Fine mapping and analysis of candidate genes for qBT2 and qBT7.2 locus controlling bolting time in radish (Raphanus sativus L.).

KEY MESSAGE: Two major QTLs for bolting time in radish were mapped to chromosome 02 and 07 in a 0.37 Mb and 0. 52 Mb interval, RsFLC1 and RsFLC2 is the critical genes. Radish (Raphanus sativus L.) is an important vegetable crop of Cruciferae. The premature bolting and flowering reduces the yield and quality of the fleshy root of radish. However, the molecular mechanism underlying bolting and flowering in radish remains unknown. In YZH (early bolting) × XHT (late bolting) F2 population, a high-density genetic linkage map was constructed with genetic distance of 2497.74 cM and an average interval of 2.31 cM. A total of nine QTLs for bolting time and two QTLs for flowering time were detected. Three QTLs associated with bolting time in radish were identified by QTL-seq using radish GDE (early bolting) × GDL (late bolting) F2 population. Fine mapping narrowed down qBT2 and qBT7.2 to an 0.37 Mb and 0.52 Mb region on chromosome 02 and 07, respectively. RNA-seq and qRT-PCR analysis showed that RsFLC1 and RsFLC2 were the candidate gene for qBT7.2 and qBT2 locus, respectively. Subcellular localization exhibited that RsFLC1 and RsFLC2 were mainly expressed in the nucleus. A 1856-bp insertion in the first intron of RsFLC1 was responsible for bolting time. Overexpression of RsFLC2 in Arabidopsis was significantly delayed flowering. These findings will provide new insights into the exploring the molecular mechanism of late bolting and promote the marker-assisted selection for breeding late-bolting varieties in radish.

[Construction of integrated platform for emergency clinical scientific research based on big data].

OBJECTIVE: To explore clinical rules based on the big data of the emergency department of the Second Affiliated Hospital of Guangzhou Medical University, and to establish an integrated platform for clinical research in emergency, which was finally applied to clinical practice. METHODS: Based on the hospital information system (HIS), laboratory information system (LIS), emergency specialty system, picture archiving and communication systems (PACS) and electronic medical record system of the Second Affiliated Hospital of Guangzhou Medical University, the structural and unstructured information of patients in the emergency department from March 2019 to April 2022 was extracted. By means of extraction and fusion, normalization and desensitization quality control, the database was established. In addition, data were extracted from the database for adult patients with pre screening triage level III and below who underwent emergency visits from March 2019 to April 2022, such as demographic characteristics, vital signs during pre screening triage, diagnosis and treatment characteristics, diagnosis and grading, time indicators, and outcome indicators, independent risk factors for poor prognosis in patients were analyzed. RESULTS: (1) The data of 338 681 patients in the emergency department of the Second Affiliated Hospital of Guangzhou Medical University from March 2019 to April 2022 were extracted, including 15 modules, such as demographic information, triage information, visit information, green pass and rescue information, diagnosis information, medical record information, laboratory examination overview, laboratory information, examination information, microbiological information, medication information, treatment information, hospitalization information, chest pain management and stroke management. The database ensured data visualization and operability. (2) Total 140 868 patients with pre-examination and triage level III and below were recruited from the emergency department database. The gender, age, type of admission to the hospital, pulse, blood pressure, Glasgow coma scale (GCS) and other indicators of the patients were included. Taking emergency admission to operating room, emergency admission to intervention room, emergency admission to intensive care unit (ICU) or emergency death as poor prognosis, the poor prognosis prediction model for patients with pre-examination and triage level III and below was constructed. The receiver operator characteristic curve and forest map results showed that the model had good predictive efficiency and could be used in clinical practice to reduce the risk of insufficient emergency pre-examination and triage. CONCLUSIONS: The establishment of high-quality clinical database based on big data in emergency department is conducive to mining the clinical value of big data, assisting clinical decision-making, and improving the quality of clinical diagnosis and treatment.

Comprehensive assessment of the anterior segment in refraction corrected OCT based on multitask learning.

