[Simulation of land use and assessment of ecosystem service value in the eastern coastal cities of Zhejiang Province, China]. / 浙江东部沿海城市土地利用模拟及生态系统服务价值评估.

Simulating the change of ecosystem service values (ESV) caused by land use/cover change (LUCC) in the eastern coastal cities of Zhejiang Province is of great significance for regional sustainable development and ecological security. Based on remote sensing images of land use and Statistics Yearbook of 2000, 2010, and 2020, we analyzed the influence of LUCC on ESV in the study area during 2000-2020. We used the PLUS model to simulate land use change under three scenarios, including inertial development, ecological protection, and urban development in 2030, analyzed the spatial distribution and concentration degree of ESVs based on grid scale, and clarified the sensitivity characteristics of ESVs. The results showed that the construction land area showed an increasing trend during 2000-2020. The area of forest, cultivated land and water decreased significantly, resulting in a continuous downward trend of ESVs, which decreased by 160×108 yuan. Under the simulation of three scenarios of inertial development, ecological development, and urban development, the construction land area would increase by 93624, 54927, and 111966 hm2, respectively. The eastern plain would become the agglomeration area of construction land expansion. The ESVs of those three scenarios was 1693×108, 1729×108, and 1688×108 yuan, respectively, which were all lower than the ESVs of the study area in 2020. The decline rate of ESV in the ecological protection scenario slowed down. The spatial distribution of ESVs in the study area was high in the west and low in the east. Hot spots and cold spots of ESVs were distributed in a large range with strong agglomeration. Hot spots were mainly concentrated in the west, while cold spots were mainly distributed in the east and north.

Deep learning-based radiomic nomograms for predicting Ki67 expression in prostate cancer.

BACKGROUND: To explore the value of a multiparametric magnetic resonance imaging (MRI)-based deep learning model for the preoperative prediction of Ki67 expression in prostate cancer (PCa). MATERIALS: The data of 229 patients with PCa from two centers were retrospectively analyzed and divided into training, internal validation, and external validation sets. Deep learning features were extracted and selected from each patient's prostate multiparametric MRI (diffusion-weighted imaging, T2-weighted imaging, and contrast-enhanced T1-weighted imaging sequences) data to establish a deep radiomic signature and construct models for the preoperative prediction of Ki67 expression. Independent predictive risk factors were identified and incorporated into a clinical model, and the clinical and deep learning models were combined to obtain a joint model. The predictive performance of multiple deep-learning models was then evaluated. RESULTS: Seven prediction models were constructed: one clinical model, three deep learning models (the DLRS-Resnet, DLRS-Inception, and DLRS-Densenet models), and three joint models (the Nomogram-Resnet, Nomogram-Inception, and Nomogram-Densenet models). The areas under the curve (AUCs) of the clinical model in the testing, internal validation, and external validation sets were 0.794, 0.711, and 0.75, respectively. The AUCs of the deep models and joint models ranged from 0.939 to 0.993. The DeLong test revealed that the predictive performance of the deep learning models and the joint models was superior to that of the clinical model (p < 0.01). The predictive performance of the DLRS-Resnet model was inferior to that of the Nomogram-Resnet model (p < 0.01), whereas the predictive performance of the remaining deep learning models and joint models did not differ significantly. CONCLUSION: The multiple easy-to-use deep learning-based models for predicting Ki67 expression in PCa developed in this study can help physicians obtain more detailed prognostic data before a patient undergoes surgery.

Novel multiparametric MRI-based radiomics in preoperative prediction of perirectal fat invasion in rectal cancer.

OBJECTIVES: To investigate the feasibility and efficacy of a nomogram that combines clinical and radiomic features of magnetic resonance imaging (MRI) for preoperative perirectal fat invasion (PFI) prediction in rectal cancer. METHODS: This was a retrospective study. A total of 363 patients from two centers were included in the study. Patients in the first center were randomly divided into training cohort (n = 212) and internal validation cohort (n = 91) at the ratio of 7:3. Patients in the second center were allocated to the external validation cohort (n = 60). Among the training cohort, the numbers of patients who were PFI positive and PFI negative were 108 and 104, respectively. The radiomics features of preoperative T2-weighted images, diffusion-weighted images and enhanced T1-weighted images were extracted, and the total Radscore of each patient was obtained. We created Clinic model and Radscore model, respectively, according to clinical data or Radscore only. And that, we assembled the combined model using the clinical data and Radscore. We used DeLong's test, receiver operating characteristic, calibration and decision curve analysis to assess the models' performance. RESULTS: The three models had good performance. Clinic model and Radscore model showed equivalent performance with AUCs of 0.85, 0.82 (accuracy of 81%, 81%) in the training cohort, AUCs of 0.78, 0.86 (accuracy of 74%, 84%) in the internal cohort, and 0.84, 0.84 (accuracy of 80%, 82%) in the external cohort without statistical difference (DeLong's test, p > 0.05). AUCs and accuracy of Combined model were 0.89 and 87%, 0.90 and 88%, and 0.90 and 88% in the three cohorts, respectively, which were higher than that of Clinic model and Radscore model, but only in the training cohort with a statistical difference (DeLong's test, p < 0.05). The calibration curves of the nomogram exhibited acceptable consistency, and the decision curve analysis indicated higher net benefit in clinical practice. CONCLUSION: A nomogram combining clinical and radiomic features of MRI to compute the probability of PFI in rectal cancer was developed and validated. It has the potential to serve as a preoperative biomarker for predicting pathological PFI of rectal cancer.

