A curated knowledgebase on endocrine disrupting chemicals and their biological systems-level perturbations

Human well-being can be affected by exposure to several chemicals in the environment. One such group is endocrine disrupting chemicals (EDCs) that can perturb the hormonal homeostasis leading to adverse health effects. In this work, we have developed a detailed workflow to identify EDCs with supporting evidence of endocrine disruption in published experiments in humans or rodents. Thereafter, this workflow was used to manually evaluate more than 16,000 published research articles and identify 686 potential EDCs with published evidence in humans or rodents. Importantly, we have compiled the observed adverse effects or endocrine-specific perturbations along with the dosage information for the potential EDCs from their supporting published experiments. Subsequently, the potential EDCs were classified based on the type of supporting evidence, their environmental source and their chemical properties. Additional compiled information for potential EDCs include their chemical structure, physicochemical properties, predicted ADMET properties and target genes. In order to enable future research based on this compiled information on potential EDCs, we have built an online knowledgebase, Database of Endocrine Disrupting Chemicals and their Toxicity profiles (DEDuCT), accessible at: https://cb.imsc.res.in/deduct/. After building this comprehensive resource, we have performed a network-centric analysis of the chemical space and the associated biological space of target genes of EDCs. Specifically, we have constructed two networks of EDCs using our resource based on similarity of chemical structures or target genes. Ensuing analysis revealed a lack of correlation between chemical structure and target genes of EDCs. Though our detailed results highlight potential challenges in developing predictive models for EDCs, the compiled information in our resource will undoubtedly enable future research in the field, especially, those focussed towards mechanistic understanding of the systems-level perturbations caused by EDCs.

Neural regeneration therapies for Alzheimer's and Parkinson's disease-related disorders

Neurodegenerative diseases are devastating mental illnesses without a cure. Alzheimer's disease (AD) characterized by memory loss, multiple cognitive impairments, and changes in personality and behavior. Although tremendous progress has made in understanding the basic biology in disease processes in AD and PD, we still do not have early detectable biomarkers for these diseases. Just in the United States alone, federal and nonfederal funding agencies have spent billions of dollars on clinical trials aimed at finding drugs, but we still do not have a drug or an agent that can slow the AD or PD disease process. One primary reason for this disappointing result may be that the clinical trials enroll patients with AD or PD at advances stages. Although many drugs and agents are tested preclinical and are promising, in human clinical trials, they are mostly ineffective in slowing disease progression. One therapy that has been promising is 'stem cell therapy' based on cell culture and pre-clinical studies. In the few clinical studies that have investigated therapies in clinical trials with AD and PD patients at stage I. The therapies, such as stem cell transplantation - appear to delay the symptoms in AD and PD. The purpose of this article is to describe clinical trials using 1) stem cell transplantation methods in AD and PD mouse models and 2) regenerative medicine in AD and PD mouse models, and 3) the current status of investigating preclinical stem cell transplantation in patients with AD and PD.

Antioxidant, DNA binding and nuclease activities of heteroleptic copper(II) complexes derived from 2-((2-(piperazin-1-yl)ethylimino)methyl)-4-substituted phenols and diimines

A series of heteroleptic copper(II) complexes of the type [CuL(1-4)(diimine)](ClO4)2 (1-8) [L(1-4)=2-((2-(piperazin-1-yl)ethylimino)methyl)-4-substituted phenols, and diimine=2,2'-bipyridyl (bpy) or 1,10-phenanthroline (phen)], have been synthesized and characterized by spectroscopic methods. The IR spectra of complexes indicate the presence of uncoordinated perchlorate anions and the electronic spectra revealed the square pyramidal geometry with N4O coordination environment around copper(II) nuclei. Electrochemical studies of the mononuclear complexes evidenced one-electron irreversible reduction wave in the cathodic region. The EPR spectra of complexes with g|| (2.206-2.214) and A|| (154-172×10(-)(4)cm(-)(1)) values support the square-based CuN3O coordination chromophore and the presence of unpaired electron localized in [Formula: see text] ground state. Antioxidant studies against DPPH revealed effective radical scavenging properties of the synthesized complexes. Binding studies suggest that the heteroleptic copper(II) complexes interact with calf thymus DNA (CT-DNA) through minor-groove and electrostatic interaction, and all the complexes display pronounced nuclease activity against supercoiled pBR322 DNA.

Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations

An adverse outcome pathway (AOP) is a compact representation of the available mechanistic information on observed adverse effects upon environmental exposure. Sharing of events across individual AOPs has led to the emergence of AOP networks. Since AOP networks are expected to be functional units of toxicity prediction, there is current interest in their development tailored to specific research question or regulatory problem. To this end, we have developed a detailed workflow to construct an endocrine-relevant AOP (ED-AOP) network based on the existing information available in AOP-Wiki. We propose a cumulative weight of evidence (WoE) score for each ED-AOP based on the WoE scores assigned to key event relationships (KERs) by AOP-Wiki, revealing gaps in AOP development. Connectivity analysis of the ED-AOP network comprising 48 AOPs reveals 7 connected components and 12 isolated AOPs. Subsequently, we apply standard network measures to perform an in-depth analysis of the two largest connected components of the ED-AOP network. Notably, the graph-theoretic analyses led to the identification of important events including points of convergence or divergence in the ED-AOP network. These findings can suggest potential adverse outcomes and facilitate the development of new endpoints or assays for chemical risk assessment. Detailed analysis of the largest component in the ED-AOP network gives insights on the systems-level perturbations caused by endocrine disruption, emergent paths, and stressor-event associations. In sum, the derived ED-AOP network can provide a broader view of the biological events disrupted by endocrine disruption, as well as facilitate better risk assessment of environmental chemicals.

Lessons from the confidential enquiry into maternal deaths, Malaysia

Malaysia has successfully reduced maternal mortality through several efforts which, in the broad sense, include (i) the overall socio-economic development of the country; (ii) strengthened health services; and (iii) specific efforts and initiatives for the reduction of maternal mortality, one of which is the audit of maternal deaths by the confidential enquiry into maternal deaths.

DEDuCT 2.0: An updated knowledgebase and an exploration of the current regulations and guidelines from the perspective of endocrine disrupting chemicals

The regulatory assessment of endocrine disrupting chemicals (EDCs) is complex due to the lack of a standardized definition of EDCs and validated testing criteria. In spite of these challenges, there is growing scientific interest in EDCs which has resulted in the rapid expansion of published literature on endocrine disruption upon chemical exposure. Here, we explore how academic research leading to curated knowledgebases can inform current chemical regulations on EDCs. To this end, we present an updated knowledgebase, DEDuCT 2.0, containing 792 potential EDCs with supporting evidence from 2218 research articles. Thereafter, we study the distribution of potential EDCs across several chemical lists that reflect guidelines for use or regulations. Further, to understand the scale of possible exposure to the potential EDCs present in chemical lists, we compare them with high production volume chemicals. Notably, we find many potential EDCs are in use across various product categories such as 'Food additives and Food contact materials' and 'Cosmetics and household products'. Several of these EDCs are also produced or manufactured in high volume across the world. Lastly, we illustrate using an example how diverse information in curated knowledgebases such as DEDuCT 2.0 can be helpful in the risk assessment of EDCs. In sum, we highlight the need to bridge the gap between academic and regulatory aspects of chemical safety, as a step towards the better management of environment and health hazards such as EDCs.

A novel polymer nanotube composite for photovoltaic packaging applications

Packaging of organic photovoltaic (OPV) devices is an important issue which has been rarely addressed in the past. With the recent reports of high efficiency organic photovoltaics (6%), the need to produce materials which can effectively protect the device from degradation due to exposure to oxygen, moisture and radiation is pressing. We report a novel Saran (a co-polymer of vinylidene chloride and acrylonitrile) based polymer nanotube composite, which shows high transparency in the visible region, good barrier properties and thermal stability, for use as an encapsulant for OPV devices. Different loadings of Saran and boron nitride nanotubes were taken and the composites were prepared to optimize the composition of the composite. UV-visible spectroscopy, infra-red spectroscopy and thermal analysis were used to characterize the composite. The barrier properties of the composite were tested on poly(3-hexylthiophene), which is used in high efficiency OPV devices.

