Long-term exposure of metamifop affects sex differentiation and reproductive system of zebrafish (Danio rerio).

The extensive use of herbicide metamifop (MET) in rice fields for weeds control will inevitably lead to its entering into water environments and threaten the aquatic organisms. Previous researches have demonstrated that sublethal exposure of MET significantly affected zebrafish development. Yet the long-term toxicological impacts of MET on aquatic life remains unknown. Herein, we investigated the potential effects of MET (5 and 50 µg/L) on zebrafish during an entire life cycle. Since the expression level of male sex differentiation-related gene dmrt1 and sex hormone synthesis-related gene cyp19a1b were significantly changed after 50 µg/L MET exposure for only 7 days, indicators related to sex differentiation and reproductive system were further investigated. Results showed that the transcript of dmrt1 was inhibited, estradiol content increased and testosterone content decreased in zebrafish of both sexes after MET exposure at 45, 60 and 120 dpf. Histopathological sections showed that the proportions of mature germ cells in the gonads of male and female zebrafish (120 dpf) were significantly decreased. Moreover, males had elevated vitellogenin content while females did not after MET exposure; MET induced feminization in zebrafish, with the proportion of females significantly increased by 19.6% while that of males significantly decreased by 13.2% at 120 dpf. These results suggested that MET interfered with the expression levels of gonad development related-genes, disrupted sex hormone balance, and affected sex differentiation and reproductive system of female and male zebrafish, implying it might have potential endocrine disrupting effects after long-term exposure.

Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence.

The prediction of patient disease risk via computed tomography (CT) images and artificial intelligence techniques shows great potential. However, training a robust artificial intelligence model typically requires large-scale data support. In practice, the collection of medical data faces obstacles related to privacy protection. Therefore, the present study aims to establish a robust federated learning model to overcome the data island problem and identify high-risk patients with postoperative gastric cancer recurrence in a multicentre, cross-institution setting, thereby enabling robust treatment with significant value. In the present study, we collect data from four independent medical institutions for experimentation. The robust federated learning model algorithm yields area under the receiver operating characteristic curve (AUC) values of 0.710, 0.798, 0.809, and 0.869 across four data centres. Additionally, the effectiveness of the algorithm is evaluated, and both adaptive and common features are identified through analysis.

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors.

Purpose: To develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs). Methods: This retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS. Results: The CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874-0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850. Conclusions: The PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery.

Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features.

BACKGROUND: Axillary lymph node (ALN) metastasis is used to select treatment strategies and define the prognosis in breast cancer (BC) patients and is typically assessed using an invasive procedure. Noninvasive, simple, and reliable tools to accurately predict ALN status are desirable. We aimed to develop and validate a point-based scoring system (PSS) for stratifying the ALN metastasis risk of BC based on clinicopathological and quantitative MRI features and to explore its prognostic significance. METHODS: A total of 219 BC patients were evaluated. The clinicopathological and quantitative MRI features of the tumors were collected. A multivariate logistic regression analysis was used to create the PSS. The performance of the models was evaluated using receiver operating characteristic curves, and the area under the curve (AUC) of the models was calculated. Kaplan-Meier curves were used to analyze the survival outcomes. RESULTS: Clinical features, including the American Joint Committee on Cancer (AJCC) stage, T stage, human epidermal growth factor receptor-2, estrogen receptor, and quantitative MRI features, including maximum tumor diameter, Kep, Ve, and TTP, were identified as risk factors for ALN metastasis and were assigned scores for the PSS. The PSS achieved an AUC of 0.799 in the primary cohort and 0.713 in the validation cohort. The recurrence-free survival (RFS) and overall survival (OS) of the high-risk (> 19.5 points) groups were significantly shorter than those of the low-risk (≤ 19.5 points) groups in the PSS. CONCLUSION: PSS could predict the ALN metastasis risk of BC. A PSS greater than 19.5 was demonstrated to be a predictor of short RFS and OS.

Gemstone Spectral CT Virtual Noncontrast Images and Iodine Maps for the Characterization of Thyroid Lesions and Distinguishing Thyroid Papillary Carcinoma from Nodular Goiter.