Anterior segment diseases are among the leading causes of irreversible blindness. However, a method capable of recognizing all important anterior segment structures for clinical diagnosis is lacking. By sharing the knowledge learned from each task, we proposed a fully automated multitask deep learning method that allows for simultaneous segmentation and quantification of all major anterior segment structures, including the iris, lens, cornea, as well as implantable collamer lens (ICL) and intraocular lens (IOL), and meanwhile for landmark detection of scleral spur and iris root in anterior segment OCT (AS-OCT) images. In addition, we proposed a refraction correction method to correct for the true geometry of the anterior segment distorted by light refraction during OCT imaging. 1251 AS-OCT images from 180 patients were collected and were used to train and test the model. Experiments demonstrated that our proposed network was superior to state-of-the-art segmentation and landmark detection methods, and close agreement was achieved between manually and automatically computed clinical parameters associated with anterior chamber, pupil, iris, ICL, and IOL. Finally, as an example, we demonstrated how our proposed method can be applied to facilitate the clinical evaluation of cataract surgery.

Automatic measurement of anterior chamber angle parameters in AS-OCT images using deep learning.

The early assessment of angle closure is of great significance for the timely diagnosis and treatment of primary angle-closure glaucoma (PACG). Anterior segment optical coherence tomography (AS-OCT) provides a fast and non-contact way to evaluate the angle close using the iris root (IR) and scleral spur (SS) information. The objective of this study was to develop a deep learning method to automatically detect IR and SS in AS-OCT for measuring anterior chamber (AC) angle parameters including angle opening distance (AOD), trabecular iris space area (TISA), trabecular iris angle (TIA), and anterior chamber angle (ACA). 3305 AS-OCT images from 362 eyes and 203 patients were collected and analyzed. Based on the recently proposed transformer-based architecture that learns to capture long-range dependencies by leveraging the self-attention mechanism, a hybrid convolutional neural network (CNN) and transformer model to encode both local and global features was developed to automatically detect IR and SS in AS-OCT images. Experiments demonstrated that our algorithm achieved a significantly better performance than state-of-the-art methods for AS-OCT and medical image analysis with a precision of 0.941, a sensitivity of 0.914, an F1 score of 0.927, and a mean absolute error (MAE) of 37.1±25.3 µm for IR, and a precision of 0.805, a sensitivity of 0.847, an F1 score of 0.826, and an MAE of 41.4±29.4 µm for SS, and a high agreement with expert human analysts for AC angle parameter measurement. We further demonstrated the application of the proposed method to evaluate the effect of cataract surgery with IOL implantation in a PACG patient and to assess the outcome of ICL implantation in a patient with high myopia with a potential risk of developing PACG. The proposed method can accurately detect IR and SS in AS-OCT images and effectively facilitate the AC angle parameter measurement for pre- and post-operative management of PACG.

Dissipation, Residue and Dietary Intake Risk Assessment of Penthiopyrad in Eggplants and Its Removal Using Various Household Processing Techniques.

A field trial was conducted to illustrate the dissipation and residue and assess the dietary intake risk of penthiopyrad in eggplants, and the distribution was further estimated after different household processing methods. Penthiopyrad dissipated quickly in eggplants, with half-lives of 1.85−2.56 days. The final residue data indicated that following the recommended spraying method, penthiopyrad would not threaten human health. Risk quotient results (<<100%) also demonstrated that the dietary intake risk of penthiopyrad in eggplants for Chinese consumers could be negligible. Washing, peeling and thermal treatments had significant removal effects on penthiopyrad from eggplants (0 < processing factor < 0.60). The characterization of the dissipation and distribution of penthiopyrad in field and processed eggplant samples could provide a more realistic reference for risk assessment of processed products, as well as some information for humans who may be exposed to penthiopyrad.

Residue, dissipation and dietary intake risk assessment of tolfenpyrad in four leafy green vegetables under greenhouse conditions.

