortality

Vibrio parahaemolyticus is a significant cause of gastroenteritis resulting from the consumption of undercooked sea foods and often cause significant infections in shrimp aquaculture. Vibrio virulence is associated with biofilm formation and is regulated by N-acylated homoserine lactone (AHL)-mediated quorum sensing. In an attempt to reduce vibrio colonisation of shrimps and mortality, we screened native intestinal bacilli from Indian white shrimps (Fenneropenaeus indicus) for an isolate which showed biofilm-inhibitory activity (quorum quenching) against the pathogen V. parahaemolyticus DAHP1. The AHL-lactonase (AiiA) expressed by one of these, Bacillus licheniformis DAHB1, was characterised as having a broad-spectrum AHL substrate specificity and intrinsic resistance to the acid conditions of the shrimp intestine. Purified recombinant AiiA inhibited vibrio biofilm development in a cover slip assay and significantly attenuated infection and mortality in shrimps reared in a recirculation aquaculture system. Investigation of intestinal samples also showed that AiiA treatment also reduced vibrio viable counts and biofilm development as determined by confocal laser scanning microscopy (CLSM) imaging. These findings suggest that the B. licheniformis DAHB1 quorum-quenching AiiA might be developed for use as a prophylactic treatment to inhibit or reduce vibrio colonisation and mortality of shrimps in aquaculture

Multisoliton solutions and integrability aspects of coupled nonlinear Schrodinger equations

Using Painleve singularity structure analysis, we show that coupled higher-order nonlinear Schrodinger (CHNLS) equations admit Painleve property. Using the results of Painleve analysis, we succeed in Hirota bilinearizing the CHNLS equations, one soliton and two soliton solutions are explictly obtained. Lax pairs are explictly constructed.Comment: Eight pages and six figures. Physical Review E (to be appear

Electroceutical fabric lowers zeta potential and eradicates coronavirus infectivity upon contact

Coronavirus with intact infectivity attached to PPE surfaces pose significant threat to the spread of COVID-19. We tested the hypothesis that an electroceutical fabric, generating weak potential difference of 0.5 V, disrupts the infectivity of coronavirus upon contact by destabilizing the electrokinetic properties of the virion. Porcine respiratory coronavirus AR310 particles (105) were placed in direct contact with the fabric for 1 or 5 min. Following one minute of contact, zeta potential of the porcine coronavirus was significantly lowered indicating destabilization of its electrokinetic properties. Size-distribution plot showed appearance of aggregation of the virus. Testing of the cytopathic effects of the virus showed eradication of infectivity as quantitatively assessed by PI-calcein and MTT cell viability tests. This work provides the rationale to consider the studied electroceutical fabric, or other materials with comparable property, as material of choice for the development of PPE in the fight against COVID-19

Detection and attribution of human influence on regional precipitation

Understanding how human influence on climate is affecting precipitation around the world is immensely important for defining mitigation policies, and for adaptation planning. Yet despite increasing evidence for the influence of climate change on global patterns of precipitation, and expectations that significant changes in regional precipitation should have already occurred as a result of human influence on climate, compelling evidence of anthropogenic fingerprints on regional precipitation is obscured by observational and modelling uncertainties and is likely to remain so using current methods for years to come. This is in spite of substantial ongoing improvements in models, new reanalyses and a satellite record that spans over thirty years. If we are to quantify how human-induced climate change is affecting the regional water cycle, we need to consider novel ways of identifying the effects of natural and anthropogenic influences on precipitation that take full advantage of our physical expectations

Artificial Muscle Intelligence System With Deep Learning for Post-Stroke Assistance and Rehabilitation

Stroke is one of the prime reasons for paralysis throughout the world caused due to impaired nervous system and resulting in disability to move the affected body parts. Rehabilitation is the natural remedy for recovering from paralysis and enhancing the quality of life. Brain Computer Interface (BCI) controlled assistive technology is the new paradigm, providing assistance and rehabilitation for the paralysed. But, most of these devices are error prone and also hard to get continuous control because of the dynamic nature of the brain signals. Moreover, existing devices like exoskeletons brings additional burden on the patient and the caregivers and also results in mental fatigue and frustration. To solve these issues Artificial Muscle Intelligence with Deep Learning (AMIDL) system is proposed in this paper. AMIDL integrates user intentions with artificial muscle movements in an efficient way to improve the performance. Human thoughts captured using Electroencephalogram (EEG) sensors are transformed into body movements, by utilising microcontroller and Transcutaneous Electrical Nerve Stimulation (TENS) device. EEG signals are subjected to pre-processing, feature extraction and classification, before being passed on to the affected body part. The received EEG signal is correlated with the recorded artificial muscle movements. If the captured EEG signal falls below the desired level, the affected body part will be stimulated by the recorded artificial muscle movements. The system also provides a feature for communicating human intentions as alert message to caregivers, in case of emergency situations. This is achieved by offline training of specific gesture and online gesture recognition algorithm. The recognised gesture is transformed into speech, thus enabling the paralysed to express their feelings to the relatives or friends. Experiments were carried out with the aid of healthy and paralysed subjects. The AMIDL system helped to reduce mental fatigue, miss-operation, frustration and provided continuous control. The thrust of lifting the exoskeleton is also reduced by using light weight wireless electrodes. The proposed system will be a great communication aid for paralysed to express their thoughts and feelings with dear and near ones, thereby enhancing the quality of life