Biomonitoring of organochlorines in women with benign and malignant breast disease

Assessing organophosphate insecticide retention in muscle tissues of juvenile common carp fish under acute toxicity tests

Organophosphate insecticide spray poses potential threat of contamination of environmental components their accumulation in aquatic organisms. Although various physiological deficits associated with their exposure in fishes are documented, yet their retention in their edible muscle tissues has been poorly studied. In this context, the study was undertaken to ascertain the bioaccumulation of two organophosphate insecticide compounds (dimethoate and chlorpyrifos) in the muscles of juvenile Cyprinus carpio. The study could provide insight into the risks to human health associated with consuming contaminated fish flesh. The fishes exposed to various concentrations of dimethoate and chlorpyrifos in-vivo for 96 to ascertain the uptake and retention of these insecticides in the muscle. Results indicated that fish muscles accumulated the residues at all the concentrations with the recovery of 2.99% (0.032 ppm) of dimethoate exposed to LC50 concentrations. In contrast, the chlorpyrifos residues were found Below the Detection Level (BDL) in the fishes exposed to LC50 concentrations. The percentage bioaccumulation of dimethoate in fish muscle was 88.10%, and that of chlorpyrifos was BDL. The bio-concentration factor was dose-dependent and increased with increasing doses of both insecticides. The study invites attention to human health risk assessment in the regions where contaminated fish are consumed without scientific supervision.

ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images

Early detection of breast cancer is an essential procedure to reduce the mortality rate among women. In this paper, a new AI-based computer-aided diagnosis (CAD) framework called ETECADx is proposed by fusing the benefits of both ensemble transfer learning of the convolutional neural networks as well as the self-attention mechanism of vision transformer encoder (ViT). The accurate and precious high-level deep features are generated via the backbone ensemble network, while the transformer encoder is used to diagnose the breast cancer probabilities in two approaches: Approach A (i.e., binary classification) and Approach B (i.e., multi-classification). To build the proposed CAD system, the benchmark public multi-class INbreast dataset is used. Meanwhile, private real breast cancer images are collected and annotated by expert radiologists to validate the prediction performance of the proposed ETECADx framework. The promising evaluation results are achieved using the INbreast mammograms with overall accuracies of 98.58% and 97.87% for the binary and multi-class approaches, respectively. Compared with the individual backbone networks, the proposed ensemble learning model improves the breast cancer prediction performance by 6.6% for binary and 4.6% for multi-class approaches. The proposed hybrid ETECADx shows further prediction improvement when the ViT-based ensemble backbone network is used by 8.1% and 6.2% for binary and multi-class diagnosis, respectively. For validation purposes using the real breast images, the proposed CAD system provides encouraging prediction accuracies of 97.16% for binary and 89.40% for multi-class approaches. The ETECADx has a capability to predict the breast lesions for a single mammogram in an average of 0.048 s. Such promising performance could be useful and helpful to assist the practical CAD framework applications providing a second supporting opinion of distinguishing various breast cancer malignancies.

A Hybrid Workflow of Residual Convolutional Transformer Encoder for Breast Cancer Classification Using Digital X-ray Mammograms

Breast cancer, which attacks the glandular epithelium of the breast, is the second most common kind of cancer in women after lung cancer, and it affects a significant number of people worldwide. Based on the advantages of Residual Convolutional Network and the Transformer Encoder with Multiple Layer Perceptron (MLP), this study proposes a novel hybrid deep learning Computer-Aided Diagnosis (CAD) system for breast lesions. While the backbone residual deep learning network is employed to create the deep features, the transformer is utilized to classify breast cancer according to the self-attention mechanism. The proposed CAD system has the capability to recognize breast cancer in two scenarios: Scenario A (Binary classification) and Scenario B (Multi-classification). Data collection and preprocessing, patch image creation and splitting, and artificial intelligence-based breast lesion identification are all components of the execution framework that are applied consistently across both cases. The effectiveness of the proposed AI model is compared against three separate deep learning models: a custom CNN, the VGG16, and the ResNet50. Two datasets, CBIS-DDSM and DDSM, are utilized to construct and test the proposed CAD system. Five-fold cross validation of the test data is used to evaluate the accuracy of the performance results. The suggested hybrid CAD system achieves encouraging evaluation results, with overall accuracies of 100% and 95.80% for binary and multiclass prediction challenges, respectively. The experimental results reveal that the proposed hybrid AI model could identify benign and malignant breast tissues significantly, which is important for radiologists to recommend further investigation of abnormal mammograms and provide the optimal treatment plan.

