A novel model combining genes associated with disulfidptosis and glycolysis to predict breast cancer prognosis, molecular subtypes, and treatment response.

Breast cancer (BC) is a heterogeneous malignancy with a dismal prognosis. Disulfidptosis is a novel type of regulated cell death that happens in the presence of glucose deficiency and is linked to the metabolic process of glycolysis. However, the mechanism of action of disulfidptosis and glycolysis-related genes (DGRG) in BC, as well as their prognostic value in BC patients, remain unknown. After identifying the differentially expressed DGRG in normal and BC tissues, a number of machine learning algorithms were utilized to select essential prognostic genes to develop a model, including SLC7A11, CACNA1H, SDC1, CHST1, and TFF3. The expression characteristics of these genes were then examined using single-cell RNA sequencing, and BC was classified into three clusters using "ConsensusClusterPlus" based on these genes. The DGRG model's median risk score can categorize BC patients into high-risk and low-risk groups. Furthermore, we investigated variations in clinical landscape, immunoinvasion analysis, tumor immune dysfunction and rejection (TIDE), and medication sensitivity in patients in the DGRG model's high- and low-risk groups. Patients in the low-risk group performed better on immunological and chemotherapeutic therapies and had lower TIDE scores. In conclusion, the DGRG model we developed has significant clinical application potential because it can accurately predict the prognosis of BC, TME, and pharmacological treatment responses.

MBD-Net: Multi-Branch Dilated Convolutional Network With Cyst Discriminator for Renal Multi-Structure Segmentation.

In surgery-based renal cancer treatment, one of the most essential tasks is the three-dimensional (3D) kidney parsing on computed tomography angiography (CTA) images. In this paper, we propose an end-to-end convolutional neural network-based framework to segment multiple renal structures, including kidneys, kidney tumors, arteries, and veins from arterial-phase CT images. Our method consists of two collaborative modules: First, we propose an encoding-decoding network, named Multi-Branch Dilated Convolutional Network (MBD-Net), consisting of residual, hybrid dilated convolutional, and reduced-dimensional convolutional structures, which improves the feature extraction ability with relatively fewer network parameters. Given that renal tumors and cysts have confusing geometric structures, we also design the Cyst Discriminator to effectively distinguish tumors from cysts without labeling information via gray-scale curves and radiographic features. We have quantitatively evaluated our approach on a publicly available dataset from MICCAI 2022 Kidney Parsing for Renal Cancer Treatment Challenge (KiPA2022), with mean Dice similarity coefficient (DSC) as 96.18%, 90.99%, 88.66% and 80.35% for the kidneys, kidney tumors, arteries, and veins respectively, winning the stable and top performance in the challenge.Clinical relevance-The proposed CNN-Based framework can automatically segment 3D kidneys, renal tumors, arteries, and veins for kidney parsing techniques, benefiting surgery-based renal cancer treatment.

A ubiquitin-proteasome system-related signature to predict prognosis, immune infiltration, and therapy efficacy for breast cancer.

The ubiquitin-proteasome system (UPS) is an essential regulatory system for maintaining homeostasis, and its dysfunction may cause various diseases. The activity of proteasome and ubiquitin-conjugating enzymes has been found to be greatly increased in breast cancer (BC), indicating that the heterogeneity of UPS may be related to the progression of BC. Gene data was obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases and performed in multiple algorithms to construct a UPS-related signature for BC. Patients in the UPS low-risk group had greater overall and recurrence-free survival probability than those in the UPS high-risk group. This signature was closely associated with functional enrichment. Some high metabolism-related pathways were more active in the UPS high-risk group. The UPS low-risk group had more abundant anti-tumor immune cells, while in the UPS high-risk group, immunosuppressive cells were dominant. More importantly, we found that the UPS low-risk group was more sensitive to immunotherapy, while the UPS high-risk group responded better to radiotherapy. Drug sensitivity analysis identified more effective chemotherapy drugs in different UPS-related risk groups. This UPS-related signature may serve as a novel biomarker and independent prognostic factor for BC. It can effectively predict prognosis, immune infiltration, and therapy efficacy, providing new strategies for individualized treatment.

