Social and Intergenerational Determinants of Children’s Physical and Cognitive Development

Identifying the key determinants of poor developmental outcomes is critical in improving the lives of millions of children who suffer from poor physical growth and cognitive deficits. Much research suggests that early life conditions, particularly those experienced within the household, critically influence children’s development across the life course. In this dissertation exercise, I explore how three dimensions of early experiences – prenatal conditions, parental education, and household socioeconomic conditions – influence children’s physical and cognitive development. Chapter 1 finds that the influences of low birth weight, often touted as a key determinant of later health, wane over time with increasing importance of postnatal factors. Chapter 2 also counters accepted evidence that maternal education matters more for children’s physical development by finding that both parents’ education matters equally in both infancy and childhood with no mechanisms distinguishing maternal and paternal education. Chapter 3 supports the evidence that household socioeconomic status matters for children’s cognitive development and finds that household assets are the critical determinant of cognitive status. Findings from each of these chapters will not only contribute new scientific evidence but will also help inform policies and programs to improve children’s health and well-being

Ambiguity-Aware In-Context Learning with Large Language Models

In-context learning (ICL) i.e. showing LLMs only a few task-specific demonstrations has led to downstream gains with no task-specific fine-tuning required. However, LLMs are sensitive to the choice of prompts, and therefore a crucial research question is how to select good demonstrations for ICL. One effective strategy is leveraging semantic similarity between the ICL demonstrations and test inputs by using a text retriever, which however is sub-optimal as that does not consider the LLM's existing knowledge about that task. From prior work (Min et al., 2022), we already know that labels paired with the demonstrations bias the model predictions. This leads us to our hypothesis whether considering LLM's existing knowledge about the task, especially with respect to the output label space can help in a better demonstration selection strategy. Through extensive experimentation on three text classification tasks, we find that it is beneficial to not only choose semantically similar ICL demonstrations but also to choose those demonstrations that help resolve the inherent label ambiguity surrounding the test example. Interestingly, we find that including demonstrations that the LLM previously mis-classified and also fall on the test example's decision boundary, brings the most performance gain.Comment: 13 pages in tota

Exploring the Viability of Synthetic Query Generation for Relevance Prediction

Query-document relevance prediction is a critical problem in Information Retrieval systems. This problem has increasingly been tackled using (pretrained) transformer-based models which are finetuned using large collections of labeled data. However, in specialized domains such as e-commerce and healthcare, the viability of this approach is limited by the dearth of large in-domain data. To address this paucity, recent methods leverage these powerful models to generate high-quality task and domain-specific synthetic data. Prior work has largely explored synthetic data generation or query generation (QGen) for Question-Answering (QA) and binary (yes/no) relevance prediction, where for instance, the QGen models are given a document, and trained to generate a query relevant to that document. However in many problems, we have a more fine-grained notion of relevance than a simple yes/no label. Thus, in this work, we conduct a detailed study into how QGen approaches can be leveraged for nuanced relevance prediction. We demonstrate that -- contrary to claims from prior works -- current QGen approaches fall short of the more conventional cross-domain transfer-learning approaches. Via empirical studies spanning 3 public e-commerce benchmarks, we identify new shortcomings of existing QGen approaches -- including their inability to distinguish between different grades of relevance. To address this, we introduce label-conditioned QGen models which incorporates knowledge about the different relevance. While our experiments demonstrate that these modifications help improve performance of QGen techniques, we also find that QGen approaches struggle to capture the full nuance of the relevance label space and as a result the generated queries are not faithful to the desired relevance label.Comment: In Proceedings of ACM SIGIRWorkshop on eCommerce (SIGIR eCom 23

