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The calibration transfer between instruments is mainly aimed at the calibration transfer between normal spectrometers. There are few studies on the calibration transfer of soil nutrient concentration from a hyperspectral camera to a normal spectrometer. In this paper, 164 soil samples from three regions in Qingdao, China, were collected. The spectral data of normal spectrometer and hyperspectral camera and the concentration of total carbon and nitrogen were obtained. And then, the models of soil total carbon and nitrogen content were established by using the spectral data of a normal spectrometer. The hyperspectral data were transferred by a variety of methods, such as single conventional calibration transfer algorithm, combination of multiple calibration transfer algorithms, and calibration transfer algorithm after spectral pretreatment. The transferred hyperspectral data were predicted by the total carbon and total nitrogen concentration model established by using a normal spectrometer. The absolute coefficients Rt2 and root mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer. After trying many calibration transfer methods, the prediction performance of calibration transfer by the Repfile-PDS and Repfile-SNV methods was the best. In the calibration transfer of the Repfile-PDS method, when the number of PDS windows was 27 and the number of standard data was 40, the Rt2 and the RMSEP of TC concentration were 0.627 and 2.351. When the number of PDS windows was 25 and the number of standard data was 100, the Rt2 and the RMSEP of TN concentration were 0.666 and 0.297. In the calibration transfer of the Repfile-SNV method, when the number of TC and TN standard data was 120, the Rt2 was the largest, 0.701 and 0.722, respectively, and the RMSEP was 2.880 and 0.399, respectively. After the hyperspectral data were calibration transferred by the above algorithms, they could be predicted by the soil TC and TN concentration model established by using a normal spectrometer, and better prediction results can be obtained. The solution of the calibration transfer of soil nutrient concentration from the hyperspectral camera to the normal spectrometer provides a powerful basis for rapid prediction of a large number of image information data collected by using a hyperspectral camera. It greatly reduces the workload and promotes the application of hyperspectral camera in quantitative analysis and rapid measurement technology.

Spectroscopy has been applied in monitoring soil nutrient concentrations. Two types of soil samples, sandy loam and silty loam, were selected as the research objects. The UV-visible near-infrared reflectance spectroscopy data and total carbon (TC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available nitrogen (AN), available phosphorus (AP), available potassium (FK), and slowly available potassium (SK) concentrations were measured. We compared the prediction results within and between two different types of soil with regard to the soil nutrient concentrations using four modeling methods, which were principal component regression (PCR), partial least squares regression (PLSR), least squares support vector machine (LS-SVM), and back propagation neural network (BPNN) models. In the prediction results within a given type of soil, LS-SVM and PLSR had better stability. In the prediction results of different types of soil, BPNN and LS-SVM had a high accuracy in most soil nutrient concentrations. By comparing different modeling methods, this study provides a basis for the subsequent selection of suitable models based on spectral technology to establish various soil nutrient models.

The central objective was to identify the role of the PI3K-Akt activation pathway on the neuroprotection of δ-opioid receptor agonist (DADLE) against cerebral ischemia-reperfusion (I/R) injury in a rat model. Fifty-five male Sprague-Dawley (SD) rats were included to establish a middle cerebral artery occlusion (MCAO) model which were then divided into the sham, MCAO, LY294002 (MCAO+DADLE+LY294002 [inhibitor of PI3K-Akt pathway]), DADLE (MCAO+DADLE) and DMSO (MCAO+DADLE+DMSO [dimethyl sulphoxide]) groups. The cerebral infarction (CI) volume and nerve cell apoptosis was determined using TTC and TUNEL staining. Quantitative real-time polymerase chain reaction (qRT-PCR), western blotting and immunohistochemistry staining were applied for the expressions of Bad, Bax, Bcl-2 and cleaved caspase-3. The MCAO group showed higher CI volume, nerve cell apoptosis and cleaved caspase-3 expressions than the DADLE and DMSO groups, which were also higher in the LY294002 group than the DADLE group. Compared with the MCAO group, the mRNA and protein expressions of PI3K and Bcl-2, and the protein expressions of p-Akt and p-Bad were elevated, while the mRNA and protein expressions of Bax were decreased in the DADLE and DMSO groups. Decreased mRNA and protein expressions of PI3K and Bcl-2, reduced protein expressions of p-Akt and p-Bad and elevated mRNA and protein expressions of Bax exhibited in the LY294002 group than the DADLE group. These results indicate that activation of PI3K-Akt pathway promotes the neuroprotection of DADLE against cerebral I/R injury in a rat model by decreasing nerve cells apoptosis.