A novel and accurate analytical method for the determination of tolfenpyrad in four leafy green vegetables, Brassica bara L., Spinacia oleracea L., Lactuca sativa L. and Brassica chinensis L., was developed and applied to investigate the residue distribution and dietary risk under greenhouse conditions. The established approach was determined to be adequate, with recoveries of 79.2%-92.9% and relative standard deviations < 8%. Tolfenpyrad dissipated relatively rapidly in four leafy green vegetables. Terminal residues of tolfenpyrad were below 0.5 mg/kg (maximum residue limit for Brassica bara L. set by China) in leafy green vegetables collected 28 d after the last application. Due to risk quotient values < 100%, the residue levels of tolfenpyrad in leafy green vegetables collected 21 days after the last application were deemed safe for consumers. The results provide field data for the reasonable use and dietary risk assessment of tolfenpyrad in leafy green vegetables.

Dissipation, residue, stereoselectivity and dietary risk assessment of penthiopyrad and metabolite PAM on cucumber and tomato in greenhouse and field.

Penthiopyrad is a broad-spectrum fungicide with wide application in agriculture with preferential degradation of the S (+)-stereoisomer in soil. An understanding of the stereoselective fate of penthiopyrad is crucial for accurate food safety risk assessment. In this study, the dissipation, distribution, and dietary intake risk of penthiopyrad and its main metabolite (PAM) was conducted in cucumber and tomato samples under greenhouse and open field conditions. The half-lives of penthiopyrad in cucumber and tomato samples were < 8 days and the dissipation rates were higher in the open field than in the greenhouse. Due to the enantiomeric fraction data > 0.5, S (+)-stereoisomer dissipated slightly faster than R-(-)-stereoisomer. The residues of total penthiopyrad (sum of rac-penthiopyrad and PAM) were lower than the maximum residue limits in cucumber and tomato samples (risk quotients â‰ª 100%). Therefore, the recommended penthiopyrad spraying method does not threaten vegetable cultivations and has negligible dietary intake risk.

Enantioselective evaluation of the chiral fungicide mandipropamid: Dissipation, distribution and potential dietary intake risk in tomato, cucumber, Chinese cabbage and cowpea.

A chiral analytical method was developed and validated for the determination of mandipropamid enantiomers in tomato, cucumber, Chinese cabbage and cowpea. The linearity (R2 > 0.99), accuracy (recovery: 73.8-106%) and precision (relative standard deviation: < 11%) were adequate for the detection of mandipropamid enantiomers in four vegetables. Field trials were further conducted to investigate the dissipation and residue distribution of mandipropamid and the possible enantioselectivity in different vegetables. Due to the shorter half-lives, mandipropamid dissipated more rapidly in Chinese cabbage (1.8-2.0 d) and cowpea (1.6-2.4 d) than in tomato (5.0-8.4 d) and cucumber (2.4-5.5 d). The residues of mandipropamid were 45-179 µg/kg in tomato 14 d at low dose, 48-98 µg/kg in cucumber 7 d after spraying twice at low dose, and < 2.5-1942 µg/kg in Chinese cabbage and cowpea in all treatments, which were below the maximum residue limits of mandipropamid set by the European Union and Codex Alimentarius Commission. Enantioselectivity was observed during the mandipropamid dissipation process in four vegetables. The S-(+)-enantiomer dissipated more rapidly than the R-(-)-enantiomer in tomato and Chinese cabbage (enantiomeric fractions > 0.5). For cucumber and cowpea, the dissipation of the R-enantiomer was preferential (enantiomeric fractions < 0.5). According to the risk quotient data (<< 100%), the residues of mandipropamid in four vegetables were safe for Chinese consumers. This study could provide useful information for the dissipation fate and residue distribution of mandipropamid in vegetables at the enantiomer level and offer some guidance for the dietary intake risk evaluation of mandipropamid in vegetables.

Contamination, spatial distribution, and source contribution of persistent organic pollutants in the soil of Guiyang city, China: a case study.

