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Background/objectivesPregnancies complicated by gestational diabetes (GDM) or maternal obesity have been linked to the development of diabetes, obesity, and fatty liver disease later in life with sex-specific manifestations. Alterations in miRNA expression in offspring exposed to GDM and maternal obesity and effects on hepatic development are unknown. Here, we describe how exposure to maternal obesity in utero leads to sex-specific changes in miRNA and target gene expression in human fetal liver.MethodsCandidate miRNA expression was measured in second trimester amniotic fluid (AF) from women with GDM. Targets of differentially expressed miRNAs were determined and pathway enrichment of target genes was performed. MiRNA and target gene expression were measured in a separate cohort of second trimester primary human fetal hepatocytes (PHFH) exposed to maternal obesity via qPCR and western blot. All studies were IRB approved.ResultsGDM-exposed AF had significant increases in miRNAs 199a-3p, 503-5p, and 1268a (fold change (FC) ≥ 1.5, p < 0.05). Female offspring-specific analysis showed enrichment in miRNAs 378a-3p, 885-5p, and 7-1-3p (p < 0.05). MiRNA gene targets were enriched in hepatic pathways. Key genes regulating de novo lipogenesis were upregulated in obesity-exposed PHFH, especially in males. Significantly altered miRNAs in GDM AF were measured in obese-exposed PHFH, with consistent increases in miRNAs 885-5p, 199-3p, 503-5p, 1268a, and 7-1-3p (FC ≥ 1.5, p < 0.05). Female PHFH exposed to maternal obesity had increased expression of miR-885-5p, miR-199-3p, miR-503-5p, miR-1268s, and miR-7-1-3p (p < 0.05), corresponding to decreased target genes expression for ABCA1, PAK4, and INSR. In male PHFHs, no miRNA changes were measured but there was increased expression of ABCA1, PAK4, and INSR (p < 0.05).ConclusionsOur data suggest sex-specific changes in miRNA and gene expression in PHFH may be one mechanism contributing to the sexual dimorphism of metabolic disease in offspring exposed to GDM and maternal obesity in utero.

Humans express seven heparan sulfate (HS) 3-O-sulfotransferases that differ in substrate specificity and tissue expression. Although genetic studies have indicated that 3-O-sulfated HS modulates many biological processes, ligand requirements for proteins engaging with HS modified by 3-O-sulfate (3-OS) have been difficult to determine. In particular, the context in which the 3-OS group needs to be presented for binding is largely unknown. We describe herein a modular synthetic approach that can provide structurally diverse HS oligosaccharides with and without 3-OS. The methodology was employed to prepare 27 hexasaccharides that were printed as a glycan microarray to examine ligand requirements of a wide range of HS-binding proteins. The binding selectivity of antithrombin-III (AT-III) compared well with anti-Factor Xa activity supporting robustness of the array technology. Many of the other examined HS-binding proteins required an IdoA2S-GlcNS3S6S sequon for binding but exhibited variable dependence for the 2-OS and 6-OS moieties, and a GlcA or IdoA2S residue neighboring the central GlcNS3S. The HS oligosaccharides were also examined as inhibitors of cell entry by herpes simplex virus type 1, which, surprisingly, showed a lack of dependence of 3-OS, indicating that, instead of glycoprotein D (gD), they competitively bind to gB and gC. The compounds were also used to examine substrate specificities of heparin lyases, which are enzymes used for depolymerization of HS/heparin for sequence determination and production of therapeutic heparins. It was found that cleavage by lyase II is influenced by 3-OS, while digestion by lyase I is only affected by 2-OS. Lyase III exhibited sensitivity to both 3-OS and 2-OS.