Exposure to endocrine disruptors and risk of breast cancer: A systematic review

AIM

The aim of this study was to investigate the association between human exposure to endocrine disruptors (EDs) and the risk of breast cancer.

METHODS

This was a systematic review conducted by searching Cochrane Library, LILACS, Livivo, PubMed, and Science Direct. Observational studies addressing the association between exposure to EDs and breast cancer risk in adults were included. Risk of bias was assessed using the National Toxicology Program's Office of Health Assessment Translation tool.

RESULTS

a total of 37 studies were included. Most studies reported that exposure to organochlorine pesticides, phthalates, heavy metals, and polycyclic aromatic hydrocarbons was associated with increased breast cancer risk.

CONCLUSION

qualitative analysis of observational studies indicates that human exposure to EDs is associated with increased breast cancer risk. Additional studies are needed to determine whether this association is causal.

Persistent Organic Pollutants and Breast Cancer: A Systematic Review and Critical Appraisal of the Literature

Persistent organic pollutants (POPs) bioaccumulate in the food chain and have been detected in human blood and adipose tissue. Experimental studies demonstrated that POPs can cause and promote growth of breast cancer. However, inconsistent results from epidemiological studies do not support a causal relationship between POPs and breast cancer in women. To identify individual POPs that are repeatedly found to be associated with both breast cancer incidence and progression, and to demystify the observed inconsistencies between epidemiological studies, we conducted a systematic review of 95 studies retrieved from three main electronic databases. While no clear pattern of associations between blood POPs and breast cancer incidence could be drawn, POPs measured in breast adipose tissue were more clearly associated with higher breast cancer incidence. POPs were more consistently associated with worse breast cancer prognosis whether measured in blood or breast adipose tissue. In contrast, POPs measured in adipose tissue other than breast were inversely associated with both breast cancer incidence and prognosis. Differences in biological tissues used for POPs measurement and methodological biases explain the discrepancies between studies results. Some individual compounds associated with both breast cancer incidence and progression, deserve further investigation.

An Effective Two Way Classification of Breast Cancer Images: A Detailed Review

Cancer, a disease of cells, causes cell growth which differs from normal cell growth ratio, this cell growth spreads in the human body and kills the body cells. Breast cancer, it’s a highly heterogeneous disease and western women commonly witness this. Mammography, a pre-screening X-ray based check is used to diagnose woman’s breast cancer. This basic test mode helps in identifying breast cancer at early stage and this early stage detection would support in recovering more number of women from this serious disease. Medical centres deputed highly skilled radiologists and they were given the responsibility of analysing this mammography results but still human errors are inevitable. An error frequency ratio is high when radiologists exhausted in their analysis task and leads variations in either observations ie., internal or external observation. Also, quality of the image plays vital role in Mammographic sensitivity and leads to variation. Several automation processes were tried in streamlining and standardising diagnosis analysis process and quality of breast cancer images were improved. This paper inducts a two way mode algorithm for grouping of breast cancer images to 1. benign (tumour growing, but not dangerous) and 2. malignant (cannot be controlled, it causes death) classes. Two-way mode data mining algorithms are used due to thinly dispersed distribution of abnormal mammograms. First type algorithm is k-means algorithm, which regroups the given data elements into clusters (ie., prioritized by the users). Second type algorithm is Support Vector Machine (SVM), which is used to identify the most suitable function which differentiates the members based on the training data.

Pesticides exposure through environment and risk of pre-term birth: a study from Agra city

Pre-term birth is an increasingly prevalent complex condition with multiple risk factors including environmental pollutants. Evidences linking organochlorine pesticides with adverse pregnancy outcomes are inconsistent for link between organochlorine pesticides and adverse pregnancy outcomes. We performed a case-control study of 50 cases of full-term births and 40 cases of pre-term births in this study. Placental organochlorine pesticides like metabolites of dichlorodiphenyltrichloroethane that is, (p,p-DDE, p,p-DDT and o,p-DDD) and isomers of hexachlorocyclohexane (α, β, γ and δ HCH) were analyzed by gas chromatography. Although the mean levels of pesticide were found higher in the placenta of the women with pre-term delivery cases placentas, but only α-HCH, total-HCH, p,p-DDE and total-DDT were found statistically significant. It was observed that pesticide exposed women were approximately 1.7 times more likely to deliver pre-term baby as compare to pregnant women that were not exposed to any pesticides. We also observed that increasing maternal age reduced the risk of having pre-term birth (OR = 0.99). Among all pesticides, α-HCH was found to be strongest isomer to induce premature baby birth (p < 0.001). This study found that pregnant women's age and chronic disease, baby's weight at the time of birth and α-HCH were important risk factors for pre-term births.

