Correlation between elevated serum interleukin-1β, interleukin-16 levels and psychiatric symptoms in patients with schizophrenia at different stages

Abstract Background There is increasing evidence that immune dysfunction plays an important role in the pathogenesis of schizophrenia. Meso Scale Discovery (MSD) is bioanalytical method, which can detect serum inflammatory factors in patients. MSD has higher sensitivities, capturing a narrower range of proteins compared to other methods typically used in similar studies. The present study was aimed to explore the correlation between the levels of serum inflammatory factors and psychiatric symptoms in patients with schizophrenia at different stages and investigate a wide panel of inflammatory factors as independent factors for the pathogenesis of schizophrenia. Methods We recruited 116 participants, including patients with first-episode schizophrenia (FEG, n = 40), recurrence patients (REG, n = 40) with relapse-episode schizophrenia, and a control group (healthy people, HP, n = 36). Patients are diagnosed according to the DSM -V. The plasma levels of IFN-γ, IL-10, IL-1β, IL-2, IL-6, TNF-α, CRP, VEGF, IL-15, and IL-16 were tested by the MSD technique. Patient-related data was collected, including sociodemographic data, positive and negative symptom scale (PANSS), and brief psychiatric rating scale (BPRS) and subscale scores. The independent sample T test, χ2 test, Analysis of covariance (ANCOVA), the least significant difference method (LSD), Spearman’s correlation test, binary logistic regression analysis and ROC curve analysis were used in this study. Results There were significant differences in serum IL-1β (F = 2.37, P = 0.014) and IL-16 (F = 4.40, P < 0.001) levels among the three groups. The level of serum IL-1β in the first-episode group was significantly higher than in the recurrence group (F = 0.87, P = 0.021) and control group (F = 2.03, P = 0.013), but there was no significant difference between the recurrence group and control group (F = 1.65, P = 0.806). The serum IL-16 levels in the first-episode group (F = 1.18, P < 0.001) and the recurrence group (F = 0.83, P < 0.001) were significantly higher than in the control group, and there was no significant difference between the first-episode group and the recurrence group (F = 1.65, P = 0.61). Serum IL-1β was negatively correlated with the general psychopathological score (GPS) of PANSS (R=-0.353, P = 0.026). In the recurrence group, serum IL-16 was positively correlated with the negative score (NEG) of the PANSS scale (R = 0.335, P = 0.035) and negatively correlated with the composite score (COM) (R=-0.329, P = 0.038). In the study, IL-16 levels were an independent variable of the onset of schizophrenia both in the first-episode (OR = 1.034, P = 0.002) and recurrence groups (OR = 1.049, P = 0.003). ROC curve analysis showed that the areas under IL-16(FEG) and IL-16(REG) curves were 0.883 (95%CI:0.794–0.942) and 0.887 (95%CI:0.801–0.950). Conclusions Serum IL-1β and IL-16 levels were different between patients with schizophrenia and healthy people. Serum IL-1β levels in first-episode schizophrenia and serum IL-16 levels in relapsing schizophrenia were correlated with the parts of psychiatric symptoms. The IL-16 level may be an independent factor associating with the onset of schizophrenia

Optimizing a Standard Spectral Measurement Protocol to Enhance the Quality of Soil Spectra: Exploration of Key Variables in Lab-Based VNIR-SWIR Spectral Measurement

The method of proximal VNIR-SWIR (with a spectral region of 400&ndash;2500 nm) spectroscopy in a laboratory setting has been widely employed in soil property estimations. Increasing attention has been focused recently on establishing an agreed-upon protocol for soil spectral measurement, fueled by the recognition that studies carried out under different laboratory settings have made future data sharing and model comparisons difficult. This study aimed to explore the key factors in a lab-based spectral measurement procedure to provide recommendations for enhancing the spectra quality and promoting the development of the spectral measurement protocol. To this aim, with the support of the standard spectral laboratory at Jilin University, China, we designed and performed control experiments on four key factors&mdash;the light interference in the measurement course, soil temperature, soil moisture, and soil particle size&mdash;to quantify the variation in the spectra quality by the subsequent estimation accuracies of different estimation models developed with different spectra obtained from control groups. The results showed that (1) the soil&ndash;probe contact measurement derived the optimum spectra quality and estimation accuracy; however, close-non-contact measurement also achieved acceptable results; (2) sieving the soil sample into particle sizes below 1 mm and drying before spectral measurement effectively enhanced spectra quality and estimation accuracy; (3) the variation in soil temperature did not have a distinct influence on spectra quality, and the estimation accuracies of models developed based on soil samples at 20&ndash;50 &deg;C were all acceptable. Moreover, a 30-min warm-up of the spectrometer and contact probe was found to be effective. We carried out a complete and detailed control experiment process, the results of which offer a guide for optimizing the process of laboratory-based soil proximal spectral measurement to enhance spectra quality and corresponding estimation accuracy. Furthermore, we present theoretical support for the development of the spectral measurement protocol. We also present optional guidance with relatively lower accuracy but effective results, which are save time and are low cost for future spectral measurement projects

Optimizing a Standard Spectral Measurement Protocol to Enhance the Quality of Soil Spectra: Exploration of Key Variables in Lab-Based VNIR-SWIR Spectral Measurement

The method of proximal VNIR-SWIR (with a spectral region of 400–2500 nm) spectroscopy in a laboratory setting has been widely employed in soil property estimations. Increasing attention has been focused recently on establishing an agreed-upon protocol for soil spectral measurement, fueled by the recognition that studies carried out under different laboratory settings have made future data sharing and model comparisons difficult. This study aimed to explore the key factors in a lab-based spectral measurement procedure to provide recommendations for enhancing the spectra quality and promoting the development of the spectral measurement protocol. To this aim, with the support of the standard spectral laboratory at Jilin University, China, we designed and performed control experiments on four key factors—the light interference in the measurement course, soil temperature, soil moisture, and soil particle size—to quantify the variation in the spectra quality by the subsequent estimation accuracies of different estimation models developed with different spectra obtained from control groups. The results showed that (1) the soil–probe contact measurement derived the optimum spectra quality and estimation accuracy; however, close-non-contact measurement also achieved acceptable results; (2) sieving the soil sample into particle sizes below 1 mm and drying before spectral measurement effectively enhanced spectra quality and estimation accuracy; (3) the variation in soil temperature did not have a distinct influence on spectra quality, and the estimation accuracies of models developed based on soil samples at 20–50 °C were all acceptable. Moreover, a 30-min warm-up of the spectrometer and contact probe was found to be effective. We carried out a complete and detailed control experiment process, the results of which offer a guide for optimizing the process of laboratory-based soil proximal spectral measurement to enhance spectra quality and corresponding estimation accuracy. Furthermore, we present theoretical support for the development of the spectral measurement protocol. We also present optional guidance with relatively lower accuracy but effective results, which are save time and are low cost for future spectral measurement projects

Determining the Effects of Light on the Fruit Peel Quality of Photosensitive and Nonphotosensitive Eggplant

With the development of facility agriculture, low-light stress is a prominent problem and a popular research topic currently. In this study, transcriptome analysis was used to analyze the genes in the fruit peel of photosensitive and nonphotosensitive eggplant and to explore the mechanism of changes in fruit color, texture, hormone content, aroma, and taste of these two different types of eggplant. We identified 51, 65, 66, and 66 genes involved in synthesizing anthocyanins, texture, hormone content, and aroma and flavor, respectively, in the two different types of eggplant based on the variation in gene expression trends in the fruit peel. These results provide a basis for further analysis of the molecular mechanism underlying the regulatory processes in eggplant fruits under low-light stress