A CONCEPTUAL STUDY REGARDING IMMUNITY IN AYURVEDA

It has been estimated that about 6 lacks infant and young children die from RSV annually, and if bacterial co infections are included this number may approach 10 lacks deaths annually. More than 2 million deaths are estimated to result each year the world over as a consequence of diarrheal disease in children of under five years. This statistic shows that children are more vulnerable to infection because their immune system is less or under developed. Ayurveda is a vast storehouse of knowledge relevant to human health, disease, medicines and general health-care. However mutual incomprehensibility of the terms and concepts has been a major impediment in meaningful dialogue between modern scientific medicine and Ayurveda. Some recent concepts of molecular medicine, immunology etc. have been found to have striking similarities with certain concepts of Ayurveda. Therefore, it is being realized that it might be possible to develop a relationship between modern medicine and Ayurveda. Here a comprehensive review of the Ayurvedic classical texts is presented to understand the concept of the Vyadhikshamatva w.s.r. to immunity.

Influence of defect pairs in Ga-based ordered defect compounds: a hybrid density functional study

In the present paper, density functional theory (DFT) based calculations have been performed to predict the stability, electronic, and optical properties of Ga-rich ordered defect compounds (ODCs). The calculated lattice constants, bulk modulus, their pressure derivatives, and optical constants show good agreement with available experimental data. The hybrid exchange correlations functional have been considered to calculate ground state total energy and energy band gap of the material. The calculated formation energy of ODCs comes smaller than pure CuGaSe2 (CGS). Our calculated optical absorption coefficients indicate that the energy band gap of ODCs can be tuned by changing the number of donor-acceptor defect pairs (2V(cu)(-), + Ga-cu(2+)). The band offset has been calculated to understand the reason of band gap alteration while the number of defect pair changes. Our results may be helpful for other experiments to further improve the performance of ODCs

EFFECTS OF MATERNAL LEAD ACETATE EXPOSURE DURING LACTATION ON POSTNATAL DEVELOPMENT OF OVARIES IN OFFSPRING OF SWISS ALBINO MICE

ABSTRACT: The course of human development from conception to adulthood is extremely complex. The developing organism is particularly vulnerable to toxic insult because of rapid cell division and differentiation and severely affected during gestation and lactation. The aim of the present study was to evaluate lead toxicity on the female reproductive system during neonatal period. A total of 30 female mice randomly divided into two equal groups; control and treatment group. During experimental period, lactating female mice was given lead acetate (0.5ml/Day) from day 1 to day 21 of lactation. At 7, 14 and 21 days after birth, the ovaries weights and diameters of different developing follicles were measured. Following tissue processing, 5 µm sections were stained with haematoxylin eosin and evaluated with quantitative techniques. Ovarian parameters in different groups were compared by one-way ANOVA. The results indicated that exposure of lead caused histological alteration in developing ovaries of mice and significantly (P< 0.05) decreased Ovaries weights and diameters of different developing ovarian follicles. Studies conducted on females revealed that lead suppresses the development of various follicles during fetal and neonatal life. It appears that lead interferes during specific events of ovarian developmental stages, which may create higher sensitivity for dysfunction in reproductive system during adulthood. The present investigation evaluates the relative influences of prenatal and postnatal exposure of lead acetate on growth and ovarian histology in female offspring during postnatal development

Lopinavir/ritonavir: is early administration better in Covid-19?

Background: To share the data of coronavirus 2019 (Covid-19) patients started on lopinavir-ritonavir (lopi/r) in relation to time period from the onset of symptoms.Method: Observational descriptive study of 23 Covid-19 patients admitted in a tertiary care center in India from March 2020 to May 2020. Patients categorized into 2 groups based on the timing of initiation of lopi/r from the onset of symptoms. Group 1 were given the drug early (≤7 days) and group 2 late (>7 days). The clinical events (oxygen requirement days and ICU stay) and outcomes of hospital stay between the two groups were evaluated.Results: Patients were started on lopi/r for a period of 14 days on admission, out of which 12 patients were in group 1 and 11 patients in group 2. Underlying co-morbidities were present in 15 patients (65.21%). The mean duration from onset of symptoms to lopi/r initiation was 4 days and 11.1 days in Group 1 and 2 respectively. Requirement for oxygen support (2.16 versus 6.54 days), mean duration of hospitalization (8.58 versus 11.54 days) and mean duration of obtaining first Covid-19 negative report from the onset of symptoms (10.5 versus 19.57 days) were all significantly lesser in group 1 (p<0.05). All patients belonging to Group 1 and eight patients of group 2 recovered completely and were discharged whereas 3 patients of group 2 expired. Diarrhea was the most commonly observed adverse effect of lopi/r in our patients.Conclusion: With no approved weapon to tackle the Covid-19 pandemic, we should keep lopi/r in our armamentarium of drugs and use it at the earliest. More clinical trials are needed in future to ascertain if lopi/r can reduce hospital stay, prompt faster recovery and result in better clinical outcome

