Integration of metabolomics and proteomics reveals the underlying hepatotoxic mechanism of perfluorooctane sulfonate (PFOS) and 6:2 chlorinated polyfluoroalkyl ether sulfonic acid (6:2 Cl-PFESA) in primary human hepatocytes.

Perfluorooctane sulfonate (PFOS) and its alternative 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA) are ubiquitous in various environmental and human samples. They have been reported to have hepatotoxicity effects, but the potential mechanisms remain unclear. Herein, we integrated metabolomics and proteomics analysis to investigate the altered profiles in metabolite and protein levels in primary human hepatocytes (PHH) exposed to 6:2 Cl-PFESA and PFOS at human exposure relevant concentrations. Our results showed that 6:2 Cl-PFESA exhibited higher perturbation effects on cell viability, metabolome and proteome than PFOS. Integration of metabolomics and proteomics revealed that the alteration of glycerophospholipid metabolism was the critical pathway of 6:2 Cl-PFESA and PFOS-induced lipid metabolism disorder in primary human hepatocytes. Interestingly, 6:2 Cl-PFESA-induced cellular metabolic process disorder was associated with the cellular membrane-bounded signaling pathway, while PFOS was associated with the intracellular transport process. Moreover, the disruption effects of 6:2 Cl-PFESA were also involved in inositol phosphate metabolism and phosphatidylinositol signaling system. Overall, this study provided comprehensive insights into the hepatic lipid toxicity mechanisms of 6:2 Cl-PFESA and PFOS in human primary hepatocytes.

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accurate cell segmentation of the MxIF images is an essential step. We propose a deep learning pipeline to train a Mask R-CNN model (deep network) for cell segmentation using nuclear (DAPI) and membrane (Na+K+ATPase) stained images. We used two-stage domain adaptation by first using a weakly labeled dataset followed by fine-tuning with a manually annotated dataset. We validated our method against manual annotations on three different datasets. Our method yields comparable results to the multi-observer agreement on an ovarian cancer dataset and improves on state-of-the-art performance on a publicly available dataset of mouse pancreatic tissues. Our proposed method, using a weakly labeled dataset for pre-training, showed superior performance in all of our experiments. When using smaller training sample sizes for fine-tuning, the proposed method provided comparable performance to that obtained using much larger training sample sizes. Our results demonstrate that using two-stage domain adaptation with a weakly labeled dataset can effectively boost system performance, especially when using a small training sample size. We deployed the model as a plug-in to CellProfiler, a widely used software platform for cellular image analysis.

The Melastoma dodecandrum genome and the evolution of Myrtales.

Melastomataceae has abundant morphological diversity with high economic and ornamental merit in Myrtales. The phylogenetic position of Myrtales is still contested. Here, we report the chromosome-level genome assembly of Melastoma dodecandrum in Melastomataceae. The assembled genome size is 299.81 Mb with a contig N50 value of 3.00 Mb. Genome evolution analysis indicated that M. dodecandrum, Eucalyptus grandis, and Punica granatum were clustered into a clade of Myrtales and formed a sister group with the ancestor of fabids and malvids. We found that M. dodecandrum experienced four whole-genome polyploidization events: the ancient event was shared with most eudicots, one event was shared with Myrtales, and the other two events were unique to M. dodecandrum. Moreover, we identified MADS-box genes and found that the AP1-like genes expanded, and AP3-like genes might have undergone subfunctionalization. The SUAR63-like genes and AG-like genes showed different expression patterns in stamens, which may be associated with heteranthery. In addition, we found that LAZY1-like genes were involved in the negative regulation of stem branching development, which may be related to its creeping features. Our study sheds new light on the evolution of Melastomataceae and Myrtales, which provides a comprehensive genetic resource for future research.

Oridonin induces ferroptosis by inhibiting gamma-glutamyl cycle in TE1 cells.