The contamination of persistent organic pollutants (POPs), including dichlorodiphenyltrichloroethane (DDT), hexachlorocyclohexane (HCH), and polycyclic aromatic hydrocarbon (PAH), is the most studied environmental issue. In 2020, a total of sixty soil samples collected from ten locations in Guiyang were analyzed to assess the presence of four DDTs and HCHs and sixteen PAHs. The concentrations of total DDTs, total HCHs and Σ16PAHs in the soil were between 0.26 and 12.76, 0.23 and 51.80 µg/kg, and 10.02 and 1708.86 µg/kg, respectively. The mean and median concentrations of total DDTs, total HCHs and Σ16PAHs in the soil were 1.04 and 0.26 µg/kg, 4.32 and 0.23 µg/kg, 139.14 and 98.98 µg/kg, respectively. p,p'-DDT, p,p'-DDD and γ-HCH the dominant organochloride pollutants in the soil, while 4-ring PAHs were the dominant PAHs, occupying 41.1-53.6% of the total PAHs in the soil. The highest levels of PAHs in the soil were observed in areas of Guiyang with relatively larger population densities and more developed heave industries. Various diagnostic tools were used to identify the potential sources of the POPs in the soil. The data indicated that DDTs and HCHs were from past and recent common inputs and that mixtures of several combustion activities (biomass, coal and petroleum combustion, diesel, gasoline, and vehicular emissions) were the major sources of PAHs in the Guiyang soil. The results provide information for the assessment of the extent of POP pollution in the Guiyang soil and can help authorities establish environmental protection regulations and soil remediation techniques.

Computer-Aided Intraoperative Toric Intraocular Lens Positioning and Alignment During Cataract Surgery.

Cataract causes more than half of all blindness worldwide. The most effective treatment is surgery, where cataract is often replaced by intraocular lens (IOL). Beyond saving vision, toric IOL implantation is becoming increasingly popular to correct corneal astigmatism. It is important to precisely position and align the axis of IOL during surgery to achieve optimal post-operative astigmatism correction. Comparing with conventional manual marking, automated markerless IOL alignment can be faster, more accurate and non-invasive. Here we propose a framework for computer-assisted intraoperative IOL positioning and alignment based on detection and tracking. Firstly, the iris boundary was segmented and the eye center was determined. A statistical sampling method was developed to segment iris and generate training labels, and both conventional algorithms and deep convolutional neural network (CNN) methods were evaluated. Then, regions of interests (ROIs) containing high density of scleral capillaries were used for tracking eye rotations. Both correlation filter and CNN methods were evaluated for tracking. Cumulative errors during long-term tracking were corrected using a reference image. Validation studies against manual labeling using 7 clinical cataract surgical videos demonstrated that the proposed algorithm achieved an average position error around 0.2 mm, an axis alignment error of < 1 °, and a frame rate of > 25 FPS, and can be potentially used intraoperatively for markerless IOL positioning and alignment during cataract surgery.

Determination, dissipation dynamics, terminal residues and dietary risk assessment of thiophanate-methyl and its metabolite carbendazim in cowpeas collected from different locations in China under field conditions.

BACKGROUND: Thiophanate-methyl and its metabolite carbendazim are broad-spectrum fungicides used on many crops. The residues of these chemicals could result in potential environmental and human health problems. Therefore, investigations of the dissipation and residue behaviors of thiophanate-methyl and its metabolite carbendazim on cowpeas and associated dietary risk assessments are essential for the safety of agricultural products. RESULTS: A simple analytical approach using liquid chromatography with tandem mass spectrometry was developed and validated for the determination of thiophanate-methyl and carbendazim concentrations in cowpeas. Good linearity (R2 > 0.998) was obtained, and the recoveries and relative standard deviations were 80.0-104.7% and 1.4-5.2%, respectively. The dissipation rates of thiophanate-methyl, carbendazim and total carbendazim were high (half-lives of 1.61-2.46 days) and varied in the field cowpea samples because of the different weather conditions and planting patterns. Based on the definition of thiophanate-methyl, the terminal residues of total carbendazim in cowpea samples were below the maximum residue limits set by Japan for other legumes. The acute and chronic risk quotients of three analytes were 0.0-27.6% in cowpea samples gathered from all terminal residue treatments, which were below 100%. CONCLUSION: An optimized approach for detecting thiophanate-methyl and carbendazim in cowpeas was applied for the investigation of field-trial samples. The potential acute and chronic dietary risks of thiophanate-methyl, carbendazim and total carbendazim to the health of Chinese consumers were low. These results could guide the safe and proper use of thiophanate-methyl in cowpeas and offer data for the dietary risk assessment of thiophanate-methyl in cowpeas. © 2021 Society of Chemical Industry.

