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Quantitative characterization of Cr3+, an important element revealing human metabolism and biological environmental variation, is still difficult to achieve by conventional biochemical methods due to the lack of high-sensitivity, real-time techniques with rapid response detection. Using surface-enhanced Raman scattering (SERS), we construct an Au/Ag composite-based SERS nanoprobe for the quantitative characterization of Cr3+ content in solution, in which DL-mercaptosuccinic acid (DL-MSA) is employed for Raman signal enhancement, and 4-mercaptobenzoic acid (4-MBA) is chosen as the Raman reporter. The achieved result demonstrates obvious advantages of the synthesized Au/Ag composite-based SERS nanoprobe in sensitivity and response speed. Importantly, this Au/Ag composite-based SERS nanoprobe might provide a new strategy for dynamic monitoring of Cr3+ content in human metabolism.

Cyclophosphamide (CTX) is a widely used anticancer drug that can cause liver injury, but there is no effective treatment available at present. The antioxidant properties of Lactobacillus plantarum Lp2 in vitro and its effect on CTX-induced liver injury in mice were investigated thoroughly. The order of antioxidant capacity of the fermentate of Lp2 was as followed: fermented supernatant cell-free extract intact cell. BALB/c mice were intraperitoneally injected with 80 mg/kg BW/d CTX for 3 days to build a liver injury model, then treated with Lp2 fermented supernatant (Lp2-s) and Lp2 culture broth (Lp2). After 10 days, the indicators of oxidative stress and liver injury were measured. Both Lp2-s and Lp2 restored the levels of T-SOD, CAT, GSH-Px, MDA, GSH, ALT, and AST. The western blotting results showed that Lp2-s and Lp2 ameliorated CTX-induced oxidative damage and hepatocyte apoptosis via inhibiting MAPKs pathway and strengthening Nrf2/HO-1/NQO1 antioxidant defense system, thus inhibiting the mitochondrial-mediated apoptosis pathway. Therefore, both Lp2-s and Lp2 had similar protective effects on CTX-induced liver injury.

Quantitative characterization of Cr

The effective and safe capture and storage of radioactive iodine (129I or 131I) are of significant importance during nuclear waste storage and nuclear energy generation. Herein, a porous silicon–carbon (pSi–C) composite derived from paper mill sludge (PMS) is synthesized and used for rapid iodine capture. The influences of the activator type, the impregnation ratio of the paper mill sludge to the activator, carbonization temperature, and carbonization time on the properties of the pSi–C composite are investigated. The pSi–C composite produced in the presence of ZnCl2 as the activator and at an impregnation ratio of 1 : 1, a carbonization temperature of 550 °C, and a carbonization time of 90 min has a surface area of 762.13 m2 g−1. The as-synthesized pSi–C composite exhibits promising iodine capture performance in terms of superior iodine adsorption capacity (qt) of around 250 mg g−1 and rapid equilibrium adsorption with in 15 min. The devised method is environmentally friendly and inexpensive and can easily be employed for the large-scale production of porous silicon-activated carbon composites with excellent iodine capture and storage from iodine-contaminated water.

Phototherapy, especially the photothermal therapy (PTT) and the photodynamic therapy (PDT), have become very promising in cancer treatment due to its low invasiveness and high efficacy. Both PTT and PDT involve the utilization of light energy, and their synergistic treatment should be a good solution for cancer treatment by ingenious design. The therapeutic effect of phototherapy is closely associated with the amount and location of anticancer-nanodrugs accumulated in tumor cells, and the receptor-mediated endocytosis should be an excellent candidate for enhancing anticancer-nanodrugs internalization. Surface enhanced Raman spectroscopy (SERS) imaging is suitable for tracing nanodrugs due to its high selectivity, sensitivity and reliability. In this paper, we hope to construct a receptor-mediated PTT/PDT synergistic anticancer nanodrugs and evaluate the corresponding efficacy through SERS tracing function. Here, the receptor-mediated PTT/PDT synergistic anticancer nanodrugs are prepared by the chemical modification of gold nanorods (GNRs), involving protoporphyrin IX (PpIX), 4-mecaptobenzoic acid (MBA), and folic acid (FA). The achieved results show that the receptor-mediated endocytosis can greatly facilitate the internalized amount and intracellular distribution of the nanodrugs, thus lead to the anti-cancer efficacy improvement. Importantly, this receptor-mediated PTT/PDT synergistic treatment with SERS tracing function will provide a simple and effective strategy for the design and application of anticancer phototherapy nanodrugs.