Morphine modulates proliferation of kidney fibroblasts

Morphine modulates proliferation of kidney fibroblasts. Renal interstitial scarring is an important component of heroin-associated nephropathy. Kidney fibroblasts have been demonstrated to play a role in the development of renal scarring in a variety of renal diseases. We studied the effect of morphine, an active metabolite of heroin, on the proliferation of kidney fibroblasts. Morphine at a concentration of 10−12M enhanced (P < 0.001) the proliferation of kidney fibroblasts (control, 67.5 ± 2.0 vs. morphine, 112.2 ± 10.1 × 104 cells/well). [3H]thymidine incorporation studies further confirmed these results. Morphine at concentrations of 10−12M to 10−10M also modulated mRNA expression of early growth related genes (c-fos, c-jun and c-myc). Morphine at concentrations of 10−8 to 10−4M promoted apoptosis of kidney fibroblasts and also enhanced the synthesis of p53 by kidney fibroblasts. We speculate that morphine-induced kidney fibroblast proliferation may be mediated through the activation of early growth related genes, whereas morphine induced kidney fibroblast apoptosis may be mediated through the generation of p53. The present in vitro study provides a hypothetical basis for the role of morphine in the development of renal interstitial scarring in patients with heroin-associated nephropathy

Metrics of early childhood growth in recent epidemiological research: a scoping review

Metrics to quantify child growth vary across studies of the developmental origins of health and disease. We conducted a scoping review of child growth studies in which length/height, weight or body mass index (BMI) was measured at 2 time points. From a 10% random sample of eligible studies published between Jan 2010-Jun 2016, and all eligible studies from Oct 2015-June 2016, we classified growth metrics based on author-assigned labels (e.g., 'weight gain') and a 'content signature', a numeric code that summarized the metric's conceptual and statistical properties. Heterogeneity was assessed by the number of unique content signatures, and label-to-content concordance. In 122 studies, we found 40 unique metrics of childhood growth. The most common approach to quantifying growth in length, weight or BMI was the calculation of each child's change in z-score. Label-to-content discordance was common due to distinct content signatures carrying the same label, and because of instances in which the same content signature was assigned multiple different labels. In conclusion, the numerous distinct growth metrics and the lack of specificity in the application of metric labels challenge the integration of data and inferences from studies investigating the determinants or consequences of variations in childhood growth

Raman spectroscopy for detection of imatinib in plasma: A proof of concept

Imatinib is the standard first line treatment for chronic myeloid leukemia (CML). Owing to dose-related toxicities of Imatinib such as neutropenia, there is scope for treatment optimization through therapeutic drug monitoring (TDM). Trough concentration of 1 μg/mL is considered the therapeutic threshhold. Existing methods for the detection of Imatinib in plasma are limited by long read out time and expensive instrumentation. Hence, Raman spectroscopy was explored as a rapid and objective tool for monitoring Imatinib concentration. Three approaches: conventional Raman spectroscopy (CRS), Drop coating deposition Raman (DCDR) spectroscopy and surface-enhanced Raman spectroscopy (SERS) were employed to detect the required trough concentration of 1 μg/mL and above. Detection of therapeutically relevant concentrations (1 μg/mL) using SERS and suitable nanoparticle substrates has been demonstrated. Prospectively, rigorous validation using clinical samples is necessary to confirm the utility of this approach in routine clinical usage

Short-term and long-term associations between household wealth and physical growth: a cross-comparative analysis of children from four low- and middle-income countries