Study of the in vivo antiviral activity against TMV treated with novel 1-(t-butyl)-5-amino-4-pyrazole derivatives containing a 1,3,4-oxadiazole sulfide moiety.

A series of new 1-tert-butyl-5-amino-4-pyrazole bioxadiazole sulfide derivatives containing a 1,3,4-oxadiazole moiety were designed and synthesized. The bioactivity results showed that some title compounds exhibited excellent protective activity against TMV and certain insecticidal activity. Among the tested compounds, the EC50 values of 5d, 5j, 5k and 5l were 165.8, 163.2, 159.7 and 193.1 mg/L, respectively, which are better than the EC50 value of ningnanmycin (271.3 mg/L). The chlorophyll contents and the defense enzyme activities of the tobacco leaves after treatment with 5j were significantly increased, which indicated that this series of title compounds may induce the systemic acquired resistance of host to defend against diseases. Further in vivo protective activity research on 5j using TMV with a GFP gene tag found that it can effectively inhibit the spread of TMV in inoculated tobacco. A morphological study with TEM revealed that title compound 5h can cause a distinct break of the rod-shaped TMV. Moreover, the insecticidal activity revealed that the fatality rates of 5a, 5b and 5m against aphidoidea were 85%, 83% and 87%, respectively, which indicated that the title compounds can effectively block the common carrier of plant viruses, thereby effectively reducing the TMV infection risk of tobacco. This series of synergistic effects provide key information for the research and development of antiviral agents.

Stent detection with very thick tissue coverage in intravascular OCT.

Coronary stenting or percutaneous coronary intervention (PCI) is widely used to treat coronary artery disease. Improper deployment of stents may lead to post-PCI complication, in-stent restenosis, stent fracture and stent thrombosis. Intravascular optical coherence tomography (OCT) with micron-scale resolution provides accurate in vivo assessment of stent apposition/malapposition and neointima coverage. However, manual stent analysis is labor intensive and time consuming. Existing automated methods with intravascular OCT mainly focused on stent struts with thin tissue coverage. We developed a deep learning method to automatically analyze stents with both thin (≤0.3mm) and very thick tissue coverage (>0.3mm), and an algorithm to accurately analyze stent area for vessels with multiple stents. 25203 images from 56 OCT pullbacks and 41 patients were analyzed. Three-fold cross-validation demonstrated that the algorithm achieved a precision of 0.932±0.009 and a sensitivity of 0.939±0.007 for stents with ≤0.3mm tissue coverage, and a precision of 0.856±0.019 and a sensitivity of 0.874±0.011 for stents with >0.3mm tissue coverage. The correlation between the automatically computed and manually measured stent area is 0.954 (p<0.0001) for vessels with a single stent, and is 0.918 (p<0.0001) for vessels implanted with multiple stents. The proposed method can accurately detect stent struts with very thick tissue coverage and analyze stent area in vessels implanted with multiple stents, and can effectively facilitate the evaluation of stent implantation and post-stent tissue coverage.

Automated segmentation of retinal nonperfusion area in fluorescein angiography in retinal vein occlusion using convolutional neural networks.