ExHuMId: A curated resource and analysis of Exposome of Human Milk across India

Human milk is a vital source of nourishment for infants. However, numerous environmental contaminants also find their way into human milk, making up the major part of a newborn's external exposome. While there are chemical regulations in India and scientific literature on environmental contaminants is available, the systematic compilation, monitoring, and risk management of human milk contaminants are inadequate. We have harnessed the potential of this large body of literature to develop the Exposome of Human Milk across India (ExHuMId) version 1.0 containing detailed information on 101 environmental contaminants detected in human milk samples across 13 Indian states, compiled from 36 research articles. ExHuMId also compiles the detected concentrations of the contaminants, structural and physicochemical properties, and factors associated with the donor of the sample. We also present findings from a three-pronged analysis of ExHuMId and two other resources on human milk contaminants, with a focus on the Indian scenario. Through a comparative analysis with global chemical regulations and guidelines, we identify human milk contaminants of high concern, such as potential carcinogens, endocrine disruptors and neurotoxins. We then study the physicochemical properties of the contaminants to gain insights on their propensity to transfer into human milk. Lastly, we employ a systems biology approach to shed light on potential effects of human milk contaminants on maternal and infant health, by identifying contaminant-gene interactions associated with lactation, cytokine signalling and production, and protein-mediated transport. ExHuMId 1.0 is accessible online at: https://cb.imsc.res.in/exhumid/.

NeurotoxKb 1.0: Compilation, curation and exploration of a knowledgebase of environmental neurotoxicants specific to mammals

Exposure to environmental neurotoxicants is a significant concern due to their potential to cause permanent or irreversible damage to the human nervous system. Here, we present the first dedicated knowledgebase, NeurotoxKb 1.0, on environmental neurotoxicants specific to mammals. Using a detailed workflow, we have compiled 475 potential non-biogenic neurotoxicants from 835 published studies with evidence of neurotoxicity specific to mammals. A unique feature of NeurotoxKb 1.0 is the manual curation effort to compile and standardize the observed neurotoxic effects for the potential neurotoxicants from 835 published studies. For the 475 potential neurotoxicants, we have compiled diverse information such as chemical structures, environmental sources, chemical classification, physicochemical properties, molecular descriptors, predicted ADMET properties, and target human genes. To better understand the prospect of human exposure, we have explored the presence of potential neurotoxicants in external exposomes via two different analyses. By analyzing 55 chemical lists representing global regulations and guidelines, we reveal potential neurotoxicants both in regular use and produced in high volume. By analyzing human biospecimens, we reveal potential neurotoxicants detected in them. Lastly, a construction of the chemical similarity network and ensuing analysis revealed the diversity of the toxicological space of 475 potential neurotoxicants. NeurotoxKb 1.0 is accessible online at: https://cb.imsc.res.in/neurotoxkb/.

IL-1 induces p62/SQSTM1 and autophagy in ERα+ /PR+ BCa cell lines concomitant with ERα and PR repression, conferring an ERα- /PR- BCa-like phenotype

Estrogen receptor α (ERα)^low/- tumors are associated with breast cancer (BCa) endocrine resistance, where ERα low tumors show a poor prognosis and a molecular profile similar to triple negative BCa tumors. Interleukin-1 (IL-1) downregulates ERα accumulation in BCa cell lines, yet the cells can remain viable. In kind, IL-1 and ERα show inverse accumulation in BCa patient tumors and IL-1 is implicated in BCa progression. IL-1 represses the androgen receptor hormone receptor in prostate cancer cells concomitant with the upregulation of the prosurvival, autophagy-related protein, Sequestome-1 (p62/SQSTM1; hereinafter, p62); and given their similar etiology, we hypothesized that IL-1 also upregulates p62 in BCa cells concomitant with hormone receptor repression. To test our hypothesis, BCa cell lines were exposed to conditioned medium from IL-1-secreting bone marrow stromal cells (BMSCs), IL-1, or IL-1 receptor antagonist. Cells were analyzed for the accumulation of ERα, progesterone receptor (PR), p62, or the autophagosome membrane protein, microtubule-associated protein 1 light chain 3 (LC3), and for p62-LC3 interaction. We found that IL-1 is sufficient to mediate BMSC-induced ERα and PR repression, p62 and autophagy upregulation, and p62-LC3 interaction in ERα⁺ /PR⁺ BCa cell lines. However, IL-1 does not significantly elevate the high basal p62 accumulation or high basal autophagy in the ERα^- /PR^- BCa cell lines. Thus, our observations imply that IL-1 confers a prosurvival ERα^- /PR^- molecular phenotype in ERα⁺ /PR⁺ BCa cells that may be dependent on p62 function and autophagy and may underlie endocrine resistance.