Accuracy of lung and diaphragm ultrasound in predicting infant weaning outcomes: a systematic review and meta-analysis.

Background: Although lung and diaphragm ultrasound are valuable tools for predicting weaning results in adults with MV, their relevance in children is debatable. The goal of this meta-analysis was to determine the predictive value of lung and diaphragm ultrasound in newborn weaning outcomes. Methods: For eligible studies, the databases MEDLINE, Web of Science, Cochrane Library, PubMed, and Embase were thoroughly searched. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) method was used to evaluate the study's quality. Results were gathered for sensitivity, specificity, diagnostic odds ratio (DOR), and the area under the curve of summary receiver operating characteristic curves (AUSROC). To investigate the causes of heterogeneity, subgroup analyses and meta-regression were conducted. Results: A total of 11 studies were suitable for inclusion in the meta-analysis, which included 828 patients. The pooled sensitivity and specificity of lung ultrasound (LUS) were 0.88 (95%CI, 0.85-0.90) and 0.81 (95%CI, 0.75-0.87), respectively. The DOR for diaphragmatic excursion (DE) is 13.17 (95%CI, 5.65-30.71). The AUSROC for diaphragm thickening fraction (DTF) is 0.86 (95%CI, 0.82-0.89). The most sensitive and specific method is LUS. The DE and DTF were the key areas where study heterogeneity was evident. Conclusions: Lung ultrasonography is an extremely accurate method for predicting weaning results in MV infants. DTF outperforms DE in terms of diaphragm ultrasound predictive power.

Diagnostic value of contrast-enhanced ultrasound for sentinel lymph node metastasis in breast cancer: an updated meta-analysis.

PURPOSE: The status of sentinel lymph nodes (SLN) is an important factor in determining the stage of breast cancer (BC) and the surgical procedure, and also a biomarker of the BC prognosis. This meta-analysis was performed to investigate the diagnostic value of contrast-enhanced ultrasound (CEUS) for SLN metastasis. METHODS: A systematic search was conducted for relevant articles published in the PubMed, Embase, Web of Science, OVID databases, and Cochrane Library from inception to March 2023. We calculated the sensitivity, specificity, positive and negative likelihood ratio (PLR; NLR), diagnostic odds ratio (DOR), and summary receiver operator characteristic (SROC) curve to evaluate the diagnostic efficacy of CEUS in SLN metastasis. Subgroup analysis was also performed to investigate potential sources of heterogeneity. RESULTS: A total of 12 studies with 1525 patients were included in this meta-analysis. The overall pooled sensitivity and specificity of CEUS in the diagnosis of SLN metastasis were 0.91 (95% CI: 0.84-0.95) and 0.86 (95% CI: 0.78-0.92). The PLR, NLR, and DOR were 6.51 (95% CI: 4.09-10.36), 0.11 (95% CI: 0.07-0.18), and 59.43 (95% CI: 33.27-106.17), respectively, and the area under the SROC curve was determined to be 0.95 (95%CI: 0.92-0.96), all showing excellent diagnostic value. In the subgroup analysis, percutaneous CEUS was more sensitive than intravenous CEUS in the diagnosis of SLN metastases (0.92 versus 0.82, p < 0.05). CONCLUSION: CEUS, especially percutaneous CEUS, is a reliable imaging technique for diagnosing SLN metastasis and providing important information in the stage management of breast cancer.

Transformer-based 3D U-Net for pulmonary vessel segmentation and artery-vein separation from CT images.