Background: Stunting, a form of anthropometric failure, disproportionately affects children in developing countries with a higher burden on children living in poverty. How early life deprivation affects physical growth over various life stages is less well-known. Objective: We investigate the short- and long-run associations between household wealth in early life with physical growth in childhood in four low- and middle-income countries to understand the persistent implications of early life conditions of poverty and resource constraints on physical growth. Design: Longitudinal study of eight cohorts of children in four countries – Ethiopia, India, Peru, and Vietnam (n=10,016) – ages 6 months to 15 years, using data from the Young Lives project, 2002–2009. Physical growth outcomes are standardized height-for-age z-scores (HAZ) and stunting. The key exposure is household wealth measured at baseline using a wealth index, an asset-based indicator. Covariates include child's age and sex, caregiver's educational status, household size, and place of residence. Results: Baseline wealth index is significantly associated with higher physical growth rates as suggested by higher HAZ and lower odds of stunting. We found these associations in all four countries, for younger and older cohorts and for children who experienced changes in living standards. For the older cohort, despite the timing of the first survey at age 7–8 years, which is beyond the critical period of 1,000 days, there are lasting influences of early poverty, even for those who experienced changes in wealth. Conclusions: Household wealth in early life matters for physical growth with conditions of poverty and deprivation influencing growth faltering even beyond the 1,000 days window. The influences of early childhood poverty, so prevalent among children in low- and middle-income countries, must be addressed by policies and programs targeting early life but also focusing on older children experiencing growth faltering

Sirtuin 6 inhibition protects against glucocorticoid-induced skeletal muscle atrophy by regulating IGF/PI3K/AKT signaling

Chronic activation of stress hormones such as glucocorticoids leads to skeletal muscle wasting in mammals. However, the molecular events that mediate glucocorticoid-induced muscle wasting are not well understood. Here, we show that SIRT6, a chromatin-associated deacetylase indirectly regulates glucocorticoid-induced muscle wasting by modulating IGF/PI3K/AKT signaling. Our results show that SIRT6 levels are increased during glucocorticoid-induced reduction of myotube size and during skeletal muscle atrophy in mice. Notably, overexpression of SIRT6 spontaneously decreases the size of primary myotubes in a cell-autonomous manner. On the other hand, SIRT6 depletion increases the diameter of myotubes and protects them against glucocorticoid-induced reduction in myotube size, which is associated with enhanced protein synthesis and repression of atrogenes. In line with this, we find that muscle-specific SIRT6 deficient mice are resistant to glucocorticoid-induced muscle wasting. Mechanistically, we find that SIRT6 deficiency hyperactivates IGF/PI3K/AKT signaling through c-Jun transcription factor-mediated increase in IGF2 expression. The increased activation, in turn, leads to nuclear exclusion and transcriptional repression of the FoxO transcription factor, a key activator of muscle atrophy. Further, we find that pharmacological inhibition of SIRT6 protects against glucocorticoid-induced muscle wasting in mice by regulating IGF/PI3K/AKT signaling implicating the role of SIRT6 in glucocorticoid-induced muscle atrophy.Fil: Mishra, Sneha. No especifíca;Fil: Cosentino, Claudia. Harvard Medical School; Estados UnidosFil: Tamta, Ankit Kumar. No especifíca;Fil: Khan, Danish. No especifíca;Fil: Srinivasan, Shalini. No especifíca;Fil: Ravi, Venkatraman. No especifíca;Fil: Abbotto, Elena. Università degli Studi di Genova; ItaliaFil: Arathi, Bangalore Prabhashankar. No especifíca;Fil: Kumar, Shweta. No especifíca;Fil: Jain, Aditi. No especifíca;Fil: Ramaian, Anand S.. No especifíca;Fil: Kizkekra, Shruti M.. No especifíca;Fil: Rajagopal, Raksha. No especifíca;Fil: Rao, Swathi. No especifíca;Fil: Krishna, Swati. No especifíca;Fil: Asirvatham Jeyaraj, Ninitha. Indian Institute of Technology; IndiaFil: Haggerty, Elizabeth R.. Harvard Medical School; Estados UnidosFil: Silberman, Dafne Magalí. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; ArgentinaFil: Kurland, Irwin J.. No especifíca;Fil: Veeranna, Ravindra P.. No especifíca;Fil: Jayavelu, Tamilselvan. No especifíca;Fil: Bruzzone, Santina. Università degli Studi di Genova; ItaliaFil: Mostoslavsky, Raul. Harvard Medical School; Estados UnidosFil: Sundaresan, Nagalingam R.. No especifíca