Oridonin (Ori) is a natural tetracyclic diterpenoid active compound with excellent antitumor activity, but the mechanism of Ori on esophageal cancer cell, TE1, remains unclear. In this study, we examined the levels of intracellular iron, malondialdehyde, and reactive oxygen species after Ori treatment, while interfering with the effects of Ori with ferroptosis inhibitor, demonstrating that Ori's inhibition of TE1 cell proliferation is associated with ferroptosis. To understand the molecular mechanism of Ori, we performed UPLC-MS/MS metabolomics profiling on TE1 cells, which show that gamma-glutamyl amino acids (gamma-glutamylleucine, gamma-glutamylvaline), 5-oxoproline, glutamate, GSH, and GSSG are changed significantly after Ori treatment. Meanwhile, the activity of gamma-glutamyl transpeptidase 1 (GGT1) decreased. This revealed that Ori inhibited the gamma-glutamyl cycle in TE1 cells. Furthermore, we found that Ori can covalently bind to cysteine to form the conjugate oridonin-cysteine (Ori-Cys), resulting in the inhibition of glutathione synthesis, which is consistent with the decrease in the enzymatic activity of glutamate cysteine ligase catalytic subunit (GCLC). Eventually, the value of intracellular GSH/GSSG was reduced, and the enzymatic activity of the glutathione peroxidase 4 (GPX4) was significantly decreased. In conclusion, our experiments indicated that Ori can inhibit the gamma-glutamyl cycle, thereby inducing ferroptosis to exert anti-cancer activity.

Application of natural cotton fibers as an extraction sorbent for the detection of trans-resveratrol in adulterated peanut oils.

The current study develops an effective, convenient, low-cost, and environmentally friendly method for determining trans-resveratrol (TRA) in peanut oils, the unique proportion of peanut oil, by employing natural cotton fibers without any pretreatment as extraction sorbent and an in-syringe extraction device. The primary factors affecting the extraction recovery are optimized in detail. The condition of 200.0 mg of cotton fibers, six push-pull times, 2.0 mL of n-hexane as washing solvent and 2.0 mL of ethanol as desorption solvent is selected as the best. The linear range is demonstrated to be 10-1000 ng/g with a satisfactory correlation coefficient (R2 = 0.9995), while the limit of detection is calculated as 2.47 ng/g. In addition, the recoveries of TRA are obtained in the range of 93.8-104.4% with RSDs less than 5.5%. Finally, the developed method is successfully applied to determine TRA concentrations in commercial peanut oils and other edible oils.

TLR-4, TLR-5 and IRF4 are diagnostic markers of knee osteoarthritis in the middle-aged and elderly patients and related to disease activity and inflammatory factors.

Expression and diagnostic value of serum toll-like receptor-4 (TLR-4), Toll-like receptor-5 (TLR-5) and interferon regulatory factor 4 (IRF4) in middle-aged and elderly patients with knee osteoarthritis (KOA) and their correlation with Interleukin 1ß (IL-1ß), interleukin-6 (IL-6), matrix metalloproteinase-1 and tumor necrosis factor-α (TNF-α) were investigated. Sixty-eight middle-aged and elderly patients with KOA in Puyang Hospital of Traditional Chinese Medicine were selected as the study group and 49 healthy people receiving physical examination were the control group. Levels of serum TLR-4, TLR-5, IRF4, IL-1ß, IL-6, MMP-1 and TNF-α were measured by enzyme linked immunosorbent assay (ELISA). Correlation between the expression levels of serum TLR-4, TLR-5, IRF4 and K-L grades was determined by Spearman correlation analysis. The diagnostic efficacy of serum TLR-4, TLR-5 and IRF4 for KOA was analyzed by the receiver operator characteristics analysis (ROC). Expression of serum TLR-4, TLR-5 and IRF4 in the study group was significantly higher than those in the control group. The sensitivity and specificity of TLR-4 in the diagnosis of KOA were, respectively, 76.47 and 93.88%, those of TLR-5 were 73.29 and 87.76%, those of IRF4 were 72.06 and 95.92%, and those of TLR-4, TLR-5 and IRF4 were 94.12 and 97.96%. Expression of serum TLR-4, TLR-5 and IRF4 was significantly higher in the severe group than in the moderate group, and significantly higher in the moderate group than those the in mild group, and significantly higher in the mild group than those in the suspected mild group. Expression of TLR-4, TLR-5 and IRF4 in serum was positively correlated with the concentration of IL-1ß, IL-6, MMP-1 and TNF-α, respectively (P<0.001). The combined detection of TLR-4, TLR-5 and IRF4 can be used for early diagnosis of KOA, and they are positively correlated with IL-1ß and IL-6, MMP-1 and TNF-α.