Current pesticide profiles in blood serum of adults in Jiangsu Province of China and a comparison with other countries

Although various pesticides were used globally, the pesticides profiles in human blood serum remain largely unknown. We determined pesticide exposure profiles using solid-phase extraction and gas chromatography tandem with triple quadrupole mass spectrometry in 200 human blood serum samples from the adult population in Jiangsu Province, China. A systematic and comprehensive literature review was carried out to identify the articles investigating pesticide exposure and compare exposure data. Of the 88 pesticides, 76 were found in the blood serum of the population in Jiangsu Province. To the best of our knowledge, 58 pesticides were reported in human blood serum for the first time, and among these pesticides, parathion-methyl, pyrimethanil, fluacrypyrim, simazine, cloquintocet-mexyl and barban were debatable in more than half of the samples. By statistical comparison of the blood serum levels of pesticides between this study and other countries, we found the levels of several organochlorine pesticides were significantly higher in the female population of Jiangsu Province. Health risks related to the pesticide profiling were then revealed, which identified higher carcinogenic toxicity and teratogenic toxicity risk in the female adults of Jiangsu Province caused by organochlorine pesticide exposure. This study not only provides a high-throughput pesticide screening method for future studies of the exposome, but also presents the first human data on exposure to a number of pesticides. It may provide a knowledge database for the risk assessment and management of the pesticides.

Persistent organochlorine pesticides and oxidant/antioxidant status in the placental tissue of the women with full-term and pre-term deliveries

In India pre-term birth is the leading cause of death of infants and this number is continuously increasing.

Exposure to fogger trucks and breast cancer incidence in the Long Island Breast Cancer Study Project: a case-control study

BACKGROUND

Few studies have supported an association between breast cancer and DDT, usually assessed with biomarkers that cannot discern timing of exposure, or differentiate between the accumulation of chronic low-dose versus acute high-dose exposures in the past. Previous studies suggest that an association may be evident only among women exposed to DDT during biologically susceptible windows, or among those diagnosed with estrogen receptor/progesterone receptor-positive (ER+PR+) breast cancer subtypes. Self-reported acute exposure to a fogger truck, which sprayed DDT prior to 1972, was hypothesized to increase the risk of breast cancer, particularly among women exposed at a young age or diagnosed with ER+PR+ breast cancer.

METHODS

We examined these possibilities in the Long Island Breast Cancer Study Project (LIBCSP) (1,508 cases, 1,556 controls), which included exposure assessment by structured questionnaire and serum samples collected between 1996-1998, using adjusted logistic and polytomous regression to estimate ORs and 95% CIs.

RESULTS

Women with ER+PR+ breast cancer had a 44% increased odds of ever seeing a pre-1972 fogger truck compared to other subtypes (OR = 1.44; 95% CI 1.08-1.93). However, there was little variation in the observed increase in breast cancer risk when considering all women who reported seeing a pre-1972 fogger truck at their residence (OR = 1.16; 95% CI 0.98, 1.37), or during hypothesized susceptible windows. Self-reported acute exposure was not correlated with serum concentrations, a biomarker of long-term exposure.

CONCLUSIONS

These findings support the hypothesis that seeing a fogger truck, a proxy measure for acute DDT exposure, may be associated with ER+PR+ tumors, the most commonly diagnosed breast cancer subtype among American women.

