The Application Value of Gemstone Spectral Imaging (GSI) Combined with an 80 mm Wide-body Detector in Head-neck CTA.

OBJECTIVE: This study aims to investigate the value of gemstone spectral imaging (GSI) combined with an 80 mm wide-body detector in head-neck CTA. METHODS: Ninety patients with head-neck CTA were prospectively selected and randomly divided into a control group and a test group, with 45 patients in each group. The control group was scanned conventionally. With a tube voltage of 100 kVp and detector width of 40 mm, a 70 ml contrast agent was injected at a flow rate of 5.0 ml/s. The test group used GSI. With a tube current fixed of 445 mAs and a detector width of 80 mm, the contrast agent was injected at a flow rate of 3.5 ml/s and 0.6 ml/kg body weight, and the 55 keV virtual monoenergetic images (VMIs) were automatically reconstructed. Finally, the target vessel CT values, background noise (BN), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective scores, contrast agent dose, CT dose index volume (CTDIvol), and dose length product (DLP) were recorded. The DLP was converted to the effective dose (ED). RESULTS: The target vessel CT values, BN, SNR, CNR, and subjective scores of the two groups were not statistically significant (all P > 0.05), and the image quality of both groups was the same and met the diagnostic requirements. The contrast agent dose and effective dose (ED) in the test group were approximately 44% and 26% lower than that of the control group, respectively (all P < 0.05). CONCLUSION: In head-neck CTA examination, the Revolution CT GSI combined with an 80 mm wide-body detector can reduce the contrast agent dose and radiation dose while ensuring image quality.

A novel insight for high-rate and low-efficiency glucose metabolism in depression through stable isotope-resolved metabolomics in CUMS-induced rats.

BACKGROUND: Existing research has suggested that depression results in disorders of glucose metabolism in the organism which causing insufficient energy supply. However, the overall changes in glucose metabolism that arise from depression have not been clarified. METHODS: In this study, the depression-like behavior in chronically unpredictable mild stressed rats was investigated, and the fate of glucose was tracked through isotope tracing and mass spectrometry, with a focus on metabolite changes in cecal contents. RESULTS: As indicated by the results, the isotopic results of cecal contents can indicate the metabolic end of the organism. Moreover, the TCA cycle activity was notably reduced, and the gluconeogenesis pathway was abnormally up-regulated in the CUMS-induced rats. The organism expedited other glucose metabolism pathways to make up for the insufficiency of energy. As a result, the activity of the inefficient glycolysis pathway was increased. LIMITATIONS: Existing research has only investigated the metabolism of 13C-glucose, and lipids and proteins have been rarely explored. CONCLUSIONS: The chronic unpredictable mild stress can inhibit the entry of pyruvate into mitochondria in SD rats, such that the activity of TCA is reduced, and insufficient energy supply is caused. The organism is capable of expediting other glucose metabolism rate pathways to make up for the insufficiency of energy, whereas it still cannot compensate for the loss of energy. As a result, CUMS-induced rats exhibited high-rate and low-efficiency glucose metabolism.

An MPA-based optimized grey Bernoulli model for China's petroleum consumption forecasting.

The remarkable prediction of petroleum consumption is of significance for energy scheduling and economic development. Considering the uncertainty and volatility of petroleum system, this paper presents a nonlinear grey Bernoulli model with combined fractional accumulated generation operator to forecast China's petroleum consumption and terminal consumption. The newly designed model introduces a combined fractional accumulated generation operator by incorporating the traditional fractional accumulation and conformable fractional accumulation; compared to the old accumulation, the newly optimized accumulation can enhance flexible ability to excavate the development patterns of time-series. In addition, to further improve the prediction performance of the new model, marine predation algorithm is applied to determine the optimal emerging coefficients such as fractional accumulation order. Furthermore, the proposed model is verified by a numerical example of coal consumption; and this newly established model is applied to predict China's petroleum consumption and terminal consumption. Our tests suggest that the designed ONGBM(1,1,k,c) model outperforms the other benchmark models. Finally, we predict China's petroleum consumption in the following years with the aid of the optimized model. According to the forecasts of this paper, some suggestions are provided for policy-makers in the relevant sectors.

A unique insight for Xiaoyao San exerts antidepressant effects by modulating hippocampal glucose catabolism using stable isotope-resolved metabolomics.