Transformer-based methods have led to the revolutionizing of multiple computer vision tasks. Inspired by this, we propose a transformer-based network with a channel-enhanced attention module to explore contextual and spatial information in non-contrast (NC) and contrast-enhanced (CE) computed tomography (CT) images for pulmonary vessel segmentation and artery-vein separation. Our proposed network employs a 3D contextual transformer module in the encoder and decoder part and a double attention module in skip connection to effectively finish high-quality vessel and artery-vein segmentation. Extensive experiments are conducted on the in-house dataset and the ISICDM2021 challenge dataset. The in-house dataset includes 56 NC CT scans with vessel annotations and the challenge dataset consists of 14 NC and 14 CE CT scans with vessel and artery-vein annotations. For vessel segmentation, Dice is 0.840 for CE CT and 0.867 for NC CT. For artery-vein separation, the proposed method achieves a Dice of 0.758 of CE images and 0.602 of NC images. Quantitative and qualitative results demonstrated that the proposed method achieved high accuracy for pulmonary vessel segmentation and artery-vein separation. It provides useful support for further research associated with the vascular system in CT images. The code is available at https://github.com/wuyanan513/Pulmonary-Vessel-Segmentation-and-Artery-vein-Separation .

NCCT-CECT image synthesizers and their application to pulmonary vessel segmentation.

BACKGROUND AND OBJECTIVES: Non-contrast CT (NCCT) and contrast-enhanced CT (CECT) are important diagnostic tools with distinct features and applications for chest diseases. We developed two synthesizers for the mutual synthesis of NCCT and CECT and evaluated their applications. METHODS: Two synthesizers (S1 and S2) were proposed based on a generative adversarial network. S1 generated synthetic CECT (SynCECT) from NCCT and S2 generated synthetic NCCT (SynNCCT) from CECT. A new training procedure for synthesizers was proposed. Initially, the synthesizers were pretrained using self-supervised learning (SSL) and dual-energy CT (DECT) and then fine-tuned using the registered NCCT and CECT images. Pulmonary vessel segmentation from NCCT was used as an example to demonstrate the effectiveness of the synthesizers. Two strategies (ST1 and ST2) were proposed for pulmonary vessel segmentation. In ST1, CECT images were used to train a segmentation model (Model-CECT), NCCT images were converted to SynCECT through S1, and SynCECT was input to Model-CECT for testing. In ST2, CECT data were converted to SynNCCT through S2. SynNCCT and CECT-based annotations were used to train an additional model (Model-NCCT), and NCCT was input to Model-NCCT for testing. Three datasets, D1 (40 paired CTs), D2 (14 NCCTs and 14 CECTs), and D3 (49 paired DECTs), were used to evaluate the synthesizers and strategies. RESULTS: For S1, the mean absolute error (MAE), mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) were 14.60± 2.19, 1644± 890, 34.34± 1.91, and 0.94± 0.02, respectively. For S2, they were 12.52± 2.59, 1460± 922, 35.08± 2.35, and 0.95± 0.02, respectively. Our synthesizers outperformed the counterparts of CycleGAN, Pix2Pix, and Pix2PixHD. The results of ablation studies on SSL pretraining, DECT pretraining, and fine-tuning showed that performance worsened (for example, for S1, MAE increased to 16.53± 3.10, 17.98± 3.10, and 20.57± 3.75, respectively). Model-NCCT and Model-CECT achieved dice similarity coefficients (DSC) of 0.77 and 0.86 on D1 and 0.77 and 0.72 on D2, respectively. CONCLUSIONS: The proposed synthesizers realized mutual and high-quality synthesis between NCCT and CECT images; the training procedures, including SSL pretraining, DECT pretraining, and fine-tuning, were critical to their effectiveness. The results demonstrated the usefulness of synthesizers for pulmonary vessel segmentation from NCCT images.

Prognosis stratification and response to treatment in breast cancer based on one-carbon metabolism-related signature.

