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Background & ObjectiveDefective beta cell function in relation to impaired insulin sensitivity results in glucose intolerance. There are few studies documenting the lifecourse evolution of this relationship. The Pune Maternal Nutrition Study (PMNS) longitudinal birth cohort offered the opportunity to document these parameters from childhood in young, rural prediabetic participants and compare them to normal glucose tolerant (NGT).MethodsPMNS subjects were classified as NGT or Glucose intolerant according to their OGTT results at 18 years of age. Insulin Sensitivity (HOMA-S) and β-cell function (HOMA-β) were estimated at 6,12 and 18 years. Their inter-relationship was estimated using HOMA-β as a nonlinear function of HOMA-S, separately for NGT and Glucose intolerant individuals at 6,12 and 18 years. Rates of change of HOMA-S and HOMA-β were estimated using a linear mixed effect model and visualized using LOESS plots.ResultOf 619 participants, 177 had glucose intolerance at 18 years of age. A nonlinear hyperbolic relationship between HOMA-S and HOMA-B was observed at all time points. There was a progressive fall in HOMA-S and rise in HOMA-B with increasing age. Glucose intolerant participants had lower HOMA-B for all levels of HOMA-S as compared to NGT, manifesting as shift towards the origin in the hyperbolic curve.ConclusionWe provide evidence for early life dysregulation in glucose insulin metabolism leading to pre-diabetes at 18 years of age. Prediabetic individuals started with lower beta cell function and lower insulin sensitivity from an early age. Diabetes prevention should start from early life.

OBJECTIVE India is a double world capital of early-life undernutrition and type 2 diabetes. We aimed to characterize life course growth and metabolic trajectories in those developing glucose intolerance as young adults in the Pune Maternal Nutrition Study (PMNS). RESEARCH DESIGN AND METHODS PMNS is a community-based intergenerational birth cohort established in 1993, with serial information on parents and children through pregnancy, childhood, and adolescence. We compared normal glucose-tolerant and glucose-intolerant participants for serial growth, estimates of insulin sensitivity and secretion (HOMA and dynamic indices), and β-cell compensation accounting for prevailing insulin sensitivity. RESULTS At 18 years (N = 619), 37% of men and 20% of women were glucose intolerant (prediabetes n = 184; diabetes n = 1) despite 48% being underweight (BMI CONCLUSIONS Inadequate compensatory insulin secretory response to decreasing insulin sensitivity in early life is the major pathophysiology underlying glucose intolerance in thin rural Indians. Smaller birth size, maternal pregnancy hyperglycemia, and higher glycemia from childhood herald future glucose intolerance, mandating a strategy for diabetes prevention from early life, preferably intergenerationally.

ObjectiveIndia is a double world capital for early life undernutrition and type 2 diabetes. We aimed to characterise lifecourse growth and metabolic trajectories in those developing glucose intolerance as young adults, in the Pune Maternal Nutrition Study (PMNS).Research design and MethodsPMNS is a community-based intergenerational birth cohort established in 1993, with serial information on parents and children through pregnancy, childhood and adolescence. We compared normal glucose tolerant and glucose intolerant participants for serial growth, estimates of insulin sensitivity and secretion (HOMA and dynamic indices) and beta cell compensation accounting for prevailing insulin sensitivity (disposition index).ResultsAt 18 years (N=619) 37% men and 20% women were glucose intolerant (184 prediabetes, 1 diabetes) despite 48% being underweight (BMI2). Glucose intolerant participants had higher fasting glucose from childhood. Mothers of glucose intolerant participants had higher glycemia in pregnancy. Glucose intolerant participants were shorter at birth. Insulin sensitivity decreased with age in all participants, and the glucose intolerant had consistently lower compensatory insulin secretion from childhood. Participants in the highest quintile of fasting glucose at 6 and 12 years had a 2.5- and 4.0-fold higher risk respectively of 18-year glucose intolerance; this finding was replicated in two other cohorts.ConclusionInadequate compensatory insulin secretory response to increasing insulin insensitivity from early life is the major pathophysiology underlying glucose intolerance in thin rural Indians. Smaller birth size, maternal pregnancy hyperglycemia, and higher glycemia in childhood herald future glucose intolerance, mandating a strategy for diabetes prevention from early life, preferably intergenerationally.

Introduction Big data and growth in telecommunications have increased the enormous promise of an informatics approach to health care. India and the United Kingdom are two countries facing these challenges of implementing learning health systems and big data health research. Analysis At present, these opportunities are more likely to be exploited in the private sector or in public‐private partnerships (eg, Public Health Foundation of India [PHFI]) than public sector ventures alone. In both India and the United Kingdom, the importance of health informatics (HIs), a relatively new discipline, is being recognised and there are national initiatives in academic and health sectors to fill gaps in big data health research. The challenges are in many ways greater in India but outweighed by three potential benefits in health‐related scientific research: (a) increased productivity; (b) a learning health system with better use of data and better health outcomes; and (c) to fill workforce gaps in both research and practice. Conclusions Despite several system‐level obstacles, in India, big data research in health care can improve the status quo, whether in terms of patient outcomes or scientific discovery. Collaboration between India and the United Kingdom in HI can result in mutual benefits to academic and health care delivery organisations in both countries and can serve as examples to other countries embracing the promises and the pitfalls of health care research in the digital era.

Response surface methodology (RSM) is a collection of techniques useful for analyzing and optimizing problems where several explanatory covariates influence a response. Although this technique is extensively used in various mixture experiments, its application in standardization of micropropagation protocols is limited. The theoretical developments of RSM are usually concerned with continuous data; hence, linear model theory becomes relevant. In plant tissue culture, in which the response variables are mostly numerical data, the development of RSM in a generalized linear model (GLM) setup is of interest from both a theoretical as well as an application perspective. In the present paper, RSM, as applicable for count data, has been used for modeling, analyzing, and optimizing in vitro regeneration of multiple shoots of Basilicum polystachyon, an important medicinal plant. The specific issues addressed herein are the determination of the optimum concentration of plant growth regulators (i.e., the range of variation in dosages of each covariate) at which the regeneration potential of shoot tip explants is expected to increase, selection of the appropriate growth function (response function) of shoot tip, and determination of the optimum levels of the explanatory variables (i.e., the different combination of dosages of various control factors) for experimentation. According to the present analysis, the optimum level combinations of growth regulators for regeneration of multiple shoots from shoot tip explants of B. polystachyon is 8.19 μM benzyladenine and 2.36 μM naphthalene acetic acid, with a response of approximately 12 regenerated shoots.