Probiotics in acute diarrhea: A randomized control trial

Background: Probiotics have been used for long in the treatment of acute diarrhea although their efficacy has always&nbsp;remains the subject of discussion. Objective: To determine the effect of probiotics in acute diarrhea among the children in&nbsp;rural population. Method: Double-blinded randomized control trial. We included children of age group 6 months - 5 years&nbsp;suffering from acute diarrhea of &lt;48 h and fulfilling the inclusion criteria. All children were given oral rehydration salts&nbsp;(ORS) ad-lib till the resolution of diarrhea and zinc 20 mg/day for 14 days while intervention arm (n=101) were given&nbsp;probiotic sachet twice a day for 7 days containing Streptococcus faecalis 30 million, Clostridium butyricum 2 million,&nbsp;Bacillus mesentericus 1 million, Lactobacillus sporogenes 50 million, control group were given identical placebo apart from&nbsp;ORS and zinc. Duration of diarrhea in both the groups was measured as primary outcome while secondary outcome was&nbsp;to know the days of maximum recovery from diarrhea in both groups. Results: Totally, 207 patients were randomized to&nbsp;control and study group, out of which, 195 completed the study. Out of total 195 patients, 94 (48.2%) patients were treatedwith standard treatment of diarrhea without probiotics while 101 (51.8%) patients were given probiotics apart from standard&nbsp;treatment of diarrhea. The mean duration of diarrhea was found to be reduced in the study group (4.6 days [2.84-4.776 days])&nbsp;as compared to control group (5.31 days [5.108-5.512 days]), p&lt;0.001. Conclusion: Probiotics significantly reduced the&nbsp;duration of acute diarrhea in children

Feeding practices in infants: ritual factors dominating mother’s education - a cross sectional study

Background: The objective was to know the impact of mother education on feeding practices of infants.Methods: Observational analytic cross sectional study. We used Semi-structured, pre-tested questionnaire to interview 355 mothers of infants, aged one and half to 12 months, who came in OPD of Department of Paediatrics UPRIMS and R, Saifai for immunization or some problem.Results: Total 267 (75.2 %) out of 355 women had initiated breast feeding within 24 hours of birth. 172 (48.5%) mothers exclusively breast fed their infants. Total 166 (46.8%) practiced Prelacteal feed. Out of 166 subjects, 121 (34.1%) practiced for 7 days and 41 (12.7%) beyond the 7 days. There were highly significant relationship found between education level of mothers with type of breast feeding, in the form of exclusive or non- exclusive breast feeding and Prelacteal feeding practices ( p 0.05), but an important pattern of initiation of breast feeding was seen at the different level of mothers education.Conclusion: Ritual and customary factors have much impact then mother’s education on breast feeding practices of infants. Apart from education, breast feeding awareness programme should be increased including both literate and illiterate mothers.

Construction of Data Driven Decomposition Based Soft Sensors with Auto Encoder Deep Neural Network for IoT Healthcare Applications

The architecture of IoT healthcare is motivated towards the data-driven realization and patient-centric health models, whereas the personalized assistance is provided by deploying the advanced sensors. According to the procedures in surgery, in the emergency unit, the patients are monitored till they are stable physically and then shifted to ward for further recovery and evaluation. Normally evaluation done in ward doesn’t suggest continuous parameters monitoring for physiological condition and thus relapse of patients are common. In real-time healthcare applications, the vital parameters will be estimated through dedicated sensors, that are still luxurious at the present situation and highly sensitive to harsh conditions of environment. Furthermore, for real-time monitoring, delay is usually present in the sensors. Because of these issues, data-driven soft sensors are highly attractive alternatives. This research is motivated towards this fact and Auto Encoder Deep Neural Network (AutoEncDeepNN) is proposed depending on Health Framework in the internet assisting the patients with trigger-based sensor activation model to manage master and slave sensors. The advantage of the proposed method is that the hidden information are mined automatically from the sensors and high representative features are generated by multiple layer’s iteration. This goal is consistently achieved and thus the proposed model outperforms few standard approaches which are considered like Hierarchical Extreme Learning Machine (HELM), Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). It is found that the proposed AutoEncDeepNN method achieves 94.72% of accuracy, 41.96% of RMSE, 34.16% of RAE and 48.68% of MAE in 74.64 ms