Introduction: Breast cancer (BC) is the most common malignant tumor in the female population. Despite staging and treatment consensus guidelines, significant heterogeneity exists in BC patients' prognosis and treatment efficacy. Alterations in one-carbon (1C) metabolism are critical for tumor growth, but the value of the role of 1C metabolism in BC has not been fully investigated. Methods: To investigate the prognostic value of 1C metabolism-related genes in BC, 72 1C metabolism-related genes from GSE20685 dataset were used to construct a risk-score model via univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression algorithm, which was validated on three external datasets. Based on the risk score, all BC patients were categorized into high-risk and low-risk groups. The predictive ability of the model in the four datasets was verified by plotting Kaplan-Meier curve and receiver operating characteristic (ROC) curve. The candidate genes were then analyzed in relation to gene mutations, gene enrichment pathways, immune infiltration, immunotherapy, and drug sensitivity. Results: We identified a 7-gene 1C metabolism-related signature for prognosis and structured a prognostic model. ROC analysis demonstrated that the model accurately predicted the 2-, 3-, and 5-year overall survival rate of BC patients in the four cohorts. Kaplan-Meier analysis revealed that survival time of high-risk patients was markedly shorter than that of low-risk patients (p < 0.05). Meanwhile, high-risk patients had a higher tumor mutational burden (TMB), enrichment of tumor-associated pathways such as the IL-17 signaling pathway, lower levels of T follicular helper (Tfh) and B cells naive infiltration, and poorer response to immunotherapy. Furthermore, a strong correlation was found between MAT2B and CHKB and immune checkpoints. Discussion: These findings offer new insights into the effect of 1C metabolism in the onset, progression, and therapy of BC and can be used to assess BC patients' prognosis, study immune infiltration, and develop potentially more effective clinical treatment options.

Diagnosis accuracy of Raman spectroscopy in the diagnosis of breast cancer: a meta-analysis.

To investigate the diagnostic efficiency of Raman spectroscopy for the diagnosis of breast cancer, we searched PubMed, Web of Science, Cochrane Library, and Embase for articles published from the database establishment to May 20, 2022. Pooled sensitivity, specificity, diagnostic odds ratio, and area under the receiver pooled operating characteristic curve were derived for the included studies as outcome measures. The methodological quality was assessed according to the questionnaires and criteria suggested by the Diagnostic Accuracy Research Quality Assessment-2 tool. Sixteen studies were included in this meta-analysis. The pooled sensitivity and specificity of Raman spectroscopy for breast cancer diagnosis were 0.97 (95% CI, [0.92-0.99]) and 0.96 (95% CI, [0.91-0.98]). The diagnostic odds ratio was 720.89 (95% CI, [135.73-3828.88]) and the area under the curve of summary receiver operating characteristic curves was 0.99 (95% CI, [0.98-1]). Subgroup analysis revealed that all subgroup types in our analysis, including different races, sample types, diagnostic algorithms, number of spectra, instrument types, and laser wavelengths, turned out to have a sensitivity and specificity greater than 0.9. Significant heterogeneity was found between studies. Deeks' funnel plot demonstrated that publication bias was acceptable. This meta-analysis suggests that Raman spectroscopy may be an effective and accurate tool to differentiate breast cancer from normal breast tissue, which will help us diagnose and treat breast cancer.

Safety and efficacy of ultrasound-guided thermal ablation in treating T1aN0M0 and T1bN0M0 papillary thyroid carcinoma: A meta-analysis.

Background: Papillary thyroid cancer (PTC) is the most common thyroid tumor, and early diagnosis and treatment can effectively improve prognosis. Many controversies surround the treatment method of T1N0M0 PTC. Recently, thermal ablation (TA) has shown some benefits in the treatment of PTC patients, but the safety and efficacy of its treatment remain controversial. This article performs a meta-analysis of TA in patients with T1aN0M0 and T1bN0M0 PTC. Methods: The PubMed, Embase, Web of Science, and Cochrane Library databases were systematically searched for retrospective or prospective studies of TA for treating patients with T1N0M0 PTC from the database establishment to May 1, 2022. Data on volume reduction rate (VRR), disease progress, and complication rate were collected. In addition, a meta-analysis was performed using the Stata 12.0 and Review Manager 5.3. Results: A total of 9 eligible studies were included. Our study demonstrated the effectiveness of VRR and disease progress. The VRR was reduced after 3 months (-75.90%; 95% CI [-118.46-33.34%]), 6 months (34.33%; 95% CI [15.01-53.65%]), 12 months (78.69%; 95% CI [71.69-85.68%]), and 24 months (89.97%; 95% CI [84.00-95.94%]). The disease progress was 1.9% (95% CI [1.1-3.0]). Safety is justified by the complication rate, which was 6.5% (95% CI [3.5-10.2]). Pain and hoarseness were the most common complications, and no life-threatening complications were reported. Egger's test demonstrated that publication bias was acceptable. Conclusions: TA is an effective and safe method for managing T1aN0M0 and T1bN0M0 papillary thyroid nodules.