Automatic cancer detection on digital histopathology images of mid-gland radical prostatectomy specimens.

Purpose: Automatic cancer detection on radical prostatectomy (RP) sections facilitates graphical and quantitative surgical pathology reporting, which can potentially benefit postsurgery follow-up care and treatment planning. It can also support imaging validation studies using a histologic reference standard and pathology research studies. This problem is challenging due to the large sizes of digital histopathology whole-mount whole-slide images (WSIs) of RP sections and staining variability across different WSIs. Approach: We proposed a calibration-free adaptive thresholding algorithm, which compensates for staining variability and yields consistent tissue component maps (TCMs) of the nuclei, lumina, and other tissues. We used and compared three machine learning methods for classifying each cancer versus noncancer region of interest (ROI) throughout each WSI: (1) conventional machine learning methods and 14 texture features extracted from TCMs, (2) transfer learning with pretrained AlexNet fine-tuned by TCM ROIs, and (3) transfer learning with pretrained AlexNet fine-tuned with raw image ROIs. Results: The three methods yielded areas under the receiver operating characteristic curve of 0.96, 0.98, and 0.98, respectively, in leave-one-patient-out cross validation using 1.3 million ROIs from 286 mid-gland whole-mount WSIs from 68 patients. Conclusion: Transfer learning with the use of TCMs demonstrated state-of-the-art overall performance and is more stable with respect to sample size across different tissue types. For the tissue types involving Gleason 5 (most aggressive) cancer, it achieved the best performance compared to the other tested methods. This tool can be translated to clinical workflow to assist graphical and quantitative pathology reporting for surgical specimens upon further multicenter validation.

Histologic tissue components provide major cues for machine learning-based prostate cancer detection and grading on prostatectomy specimens.

Automatically detecting and grading cancerous regions on radical prostatectomy (RP) sections facilitates graphical and quantitative pathology reporting, potentially benefitting post-surgery prognosis, recurrence prediction, and treatment planning after RP. Promising results for detecting and grading prostate cancer on digital histopathology images have been reported using machine learning techniques. However, the importance and applicability of those methods have not been fully investigated. We computed three-class tissue component maps (TCMs) from the images, where each pixel was labeled as nuclei, lumina, or other. We applied seven different machine learning approaches: three non-deep learning classifiers with features extracted from TCMs, and four deep learning, using transfer learning with the 1) TCMs, 2) nuclei maps, 3) lumina maps, and 4) raw images for cancer detection and grading on whole-mount RP tissue sections. We performed leave-one-patient-out cross-validation against expert annotations using 286 whole-slide images from 68 patients. For both cancer detection and grading, transfer learning using TCMs performed best. Transfer learning using nuclei maps yielded slightly inferior overall performance, but the best performance for classifying higher-grade cancer. This suggests that 3-class TCMs provide the major cues for cancer detection and grading primarily using nucleus features, which are the most important information for identifying higher-grade cancer.

Flavokawain A inhibits prostate cancer cells by inducing cell cycle arrest and cell apoptosis and regulating the glutamine metabolism pathway.

Flavokawain A (FKA), a major chalcone in kava extracts, has exhibited anti-proliferative and apoptotic effects in the prostate cancer. However, the molecular mechanism of FKA remains unclear. In this study, FKA induces cell apoptosis and cell cycle arrest in a G2M phase to prostate cancer cells. FKA interferes with tubulin polymerization and inhibits survivin expression in PC3 cells. Molecular docking simulation experiment finds that FKA can bind to colchicine binding sites that inhibit tubulin polymerization. FKA treatment regulates the glutamine metabolism pathway in PC3 cells by reducing intracellular glutamine, glutamic and proline. FKA treatment also decreases the GSH content by decreasing the activity of GSH synthetase (GSS) and increasing the activity of glutathione thiol transferase (GSTP1), which subsequently induces ROS production and PC3 cell apoptosis.