Background: Gemstone spectral contrast-enhanced CT with virtual noncontrast (VNC) images and iodine maps can potentially reduce the number of required CT scans for thyroid lesions. However, data regarding the clinical utility of VNC images and iodine maps in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter are still limited. Purpose: To determine whether VNC images and iodine density could reliably aid in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter compared with true noncontrast (TNC) images. Methods: This retrospective study included patients with thyroid papillary carcinoma or nodular goiter who underwent TNC and contrast-enhanced gemstone spectral CT scans. The consistency of qualitative parameters, including intralesional calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis, between TNC and VNC images, was analyzed using the kappa statistic. TNC attenuation, VNC attenuation, absolute attenuation between TNC and VNC, and iodine density were compared between thyroid papillary carcinoma and nodular goiter by using Student's t-test. The diagnostic performance for distinguishing papillary carcinoma from nodular goiter was evaluated by using the area under the receiver operating characteristic curve (AUC) value, sensitivity, and specificity. Results: VNC and TNC imaging showed comparable performance in delineating calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis (all k > 0.75). Papillary carcinoma showed significantly lower absolute attenuation between VNC and TNC than nodular goiter (7.86 ± 6.74 vs. 13.43 ± 10.53, P=0.026), which was similarly observed for iodine density (31.45 ± 8.51 vs. 37.27 ± 10.34, P=0.016). The iodine density showed higher diagnostic performance (AUC = 0.727), accuracy (0.773 vs. 0.667), sensitivity (0.750 vs. 0.708), and specificity (0.786 vs. 0.643) than the absolute attenuation between TNC and VNC images (AUC = 0.683). Conclusions: VNC imaging, a promising substitute for TNC imaging, has comparable diagnostic efficacy for reliably characterizing thyroid lesions. Iodine density could be valuable for distinguishing thyroid papillary carcinoma from nodular goiter.

Online-Dynamic-Clustering-Based Soft Sensor for Industrial Semi-Supervised Data Streams.

In the era of big data, industrial process data are often generated rapidly in the form of streams. Thus, how to process such sequential and high-speed stream data in real time and provide critical quality variable predictions has become a critical issue for facilitating efficient process control and monitoring in the process industry. Traditionally, soft sensor models are usually built through offline batch learning, which remain unchanged during the online implementation phase. Once the process state changes, soft sensors built from historical data cannot provide accurate predictions. In practice, industrial process data streams often exhibit characteristics such as nonlinearity, time-varying behavior, and label scarcity, which pose great challenges for building high-performance soft sensor models. To address this issue, an online-dynamic-clustering-based soft sensor (ODCSS) is proposed for industrial semi-supervised data streams. The method achieves automatic generation and update of clusters and samples deletion through online dynamic clustering, thus enabling online dynamic identification of process states. Meanwhile, selective ensemble learning and just-in-time learning (JITL) are employed through an adaptive switching prediction strategy, which enables dealing with gradual and abrupt changes in process characteristics and thus alleviates model performance degradation caused by concept drift. In addition, semi-supervised learning is introduced to exploit the information of unlabeled samples and obtain high-confidence pseudo-labeled samples to expand the labeled training set. The proposed method can effectively deal with nonlinearity, time-variability, and label scarcity issues in the process data stream environment and thus enable reliable target variable predictions. The application results from two case studies show that the proposed ODCSS soft sensor approach is superior to conventional soft sensors in a semi-supervised data stream environment.

Transcriptome analysis reveals hepatotoxicity in zebrafish induced by cyhalofop­butyl.

Cyhalofop­butyl is a highly effective aryloxyphenoxypropionate herbicide and widely used for weed control in paddy fields. With the increasing residue of cyhalofop­butyl, it poses a threat to the survival of aquatic organisms. Here, we investigated the effect of cyhalofop­butyl on zebrafish to explore its potential hepatotoxic mechanism. The results showed that cyhalofop­butyl induced hepatocyte degeneration, vacuolation and necrosis of larvae after embryonic exposure for 4 days and caused liver atrophy after 5 days. Meanwhile, the activities of enzymes related to liver function were significantly increased by 0.2 mg/L cyhalofop­butyl and higher, such as alanine transaminase (ALT) and aspartate transaminase (AST). And the contents of triglyceride (TG) involved in lipid metabolism were significantly decreased by 0.4 mg/L cyhalofop-buty. The expression of genes related to liver development was also significantly down-regulated. Furthermore, transcriptome results showed that the pathways involved in metabolism, immune system and endocrine system were significantly impacted, which may be related to hepatoxicity. To sum up, the present study demonstrated the hepatoxicity caused by cyhalofop-buty and its underlying mechanism. The results may provide new insights for the risk of cyhalofop­butyl to aquatic organisms and new horizons for the pathogenesis of hepatotoxicity.

Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging to predict lymphovascular invasion and survival outcome in breast cancer.

BACKGROUND: Lymphovascular invasion (LVI) predicts a poor outcome of breast cancer (BC), but LVI can only be postoperatively diagnosed by histopathology. We aimed to determine whether quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can preoperatively predict LVI and clinical outcome of BC patients. METHODS: A total of 189 consecutive BC patients who underwent multiparametric MRI scans were retrospectively evaluated. Quantitative (Ktrans, Ve, Kep) and semiquantitative DCE-MRI parameters (W- in, W- out, TTP), and clinicopathological features were compared between LVI-positive and LVI-negative groups. All variables were calculated by using univariate logistic regression analysis to determine the predictors for LVI. Multivariate logistic regression was used to build a combined-predicted model for LVI-positive status. Receiver operating characteristic (ROC) curves evaluated the diagnostic efficiency of the model and Kaplan-Meier curves showed the relationships with the clinical outcomes. Multivariate analyses with a Cox proportional hazard model were used to analyze the hazard ratio (HR) for recurrence-free survival (RFS) and overall survival (OS). RESULTS: LVI-positive patients had a higher Kep value than LVI-negative patients (0.92 ± 0.30 vs. 0.81 ± 0.23, P = 0.012). N2 stage [odds ratio (OR) = 3.75, P = 0.018], N3 stage (OR = 4.28, P = 0.044), and Kep value (OR = 5.52, P = 0.016) were associated with LVI positivity. The combined-predicted LVI model that incorporated the N stage and Kep yielded an accuracy of 0.735 and a specificity of 0.801. The median RFS was significantly different between the LVI-positive and LVI-negative groups (31.5 vs. 34.0 months, P = 0.010) and between the combined-predicted LVI-positive and LVI-negative groups (31.8 vs. 32.0 months, P = 0.007). The median OS was not significantly different between the LVI-positive and LVI-negative groups (41.5 vs. 44.0 months, P = 0.270) and between the combined-predicted LVI-positive and LVI-negative groups (42.8 vs. 43.5 months, P = 0.970). LVI status (HR = 2.40), N2 (HR = 3.35), and the combined-predicted LVI model (HR = 1.61) were independently associated with disease recurrence. CONCLUSION: The quantitative parameter of Kep could predict LVI. LVI status, N stage, and the combined-predicted LVI model were predictors of a poor RFS but not OS.

Life Cycle Exposure to Cyhalofop-Butyl Induced Reproductive Toxicity in Zebrafish.

Cyhalofop-butyl (CyB) is a herbicide widely used in paddy fields that may transfer to aquatic ecosystems and cause harm to aquatic organisms. In this study, zebrafish (Danio rerio) were exposed to CyB at environmental concentrations (0.1, 1 and 10 µg/L) throughout their adult life cycle, from embryo to sexual maturity. The effects of CyB on zebrafish growth and reproduction were studied. It was found that female spawning was inhibited, and adult male fertility decreased. In addition, we examined the expression of sex steroid hormones and genes related to the hypothalamus-pituitary-gonad-liver (HPGL) axis. After 150 days of exposure, the hormone balance in zebrafish was disturbed, and the concentrations of 17ß-estradiol (E2) and vitellogenin (VTG) were decreased. Changes in sex hormone were regulated by the expression of genes related to the HPGL axis. These results confirmed that long-term exposure to CyB at environmental concentrations can damage the reproductive capacity of zebrafish by disrupting the transcription of genes related to the HPGL axis. Overall, these data may provide a new understanding of the reproductive toxicity of long-term exposure to CyB in zebrafish parents and offspring.

Online prediction of total sugar content and optimal control of glucose feed rate during chlortetracycline fermentation based on soft sensor modeling.

