Carbon budget and evaluation of marine industry in Jiangsu Province, China.

The measurement and evaluation of carbon budget of marine industry is the basis for promoting green and efficient development of marine economy under the goal of carbon neutrality. We constructed a carbon accounting system for the marine industry in Jiangsu Province, and assessed carbon efficiency and neutrality. The results showed that from 2016 to 2020, the total amount of marine carbon sinks in Jiangsu Province were 894.8 to 2773.2 thousand tons, while carbon emissions of major marine industries were 3538.4 to 4350.6 thousand tons. The net emissions of marine industries ranged from 1478.7 to 2906.1 thousand tons. Both of carbon sinks and emissions were significantly increased in this period. In terms of carbon sinks, the offshore wind power accounted for the largest contribution, followed by ecosystem carbon sequestration, and mariculture carbon sequestration was the smallest. In terms of carbon emissions, the marine transportation industry played a dominant role, followed by coastal tourism and marine fisheries, while the marine engineering and construction industry and marine shipping industry accounted for a small proportion. In general, the carbon neutral status showed that marine industry in Jiangsu Province was in carbon deficit from 2016-2020, but the net emissions were decreasing year by year. The net carbon sink efficiency of mariculture in Jiangsu Province was lower than the national level, and carbon efficiency of offshore wind power was stable.

Interaction between carboxymethyl pachyman and lotus seedpod oligomeric procyanidins with superior synergistic antibacterial activity.

The inhibitory effect of carboxymethyl pachyman (CMP) mixed with lotus seedpod oligomeric procyanidins (LSPC) in certain ratios against E. coli 10899 was determined. Added low concentration of LSPC could improve the antibacterial activity of CMP, and a significant synergistic effect could be observed between them, especially when the concentration of CMP was below its critical concentration (1.35 mg/mL). Then, the interaction between CMP and LSPC was characterized after mixing; the changes in spectral characteristics, thermal properties, crystallinity pattern, molecular weight, chain morphology and microrheological behaviour explained the influence of interaction on the structure of CMP and LSPC. The smaller molecular size, electrostatic interaction and stronger hydrophobic interaction might play important roles in improving the antibacterial activity of mixture. The dissociation constant (Kd) was determined to be 0.102±0.0008 mg/mL using MicroScale Thermophoresis (MST), and the micromorphology was observed by SEM. Therefore, this mixture might be an effective natural bacteriostat.

A novel one-step synthesis of Gd3+-incorporated mesoporous SiO2 nanoparticles for use as an efficient MRI contrast agent.

Molecular imaging has generated a demand for more sensitive contrast agents for magnetic resonance (MR) imaging. We synthesized, by a novel one-step method, Gd(3+) incorporated mesoporous SiO(2) nanoparticles, Gd(2)O(3)@SiO(2), for use as an efficient contrast agent. The prepared nanoparticles were also coated with poly(lactic-co-glycolic acid) (PLGA). The size, morphology, composition and Brunauer-Emmett-Teller specific surface area of the nanoparticles were evaluated. The Gd(2)O(3)@SiO(2) nanoparticles possess intragranular network morphology with a uniform size distribution and an average size of approximately 20-40 nm. The PLGA-coated nanoparticles were spherical or near-spherical in shape with a diameter of approximately 120 nm, a smooth surface, and neither aggregation nor adhesion tendencies. No free Gd ions were detected to dissociate from Gd(2)O(3)@SiO(2) even up to the limit (<0.03 mg/l) of the ICP equipment (IRIS Advantage). Our theoretical computation based on density functional theory (using DMol3, Materials Studio) revealed that the Gd(2)O(3) molecules are fully absorbed on the interface of mesoporous SiO(2) with a stable state of lower energy. Both Gd(2)O(3)@SiO(2) and PLGA-coated Gd(2)O(3)@SiO(2) samples have a larger T(1) relaxivitiy than commercial gadolinium diethylene triaminepentaacetate (Gd-DTPA). In vitro and in vivo MR images using the Gd(2)O(3)@SiO(2) nanoparticles were observed with a 1.5 T clinical MR scanner and compared with the images using Gd-DTPA. The Gd(2)O(3)@SiO(2) nanoparticles display a better magnetic property than commercial Gd-DTPA. In vivo MR imaging demonstrated that the nanoparticles were mainly distributed in the liver. Strong enhancement was also detected in nasopharyngeal carcinoma CNE-2 xenografted tumors. The Gd(2)O(3)@SiO(2) nanoparticles are not only potential candidates for highly efficient contrast agents for MR imaging, but also might be developed into potent targeted probes for in vivo molecular imaging of cancer.

Characterizing the clustered microcalcifications on mammograms to predict the pathological classification and grading: a mathematical modeling approach.

In this study, we explore a mathematical model to characterize the clustered microcalcifications on mammograms for predicting the pathological classification and grading. Our database consists of both retrospective cases (78 cases) and prospective cases (31 cases) with pathologically diagnosed clusters of microcalcifications on mammograms. The microcalcifications were divided into four grades: grade 0, benign breast disease including mastopathies (n = 12) and fibroadenomas (n = 20); grade 1, well-differentiated infiltrating ductal carcinoma (n = 12); grade 2, moderately differentiated infiltrating ductal carcinoma (n = 38); grade 3, poorly differentiated infiltrating ductal carcinoma (n = 27). A feature parameter, defined as the pattern form factor of microcalcification cluster θ by us, combines five computer-extracted image parameters of microcalcification clusters of those mammograms. In every case, only one imaging was selected for modeling analysis. A total of 109 imagings were adopted in current study. We find the existence of a positive relationship between the feature parameter θ and pathological grading G of microcalcifications in retrospective cases, which was expressed as G = 6.438 + 1.186 × Ln <θ>. The model above has been verified further by the prospective study with a comparative evaluation accuracy of approximately 77.42%. The binary predication simply for both benignancy and malignancy was also included using same but reshuffled data, and the receiver operating characteristic (ROC) analysis was performed with ROC value 0.74351∼0.79891. As one candidate for feature parameter in computer-aided diagnosis, the pattern form factor θ of clustered microcalcifications may be useful to predict the pathological grading and classification of microcalcification clusters on mammography in breast cancer.

[Quantitative evaluation of CT-MRI images of various tumors with expansive or infiltrative growth pattern].

OBJECTIVE: To investigate quantitatively the proliferation of tumors in characteristic of either expansive or infiltrative growth pattern. METHODS: The CT/MRI images of 34 tumor patients with 6 different pathological types were adopted to undergo quantitative evaluation of the growth pattern of these tumors. Three key parameters, fractal dimension (Df) of the border between the tumor and neighboring tissues, degree of heterogeneity (H), and clumsiness (C) inside the tumor, were computed numerically. RESULTS: The Df values of the infiltrative tumors were higher than those of the expansive tumors, thus revealing the more evident complexity and openness of the border of infiltrative tumor. Heterogeneity and clumsiness existed within both expansive and infiltrative tumors. The clumsiness derived from heterogeneity and they were correlated positively with each other. The growth coefficient of clumsiness of the expansive tumor was greater than that of the infiltrative tumor. CONCLUSION: The method to analyze the fractal dimension of tumor border, and degrees of heterogeneity and clumsiness within a tumor presented in this paper gives some enlightenment to the fundamental research in characterizing tumor growth and shows practical value in clinical diagnosis of tumor, and may be of benefit to the quantitative evaluation of radiological images and computer-aided diagnosis.