Quercetin overcomes colon cancer cells resistance to chemotherapy by inhibiting solute carrier family 1, member 5 transporter.

P-glycoprotein (P-gp)-mediated multidrug resistance (MDR) remains a significant impediment to the success of cancer chemotherapy. The natural flavonoid Quercetin (Que) has been reported to be able to inhibit P-gp-mediated MDR in various cancer cells. However, the MDR reversal effect of Que on human colon cancer cells and its mechanism at the metabolic level requires further clarification. This study was designed to provide a better understanding of the MDR reversal effect of Que. Our present results showed that 33 µM of Que significantly improved the cytotoxicity of doxorubicin (Dox) to P-gp-overexpressed SW620/Ad300 cells by proliferation and apoptpsis assay. Further mechanism studies demonstrated that Que inhibited the ATP-driven transport activity of P-gp, which in turn increased the intracellular accumulation of Dox. The metabolomics studies based on UPLC-MS/MS analysis revealed that Que could reverse the MDR by significantly blocking D-glutamine and D-glutamate metabolism, and the underlying mechanism is that Que down-regulated the expression of the glutamine transporter solute sarrier family 1, member 5 (SLC1A5) in SW620/Ad300 cells. This is the first time to report that Que was a SLC1A5 inhibitor, which could be served as a template compound to potentially develop novel P-gp-mediated MDR reversal modulators in cancer chemotherapy.

Cord blood Per- and polyfluoroalkyl substances, placental steroidogenic enzyme, and cord blood reproductive hormone.

BACKGROUND: Per- and polyfluoroalkyl substances (PFASs) are widely used in China, but little is known about the association between prenatal PFASs exposure and fetal reproductive development as well as its potential mechanism. OBJECTIVE: We investigated the effects of cord blood PFASs on fetal reproductive hormones and its potential mechanism in relation to steroidogenic enzymes. METHODS: Ten selected PFASs (n = 351) including PFOS, PFOA, PFBS, PFDA, PFDoA, PFHpA, PFHxS, PFNA, PFOSA, and PFUA, and two reproductive hormones estradiol (E2) (n = 351) and testosterone (T) (n = 349) were measured in 351 cord blood serum samples from a Chinese birth cohort between 2010 and 2013. Three steroidogenic enzymes including P450arom (n = 125), 3ß-HSD1 (n = 123), and 17ß-HSD1 (n = 116) were measured in 125 placental tissue samples. Linear regression tested the associations between cord blood PFASs and reproductive hormones in cord blood. Mediation analysis assessed the role of placental steroidogenic enzymes between cord blood PFASs and reproductive hormones. RESULTS: The positive associations between PFOA, PFHxS and E2 levels, PFOS, PFUA, PFNA and T levels, and PFOS, PFUA and T/E2 ratio were significant. PFUA, PFNA, PFDA, PFHxS, and ∑PFASs were associated with higher P450arom levels. PFHxS was also associated with increased 3ß-HSD1 and 17ß-HSD1 levels. These associations were more pronounced in females than males when stratified by gender. Furthermore, 17ß-HSD1 demonstrated mediating effects in the positive association between cord blood PFHxS and E2 levels in females. CONCLUSION: Our findings suggested the potential impacts of cord blood PFASs on fetal reproductive hormones, in which steroidogenic enzymes may play important roles. These associations were more pronounced in females than males.

Organophosphate and Pyrethroid Pesticide Exposures Measured before Conception and Associations with Time to Pregnancy in Chinese Couples Enrolled in the Shanghai Birth Cohort.