In the process of chlortetracycline (CTC) fermentation, no instrument can be used to measure the total sugar content of the fermentation broth online due to its high viscosity and large amount of impurities, so it is difficult to realize the optimal control of glucose feed rate in the fermentation process. In order to solve this intractable problem, the relationship between on-line measurable parameters and total sugar content (One of the parameters that are difficult to measure online) in fermentation tank is deeply analyzed, and a new soft sensor model of total sugar content in fermentation tank and a new optimal control method of glucose feed rate are proposed in this paper. By selecting measurable variables of fermentation tank, determining different fermentation stages, constructing recursive fuzzy neural network (RFNN) and applying network rolling training method, an online soft sensor model of total sugar content is established. Based on the field multi-batch data, the change trend of the amount of glucose feed required at each fermentation stage is divided, and the online prediction of total sugar content and the optimal control strategy of glucose feed rate are realized by using the inference algorithm of expert experience regulation rules and soft sensor model of total sugar content. The experiment results in the real field demonstrate that the proposed scheme can effectively predict the total sugar content of fermentation broth online, optimize the control of glucose feed rate during fermentation process, reduce production cost and meet the requirements of production technology.

Parental exposure to propiconazole at environmentally relevant concentrations induces thyroid and metabolism disruption in zebrafish (Danio rerio) offspring: An in vivo, in silico and in vitro study.

Propiconazole is used against fungal growth in agriculture and is released into the environment, but is a potential health threat to aquatic organisms. Propiconazole induces a generational effect on zebrafish, although the toxic mechanisms involved have not been described. The aim of this study was to investigate the potential mechanisms of abnormal offspring development after propiconazole exposure in zebrafish parents. Zebrafish were exposed to propiconazole at environmentally realistic concentrations (0.1, 5, and 250 µg/L) for 100 days and their offspring were grown in control solution for further study. Heart rate, hatching rate, and body length of hatched offspring were reduced. An increase in triiodothyronine (T3) content and the T3/T4 (tetraiodothyronine) ratio was observed, indicating disruption of thyroid hormones. Increased protein level of transthyretin (TTR) in vivo was consistent with the in silico molecular docking results and T4 competitive binding in vitro assay, suggests higher binding affinity between propiconazole and TTR, more than with T4. Increased expression of genes related to the hypothalamus-pituitary-thyroid (HPT) axis and altered metabolite levels may have affected offspring development. These findings emphasizes that propiconazole, even on indirect exposure, represents health and environmental risk that should not be ignored.

Distinguishing COVID-19 From Influenza Pneumonia in the Early Stage Through CT Imaging and Clinical Features.

Background: Both coronavirus disease 2019 (COVID-19) and influenza pneumonia are highly contagious and present with similar symptoms. We aimed to identify differences in CT imaging and clinical features between COVID-19 and influenza pneumonia in the early stage and to identify the most valuable features in the differential diagnosis. Methods: Seventy-three patients with COVID-19 confirmed by real-time reverse transcription-polymerase chain reaction (RT-PCR) and 48 patients with influenza pneumonia confirmed by direct/indirect immunofluorescence antibody staining or RT-PCR were retrospectively reviewed. Clinical data including course of disease, age, sex, body temperature, clinical symptoms, total white blood cell (WBC) count, lymphocyte count, lymphocyte ratio, neutrophil count, neutrophil ratio, and C-reactive protein, as well as 22 qualitative and 25 numerical imaging features from non-contrast-enhanced chest CT images were obtained and compared between the COVID-19 and influenza pneumonia groups. Correlation tests between feature metrics and diagnosis outcomes were assessed. The diagnostic performance of each feature in differentiating COVID-19 from influenza pneumonia was also evaluated. Results: Seventy-three COVID-19 patients including 41 male and 32 female with mean age of 41.9 ± 14.1 and 48 influenza pneumonia patients including 30 male and 18 female with mean age of 40.4 ± 27.3 were reviewed. Temperature, WBC count, crazy paving pattern, pure GGO in peripheral area, pure GGO, lesion sizes (1-3 cm), emphysema, and pleural traction were significantly independent associated with COVID-19. The AUC of clinical-based model on the combination of temperature and WBC count is 0.880 (95% CI: 0.819-0.940). The AUC of radiological-based model on the combination of crazy paving pattern, pure GGO in peripheral area, pure GGO, lesion sizes (1-3 cm), emphysema, and pleural traction is 0.957 (95% CI: 0.924-0.989). The AUC of combined model based on the combination of clinical and radiological is 0.991 (95% CI: 0.980-0.999). Conclusion: COVID-19 can be distinguished from influenza pneumonia based on CT imaging and clinical features, with the highest AUC of 0.991, of which crazy-paving pattern and WBC count play most important role in the differential diagnosis.