ETHNOPHARMACOLOGICAL RELEVANCE: In traditional Chinese medicine (TCM) theory, depression is an emotional disease, which is thought to be related to stagnation of liver qi and dysfunction of the spleen in transport. Xiaoyao San (XYS) is considered to have the effects of soothing liver-qi stagnation and invigorating the spleen. The spleen has the function to transport and transform nutrients. The liver has also termed the center of energy metabolism in the body. Therefore, exploring the antidepressant effects of XYS from the perspective of energy metabolism may reveal new findings. AIM OF THE STUDY: Glucose catabolism is an important part of energy metabolism. In recent years, several researchers have found that XYS can exert antidepressant effects by modulating abnormalities in glucose catabolism-related metabolites. The previous research of our research group found that the hippocampus glucose catabolism was disordered in depression. However, the antidepressant potential of XYS through modulating the disorders of hippocampal glucose catabolism and the specific metabolic pathways and targets of XYS action were still unknown. The aim of this study was to address the above scientific questions. MATERIALS AND METHODS: In this research, the CUMS (chronic unpredictable mild stress) model was used as the animal model of depression. The antidepressant effect of XYS was evaluated by behavioral indicators. The specific pathways and targets of XYS modulating the disorders of glucose catabolism in the hippocampus of CUMS rats were obtained by stable isotope-resolved metabolomics. Further, the isotope tracing results were also verified by molecular biology and electron transmission electron microscopy. RESULTS: The results demonstrated that XYS pretreatment could significantly improve the depressive symptoms induced by CUMS. More importantly, it was found that XYS could modulate the disorders of glucose catabolism in the hippocampus of CUMS rats. Stable isotope-resolved metabolomics and enzyme activity tests showed that Lactate dehydrogenase (LDH), Pyruvate carboxylase (PC), and Pyruvate dehydrogenase (PDH) were targets of XYS for modulating the disorders of glucose catabolism in the hippocampus of CUMS rats. The Succinate dehydrogenase (SDH) and mitochondrial respiratory chain complex V (MRCC-Ⅴ) were targets of XYS to improve abnormal mitochondrial oxidative phosphorylation in the hippocampus of CUMS rats. XYS was also found to have the ability to improve the structural damage of mitochondria and nuclei in the hippocampal caused by CUMS. CONCLUSIONS: This study was to explore the antidepressant effect of XYS from the perspective of glucose catabolism based on a strategy combining stable isotope tracing, molecular biology techniques, and transmission electron microscopy. We not only obtained the specific pathways and targets of XYS to improve the disorders of glucose catabolism in the hippocampus of CUMS rats, but also revealed the specific targets of the pathways of XYS compared with VLF.

Altered Metabolomics in Bipolar Depression With Gastrointestinal Symptoms.

Objective: Although gastrointestinal (GI) symptoms are very common in patients with bipolar disorder (BD), Few studies have researched the pathomechanism behind these symptoms. In the present study, we aim at elucidate the pathomechanism of GI symptoms in BD through metabolomic analysis. Method: BD patients were recruited from Shanxi Bethune Hospital that divided into two groups, each group assessed with the 24-item Hamilton Depression Rating Scale (HAMD-24) according to the presence or absence of GI symptoms. Healthy controls were recruited from the medical examination center of the same hospital. Differential metabolites were identified and further analyzed using Metabo Analyst 3.0 to identify associated metabolic pathways. Results: There were significantly higher HAMD-24 scores in the GI symptoms group than that of non-GI symptoms group (p = 0.007). Based on metabolomic analysis results, we found that the common disturbances metabolic pathway of both two patients groups was ketone body metabolism, and the unique disturbances metabolic pathways of BD with GI symptoms were fatty acid biosynthesis and tyrosine metabolism, and these changes were independent of dietary habits. Conclusion: BD patients with GI symptoms exhibited disturbances in fatty acid and tyrosine metabolism, perhaps suggesting that the GI symptoms in BD patients are related to disturbances of the gut microbiome. Both groups of patients jointly exhibit disturbances of ketone body metabolism, which may serve as a biomarker for the pathogenesis of BD patients.

Generalized fractional grey system models: The memory effects perspective.

In recent years, grey models based on fractional-order accumulation and/or derivatives have attracted considerable research interest because they offer better performance in handling limited samples with uncertainty than integer-order grey models; however, there remains room for improvement. This paper considers a more flexible and general structure for the fractional grey model by incorporating a generalized fractional-order derivative (GFOD) that complies by memory effects, resulting in the development of a generalized fractional grey model (denoted as GFGM(1,1)). Specifically, we comprehensively analyse the modelling mechanism of the proposed GFGM(1,1) model, involving model parameter estimation and time response function derivation, and discuss the link between the proposed approach and existing special cases. Then, to further improve the efficacy of the proposed approach, four mainstream metaheuristic algorithms are employed to ascertain the orders of fractional accumulation and derivatives. Finally, we carry out a series of simulation studies and a real-world application case to demonstrate the applicability and advantage of the our approach. The numerical results show that GFGM(1,1) outperforms other benchmarks, and some significant insights are obtained from the numerical experiments.