A circadian rhythm-related gene signature for prognosis, invasion and immune microenvironment of breast cancer.

Background: Circadian dysregulation is linked to the onset and progression of cancer, but current knowledge of the role of circadian rhythm-related genes (CRRGs) in breast cancer (BC) is limited and incomplete. The purpose of this study was to investigate the potential role and immune-related prognostic significance of CRRGs in BC. Methods: The Cancer Genome Atlas breast cancer (TCGA-BRCA) genetic data were combined with 1369 CRRGs to create a model of BC prognosis-related CRRGs. To validate the model's predictive power in TCGA and other external datasets, the Kaplan-Meier survival curve and receptor operation characteristic curve were plotted. The relationship between CRRGs model and gene enrichment pathways, immune cell infiltration, and differences in patient response to immune checkpoint inhibitors (ICIs) therapy was then discussed. Results: A CRRG-based eighteen-gene model was developed that accurately predicted the survival time of BC patients. Based on this model, BC patients can be classified as high or low risk. The high-risk group has negative immune cell infiltration (such as macrophages M0 and M2) and a poor therapeutic response to ICIs due to lower immune checkpoint gene expression. Furthermore, TCF7 and IFNG were found to be strongly associated with immune checkpoints in CRRGs model. Conclusion: The 18 CRRGs may be useful in assessing the prognosis of BC patients, studying immune infiltration, and developing more effective immunotherapy strategies.

Organophosphate flame retardants and diesters in the urine of e-waste dismantling workers: associations with indoor dust and implications for urinary biomonitoring.

Indoor dust ingestion is one of the main pathways for human exposure to organophosphate flame retardants (PFRs). The urinary concentrations of diesters (DAPs) are usually used as biomarkers to assess human exposure to PFRs. In this study, the PFR and DAP levels were measured in morning and evening urine samples of 30 workers from an e-waste dismantling site in southern China. The indoor dust samples were also collected from workshops and houses for analyzing associations between PFR and DAP levels in urine and dust. Tris(1-chloro-2-propyl) phosphate (TCIPP) and triphenyl phosphate (TPHP) were the dominant PFRs in dust, while bis(2-chloroethyl) phosphate (BCEP) and diphenyl phosphate (DPHP) were the major DAPs in dust. A significant positive correlation was observed between TPHP and DPHP concentrations in dust (p < 0.001), suggesting their potentially same source and the degradation of TPHP to form DPHP. TCIPP and tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) were the predominant PFRs, and BCEP, bis(1,3-dichloro-2-propyl) phosphate (BDCIPP), and DPHP were the main DAPs in both the morning and evening urine samples. The DPHP levels in evening urine samples were significantly correlated with TPHP and DPHP levels (p < 0.01) in dust. A similar correlation was found for the BCEP levels in the evening urine samples and the TCEP and BCEP levels (p < 0.01) in dust. These results indicated that in addition to being biotransformed from their respective parent PFRs, direct ingestion from indoor dust could also be the potential source for urinary DPHP and BCEP. Since relatively low detection frequencies were observed for bis(1-chloro-2-propyl) phosphate (BCIPP) and bis(butoxyethyl) phosphate (BBOEP) in urine, they may not be the major metabolites of TCIPP and tris(2-butoxyethyl) phosphate (TBOEP), respectively, in the human body. However, BDCIPP can be considered a useful biomarker because it is a unique metabolite of TDCIPP and has high detection frequencies in urine samples. The results of this study indicated the limitations of solely using urinary DAPs as biomarkers for the evaluation of human exposure to PFRs, and certain PFRs as well as hydroxylated PFRs (OH-PFRs) should also be considered for urinary biomonitoring in future studies.

Analysis of polybrominated diphenyl ethers, hexabromocyclododecanes, and legacy and emerging phosphorus flame retardants in human hair.