PURPOSE: Retinal vein occlusion (RVO) is the second most common cause of vision loss after diabetic retinopathy due to retinal vascular disease. Retinal nonperfusion (RNP), identified on fluorescein angiograms (FA) and appearing as hypofluorescence regions, is one of the most significant characteristics of RVO. Quantification of RNP is crucial for assessing the severity and progression of RVO. However, in current clinical practice, it is mostly conducted manually, which is time-consuming, subjective, and error-prone. The purpose of this study is to develop fully automated methods for segmentation of RNP using convolutional neural networks (CNNs). METHODS: FA images from 161 patients were analyzed, and RNP areas were annotated by three independent physicians. The optimal method to use multi-physicians' labeled data to train the CNNs was evaluated. An adaptive histogram-based data augmentation method was utilized to boost the CNN performance. CNN methods based on context encoder module were developed for automated segmentation of RNP and compared with existing state-of-the-art methods. RESULTS: The proposed methods achieved excellent agreements with physicians for segmentation of RNP in FA images. The CNN performance can be improved significantly by the proposed adaptive histogram-based data augmentation method. Using the averaged labels from physicians to train the CNNs achieved the best consensus with all physicians, with a mean accuracy of 0.883±0.166 with fivefold cross-validation. CONCLUSIONS: We reported CNN methods to segment RNP in RVO in FA images. Our work can help improve clinical workflow, and can be useful for further investigating the association between RNP and retinal disease progression, as well as for evaluating the optimal treatments for the management of RVO.

Machine learning-based models to support decision-making in emergency department triage for patients with suspected cardiovascular disease.

BACKGROUND: Accurate differentiation and prioritization in emergency department (ED) triage is important to identify high-risk patients and to efficiently allocate of finite resources. Using data available from patients with suspected cardiovascular disease presenting at ED triage, this study aimed to train and compare the performance of four common machine learning models to assist in decision making of triage levels. METHODS: This cross-sectional study in the second Affiliated Hospital of Guangzhou Medical University was conducted from August 2015 to December 2018 inclusive. Demographic information, vital signs, blood glucose, and other available triage scores were collected. Four machine learning models - multinomial logistic regression (multinomial LR), eXtreme gradient boosting (XGBoost), random forest (RF) and gradient-boosted decision tree (GBDT) - were compared. For each model, 80 % of the data set was used for training and 20 % was used to test the models. The area under the receiver operating characteristic curve (AUC), accuracy and macro- F1 were calculated for each model. RESULTS: In 17,661 patients presenting with suspected cardiovascular disease, the distribution of triage of level 1, level 2, level 3 and level 4 were 1.3 %, 18.6 %, 76.5 %, and 3.6 % respectively. The AUCs were: XGBoost (0.937), GBDT (0.921), RF (0.919) and multinomial LR (0.908). Based on feature importance generated by XGBoost, blood pressure, pulse rate, oxygen saturation, and age were the most significant variables for making decisions at triage. CONCLUSION: Four machine learning models had good discriminative ability of triage. XGBoost demonstrated a slight advantage over other models. These models could be used for differential triage of low-risk patients and high-risk patients as a strategy to improve efficiency and allocation of finite resources.

Disruption of Intracellular ATP Generation and Tight Junction Protein Expression during the Course of Brain Edema Induced by Subacute Poisoning of 1,2-Dichloroethane.

The aim of this study was to explore changes in intracellular ATP generation and tight junction protein expression during the course of brain edema induced by subacute poisoning of 1,2-dichloroethane (1,2-DCE). Mice were exposed to 1.2 g/m3 1,2-DCE for 3.5 h per day for 1, 2, or 3 days, namely group A, B, and C. Na+-K+-ATPase and Ca2+-ATPase activity, ATP and lactic acid content, intracellular free Ca2+ concentration and ZO-1 and occludin expression in the brain were measured. Results of present study disclosed that Ca2+-ATPase activities in group B and C, and Na+/K+-ATPase activity in group C decreased, whereas intracellular free Ca2+ concentrations in group B and C increased significantly compared with control. Moreover, ATP content decreased, whereas lactic acid content increased significantly in group C compared with control. On the other hand, expressions of ZO-1 and occludin at both the protein and gene levels in group B and C decreased significantly compared with control. In conclusion, findings from this study suggest that calcium overload and depressed expression of tight junction associated proteins, such as ZO-1 and occludin might play an important role in the early phase of brain edema formation induced by subacute poisoning of 1,2-DCE.