Purpose: This study aims to explore the factors influencing Indian investors' intentions to adopt robo-advisors, focusing on the interplay between trust, technology acceptance, and traditional financial preferences. The research seeks to provide actionable insights for fintech companies, policymakers, and traditional financial advisors to facilitate the adoption of robo-advisory services in India. Design/methodology/approach: The research is a pilot study that employs a quantitative approach, utilising a structured questionnaire to collect data from a diverse sample of Indian investors. Exploratory Factor Analysis (EFA) was conducted to identify key constructs, followed by multiple regression analysis to examine the relationships between trust, technology acceptance, traditional preferences, and the intention to adopt robo-advisors. Findings: The analysis revealed that trust and technology acceptance significantly positively influence the intention to adopt robo-advisors. Traditional preferences negatively impact adoption intentions, with a notable mediating effect between trust, technology acceptance, and adoption intentions. Additionally, demographic factors such as age and investment experience play a significant role, with younger investors and those with less investment experience more inclined to adopt robo-advisors. Research limitations/implications: The study's findings highlight the critical importance of building trust and ensuring technology acceptance among potential users. Fintech companies should prioritise enhancing the perceived trustworthiness of their services through robust security measures and transparent operations. Policymakers should promote financial literacy and digital inclusion, particularly in underserved areas. Traditional advisors can integrate robo-advisory services to create a hybrid model. The study's limitations include reliance on self-reported data and a sample that may not fully represent the entire Indian investor population. Originality/value: This paper provides new insights into the adoption of robo-advisors in the Indian context, emphasising the interplay between trust, technology, and traditional financial preferences. It offers valuable guidance for fintech companies, policymakers, and traditional advisors to enhance their strategies and foster broader adoption of robo-advisory services in India.

Time-dependent changes in the lipid body (LB) lipidome of two oleaginous yeasts, Yarrowia lipolytica NCIM 3589 and Yarrowia bubula NCIM 3590 differing in growth temperature was investigated. LB size and lipid content were higher in Y. lipolytica based on microscopy, Feret, and integrated density analysis with lipid accumulation and mobilization occurring at 48 h in both strains. Variations in LB lipidome were reflected in interfacial tension (59.67 and 68.59 mN m−1) and phase transition temperatures (30°C–100°C and 60°C–100°C) for Y. lipolytica and Y. bubula, respectively. Liquid Chromatography-Mass Spectroscopy (LC–MS) analysis revealed neutral lipids (NLs), phospholipids, sphingolipids, sterols, and fatty acids as the major classes present in both strains while fatty acid amides were seen only in Y. lipolytica. Amongst the lipid classes, a few species were present in abundance with a number of lipids being less dominant. Permutational multivariate analysis of variance (PERMANOVA) and Analysis of covariance (ANOCOVA) analysis suggest 22 lipids belonging to NLs, fatty acid amides, and free fatty acids were found to be statistically different between the two strains. Analysis of the ratios between different lipid components suggest changes in LB size and mobilization as a function of time. The results indicate influence of temperature and strain variation on the dynamics of LB lipidome in Yarrowia species. Lipidome dynamics of LBs in Yarrowia sp.

We report the high-temperature thermoelectric properties of electron- and hole-doped calcium manganese oxide materials, which exhibit potential of a thermoelectric device for conversion of wasteful thermal energy into useful electrical energy. Electron-doped Ca 0.9 R 0.1 MnO 3 (R = La, Yb) and hole-doped Ca 4 Mn 2.85 Nb 0.15 O 10 manganites chosen for the present study were prepared by solid-state reaction of starting compounds and characterized by powder X-ray diffraction. Electrical resistivity and thermopower were measured as a function of temperature to determine the power factor for all the three compounds studied. We discuss these results according to their application potential as a thermoelectric device.