Background: Chemotherapy and radiotherapy are common methods of cancer treatment, but they are accompanied by serious side effects. Actually, many cancer cells have overexpression of folic acid (FA) receptor and by FA receptor-mediated endocytosis, anticancer drugs can be easily internalized into cancer cell, this will greatly improve the curative effect and decrease side effects. Along with the development of nanotechnology, phototherapy, owning advantages in tissue selectivity, process controlling, low toxicity and reproducible treatment, has become very promising, especially for photothermal therapy (PTT) and photodynamic therapy (PDT). Since both PTT and PDT involve the utilization of light energy, so they synergistic treatment should be a good solution by ingenious design. In this paper, based on surface enhanced Raman spectroscopy (SERS) imaging, we hope to construct a FA receptor-mediated PTT/PDT synergistic anticancer nanodrug (nanoprobe), and achieve the intracellular distribution information of the nanodrugs during cell apoptosis, and then elucidate PTT/PDT-induced cell apoptosis and synergistic efficiency.Results: FA receptor-mediated PTT/PDT synergistic anticancer nanodrugs with tracing function are prepared by the chemical synthesis and modification of gold nanorods (GNR), involving protoporphyrin IX (PpIX), 4-mecaptobenzoic acid (MBA), and FA. Based on SERS imaging, it is found that the FA receptor-mediated endocytosis can greatly facilitate the nanodrugs internalization, in which both the number and intracellular dispersion of the PpIX-GNR-MBA-FA nanodrugs are improved relative to the GNR-MBA or PpIX-GNR-MBA compositions, and then enhance the PTT/PDT-induced cell apoptosis.Conclusion: SERS imaging is very suitable for the phototherapy tracing due to its high sensitivity and stability. The FA receptor-mediated way can significantly facilitate nanodrugs internalization, PTT/PDT-induced cell apoptosis and synergistic efficiency. Importantly, this FA receptor-mediated SERS imaging based PTT/PDT synergistic treatment will provide a novel strategy for the design and application of anticancer phototherapy nanodrugs.

Quantitative characterization of intracellular H2O2 content, which is still difficult by the conventional biochemical methods due to the lack of real-time and non-invasive technique of single cell measurement, is a useful solution for cell state assessment. Based on the surface enhanced Raman scattering (SERS), we construct a novel boric acid (BA) nanoprobe to perform quantitative characterization of H2O2 content, in which the p-thiol benzene boric acid (4-MPBA) reporter molecule modified with gold nanorods (AuNRs) is employed for Raman signal enhancement. The achieved result demonstrates obvious advantages of the synthesized AuNRs/4-MPBA/BA nanoprobe in measurement sensitivity of H2O2 content. Importantly, this AuNRs/4-MPBA/BA nanoprobe will provide a powerful tool for dynamic monitoring and quantitative characterization of intracellular H2O2 content during cell apoptosis or other cell growth processes, and then achieve important reference data for studying the corresponding molecular mechanism.

The power fluctuation of wind farm will affect the operation of regional power grid, mainly due to the power fluctuation caused by voltage fluctuation. In order to submit information to power dispatching department as soon as possible, it is convenient for system dispatching. It is necessary to research and develop wind power forecasting technology, especially ultra-short term wind power forecasting technology. At present, the power forecasting system of the dispatching side and some wind farms in China has been widely used. However, the system has some shortcomings in stable operation. Combined with the actual production experience of the existing wind power prediction system, analyze the performance of the existing wind power prediction system, find out the problems that affect the smooth operation of the system, and refer to domestic and foreign data to provide targeted information for each problem. Finally, some constructive optimization Suggestions and a set of optimization scheme are given. In addition, according to the final proposed solution, this paper also developed an optimization model for wind power prediction system, and compared the changes in system performance before and after optimization to verify whether the optimization plan is correct.

The wind power is a vigorously developed clean energy in China recent years. It’s installed capacity of our country is increasing year by year. Since 2012, the new wind power installed capacity in China has became the first place all around the world. By the end of 2016, our wind power installed capacity has added a total of 87 million 580 thousand kilowatts. Besides the rapid growth of wind power, there are still many problems in China’s wind power business. In order to solve the following problems: the inspection environment of the wind farm equipment is quite complex, the efficiency is not high enough, and the statistical data of the inspection is not good enough, this paper puts forward the “full digital monitoring and inspection platform of wind farm based on AR augmented reality” as the solution of the problems. The project implements fan positioning, model-assisted inspection, process recording, and expert remote assistant APP functions. It promotes the development of wind farm detection and inspection, which can greatly improve the inspection efficiency of wind farms and reduce the workload of inspectors.

ICU readmission is associated with longer hospitalization, mortality and adverse outcomes. An early recognition of ICU readmission can help prevent patients from worse situation and lead to lower treatment cost. As the abundance of Electronics Health Records (EHR), it is popular to design clinical decision tools with machine learning techniques manipulating on healthcare large scale data. To this end, we designed data-driven predictive models to estimate the risk of Intensive Care Unit (ICU) readmission. The discharge summary of each hospital admission was carefully represented by natural language processing algorithms. Unified Medical Language System (UMLS) was further used to standardize inconsistency of discharge summaries. 5 machine learning classifiers including naive Bayes, support vector machine, logistic regression, gradient boosting decision tree and 2 feature representations including Bag-of-Words and Bag-of-CUIs were adopted to construct predictive configurations. The best configuration yielded a competitive AUC of 0.748. High contribution words and medical terms were further investigated to ensure that they were clinical meaningful. A comparative study between two feature representations were also discussed. Our work suggests that natural language processing of discharge summaries is capable to extract meaningful information from discharge summary automatically and to send clinicians the warning of unplanned 30-day readmission upon discharge.