[{"id":370,"title":"Novel bioremediation methodology for utilisation of biomedical waste ash","sha":"6b3d7be21f74926053fb6df4675169c7","user_id":null,"state":"published","body":"Biomedical waste (BMW) ash, generated from incineration of BMW, consists of several heavy metals and polycyclic aromatic hydrocarbons (PAHs) which can cause severe damage to the environment by seeping into the ground and by polluting the surface and groundwater. \r\nPreviously reported bioremediation technique combined with synthetic biology can lead to a novel methodology to reduce the toxicity of the BMW ash before disposing into the environment. Several bacterial species such as Bacillus sp. KGMDI have been shown to tolerate upto [75mg/l of heavy metal](https://www.hindawi.com/archive/2014/956316/) such as manganese, molybdenum, iron, chromium, copper. Reduction of toxicity, by treatment with bacteria, has also been reported earlier, indicating uptake of toxic [heavy metals](http://nopr.niscair.res.in/bitstream/123456789/17153/1/IJEB%2041(9)%20935-944.pdf). Here, we propose to engineer the bacterium’s metabolic pathway to utilise such heavy metals in a constructive manner. The chemistry space based on the diversity of PAHs seems fascinating and allow scope for the synthesis of compounds of social interest. These bacterial species can further be configured for differential higher uptake of heavy metals, such as iron, from the BMW ash by modifying their biochemical pathways and can be utilised to synthesize nanoparticles. Hence, it is possible to synthesize iron nanoparticles which have clinical and laboratory applications, thus incurring immense societal benefits.","created_at":"2017-03-09T17:29:39.969Z","updated_at":"2017-03-28T07:43:39.205Z","zenodo_id":376323,"doi":"https://doi.org/10.5281/zenodo.376323","subject":null,"tags":["biomedical waste","nanoparticles","heavy metals","bioremediation","synthetic biology"],"vote_count":1,"view_count":1,"score":1.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null},{"id":722,"title":"Vein Dynamics to predict the immune response and susceptibility to disorders","sha":"665ce75e67bd2011f08c961a4f1978f4","user_id":null,"state":"published","body":"The immune system acts as a protective framework against the pathogenic microbes. Understanding the immune system can give us insights of how vulnerable someone is to foreign invaders. Amidst the recent events such as virus outbreaks it becomes highly advantageous if we pinpoint the individuals who are more prone to be affected.\r\n\r\nThe vein patterns such as finger veins or palm veins are amongst the most robust features which are [unique](https://www.mdpi.com/2078-2489/9/9/213) to individuals. These vascular networks which are determined by genetic and chromosomal patterns can give us more insights to a person’s response to fight foreign microbes. In order to understand how these vascular patterns can predict the immune response and susceptibility to foreign microbes we can make use of artificial intelligence and cutting-edge machine learning algorithms, which can be trained to correlate with immune markers such as C-reactive proteins, differential cell count, lymphocyte proliferation and subset distribution and red blood cell distribution width. A designated score sheet which categorizes the vein patterns with the immune markers can help us mark the groups that are more immunocompromised and thereby keep us prepared during pandemics. \r\n","created_at":"2020-03-25T03:00:11.873Z","updated_at":"2020-04-08T06:00:21.745Z","zenodo_id":3742668,"doi":"https://doi.org/10.5281/zenodo.3742668","subject":null,"tags":["vein patterns","immune response","machine learning","artificial intelligence"],"vote_count":0,"view_count":1,"score":0.1,"deleted":false,"muted":false,"tweeted":false,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null}]