Aconitine induces apoptosis in H9c2 cardiac cells via mitochondria­mediated pathway.

Aconitine, a diterpenoid alkaloids derived from Aconitum plants, is widely employed to treat various diseases. The aim of the present study was to investigate the apoptotic effect of aconitine in H9c2 cardiac cells. H9c2 cell apoptosis induced by aconitine was detected by a Cell Counting kit­8 assay, DAPI staining, Annexin V­FITC/propidium iodide double staining and western blotting. The effects of aconitine on reactive oxygen species levels and mitochondrial membrane potential were confirmed by fluorescence microscopy and flow cytometry. In addition, ATP contents were determined using a ATP­dependent bioluminescence assay kit. The levels of peroxisome proliferator activated receptor Î³ co­activator 1α (PGC­1α) expression and apoptosis­associated proteins including Caspase­3, B­cell lymphoma 2 (Bcl­2), Bcl­2­associated X protein (Bax) and Cytochrome c were also assessed. Taken together, the results indicated that aconitine may inhibit cell viability, decrease PGC­1α expression, induce mitochondrial dysfunctions, upregulate Cytochrome c, Bax and Caspase­3, and downregulate Bcl­2, suggesting that aconitine may induce apoptosis through mitochondria­mediated signaling pathways in H9c2 cells.

Electrochemical oxidation of quinoline aqueous solution on ß-PbO2 anode and the evolution of phytotoxicity on duckweed.

Electrochemical oxidation of quinoline on a ß-PbO2 electrode modified with fluoride resin and the comprehensive toxicity of intermediates formed during oxidation on duckweed were investigated in detail. The results showed that quinoline was initially hydroxylated at the C-2 and C-8 positions by hydroxyl radicals (·OH) electro-generated on a ß-PbO2 anode, yielding 2(1H)-quinolinone and 8-hydroxyquinoline, then undergoing ring cleavage to form pyridine, nicotinic acid, pyridine-2-carboxaldehyde and acetophenone, which were ultimately converted to biodegradable organic acids. NO3- was the final form of quinoline-N. The growth of duckweed exposed to the oxidized quinoline solution was gradually inhibited with the decrease in pH and the formation of intermediates. However, the growth inhibition of duckweed could be eliminated beyond 120 min of oxidation, indicating the comprehensive toxicity of the quinoline solution reduced when the amount of quinoline removed was above 80%. Additionally, the adjustment of the pH to 7.5 and the addition of nutrients to the treated quinoline solution before culturing duckweed could obviously alleviate the inhibition on duckweed. Thus, partial electrochemical degradation of quinoline offers a cost-effective and clean alternative for pretreatment of wastewater containing nitrogen-heterocyclic compounds before biological treatment. The duckweed test presents a simple method for assessing the comprehensive toxicity of intermediates.

[Relationship between myocyte proliferation and cardiac function in adult rats with heart failure].

OBJECTIVE: To confirm whether there is myocytes proliferation in the adult rat with heart failure or not, and to investigate the relationship between myocyte proliferation and heart function. METHODS: Descending anterior branch of left coronary artery was ligated in 20 adult male SD rats so as to establish an heart failure models. Eight rats were used as controls. Hemodynamic parameters, blood pressure (BP), left ventricle end systolic pressure (LVESP), left ventricle end diastolic pressure (LVEDP), +LVdp/dt(max), and -LVdp/dt(max), were measured 30 days after the coronary occlusion. Based on the results of heart function examination, the heart infarct rats were divided into 2 subgroups: cardiac functional compensation subgroup (8 rats), and cardiac functional decompensation subgroup (6 rats). Then the rats were killed and their hearts were taken out and stained with propidium iodide (PI) and antibody to alpha-sarcomeric actin. Immunohistochemistry was used to detect the proliferation cell nuclear antigen (PCNA). Confocal microscopy was used to observe the mitotic image. Light microscopy was used to observe the PCNA positive rate in the myocardium. RESULTS: (1) Mitotic images of myocytes could be identified by confocal microscopy in the left ventricle of all rats. (2) PCNA expression was detected in the nuclei of both infarct and normal hearts. The PCNA positive rate of the cardiac functional compensation subgroup was 7.2% +/- 1.4%, significantly higher than that of the control group (2.2% +/- 0.8%, P = 0.648). However, the PCNA positive rate of the cardiac functional decompensation subgroup was 3.0% +/- 1.3%, not significantly different from that of the control group (P = 0.648). (3) The correlation coefficient between PCNA-positivity of cardiomyocytes and +LVdp/dt(max) in the infarct rats were 0.80 (P < 0.01) and the correlation coefficient between PCNA-positivity of cardiomyocytes and -LVdp/dt(max) was -0.76 (P = 0.01). CONCLUSION: (1) There is myocyte proliferation in the adult rat heart. (2) Myocyte proliferation is positively correlated with heart systolic function, and negatively correlated with heart diastolic function in chronic heart failure.