[Roles of CYP2E1 in liver damage induced by 1,2-dichloroethane].

OBJECTIVE: To explore the expression of CYP2E1 in the liver of mice and its effects on liver injury induced by 1,2-dichloroethane (1, 2-DCE). METHODS: (1) Thirty-two female mice were randomly divided into four groups, which were control group, low dose group, medium dose group and high dose group. Mice were exposed to 1,2-DCE through respiratory for 4 h per day for 10 days. At the end of exposure, the mice were sacrificed, their blood and liver were collected rapidly. Pathological analysis was examined. Activity of ALT and AST in serum and activity of CYP2E1 in liver were mice were randomly divided into six groups, ie simple control group, corn oil control group, inhibitor control group, simple poisonous group, low and high dose diallyl sulfide (DAS) intervention groups. Mice were treated orally with DAS in corn oil 4 hours before 1, 2-DCE exposure. The examination indicators were as aforementioned. RESULTS: (1) Compared to control group, activity of ALT in serum of mice in the high dose group and expression of CYP2E1 in the liver of mice in medium and high dose group increased significantly. In addition, the histological observation suggested obvious liver damage in medium and high dose group. (2) CYP2E1 protein expression and activity in liver and ALT in serum decreased significantly in DAS-intervention groups compared to simple poisonous group. Along with the changes of CYP2E1 and ALT, pathological changes of liver damage was better. CONCLUSION: Our results suggested that expression of CYP2E1 and oxidative damage in the liver could be induced by 1,2-DCE exposure, and CYP2E1 inhibitors can reduce the hepatic tissue damage caused by DCE.

Roles of aquaporins and matrix metalloproteinases in mouse brain edema formation induced by subacute exposure to 1,2-dichloroethane.

The aim of this study was to explore the effects of 1,2-dichloroethane (1,2-DCE) on expression of aquaporins (AQPs) and matrix metalloproteinases (MMPs) in the process of brain edema formation. Two parts were included in this study, establishment of animal model of brain edema, and mechanism of brain edema induced by subacute exposure to 1,2-DCE. In part one, mice were exposed to 0, 1.1, 1.2 or 1.3g/m(3) 1,2-DCE, 3.5h per day for 3days. Pathological analysis and water content detection in the brain were examined. In part two, mice were exposed to 1.2g/m(3) 1,2-DCE, 3.5h per day for 1, 2 or 3days, named group D, E and F, respectively. Expression of AQP4, MMP2 and MMP9 in the brain was determined by immunochemical staining, western blot and real time PCR. According to the results of part one, the 1.2g/m(3) dose was chosen for part two, a follow-up time-course study. In part two, protein expression of MMP2 and MMP9 in group F, and AQP4 in group E and F significantly increased compared to the control. Similarly, mRNA levels of AQP4 in group F, and MMP9 in group E and F significantly increased. Our results suggested that exposure to 1,2-DCE might up-regulate the expression of AQP4 protein and MMP9 mRNA at the early phase of brain edema, and AQP4 may play an important role in the brain edema formation.

Transparent poly(methyl methacrylate)/ZnO nanocomposites based on KH570 surface modified ZnO quantum dots.

Transparent luminescent ZnO embedded PMMA polymer has been synthesized by means of grafting poly(methyl methacrylate) (PMMA) onto the surface of ZnO QDs after g-methacryloxypropyl trimethoxy silane (KH570) modification. The resulting ZnO/PMMA nanocomposites with KH570-modified nanoparticles have better dispersibility and preserve the superior luminescence of ZnO nanoparticles in the nanocomposites. The obtained PMMA/ZnO nanocomposite films show high transparency, high UV-shielding efficiency and improved thermal stability. The obtained nanocomposite was characterized by Fourier transform infrared spectroscopy (FT-IR), transmission electron microscope (TEM), X-ray powder diffraction (XRD), thermogravimetry (TG), ultraviolet-visible (UV-vis) absorption spectroscopy.