Human hair has been identified as a non-invasive alternative matrix for assessing the human exposure to specific organic contaminants. In the present study, a solvent-saving analytical method for the simultaneous determination of 8 polybrominated diphenyl ethers (PBDEs), 3 hexabromocyclododecanes (HBCDDs), 12 phosphorus flame retardants (PFRs), and 4 emerging PFRs (ePFRs) has been developed and validated for the first time. Hair sample preparation protocols include precleaning with Milli-Q water, digestion with HNO3/H2O2 (1:1, v/v), liquid-liquid extraction with hexane:dichloromethane (4:1, v/v), and fractionation and cleanup on a Florisil cartridge. The method was validated by using two levels of spiked hair samples of 3 replicates for each spiking group. Limits of quantification (LOQs) were 0.12-22.4 ng/g for all analytes, average values of accuracies were ranging between 88 and 115%, 82-117%, 81-128%, and 81-95% for PBDEs, HBCDDs, PFRs, and ePFRs, respectively; and precision was also acceptable (RSD < 20%) for all analytes. Eventually, this method was applied to measure the levels of the targeted analytes in hair samples of e-waste dismantling workers (n = 14) from Qingyuan, South China. Median values ranged between 3.00 and 18.1 ng/g for PBDEs, 0.84-4.04 ng/g for HBCDDs, 2.13-131 ng/g PFRs, and 1.49-29.4 ng/g for ePFRs, respectively. PFRs/ePFRs constitute the major compounds in human hair samples, implying the wide use of PFRs/ePFRs as replacements of PBDEs and HBCDDs, as well the potential high human exposure risks of PFRs/ePFRs. Overall, this work will allow to a comprehensive assessment of human exposure to multiple groups of FRs using hair as a non-invasive bioindicator.

PCDD/Fs in paired hair and serum of workers from a municipal solid waste incinerator plant in South China: Concentrations, correlations, and source identification.

Human hair has been widely used to evaluate the exposure to drugs and organic pollutants. However, reports on the relationship between polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzo-p-furans (PCDFs) in hair and the body burden of PCDD/Fs are limited. In this study, the association between PCDD/Fs in paired hair and serum samples from workers was examined in a municipal solid waste incinerator (MSWI) plant in South China. Fly ash and flue gas from the MSWI plant were also analyzed to determine the source apportionment of PCDD/Fs in the hair. The median international toxic equivalents (I-TEQs) of ΣPCDD/F in serum and hair were 28.0 pg TEQ/g (lipid weight) and 0.30 pg TEQ/g (dry weight), respectively. The indicator congener of PCDD/Fs for the TEQ levels was 2,3,4,7,8-pentachlorodibenzofuran (PeCDF) in both hair and serum, the concentrations of which both exhibited significant and strong linear dependence on the total TEQ levels (p < 0.01, R2 = 0.966 and R2 = 0.670, respectively). Significant positive correlations were found in the 1,2,3,6,7,8-hexachlorodibenzo-p-dioxin (HxCDD) and octachlorodibenzo-p-dioxin (OCDD) levels between the hair and serum samples (p < 0.05). Flue gas (which is an external source) was identified as the primary source of PCDD/Fs in human hair. Blood and flue gas were accountable for, on average, 37% and 61% of the PCDD/Fs in hair, respectively.

[Liver and Kidney Function of E-waste Dismantling Workers and Potential Influencing Factors].

High levels of exposure to heavy metals and persistent organic pollutants (POPs) by e-waste dismantling workers has attracted increasing attention, but the health conditions of the workers are seldom reported. The liver and kidney functions of the workers were studied by comparing the blood indicators of the worker group with those of the control group. Moreover, factors affecting the liver and kidney functions, such as the sexuality, age, and working time, were identified using correlation analysis. The ratio of aspartate transaminase and alanine aminotransferase (AST/ALT) and the direct bilirubin (DBIL) of the workers were significantly lower than the control group but the abnormal rate of liver and kidney remained the same in both groups. The abnormal rates of liver and kidney were higher in men than in women. ALT, AST/ALT, and urea nitrogen (BUN) increased with age while creatinine (CREA) increased with working time. The factors of liver and kidney damage caused by POPs and DBIL can be used as the indicators of the damage caused by multi-factors.