An atlas of fragrance chemicals in children's products

Exposure to environmental chemicals during early childhood is a potential health concern. At a tender age, children are exposed to fragrance chemicals used in toys and child care products. Although there are few initiatives in Europe and United States towards monitoring and regulation of fragrance chemicals in children's products, such efforts are still lacking elsewhere. Besides there has been no systematic effort to create a database compiling the surrounding knowledge on fragrance chemicals used in children's products from published literature. Here, we built a database of Fragrance Chemicals in Children's Products (FCCP) that compiles information on 153 fragrance chemicals from published literature. The fragrance chemicals in FCCP have been classified based on their chemical structure, children's product source, chemical origin and odor profile. Moreover, we have also compiled the physicochemical properties, predicted Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties, molecular descriptors and human target genes for the fragrance chemicals in FCCP. After building FCCP, we performed multiple analyses of the associated fragrance chemical space. Firstly, we assessed the regulatory status of the fragrance chemicals in FCCP through a comparative analysis with 21 chemical lists reflecting current guidelines or regulations. We find that several fragrance chemicals in children's products are potential carcinogens, endocrine disruptors, neurotoxicants, phytotoxins and skin sensitizers. Secondly, we performed a similarity network based analysis of the fragrance chemicals in children's products to reveal the high structural diversity of the associated chemical space. Lastly, we identified skin sensitizing fragrance chemicals in children's products using ToxCast assays. In a nutshell, we present a comprehensive resource and detailed analysis of fragrance chemicals in children's products highlighting the need for their better risk assessment and regulation to deliver safer products for children. FCCP is accessible at: https://cb.imsc.res.in/fccp.

Identification of activity cliffs in structure-activity landscape of androgen receptor binding chemicals

Androgen mimicking environmental chemicals can bind to Androgen receptor (AR) and can cause severe effects on the reproductive health of males. Predicting such endocrine disrupting chemicals (EDCs) in the human exposome is vital for improving current chemical regulations. To this end, QSAR models have been developed to predict androgen binders. However, a continuous structure-activity relationship (SAR) wherein chemicals with similar structure have similar activity does not always hold. Activity landscape analysis can help map the structure-activity landscape and identify unique features such as activity cliffs. Here we performed a systematic investigation of the chemical diversity along with the global and local structure-activity landscape of a curated list of 144 AR binding chemicals. Specifically, we clustered the AR binding chemicals and visualized the associated chemical space. Thereafter, consensus diversity plot was used to assess the global diversity of the chemical space. Subsequently, the structure-activity landscape was investigated using SAS maps which capture the activity difference and structural similarity among the AR binders. This analysis led to a subset of 41 AR binding chemicals forming 86 activity cliffs, of which 14 are activity cliff generators. Additionally, SALI scores were computed for all pairs of AR binding chemicals and the SALI heatmap was also used to evaluate the activity cliffs identified using SAS map. Finally, we provide a classification of the 86 activity cliffs into six categories using structural information of chemicals at different levels. Overall, this investigation reveals the heterogeneous nature of the structure-activity landscape of AR binding chemicals and provides insights which will be crucial in preventing false prediction of chemicals as androgen binders and developing predictive computational toxicity models in the future.