Background Most elderly patients suffer from multiple diseases and are on multiple drugs for treatment. Polypharmacy in the elderly, physiological changes with old age, changes in the pharmacokinetics and pharmacodynamic effects of many drugs, and newer drug prescription trends for diseases like diabetes and cardiovascular disease make drug prescribing in the elderly more difficult. There are many chances of drug-drug interactions with easily available over-the-counter (OTC) medications. To prevent the irrational use of drugs in the elderly, there is a need for prescription analysis studies. Prescription analysis studies will help in finding errors in prescriptions and also change trends in the use of medication among the elderly. Methodology This cross-sectional observation study was conducted on 234 elderly patients to investigate medicine use patterns among the geriatric patients attending the Medicine Outpatient Department in a tertiary care teaching hospital. Drug data were collected from the study participants after obtaining written informed consent and analysed, including demographic details, personal history, disease history, and details of the drug, including the generic name of the drug, dose and duration of therapy, and prescription pattern. The proportions of drugs prescribed for different diseases were analysed. Also, the drugs were analysed as per their pharmacological profiles. Results and interpretation A total of 1298 drug prescriptions were analysed in this study. Of the total participants, 60.26% were male, 35% were unemployed, 53% were retired, and 27% were taking OTC herbal medications. Most of the patients included in this study were suffering from diabetes, hypertension, and other comorbidities. Telmisartan and telmisartan in combination with other drugs were the most commonly encountered prescription drugs, i.e., 24% among the cardiovascular drugs. Aspirin and statins alone or in combination were the most commonly encountered prescriptions, i.e., 27.88% of the drugs used for prophylaxis of cardiovascular diseases. Conclusion This study showed a prescription pattern for the elderly and highlighted precautions to be taken with some of the prescribed drugs. As polypharmacy is observed with elderly prescriptions, possible drug interactions must be taken into account. Regular prescription analysis of drugs prescribed to the elderly will help in the appropriate and rational use of drugs.

This study aims to investigate the interaction between market volatility, economic growth, and cognitive biases over the period from April 2006 to March 2024. Market volatility and economic growth are critical indicators that influence economic stability and investment behavior. Financial market volatility, defined by abrupt and erratic changes in asset values, can have a big impact on the expansion and stability of the economy. According to conventional economic theory, there should be an inverse relationship between market volatility and economic growth since high volatility can discourage investment and erode trust. Market participants’ cognitive biases are a major aspect that complicates this connection. Due to our innate susceptibility to cognitive biases, including herd mentality, overconfidence, and loss aversion, humans can make poor decisions and increase market volatility. These prejudices frequently cause investors to behave erratically and irrationally, departing from reasonable expectations and causing inefficiencies in the market. Cognitive biases have the capacity to sustain feedback loops, which heighten market turbulence and may hinder economic expansion. Similarly, cognitive biases have the potential to cause investors to misread economic indicators or ignore important details, which would increase volatility. This study uses the generalized autoregressive conditional heteroskedasticity (GARCH) model on GDP growth data from the US, the UK, and India, alongside S&P 500, FTSE 100, and NIFTY 50 data sourced from Bloomberg, to examine evidence of these biases. The results show evidence of the predictive nature of market fluctuations on economic performance across the markets and highlight the substantial effects of cognitive biases on market volatility, disregarding economic fundamentals and growth, emphasizing the necessity of considering psychological factors in financial market analyses and developing strategies to mitigate their adverse effects.

Wildlife crimes such as poaching and the illegal trade in wild animals and plants are globally prolific and may converge with other serious crimes including drugs and arms trafficking. Wildlife crime is a wicked problem, requiring interdisciplinary approaches to manage its far-reaching impacts on the environment, social justice, public health, the economy, governance, etc. Conservation organizations frequently use public communication and campaigns to draw the public’s attention to issues such as wildlife crime. These campaigns often urge audiences to take various actions such as donating money to support the organizations’ efforts to combat wildlife crime. Despite their reliance on communication to reach and engage their audiences, little is publicly known about the effects of such communication on conservation behaviors. In fact, we do not yet know which social-psychological factors matter most in driving behaviors linked to curbing wildlife crime. This dissertation compares the theory of planned behavior and the value-belief-norm theory – both widely used to explain environmental behaviors – and compares responses from a cross-national group of participants from India and the United States of America to provide new empirical evidence of how well each theory performs in predicting intentions to donate money to conservation organizations to reduce wildlife crime. It also explores the potential for using wildlife value orientations in studies that focus specifically on wildlife-related behaviors, rather than the New Ecological Paradigm scale that is used as part of the value-belief-norm model. Data was collected from a total of 1,820 participants, of which 900 were from the U.S. and 920 were from India. The survey instrument assessed responses to the primary constructs in the planned behavior and value-belief-norm theory. Data were analyzed using correlations, regressions, multi-group confirmatory factor analysis, and structural equation modeling. Results indicate that the theory of planned behavior explained greater variance in donation intentions for both Indian and U.S. groups but attitude toward behavior did not have a significant association with intention in the multivariate analysis in either sample. While the value-belief-norm theory explained lesser variance in donation intentions, and it held up as expected for the U.S. sample with good reliability metrics, scale reliability was low for the Indian sample and convergent validity was poor overall with values and ecological worldview dimensions manifesting unexpectedly in multivariate regressions. Measurement models and structural models were different for both samples, necessitating a parallel analysis. A modified value-belief-norm model with mutualistic wildlife value orientations had slightly better fit for the India sample but slightly lower for the U.S. sample. Perceived behavioral control was the strongest predictor for India while personal norms mattered most in the US sample. Key contributions of this dissertation to advancing theory and building new empirical knowledge in environmental communication and conservation social science research are discussed. In recognizing that several existing scales were developed by and for primarily Western audiences, this dissertation also underscores the importance of cross-validating measures and being inclusive of communities in non-Western emerging economies. Theoretical and practical implications of the results along with directions for future research and limitations are also discussed.

