Fish oil omega-3 Fatty Acids Alleviate Postoperative delirium-like Behavior in aged mice by Attenuating Neuroinflammation and Oxidative Stress.

Postoperative delirium (POD) is a common and serious neuropsychiatric syndrome among older patients, and lacks effective therapies. Omega-3 fatty acids, possessing anti-inflammatory and antioxidant properties, have shown potent neuroprotective effects in several diseases. The present study investigated whether omega-3 fatty acids could exert a neuroprotective role against POD in aged mice. A mouse model of POD was established to explore the role of omega-3 fatty acids in laparotomy-induced delirium-like behavior by evaluating systemic inflammatory changes, neuroinflammation, oxidative stress, and behavior at different time points in aged mice. Oral gavage with omega-3 fatty acids (300 mg/kg) for 3 weeks before surgery significantly attenuated anesthesia/surgery-induced POD-like behavior and the accumulation of proinflammatory cytokines from the peripheral blood in aged mice. Moreover, it also remarkably mitigated neuroinflammation and the oxidative stress response (malondialdehyde [MDA] and superoxide dismutase [SOD]) in the prefrontal cortex and hippocampus of surgical mice. Our findings provided evidence that pretreatment with omega-3 fatty acids may play a vital role in the treatment of POD through mechanisms involving its anti-inflammatory and antioxidant effects, which may be a promising prevention strategy for POD in aged patients.

A Traditional Chinese Medicine Syndrome Classification Model Based on Cross-Feature Generation by Convolution Neural Network: Model Development and Validation.

BACKGROUND: Nowadays, intelligent medicine is gaining widespread attention, and great progress has been made in Western medicine with the help of artificial intelligence to assist in decision making. Compared with Western medicine, traditional Chinese medicine (TCM) involves selecting the specific treatment method, prescription, and medication based on the dialectical results of each patient's symptoms. For this reason, the development of a TCM-assisted decision-making system has lagged. Treatment based on syndrome differentiation is the core of TCM treatment; TCM doctors can dialectically classify diseases according to patients' symptoms and optimize treatment in time. Therefore, the essence of a TCM-assisted decision-making system is a TCM intelligent, dialectical algorithm. Symptoms stored in electronic medical records are mostly associated with patients' diseases; however, symptoms of TCM are mostly subjectively identified. In general electronic medical records, there are many missing values. TCM medical records, in which symptoms tend to cause high-dimensional sparse data, reduce algorithm accuracy. OBJECTIVE: This study aims to construct an algorithm model compatible for the multidimensional, highly sparse, and multiclassification task of TCM syndrome differentiation, so that it can be effectively applied to the intelligent dialectic of different diseases. METHODS: The relevant terms in electronic medical records were standardized with respect to symptoms and evidence-based criteria of TCM. We structuralized case data based on the classification of different symptoms and physical signs according to the 4 diagnostic examinations in TCM diagnosis. A novel cross-feature generation by convolution neural network model performed evidence-based recommendations based on the input embedded, structured medical record data. RESULTS: The data set included 5273 real dysmenorrhea cases from the Sichuan TCM big data management platform and the Chinese literature database, which were embedded into 60 fields after being structured and standardized. The training set and test set were randomly constructed in a ratio of 3:1. For the classification of different syndrome types, compared with 6 traditional, intelligent dialectical models and 3 click-through-rate models, the new model showed a good generalization ability and good classification effect. The comprehensive accuracy rate reached 96.21%. CONCLUSIONS: The main contribution of this study is the construction of a new intelligent dialectical model combining the characteristics of TCM by treating intelligent dialectics as a high-dimensional sparse vector classification task. Owing to the standardization of the input symptoms, all the common symptoms of TCM are covered, and the model can differentiate the symptoms with a variety of missing values. Therefore, with the continuous improvement of disease data sets, this model has the potential to be applied to the dialectical classification of different diseases in TCM.

Capture and recover dissolved phosphorous from aqueous solutions by a designer biochar: Mechanism and performance insights.

Excessive phosphorus (P) in marine and freshwater systems has been identified as a primary perpetrator for the harmful and nuisance algal blooms. In this study, a novel designer biochar was produced from sawdust biomass treated with lime sludge prior to pyrolysis. The adsorption of dissolved P on the designer biochar was comprehensively evaluated under different experimental conditions. It revealed that the removal of dissolved P by the designer biochar was more efficient than unmodified biochar, lime sludge, and their post-combination, suggesting that the pretreatment of biomass with lime sludge for the designer biochar production has a significantly synergic effect on enhancing P removal. Post-adsorption characterization and mathematical modeling analyses indicated that the adsorption of dissolved P on the designer biochar could be controlled by multiple mechanisms including physical and chemical adsorption. The precipitation reaction between P anions and metal ions on the surface of the designer biochar was identified as a predominant mechanism. The X-ray diffraction showed that the precipitation reaction generated a series of P fertilizer forms depositing onto the designer biochar. In addition, batch adsorption experiments showed that both initial solution pH and coexisting anions had a lesser effect on the P removal by the designer biochar. This study proposed that the designer biochar could be a promising sorbent to remove dissolved P, and the nutrient-captured biochar could be used as a fertilizer to recover nutrients.

Antitumor effect and mechanism of action of a tumor-targeting recombinant human tumor necrosis factor-α fusion protein mediated by urokinase.

The aim of this study was to investigate the effect of the tumor­targeting recombinant human tumor necrosis factor (rhTNF)­α fusion protein mediated by urokinase on Sl80 tumor­bearing mice, as well as to explore its mechanisms of action. Furthermore, the study aimed to observe the effect of the protein on liver and kidney function. rhTNF­α fusion protein prokaryotic expression vectors were constructed using genetic engineering techniques, and were introduced into Escherichia coli. Expression of the fusion protein was induced, and it was then separated and purified in order to determine its cytotoxic activity on L929 cells. Kunming mice were randomly divided into four groups after being inoculated with S180 tumor cells. The groups were then injected with saline (control group, group S), or saline with 0.1 µg/ml fusion protein (low dose group, group L), 0.2 µg/ml fusion protein (middle dose group, group M) or 0.3 µg/ml (high dose group, group H). The mice were sacrificed after 12 days and liver [mg/kg; (liver weight/body weight) x 1,000] and kidney [mg/kg; (kidney weight/body weight) x 1,000] indices, tumor weight, the percentage reduction in mean tumor size, and the levels of alanine transaminase (ALT), albumin (ALB), creatinine (Cr) and blood urea nitrogen (BUN) in each group of mice were determined. In addition, the levels of urokinase­type plasminogen activator (uPA), the expression of bcl­2, bax and vascular endothelial growth factor (VEGF), and the percentage of apoptotic cells were measured with an enzyme­linked immunosorbent assay, streptavidin­biotin complex of immunohistochemistry and terminal deoxynucleotidyl transferase­mediated dUTP nick end labeling, respectively. The fusion protein significantly inhibited the growth of S180 tumor cells in vivo in a dose­dependent manner. With an increase in the dose of fusion protein, ALT, uPA, bcl­2 and VEGF levels decreased, and ALB levels increased. However, liver and kidney indices and bax expression were not significantly altered. Cr and BUN levels did not change significantly in the low and middle dose groups, but did increase in the high dose group. Compared with the control group, the percentage of apoptotic cells in the high­dose group was significantly higher. In conclusion, the fusion protein significantly inhibited S180 tumor growth in a mouse model, possibly by reducing the levels of uPA, bcl­2 and VEGF. There was a mildly toxic effect on the kidneys with the high dose, but a protective effect in the liver.