BACKGROUND: Pesticides have been associated with reproductive disorders, but there is limited research on pesticide exposures and human fertility. OBJECTIVE: We aimed to investigate the effects of preconception exposure to pesticides on time to pregnancy (TTP) and on infertility in a general population of couples planning to become pregnant in Shanghai, China. METHOD: A total of 615 women who were planning a pregnancy were enrolled before conception and were prospectively followed for 1 y to observe their TTP. Preconception pesticide exposures were assessed by measuring urinary metabolites of organophosphates (OPs) and pyrethroids (PYRs). Fecundability odds ratios (FORs) and odds ratios (ORs) of infertility were estimated using Cox and logistic regression models, respectively. All analyses were repeated after restricting the sample to nulliparous women (n=569). RESULTS: After adjusting for age, prepregnancy BMI, current smoking, education, annual household income, age at menarche, and two items from the Perceived Stress Scale (PSS-10), women in the highest quartile of diethylthiophosphate (DETP; an OP metabolite) had significantly longer TTP [adjusted FOR=0.68 (95% CI: 0.51, 0.92)] and increased infertility [adjusted OR=2.17 (95% CI: 1.19, 3.93)] compared with women in the lowest quartile. The highest versus lowest quartile of 3-phenoxybenzoic acid (3PBA; a PYR metabolite) was associated with longer TTP and infertility, with significant associations in nulliparous women [adjusted FOR=0.72 (95% CI: 0.53, 0.98); adjusted OR for infertility=2.03 (95% CI: 1.10, 3.74)]. CONCLUSION: Our study provides some of the first evidence that preconception OP and PYR exposures are associated with decreased fertility in Chinese couples. Given that OPs and PYRs are rapidly metabolized in humans, more studies are needed to confirm our findings. https://doi.org/10.1289/EHP2987.

Perfluoroalkyl and polyfluoroalkyl substances in matched parental and cord serum in Shandong, China.

BACKGROUND: Perfluoroalkyl and polyfluoroalkyl substances (PFASs) have been widely detected in different populations. However, limited data is available about exposure among family members. OBJECTIVES: To investigate the PFASs levels in parents and their newborns and to understand their correlation and health implications of in utero exposure to PFASs. METHODS: Ten PFASs were measured in matched parental and cord serum (N = 369 families) from a birth cohort in Shandong, one of the regions seriously polluted by PFASs in China. The correlation of PFASs levels within families was examined. A questionnaire survey on maternal factors and risk assessment using the hazard quotients (HQs) approach based on maternal PFASs levels was conducted. RESULTS: Within a family, the father had the highest levels of all PFASs. Among the 10 PFASs, perfluorooctanoic acid (PFOA) was the highest, with 103.38, 42.83, and 34.67 ng/ml in paternal, maternal and cord serum, respectively. PFASs levels were positively correlated among family members (r = 0.14-0.91, p < 0.01). Maternal age, body mass index (BMI); smoking history; and intake of fish, milk, poultry, vegetables and tap water were significantly related to PFASs concentrations in cord serum. Twenty-seven (7.3%) HQ values exceeded 1 for both PFOA and the sum of PFOA and perfluorooctane sulfonate (PFOS), indicating potential concern for developmental toxicity in the local newborns. CONCLUSIONS: PFASs, and especially PFOA levels were extremely high and positively correlated between parents, indicating heavy pollution in this region and common sources of exposure. In utero exposure to PFASs might pose potential concern for developmental toxicity in the local newborns.

An optical remote sensing model for estimating oil slick thickness based on two-beam interference theory.

Oil slick thickness was an important parameter for estimating oil spill volume. Two-beam interference theory could be used to interpret the behavior of reflected and refracted light in oil slick. A quantitative relationship between thickness and spectral reflectance of oil slick could be established based on this theory. Some parameters have the properties of numerical oscillation and can be ignored in practical application. In addition, numerical approximation results showed that two parameters of the relationship were closely related to the spectral reflectance of background water and the thick oil slick. Therefore, a practical model for estimating oil slick thickness could be derived and proved to be consisted with theoretical relationship.