Increased cancer burden among pesticide applicators and others due to pesticide exposure

A growing number of well-designed epidemiological and molecular studies provide substantial evidence that the pesticides used in agricultural, commercial, and home and garden applications are associated with excess cancer risk. This risk is associated both with those applying the pesticide and, under some conditions, those who are simply bystanders to the application. In this article, the epidemiological, molecular biology, and toxicological evidence emerging from recent literature assessing the link between specific pesticides and several cancers including prostate cancer, non-Hodgkin lymphoma, leukemia, multiple myeloma, and breast cancer are integrated. Although the review is not exhaustive in its scope or depth, the literature does strongly suggest that the public health problem is real. If we are to avoid the introduction of harmful chemicals into the environment in the future, the integrated efforts of molecular biology, pesticide toxicology, and epidemiology are needed to help identify the human carcinogens and thereby improve our understanding of human carcinogenicity and reduce cancer risk.

A fully automated scheme for mammographic segmentation and classification based on breast density and asymmetry

This paper presents a fully automated segmentation and classification scheme for mammograms, based on breast density estimation and detection of asymmetry. First, image preprocessing and segmentation techniques are applied, including a breast boundary extraction algorithm and an improved version of a pectoral muscle segmentation scheme. Features for breast density categorization are extracted, including a new fractal dimension-related feature, and support vector machines (SVMs) are employed for classification, achieving accuracy of up to 85.7%. Most of these properties are used to extract a new set of statistical features for each breast; the differences among these feature values from the two images of each pair of mammograms are used to detect breast asymmetry, using an one-class SVM classifier, which resulted in a success rate of 84.47%. This composite methodology has been applied to the miniMIAS database, consisting of 322 (MLO) mammograms -including 15 asymmetric pairs of images-, obtained via a (noisy) digitization procedure. The results were evaluated by expert radiologists and are very promising, showing equal or higher success rates compared to other related works, despite the fact that some of them used only selected portions of this specific mammographic database. In contrast, our methodology is applied to the complete miniMIAS database and it exhibits the reliability that is normally required for clinical use in CAD systems.

Organochlorine pesticide residues in inland wetland fishes of Karnataka, India and their implications on human dietary intake

As part of a larger study assessing contamination status of inland wetlands of India, we evaluated the organochlorine pesticide (OCP) residues in fishes collected from different inland wetlands in Karnataka, India and their suitability for human consumption. Among the OCPs tested, isomers of hexachlorocyclohexane (HCH) were the most frequently detected with β- and γ-HCH as the main pollutants. Average concentration of ∑HCH and ∑DDT ranged from 2.1 to 51.7 μg/kg and below detection level to 12.3 μg/kg respectively. Other organochlorine pesticides such as heptachlor epoxide, dieldrin and endosulphan were found at lower levels. Among various fish species tested, the higher pesticide burden was recorded in Anguilla bicolor bicolour (77.9 μg/kg) and the lower was in Heteropneustes fossilis (2.1 μg/kg). OCPs detected in the present study were well below the tolerance limits recommended for fishes. The calculated daily dietary intake of OCPs in all the species examined was lower than the maximum acceptable dietary intake (ADI) limits prescribed for human consumption. However, continuous monitoring is recommended to facilitate the early identification of risks.

The Pine River statement: human health consequences of DDT use

OBJECTIVES

Dichlorodiphenyltrichloroethane (DDT) was used worldwide until the 1970s, when concerns about its toxic effects, its environmental persistence, and its concentration in the food supply led to use restrictions and prohibitions. In 2001, more than 100 countries signed the Stockholm Convention on Persistent Organic Pollutants (POPs), committing to eliminate the use of 12 POPs of greatest concern. However, DDT use was allowed for disease vector control. In 2006, the World Health Organization and the U.S. Agency for International Development endorsed indoor DDT spraying to control malaria. To better inform current policy, we reviewed epidemiologic studies published from 2003 to 2008 that investigated the human health consequences of DDT and/or DDE (dichlorodiphenyldichloroethylene) exposure.

DATA SOURCES AND EXTRACTION

We conducted a PubMed search in October 2008 and retrieved 494 studies.

DATA SYNTHESIS

Use restrictions have been successful in lowering human exposure to DDT, but blood concentrations of DDT and DDE are high in countries where DDT is currently being used or was more recently restricted. The recent literature shows a growing body of evidence that exposure to DDT and its breakdown product DDE may be associated with adverse health outcomes such as breast cancer, diabetes, decreased semen quality, spontaneous abortion, and impaired neurodevelopment in children.

CONCLUSIONS

Although we provide evidence to suggest that DDT and DDE may pose a risk to human health, we also highlight the lack of knowledge about human exposure and health effects in communities where DDT is currently being sprayed for malaria control. We recommend research to address this gap and to develop safe and effective alternatives to DDT.