Urinary metabolites of phosphate flame retardants in workers occupied with e-waste recycling and incineration.

Urinary metabolites of phosphate flame retardants (PFRs) were determined in workers from an electronic waste (e-waste) recycling site and an incineration plant, in order to assess the PFR exposure risks of workers occupied with e-waste recycling and incineration. Bis(2-chloroethyl) phosphate (BCEP), bis(1,3-dichloro-2-propyl) phosphate (BDCIPP), and diphenyl phosphate (DPHP) were the most frequently detected chemicals (82-93%). The median concentrations of BCEP, BDCIPP, and DPHP were 1.77, 0.23, and 0.70 ng/mL, and 1.44, 0.22, and 0.11 ng/mL in samples from the e-waste site and the incineration plant, respectively. Dibutyl phosphate (DBP) was detected in all samples from the incineration plant, with a median level of 0.30 ng/mL. The concentrations of BDCIPP (r = -0.31, p < 0.05) were significantly correlated with the occupational exposure time rather than age in workers from the e-waste site. Negative and significant correlations were also observed between the concentrations of BCEP (r = -0.42, p < 0.05), BDCIPP (r = -0.37, p < 0.05), and DPHP (r = -0.37, p < 0.05) and occupational exposure time rather than age in workers from the incineration plant. No gender differences were observed in levels of PFR metabolites in urine samples (p > 0.05). Concentrations of BDCIPP in female were significantly correlated with occupational exposure time (r = -0.507, p < 0.01). Concentrations of PFR metabolites in male were not significantly correlated with age or occupational exposure time (p > 0.05). Overall, the workers with occupational exposure to PFRs had different profiles of urinary PFR metabolites. The age, occupational exposure time, and gender seemed not to be main factors mediating the exposure to PFRs for workers occupied with e-waste recycling and incineration.

Disruption of thyroid hormone (TH) levels and TH-regulated gene expression by polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), and hydroxylated PCBs in e-waste recycling workers.

Polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) are the primary toxicants released by electronic waste (e-waste) recycling, but their adverse effects on people working in e-waste recycling or living near e-waste sites have not been studied well. In the present study, the serum concentrations of PBDEs, PCBs, and hydroxylated PCBs, the circulating levels of thyroid hormones (THs), and the mRNA levels of seven TH-regulated genes in peripheral blood leukocytes of e-waste recycling workers were analyzed. The associations of the hormone levels and gene expression with the exposure to these contaminants were examined using multiple linear regression models. There were nearly no associations of the TH levels with PCBs and hydroxylated PCBs, whereas elevated hormone (T4 and T3) levels were associated with certain lower-brominated BDEs. While not statistically significant, we did observe a negative association between highly brominated PBDE congeners and thyroid-stimulating hormone (TSH) levels in the e-waste workers. The TH-regulated gene expression was more significantly associated with the organohalogen compounds (OHCs) than the TH levels in these workers. The TH-regulated gene expression was significantly associated with certain PCB and hydroxylated PCB congeners. However, the expression of most target genes was suppressed by PBDEs (mostly highly brominated congeners). This is the first evidence of alterations in TH-regulated gene expression in humans exposed to OHCs. Our findings indicated that OHCs may interfere with TH signaling and/or exert TH-like effects, leading to alterations in related gene expression in humans. Further research is needed to investigate the mechanisms of action and associated biological consequences of the gene expression disruption by OHCs.

Organic contaminants and heavy metals in indoor dust from e-waste recycling, rural, and urban areas in South China: Spatial characteristics and implications for human exposure.