Exposure to difenoconazole induces reproductive toxicity in zebrafish by interfering with gamete maturation and reproductive behavior.

Difenoconazole (DCZ) is a triazole fungicide that negatively affects aquatic organisms and humans. However, data regarding the reproductive toxicity of DCZ are insufficient. In this study, we used zebrafish (from 2 h post-fertilization [hpf] to adulthood) as a model to evaluate whether DCZ at environmentally relevant concentrations (0.1, 1.0, and 10.0 µg/L) induces reproductive toxicity. After exposure to DCZ, egg production and fertilization rates were reduced by 1.0 and 10.0 µg/L. A significant decrease in gamete frequency (late vitellogenic oocytes and spermatozoa) was observed at 10.0 µg/L. The concentrations of 17ß-estradiol (E2), testosterone (T), and vitellogenin (VTG) were disrupted in females and males by 1.0 and 10.0 µg/L. Exposure to 10.0 µg/L DCZ significantly inhibited the contact time between female and male fish, which was mainly achieved by affecting male fish. The transcription of genes involved in the hypothalamus-pituitary-gonad (HPG) axis was significantly changed after treatment with DCZ. Overall, these data show that the endocrine-disrupting effect of DCZ on the zebrafish HPG axis inhibited gamete maturation and disrupted reproductive behavior, reducing fertility.

Readout-Segmented Echo-Planar Diffusion-Weighted MR Imaging Improves the Differentiation of Breast Cancer Receptor Statuses Compared With Conventional Diffusion-Weighted Imaging.

BACKGROUND: Readout-segmented echo-planar diffusion-weighted imaging (RS-EPI) can improve image quality and signal-to-noise ratio, the resulting apparent diffusion coefficient (ADC) value acts as a more sensitive biomarker to characterize tumors. However, data regarding the differentiation of breast cancer (BC) receptor statuses using RS-EPI are limited. PURPOSE: To determine whether RS-EPI improves the differentiation of receptor statuses compared with conventional single-shot (SS) EPI in breast MRI. STUDY TYPE: Retrospective. POPULATION: A total of 151 BC women with the mean age of 50.6 years. FIELD STRENGTH/SEQUENCE: A 3 T/ RS-EPI and SS-EPI. ASSESSMENT: The ADCs of the lesion and normal background tissue from the two sequences were collected by two radiologists with 15 years of experience working of breast MRI (M.H.Z. and X.F.C.), and a normalized ADC was calculated by dividing the mean ADC value of the lesion by the mean ADC value of the normal background tissue. STATISTICAL TESTS: Agreement between the ADC measurements from the two sequences was assessed using the Pearson correlation coefficient and Bland-Altman plots. One-way analysis of variance, Kruskal-Wallis test, and median difference were used to compare the ADC measurements for all lesions and different receptor statuses. A P value less than 0.05 indicated a significant result. RESULTS: The ADC measurements of all lesions and normal background tissues were significantly higher on RS-EPI than on SS-EPI (1.82 ± 0.33 vs. 1.55 ± 0.30 and 0.83 ± 0.11 vs. 0.79 ± 0.10). The normalized ADC was lower on RS-EPI than on SS-EPI (0.47 ± 0.11 vs. 0.53 ± 0.12, a median difference of -0.04 [95% CI: -0.256 to 0.111]). For both diffusion methods, only the ADC measurement of RS-EPI was higher for human epidermal growth factor receptor-2 (HER-2)-positive tumors than for HER-2-negative tumors (0.87 ± 0.10 vs. 0.81 ± 0.11), and this measurement was associated with HER-2 positive status (adjusted odds ratio [OR] = 654.4); however, similar results were not observed for the ADC measurement of SS-EPI (0.80 ± 0.10 vs. 0.78 ± 0.11 with P = 0.199 and adjusted OR = 0.21 with P = 0.464, respectively). DATA CONCLUSION: RS-EPI can improve the distinction between HER-2-positive and HER-2-negative breast cancer, complementing the clinical application of diffusion imaging. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Tralopyril affects locomotor activity of zebrafish (Danio rerio) by impairing tail muscle tissue, the nervous system, and energy metabolism.