Stable Isotope-Resolved Metabolomics Studies on Corticosteroid-Induced PC12 Cells: A Strategy for Evaluating Glucose Catabolism in an in Vitro Model of Depression.

Depression is a common psychopathological state or mood disorder syndrome. The serious risks to human life and the inadequacy of the existing antidepressant drugs have driven us to understand the pathogenesis of depression from a new perspective. Our research group has found disturbances in glucose catabolism in both depression and nephrotic syndrome. What are the specific metabolic pathways and specificities of glucose catabolism disorders caused by depression? To address the above scientific questions, we creatively combined traditional metabolomics technology with stable isotope-resolved metabolomics to research the glucose catabolism of the corticosterone-induced PC12 cell damage model and the adriamycin-induced glomerular podocyte damage model. The results showed an increased flux of pyruvate metabolism in depression. The increased flux of pyruvate metabolism led to an activation of gluconeogenesis in depression. The disturbed upstream metabolism of succinate caused the tricarboxylic acid cycle (TCA cycle) to be blocked in depression. In addition, there were metabolic disturbances in the purine metabolism and pentose phosphate pathways in depression. Compared with nephrotic syndrome, pyruvate metabolism, the TCA cycle, and gluconeogenesis metabolism in depression were specific. The metabolic pathways researched above are likely to be important targets for the efficacy of antidepressants.

Forecasting fuel combustion-related CO2 emissions by a novel continuous fractional nonlinear grey Bernoulli model with grey wolf optimizer.

Foresight of CO2 emissions from fuel combustion is essential for policy-makers to identify ready targets for effective reduction plans and to further improve energy policies and plans. A new method for forecasting the future development of China's CO2 emissions from fuel combustion is proposed in this paper by using grey forecasting theory. Although the existing fractional nonlinear grey Bernoulli model (denoted as FNGBM(1,1)) has been theoretically proven to enhance the adaptability to diverse sequences, its fixed integer-order differential derivative still impairs the performance to some extent. To this end, a varying-order differential derivative is introduced into the existing differential equation to enable a more flexible structure, thus improving the prediction ability of FNGBM(1,1). Specifically, because of the advantages of conformable fractional accumulation, the traditional differential derivative is first replaced by the conformable fractional differential derivative. As a consequence, the continuous conformable fractional nonlinear grey Bernoulli model (hereinafter referred to as CCFNGBM(1,1)) is proposed. To further increase the validity of the model, a metaheuristic algorithm, namely Grey Wolf Optimizer (GWO), is then applied to search for the optimal emerging coefficients for the proposed model. Two real examples and China's CO2 emissions from fuel combustion are considered to verify the effectiveness of the newly proposed model, the experimental results show that the newly proposed model outperforms other benchmark models in terms of forecasting accuracy. The proposed model is finally employed to forecast the future China's CO2 emissions from fuel combustion by 2023, accounting for 10,039.80 million tons. Based on the forecasts, several policy suggestions are provided to curb CO2 emissions.

[Effect of surgical manipulation on the dissemination of cancer cells into peripheral blood in patients with gastric cancer and its risk factor analysis].

OBJECTIVE: To evaluate the effect of surgical manipulation on the dissemination of cancer cells into blood circulation in patients with gastric cancer and to analyze its risk factors. METHODS: This study included 45 consecutive patients with gastric cancer undergoing curative resection and 13 control cases (10 healthy persons and 3 patients with peptic ulcer receiving gastrectomy). Peripheral blood was obtained preoperatively and just after surgical manipulation. The mRNA levels of carcinoembryonic antigen (CEA) from the blood samples were assayed by reverse transcription-polymerase chain reaction(RT-PCR) and compared between the 2 groups. RESULTS: CEA mRNA was negative in all control cases. Of the 45 gastric cancer patients, the preoperative positive rate of CEA mRNA was 8.9%, while the postoperative positive rate was 48.9%, which was significantly higher than that of preoperation (P=0.000). Multivariable Logistic regression analysis showed that operative duration (P=0.014) and tumor depth (P=0.010) were independent risk factors for cancer cell dissemination. Furthermore, the operative duration in patients with positive postoperative CEA mRNA was markedly longer than that in patients with negative postoperative CEA mRNA (P=0.000), and positive rate of postoperative CEA mRNA in advanced gastric cancer was higher compared with that in early gastric cancer (P=0.034). CONCLUSIONS: Surgical manipulation of curative gastrectomy can provoke dissemination of cancer cells into blood circulation, and the operative duration and tumor invasion depth may be 2 of the risk factors for cancer cell dissemination.