Network biology approach to human tissue-specific chemical exposome

Human exposure to environmental chemicals is a major contributor to the global disease burden. To characterize the external exposome it is important to assess its chemical components and to study their impact on human health. Biomonitoring studies measure the body burden of environmental chemicals detected in biospecimens from a wide range of the population. The detection of these chemicals in biospecimens (and, hence, human tissues) is considered an important biomarker of human exposure. However, there is no readily available resource that compiles such exposure data for human tissues from published literature, and no studies that explore the patterns in the associations between tissue-specific exposures and human diseases. We present Human Tissue-specific Exposome Atlas (TExAs), a compilation of 380 environmental chemicals detected across 27 human tissues. TExAs is accessible via a user friendly webserver: https://cb.imsc.res.in/texas. We compare the chemicals in TExAs with 55 global chemical regulations, guidelines, and inventories, which represent several categories of the external exposome of humans. Further to understand the potential implications on human health of chemicals detected across human tissues, we employ a network biology approach and explore possible chemical exposure-disease associations. Ensuing analyses reveal the possibilities of disease comorbidities and demonstrate the application of network biology in unraveling complex disease associations due to chemical exposure.

An apparatus for simultaneous measurement of electrical conductivity and thermopower of thin films in the temperature range of 300-750 K

An automated apparatus capable of measuring the electrical conductivity and thermopower of thin films over a temperature range of 300-750 K is reported. A standard dc resistance measurement in van der Pauw geometry was used to evaluate the electrical conductivity, and the thermopower was measured using the differential method. The design of the instrument, the methods used for calibration, and the measurement procedure are described in detail. Given the lack of a standard National Institute of Standards and Technology (Gaithersburg, Md.) sample for high temperature thermopower calibration, the disclosed calibration procedure shall be useful for calibration of new instruments.

Ambipolar transport and magneto-resistance crossover in a Mott insulator, Sr2IrO4

Electric field effect (EFE) controlled magnetoelectric transport in thin films of undoped and La-doped Sr₂IrO₄ (SIO) is investigated using ionic liquid gating. The temperature dependent resistance measurements exhibit insulating behavior in chemically and EFE doped samples with the band filling up to 10%. The ambipolar transport across the Mott gap is demonstrated by EFE tuning of the channel resistance and chemical doping. We observe a crossover from high temperature negative to low temperature positive magnetoresistance around  ∼80-90 K, irrespective of the filling. This temperature and magnetic field dependent crossover is discussed in the light of conduction mechanisms of SIO, especially variable range hopping (VRH), and its relevance to the insulating ground state of SIO.

Machine Learning Models for Prediction of Xenobiotic Chemicals with High Propensity to Transfer into Human Milk

Breast milk serves as a vital source of essential nutrients for infants. However, human milk contamination via the transfer of environmental chemicals from maternal exposome is a significant concern for infant health. The milk to plasma concentration (M/P) ratio is a critical metric that quantifies the extent to which these chemicals transfer from maternal plasma into breast milk, impacting infant exposure. Machine learning-based predictive toxicology models can be valuable in predicting chemicals with a high propensity to transfer into human milk. To this end, we build such classification- and regression-based models by employing multiple machine learning algorithms and leveraging the largest curated data set, to date, of 375 chemicals with known milk-to-plasma concentration (M/P) ratios. Our support vector machine (SVM)-based classifier outperforms other models in terms of different performance metrics, when evaluated on both (internal) test data and an external test data set. Specifically, the SVM-based classifier on (internal) test data achieved a classification accuracy of 77.33%, a specificity of 84%, a sensitivity of 64%, and an F-score of 65.31%. When evaluated on an external test data set, our SVM-based classifier is found to be generalizable with a sensitivity of 77.78%. While we were able to build highly predictive classification models, our best regression models for predicting the M/P ratio of chemicals could achieve only moderate R2 values on the (internal) test data. As noted in the earlier literature, our study also highlights the challenges in developing accurate regression models for predicting the M/P ratio of xenobiotic chemicals. Overall, this study attests to the immense potential of predictive computational toxicology models in characterizing the myriad of chemicals in the human exposome.