Abstract Context Gestational diabetes (GDM) has profound effects on the intrauterine metabolic milieu and is linked to obesity and diabetes in offspring, but the mechanisms driving these effects remain largely unknown. Alterations in DNA methylation and gene expression in amniocytes exposed to GDM in utero represent a potential mechanism leading to metabolic dysfunction later in life. Objective To profile changes in genome-wide DNA methylation and expression in human amniocytes exposed to GDM. Design A nested case-control study (n = 14 pairs) was performed in amniocytes matched for offspring sex, maternal race/ethnicity, maternal age, gestational age at amniocentesis, and gestational age at birth. Sex-specific genome-wide DNA methylation analysis and RNA-sequencing were completed and differentially methylated regions (DMRs) and gene expression changes were identified. Ingenuity pathway analysis identified biologically relevant pathways enriched after GDM exposure. In silico high-throughput chromosome conformation capture (Hi-C) analysis identified potential chromatin interactions with DMRs. Results Expression of interferon-stimulated genes was increased in GDM amniocytes, accounting for 6 of the top 10 altered genes (q < 0.05). Enriched biological pathways in GDM amniocytes included pathways involving inflammation, the interferon response, fatty liver disease, monogenic diabetes, and atherosclerosis. Forty-two DMRs were identified in male GDM-exposed amniocytes and 20 in female amniocyte analysis (q < 0.05). Hi-C analysis identified interactions between DMRs and 11 genes with significant expression changes in male amniocytes and 9 in female amniocytes (P < .05). Conclusion In a unique repository of human amniocytes exposed to GDM in utero, transcriptome analysis identified enrichment of inflammation and interferon-related pathways and novel DMRs with potential distal regulatory functions.

Abstract Fasting during pregnancy is an enigma: why would a woman restrict her food intake during a period of increased nutritional need? Relative to the costs to healthy individuals who are not pregnant, the physiological costs of fasting in pregnancy are amplified, with intrauterine death being one possible outcome. Given these physiological costs, the question arises as to the socioecological factors that give rise to fasting during pregnancy. There has been little formal research regarding the emic perceptions and socioecological factors associated with such fasting. This study therefore took an emic approach and investigated the types of fasts that are common in pregnancy, women’s perceptions of the consequences of fasting, and the socioecological models of pregnancy fasting in three Indian communities. This cross-sectional study took place in Bhubaneshwar, Odisha state, and Mysore, Karnataka state, among two populations of Hindu women and one population of Muslim women (N = 85). In total, 64% of women fasted in prior pregnancies. Findings revealed variation in the number and types of fasts that are common in pregnancy across the three communities. Each community reported differences in positive and negative consequences of fasting, with varied emphasis on reproductive health, religiosity, and general health and well-being. Finally, quantitative analyses indicated that the best-fitting model for fasting during pregnancy was religiosity, and the poorest-fitting models were resource scarcity and general health. This study provides insight into motivations for such fasting and highlights the need to investigate the relationship between supernatural beliefs and maternal–fetal protection further, as well as social functions of pregnancy fasting within the family and community.