The concentrations of several organic contaminants (OCs) and heavy metals were measured in indoor dust from e-waste recycling, rural, and urban areas in South China to illustrate the spatial characteristics of these pollutants and to further evaluate human exposure risks. The median concentrations of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), decabromodiphenyl ethane (DBDPE), and dechlorane plus (DPs) were 38.6-3560, 2360-30,100, 665-2720, and 19.5-1860ng/g, while the median concentrations of Cd, Pb, Cu, Cr, and Zn were 2.46-40.4, 206-1380, 217- 1200, 25.3-134, and 176-212µg/g in indoor dust. The levels of all pollutants, except Zn, in dust from the e-waste recycling area were significantly higher than those from the other areas. Cd, Pb, and most OCs exhibited similar pollution patterns in the three areas, indicating that e-waste recycling activities are the major pollution source. In contrast, Cu, Cr, Zn, and penta-BDE are likely derived from household products in the rural and urban areas. The highest estimated daily intakes (EDIs) of PCBs, PBDEs, DBDPE, and DPs were 0.15-163, 3.97-1470, 1.26-169, and 0.11-134ng/kg bw/day for toddlers and adults. The highest EDIs of BDE 209 and Pb in toddlers in the e-waste recycling area were 16% and 18 times higher than the reference doses, indicating the high exposure risk of these pollutants in the e-waste recycling area.

Dichloro-diphenyl-trichloroethanes (DDTs) in human hair and serum in rural and urban areas in South China.

Human hair has been employed as a biomarker for exposure to persistent organic pollutants (POPs), but information on the source of dichloro-diphenyl-trichloroethane (DDT) and its metabolites in hair is limited. The present study investigated the contamination of DDTs in human hair from a rural area and an urban area of South China and compared with those in human serum and indoor dust. The concentrations of ∑DDTs ranged from 2.30 to 489ng/g, with a median of 21.8ng/g in human hair. The ∑DDT concentrations (median=40.8ng/g) in female hair were significantly higher than those in male hair (median=20.6ng/g). There were significantly positive correlations between the concentrations of DDTs and ages in both the female and male hair, but the age-dependence for DDTs in serum was less significant. The profile of DDT analogues in female hair, differing from that in the male hair, was more similar to that in the indoor dust, suggesting a more important role of exogenous exposure in female hair. We estimated that exogenous source is responsible for approximately 11% and 20% of the burden of DDTs in the male and female hair, respectively. Adjusted multiple linear regression model showed significantly positive association between the p,p'-DDE concentrations in the paired hair and serum samples, indicating that endogenous origins are the primary sources of DDTs in the hair of the residents in the study areas. Our findings demonstrated that human hair is a reliable biomarker for body burden of DDTs and can be used in epidemiology research and retrospective assessment of DDT exposure.

Analysis of human hair to assess exposure to organophosphate flame retardants: Influence of hair segments and gender differences.

Hair is a promising, non-invasive, human biomonitoring matrix that can provide insight into retrospective and integral exposure to organic pollutants. In the present study, we measured the concentrations of organophosphate flame retardants (PFRs) in hair and serum samples from university students in Guangzhou, China, and compared the PFR concentrations in the female hair segments using paired distal (5~10cm from the root) and proximal (0~5cm from the root) samples. PFRs were not detected in the serum samples. All PFRs except tricresyl phosphate (TMPP) and tri-n-propyl phosphate (TPP) were detected in more than half of all hair samples. The concentrations of total PFRs varied from 10.1 to 604ng/g, with a median of 148ng/g. Tris(chloroisopropyl) phosphate (TCIPP) and tri(2-ethylexyl) phosphate (TEHP) were the predominant PFRs in hair. The concentrations of most PFRs in the distal segments were 1.5~8.6 times higher than those in the proximal segments of the hair (t-test, p<0.05), which may be due to the longer exposure time of the distal segments to external sources. The values of log (PFR concentrations-distal/PFR concentrations-proximal) were positively and significantly correlated with log KOA of PFRs (p<0.05, r=0.68), indicating that PFRs with a higher log KOA tend to accumulate in hair at a higher rate than PFRs with a lower log KOA. Using combined segments of female hair, significantly higher PFR concentrations were observed in female hair than in male hair. In contrast, female hair exhibited significantly lower PFR concentrations than male hair when using the same hair position for both genders (0-5cm from the scalp). The controversial results regarding gender differences in PFRs in hair highlight the importance of segmental analysis when using hair as an indicator of human exposure to PFRs.