Understanding the plant-pathogen interactions is of utmost importance to design strategies for minimizing the economic deficits caused by pathogens in crops. With an aim to identify genes underlying resistance to downy mildew, a major disease responsible for productivity loss in pearl millet, transcriptome analysis was performed in downy mildew resistant and susceptible genotypes upon infection and control on 454 Roche NGS platform. A total of ~685 Mb data was obtained with 1 575 290 raw reads. The raw reads were pre-processed into high-quality (HQ) reads making to ~82% with an average of 427 bases. The assembly was optimized using four assemblers viz. Newbler, MIRA, CLC and Trinity, out of which MIRA with a total of 14.10 Mb and 90118 transcripts proved to be the best for assembling reads. Differential expression analysis depicted 1396 and 936 and 1000 and 1591 transcripts up and down regulated in resistant inoculated/resistant control and susceptible inoculated/susceptible control respectively with a common of 3644 transcripts. The pathways for secondary metabolism, specifically the phenylpropanoid pathway was up-regulated in resistant genotype. Transcripts up-regulated as a part of defense response included classes of R genes, PR proteins, HR induced proteins and plant hormonal signaling transduction proteins. The transcripts for skp1 protein, purothionin, V type proton ATPase were found to have the highest expression in resistant genotype. Ten transcripts, selected on the basis of their involvement in defense mechanism were validated with qRT-PCR and showed positive co-relation with transcriptome data. Transcriptome analysis evoked potentials of hypersensitive response and systemic acquired resistance as possible mechanism operating in defense mechanism in pearl millet against downy mildew infection.

The worldwide pandemic situation of COVID-19 generates a situation in which healthcare resources such as diagnostic kits, drugs and basic healthcare infrastructure were on shortage throughout the period, along with negative impact on socio-economic system. Standardized public healthcare models were missing in pandemic situation, covering from hospitalized patient care to local resident’s healthcare managements in terms of monitoring, assess to diagnosis and medicines. This exploratory and intervention-based study with the objective of proposing COVID-19 Care Management Model representing comprehensive care of society including patients (COVID-19 and other diseases) and healthy subjects under integrated framework of healthier management model. Shifting policy towards technology-oriented models with well-aligned infrastructure can achieve better outcomes in COVID-19 prevention and care. The planned development of technical healthcare models for prognosis and improved treatment outcomes that take into account not only genomics, proteomics, nanotechnology, materials science perspectives but also the possible contribution of advanced digital technologies is best strategies for early diagnosis and infections control. In view of current pandemic, a Healthier Healthcare Management Model is proposed here as a source of standardized care having technology support, medical consultation, along with public health model of sanitization, distancing and contact less behaviours practices. Effective healthcare managements have been the main driver of healthier society where, positive action at identified research, technology and management segment more specifically public health, patient health, technology selection and political influence has great potential to enhanced the global response to COVID-19. The implementation of such practices will deliver effective diagnosis and control mechanism and make healthier society.

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Background: Protein energy malnutrition is a major public health problem in India with maximum prevalence in central part of country known as Madhya Pradesh (60.3%). It is one of the leading causes of morbidity and mortality in under five children. The objective of the study if the study was to identify the risk factors for severe malnutrition in under five children admitted to Nutritional Rehabilitation Centre as compared to normal nourished children in the community. Methods: This was a case control study design. 350 cases were selected from N.R.C. of N.S.C.B Medical College Jabalpur and 350 neighbourhood controls were selected from same community. The chi-square test, student t test and binary logistic regression were used for data analysis using spss-17.0 software. Results: In logistic regression age 0-2 years, female sex, low birth weight, rural locality, S.T caste, illiterate paternal education, early marriage of mother, partially or unimmunized children, kaccha house, lack of hygiene, open field defecation, inadequate calorie, infectious diseases ARI, diarrhoea, and fever were significantly associated with severe malnutrition. The overall Prediction of model was R 2 = 92.9%. The mean time gap between first identification of children as malnourished and their admission to N.R.C. is 4.38 months. Conclusions: There is evidence of strong association between severe malnutrition and some of the risk factors. Long delay in referral and admission of severe malnourished children is a major challenge.

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