Organochlorine pesticides in commercial marine fishes of Coimbatore, India and their suitability for human consumption

Organochlorine pesticide residues were determined in 10 species of fishes caught at Cochin and Rameshwaram coast, and sold in Coimbatore, Tamil Nadu, India. Species were selected on the basis of their regular availability throughout the year and commercial value. A total of 389 fishes were analyzed for organochlorine residues and their suitability for human consumption was evaluated. Results show varying levels of residues of hexachlorocyclohexane (HCH), DDT, heptachlor epoxide, endosulfan and dieldrin. Among the 10 species, high concentration of pesticide residues were recorded in Sardinella longiceps, Carangoides malabaricus, Chlorophthalmus agassizi, Saurida tumbil and Rastrelliger kanagurta. The variation in total organochlorine residues among species and between places was not significant (P>0.05). Only five species of fishes showed monthly variation in residue levels and there was no significant correlation between the body size and residue levels in the tissue. About 22% of the fishes exceeded the maximum residue limits (MRL) of total HCH prescribed by FAO/WHO for fish products. The calculated dietary intake of total HCH through consumption of C. malabaricus, C. agassizi and S. longiceps exceeded the maximum acceptable dietary intake (ADI) limits prescribed for human consumption. The present study recommends continuous monitoring of environmental contaminants in marine fishes to assess the possible impact on human health.

Human breast biomonitoring and environmental chemicals: use of breast tissues and fluids in breast cancer etiologic research

Extensive research indicates that the etiology of breast cancer is complex and multifactorial and may include environmental risk factors. Breast cancer etiology and exposure to xenobiotic compounds, diet, electromagnetic fields, and lifestyle have been the subject of numerous scientific inquiries, but research has yielded inconsistent results. Biomonitoring has been used to explore associations between breast cancer and levels of environmental chemicals in the breast. Research using breast tissues and fluids to cast light on the etiology of breast cancer is, for the most part, predicated on the assumption that the tissue or fluid samples either contain measurable traces of the environmental agent(s) associated with the cancer or that they retain biological changes that are biomarkers of such exposure or precursors of carcinogenic effect. In this paper, we review breast cancer etiology research utilizing breast biomonitoring. We first provide a brief synopsis of the current state of understanding of associations between exposure to environmental chemicals and breast cancer etiology. We then describe the published breast cancer research on tissues and fluids, which have been used for biomonitoring, specifically human milk and its components, malignant and benign breast tissue, nipple aspirate fluid (NAF) and breast cyst fluid. We conclude with a discussion on recommendations for biomonitoring of breast tissues and fluids in future breast cancer etiology research. Both human milk and NAF fluids, and the cells contained therein, hold promise for future biomonitoring research into breast cancer etiology, but must be conducted with carefully delineated hypotheses and a scientifically supportable epidemiological approach.

Biomonitoring of organochlorines, glutathione, lipid peroxidation and cholinesterase activity among pesticide sprayers in mango orchards

BACKGROUND

Pesticide sprayers in mango orchards of Malihabad, Lucknow (India) are generally exposed to organophosphate (OP) and pyrethroid pesticides. We determined the pesticide exposure levels along with their biochemical and clinical effects in 31 sprayers, compared with 18 controls.

METHODS

Assay of acetyl and butyrylcholinesterases (AChE, BChE respectively) as an indirect measurement of OP exposure and levels of malondialdehyde (MDA) and glutathione (GSH) were estimated in blood samples to determine their impact on redox potential. Organochlorines were estimated by GLC-ECD.

RESULTS

Significantly inhibited AChE, BChE activities and higher MDA level were found among sprayers compared to controls (p<0.05). Mean of total organochlorines were surprisingly higher (97.65+/-13.38 ppb) in sprayers than in those of controls (20.42+/-3.56 ppb) (p<0.05). Respiratory morbidity (32.4%), ocular problems (8.8%), gastrointestinal (17.6%) and skin problems (23.5%) were found in sprayers. There was significant correlation between AChE and GSH (r=0.29, p<0.05) and AChE with MDA (r=-0.34, p<0.05).

CONCLUSION

Results indicated the significantly enhanced lipid peroxidation in sprayers correlated with cholinesterases inhibition. A small sample size limits the significance of this study. However, it paves the way for a larger Indian study with extended practical significance.