Background Tinospora cordifolia (Guduchi or Amrita) is an important drug of Ayurvedic System of Medicine and found mention in various classical texts for the treatment of diseases such as jaundice, fever, diabetes, cancer and skin disease etc. In view of its traditional claims, antioxidant and anti-proliferative activities were evaluated in the present study.MethodsEthanol extract (TCE) and subsequent petroleum ether (TCP), dichloromethane (TCD), n-Butanol (TCB) and aqueous (TCA) fractions of were prepared from stems of T cordifolia. Total phenolic, flavonoid content and anti-oxidant activity was assessed by different methods. Anti-proliferative activity was assessed in cervical carcinoma (HeLa) cell lines by MTT and SRB assay.ResultsEthanol extract and n-butanol fractions shown to be superior in their scavenging activity in all the tested methods. n-butanol fractions shown antioxidant activity with an IC50 of 14.81 ± 0.53, 29.48 ± 2.23, 58.20 ± 0.70 and 21.17 ± 1.19 μg/mL by DPPH, ABTS, Nitric oxide and iron chelating activities respectively. Anti-proliferative activity results demonstrates that the TCD and ethanol extract of T cordifolia exhibits potent cytotoxic effect against HeLa with an IC50 of 54.23 ± 0.94 μg/mL and 101.26 ± 1.42 μg/mL respectively by MTT assay; and with an IC50 of 48.91 ± 0.33 μg/mL and 87.93 ± 0.85 μg/mL respectively by SRB assay.ConclusionThe outcomes of the present study support the fact that T Cordifolia is a promising source of antioxidant agent and propose its further investigation. Moreover, dichloromethane fraction of T cordifolia shown to be the most potent anti-proliferative fraction and further mechanistic and phytochemical investigations are under way to identify the active principles.

Natural disasters are adverse actions that happen due to the natural processes of the earth. In today’s world with so much pollution, global warming and because of so many reasons, natural disasters are happening far more than they used to happen before and many people in the world face problems, lose their houses, livelihoods and even their houses. It is really painful to get to know the effects of these natural disasters. So, this paper proposes a model which helps us predict natural disasters before they happen using wireless technologies. In this paper modern technologies like IOT, artificial intelligence and machine learning are used. Here for the prediction of each disaster, data/signals given by nature are used , for example for the earthquake module the seismic signals from the earth are used, systems like UNITE are used where the sensors placed in the earth to get the seismic data. For the other disasters also such data is taken from signals given by nature. A detailed explanation on how disasters are predicted based on these simple signals and data from nature is given. In this paper solutions based on wireless technologies to solve some after effects of these natural disasters are also suggested . So, basically our idea is to have all disasters predicted in one place using modern computer science technologies.