Tralopyril (TP), an antifouling biocide, is widely used to prevent heavy biofouling, and can have potential risks to aquatic organisms. In this study, the effect of TP on locomotor activity and related mechanisms were evaluated in zebrafish (Danio rerio) larvae. TP significantly reduced locomotor activity after 168 -h exposure. Adverse modifications in tail muscle tissue, the nervous system, and energy metabolism were also observed in larvae. TP caused thinning of the muscle bundle in the tail of larvae. In conjunction with the metabolomics results, changes in dopamine (DA) and acetylcholine (ACh), acetylcholinesterase (AChE) activity, and the expression of genes involved in neurodevelopment, indicate that TP may disrupt the nervous system in zebrafish larvae. The change in metabolites (e.g., glucose 6-phosphate, cis-Aconitic acid, acetoacetyl-CoA, coenzyme-A and 3-Oxohexanoyl-CoA) involved in carbohydrate and lipid metabolism indicates that TP may disrupt energy metabolism. TP exposure may inhibit the locomotor activity of zebrafish larvae by impairing tail muscle tissue, the nervous system, and energy metabolism.

Pseudo-Labeling Optimization Based Ensemble Semi-Supervised Soft Sensor in the Process Industry.

Nowadays, soft sensor techniques have become promising solutions for enabling real-time estimation of difficult-to-measure quality variables in industrial processes. However, labeled data are often scarce in many real-world applications, which poses a significant challenge when building accurate soft sensor models. Therefore, this paper proposes a novel semi-supervised soft sensor method, referred to as ensemble semi-supervised negative correlation learning extreme learning machine (EnSSNCLELM), for industrial processes with limited labeled data. First, an improved supervised regression algorithm called NCLELM is developed, by integrating the philosophy of negative correlation learning into extreme learning machine (ELM). Then, with NCLELM as the base learning technique, a multi-learner pseudo-labeling optimization approach is proposed, by converting the estimation of pseudo labels as an explicit optimization problem, in order to obtain high-confidence pseudo-labeled data. Furthermore, a set of diverse semi-supervised NCLELM models (SSNCLELM) are developed from different enlarged labeled sets, which are obtained by combining the labeled and pseudo-labeled training data. Finally, those SSNCLELM models whose prediction accuracies were not worse than their supervised counterparts were combined using a stacking strategy. The proposed method can not only exploit both labeled and unlabeled data, but also combine the merits of semi-supervised and ensemble learning paradigms, thereby providing superior predictions over traditional supervised and semi-supervised soft sensor methods. The effectiveness and superiority of the proposed method were demonstrated through two chemical applications.

Primary aortic intimal sarcoma masquerading as intramural hematoma.

Primary aortic intimal sarcoma is a very rare disease and most patients present with features similar to those of atherosclerotic plaque and thrombus; however, primary aortic intimal sarcoma presents with features similar to those of intramural hematoma (IMH) on CT imaging and clinical presentation had never been previously reported. Here we report a case involving a 49-year-old woman with primary aortic intimal sarcoma masquerading as IMH on radiological images and clinical presentation. We also discuss some of the diagnostic pitfalls and hope that these diagnostic pitfalls will be very useful for clinicians.

Effects of sublethal concentration of metamifop on hepatic lipid metabolism in adult zebrafish (Danio rerio).