The study aims at investigating the effects of coagulation factors VIII/XI/XIII polymorphisms in coagulation factor activities and deep vein thrombosis (DVT). A total of 130 patients with history of artificial joint replacement surgery were recruited, including 65 patients with DVT (cases) and 65 patients without DVT (controls). Cases and controls had comparable age, sex, and body mass index. Activities of VIII/XI and XIII were, respectively, detected by 1 phase anticoagulation method and microtitrimetry. Polymorphisms of VIII rs1800291 (3591CG), XI rs2289252 (25264CT), and XIII rs5985 (103GT) were detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Activities of VIII/XI were significantly increased in cases than in controls (P0.001 for VIII, P = 0.024 for XI). Activity of XI was significantly increased by 11.11% in CT + TT mutant type (25264CT) compared with wild-type CC (95% confidence interval (CI), 2.28-19.95). In univariate analysis, incidence of DVT for CT mutant was 2.41-fold compared with wild-type CC (95% CI, 1.16-5.03). T allele had 1.83-fold increased risk of DVT than C allele (95% CI, 1.06-3.14). In multivariate analysis, incidence of DVT for CT + TT mutant type was 2.39-fold compared with wild type (95% CI, 1.07-5.35). Distributions of VIII gene 3951CG and genotypes were not significant between groups (both P0.05). The mutation rate of VIII gene 103GT was low in study population (0.77%) and was not significant between groups. XI 25264CT genotype is significantly associated with XI activity. T mutation of this locus significantly increases XI activity and is a risk factor for DVT.

Earthworms may regulate carbon (C) mineralization through a top-down process by altering microbiota community and/or a bottom-up process by providing basic conditions such as mineralizable substrates. However, these two roles performed by earthworms have not been separately quantified. Here, we focused on how the pantropical widespread earthworm, Pontoscolex corethrurus, affected CO2 emission by changing soil microbiota community and substrate availability in infertile subtropical soils. Two experiments were performed. Firstly, we conducted a 3-year field experiment wherein P. corethrurus population was manipulated by electrical shocking. The two treatments were earthworm reduction (ER) and earthworm addition (EA). Thereby, we tried to understand CO2 emission pattern through the earthworm-induced changes in soil microbiota community and C-related enzyme activities in field plots. Secondly, a cross-soil inoculation microcosm experiment was conducted to partition the contributions of earthworm-regulated microbiota community and substrate quality to CO2 emission. The four treatments were 1) autoclaved ER soil + ER microbiota, 2) autoclaved EA soil + ER microbiota, 3) autoclaved ER soil + EA microbiota, and 4) autoclaved EA soil + EA microbiota. We found that, in the field experiment, earthworm addition changed soil microbiota community structure, but increased CO2 emission despite decreasing soil β-glucosidase activity by 12%. In the cross-inoculation experiment, the β-glucosidase activity and CO2 emission (1-day incubation) in EA soils was 65.5% and 35.5% greater than that in the ER soils, respectively; the cumulative CO2 emission (30-day incubation) in EA soils was also significantly greater than that in ER soils. However, no significant effects of microbiota inoculation on soil CO2 emissions were observed. These results suggested that the earthworm-enhanced substrate availability, rather than the earthworm-induced changing in the microbiota community structure and enzymatic activities, played a key role in C mineralization. This study implies that P. corethrurus occupies a "bottom niche" in infertile subtropical soils.

Although visible-near-infrared spectroscopy can rapidly and accurately determine soil nutrients without sample destruction, some problems remain unresolved, such as the mismatch of the established spectral model with different types of samples, limiting the wide application of this technology. Here, we took riverside and mountain soils as examples to explore the calibration transfer between two different types of soils by the WMPDS-S/B algorithm (wavelet multiscale piecewise direct standardization combined with Slope/Bias correction method) and by adding new samples. The predicted TN and TC concentrations improved significantly after being transformed. Compared with adding new samples, the WMPDS-S/B algorithm obtained more accurate results. The average relative errors dropped from 440.2% (without transformation) to approximately 6% for TN and from 342.0% to approximately 7% for TC. The maximum relative errors were reduced from 538.1% to less than 20% for TN and from 403.7% to less than 20% for TC. The RMSEP decreased from 2.42 to approximately 0.04 for TN and from 15.74 to approximately 0.4 for TC. The WMPDS-S/B algorithm had advantages in selecting fewer known samples and obtaining better prediction results. In contrast to past studies, which resolved the calibration transfer between different spectrometers and the measurement environment for the same samples, our study resolved the calibration transfer between different types of samples under the same spectrometer and the measurement environment. The former could only be used for correction among instruments, while the latter fundamentally solved the problem of model sharing across different samples.

Although some studies have reported potential associations of dietary patterns with depression risk, a consistent perspective hasn't been estimated to date. Therefore, we conducted this meta-analysis to evaluate the relation between dietary patterns and the risk of depression. A literature research was conducted searching MEDLINE and EMBASE databases up to September 2016. In total, 21 studies from ten countries met the inclusion criteria and were included in the present meta-analysis. A dietary pattern characterized by a high intakes of fruit, vegetables, whole grain, fish, olive oil, low-fat dairy and antioxidants and low intakes of animal foods was apparently associated with a decreased risk of depression. A dietary pattern characterized by a high consumption of red and/or processed meat, refined grains, sweets, high-fat dairy products, butter, potatoes and high-fat gravy, and low intakes of fruits and vegetables is associated with an increased risk of depression. The results of this meta-analysis suggest that healthy pattern may decrease the risk of depression, whereas western-style may increase the risk of depression. However, more randomized controlled trails and cohort studies are urgently required to confirm this findings.