A Prospective Cohort Study of Inter-Alpha-Trypsin Inhibitor Heavy Chain 4 as a Serologic Marker in Relation to Severity and Functional Outcome of Acute Intracerebral Hemorrhage.

Background: The inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) may regulate immunity and inflammation. The current study was conducted to determine its role as a biomarker for reflecting the severity and predicting outcomes of intracerebral hemorrhage (ICH). Methods: In this prospective cohort study, 185 patients with supratentorial ICH were enrolled, among whom 62 had blood obtained not only at admission but also on days 1, 3, 5, 7, 10, and 14. In addition, 62 healthy controls underwent blood collection at the start of the study. The serum ITIH4 levels were then quantified. We recorded early neurological deterioration (END) and poor prognosis (modified Rankin Scale [mRS] scores of 3-6]) six months after ICH. Results: Serum ITIH4 levels decreased prominently in the early phase after ICH, continued to decline until day 5, then gradually increased until day 14, and were significantly lower during 14 days in patients than in controls. Serum ITIH4 levels on admission were independently associated with serum C-reactive protein levels, National Institutes of Health Stroke Scale (NIHSS) scores and hematoma volume. Admission serum ITIH4 levels were independently associated with mRS scores, END, and poor prognosis. No substantial differences existed in the areas under the receiver operating characteristic curve of END and poor prognosis prediction between the serum ITIH4 levels, NIHSS scores, and hematoma volume. Prediction models, in which serum ITIH4 levels, NIHSS scores, and hematoma volume were integrated, were relatively reliable and stable using a series of statistical methods. In addition, the prediction model of poor prognosis had a higher discriminatory ability than the NIHSS scores and hematoma volume alone. Conclusion: A dramatic decline in serum ITIH4 levels during the early period following ICH is independently related to the inflammatory response, stroke severity, and poor neurologic outcomes, suggesting that serum ITIH4 may be a useful prognostic biomarker of ICH.

Analysis of association between MALAT1 haplotype and the severity of normal-tension glaucoma (NTG).

MALAT1, which is disorderly expressed in the growth, invasion, migration and cancer cell apoptosis, was shown to be associated with normal-tension glaucoma (NTG), a type of optic neuropathy. The haplotype in MALAT1 affects its expression and is correlated with human diseases like normal-tension glaucoma (NTG). However, the underlying detailed mechanism remains unclear. In this study, we aimed to analyse the association between MALAT1 haplotype and the severity of NTG in a molecular level. Quantitative real-time PCR, ELISA and luciferase assays were performed to establish the underlying signalling pathways. RNFL thickness, RA and C/D ratio were calculated for NTG patients. Accordingly, GGGT haplotype was demonstrated to be associated with a decreased risk of NTG. The MALAT1 level in serum of NTG patients carrying GGGT haplotype was significantly decreased compared with NTG patients carrying other haplotypes, along with elevated miR-1 expression and diminished IL-6 expression. NTG patients carrying GGGT haplotype had thicker RNFL and RA, but a smaller C/D ratio. Sequence analysis found potential target sites of miR-1 on MALAT1 and IL-6, and luciferase assay confirmed the inhibitory effect of miR-1 on MALAT1 and IL-6 expression. Meanwhile, MALAT1 also down-regulated miR-1 expression and consequently up-regulated IL-6 expression. This study presented evidence for a regulatory network containing MALAT1, miR-1 and IL-6, and further demonstrated the effect of MALAT1 haplotype on the risk and severity of NTG.

[Hyper spectral characteristics and estimation model of leaf chlorophyll content in cotton under waterlogging stress.] / æ°´èƒè¿«ä¸‹æ£‰èŠ±å¶ç‰‡é«˜å ‰è°±ç‰¹å¾åŠå¶ç»¿ç´ å«é‡ä¼°ç®—æ¨¡åž‹.

In order to rapidly monitor chlorophyll content in cotton functional leaf, and establish the quantitative relationship between chlorophyll content and spectral characteristic parameter of single cotton leaf, cotton was pot cultivated in a rain shelter and subjected to waterlogging at squaring stage. Cotton leaf samples were taken and measured every 3 days after waterlogging. The correlation between chlorophyll content and spectral characteristic parameter was synthetically analyzed, and then the estimation model of chlorophyll content was established and verified. The results showed that the chlorophyll content decreased with increasing waterlogging stress. The original spectral reflectance and first order differential spectral reflectance was negatively correlated with the chlorophyll content in the band near 580 and 697 nm. The estimation model established by difference vegetation index and normalized difference vegetation index performed better than that established by linear model of single band. Furthermore, the estimation model with (DR697-DR738)/(DR697+DR738) as the independent variable fitted the best with the correlation coefficient of 0.814, which could be utilized to estimate chlorophyll content of single leaf under waterlogging stress.

[Black soil organic matter predicting model based on field hyperspectral reflectance].

To develop soil organic matter (OM) quick measuring methods, deepen the application of remote sensing in agriculture, improve agricultural production and management way, and promote the development of quantitative remote sensing studies relating to terrestrial ecosystem, field hyperspectral reflectance in the visible/near infrared bands of black soil in Hailun city, northeast China, was collected and analyzed with spectral analysis methods to discover the spectral characteristics of field reflectance and its influencing factors, and the spectral indices were derived, then black soil organic matter predicting model based on the correlation between OM content and spectral indices was built. Root mean squared error (RMSE) was introduced to validate the predictability and precision of the models, and coefficient of the determination (R2) was used to evaluate stability of the models. The results are as follows: the main spectral region of remarkable differences between field black soil reflectance curves is less than 1 250 nm, especially less than 1 000 nm; OM is the main factor determining the curve shape of field black soil reflectance, anc there are single or double spectral wave troughs for different soil samples because of varying OM content at the spectral region less 1 100 nm; correlation between OM and differential coefficient of logarithmic reflectance reciprocal (DCLRR) is much more significant than that between OM and other reflectance or its transforms, and the maximum coefficient of correlation is at 1 260 nm; the predicting model for black soil OM content is built with DCLRR at 1 260 nm as independent varialble and OM as dependent variable, and the coefficients of determination R2 of the model is 0.71, RMSE is 0.42, so the model is quite good in stability and predictability, and can be used in fast testing of organic matter in black soil.