Metamifop (MET) is an effective herbicide that has been extensively used in paddy fields. Previous research demonstrated that MET was highly toxic to zebrafish embryos, and this threat has caused great concern; moreover, 0.40 mg/L MET elevated the hepatosomatic index (HSI) in adult zebrafish without lethal effect after 21 d of exposure. In this study, we further determined the detailed impacts of MET on adult zebrafish at sublethal concentrations (0.025, 0.10 and 0.40 mg/L). We found that 0.40 mg/L MET caused liver injury by increasing the activity of aspartate aminotransferase and alanine aminotransferase in plasma, the content of interleukin-1ß, IL-6, tumor necrosis factor-α, and mRNA expression level of genes associated with inflammatory response in liver of adult zebrafish. The hepatic triglyceride (TG), free fatty acid and fatty acid synthase levels were significantly elevated in 0.40 mg/L MET-treated group (1.55-, 2.20- and 2.30-fold, respectively), and the transcript of lipid accumulation-related genes (fabp10, fas, acc, chrebp, dagt2 and agpat4) were upregulated. Meanwhile, the total cholesterol content was decreased by 0.48-fold, bile acid level was increased by 2.44-fold, and levels of cholesterol metabolism-related genes (apoa-1a, hmgcra, cyp51, dhcr7 and cyp7a1) were increased, suggesting cholesterol metabolism disorder occurred in zebrafish. Furthermore, analysis of lipidomics revealed that 0.40 mg/L MET significantly increased the abundance of 91 lipids, which mainly belonged to TG lipid class and were enriched in pathways of glycerolipid metabolism, cholesterol metabolism, etc. These results suggested that MET exposure at sublethal concentrations would induce hepatic inflammation and lipid metabolism disorders in adult zebrafish.

Environmentally relevant concentrations of tralopyril affect carbohydrate metabolism and lipid metabolism of zebrafish (Danio rerio) by disrupting mitochondrial function.

Tralopyril (TP), an antifouling biocide, is widely used to prevent heavy biofouling, and can have potential risks to aquatic organisms. However, there is little information available on the toxicity of tralopyril to aquatic organisms. In this study, the effect of TP on carbohydrate and lipid metabolism, and related mechanisms were evaluated in zebrafish (Danio rerio) larvae. Adverse modifications in carbohydrate metabolism were observed in larvae: hexokinase (HK) activity, succinate dehydrogenase (SDH) activity, and adenosine triphosphate (ATP) content were significantly decreased; and transcript expression of genes (GK, HK1, and PCK1) was also significantly changed. Changes of TG content, FAS activity and transcript expression of genes (ACO, ehhadh, and fas) indicate that TP disrupt lipid metabolism in zebrafish larvae. The change in expression of genes (ndufs4, Sdhα, and uqcrc2) involved in the mitochondrial respiratory complexes, and genes (polg1 and tk2) involved in the mitochondrial DNA replication and transcription indicates that these adverse effects on carbohydrate and lipid metabolism are caused by mitochondrial dysfunction.

Bioaccumulation, Metabolism and the Toxic Effects of Chlorfenapyr in Zebrafish (Danio rerio).

Chlorfenapyr is widely used as an insecticide/miticide. Tralopyril, the active metabolite of chlorfenapyr, is used as an antifouling biocide in antifouling systems, and negatively affects aquatic environments. However, it is unclear whether tralopyril is a metabolite of chlorfenapyr in aquatic vertebrates, and there is little data on the bioaccumulation and toxicity of chlorfenapyr to aquatic vertebrates. In this study, the bioaccumulation and elimination of chlorfenapyr in zebrafish were assessed, and tralopyril, the active metabolite of chlorfenapyr, was determined. The effects of chronic exposure to chlorfenapyr on zebrafish liver and brain oxidative damage, apoptosis, immune response, and metabolome were investigated. These results showed that chlorfenapyr has a high bioaccumulation in zebrafish, with bioaccumulation factors of 864.6 and 1321.9 after exposure to 1.0 and 10 µg/L chlorfenapyr for 21 days, respectively. Chlorfenapyr at these concentrations also rapidly accumulated in zebrafish, reaching 615.5 and 10336 µg/kg on the second and third days of exposure, respectively. Chlorfenapyr was degraded to tralopyril in zebrafish; therefore, both chlorfenapyr and tralopyril should be considered when evaluating the risk of chlorfenapyr to aquatic organisms. In addition, chronic exposure caused oxidative damage, apoptosis, and immune disorders in zebrafish liver. Chronic exposure also altered the levels of endogenous metabolites in liver and brain. After 9 days of depuration, some indicators of oxidative damage, apoptosis, and immunity returned to normal levels, but the concentration of endogenous metabolites in zebrafish liver was still altered. Overall, these results provide useful information for evaluating the toxicity and environmental fate of chlorfenapyr in aquatic vertebrates.