Search

Objective To investigate the role of plasma chromogranin A (CgA) and free metanephrines (MNs) levels in the diagnosis of pheochromocytoma (PHEO). Methods The clinical data of 26 patients with PHEO (PHEO group) and 31 patients with other adrenal tumors (non-PHEO group) admitted to Shanxi Bethune Hospital from January 2021 to January 2023 were analyzed retrospectively. The preoperative plasma CgA levels were compared between PHEO patients and non-PHEO patients, and the changes of plasma CgA levels of PHEO patients were compared between postoperative and preoperative. The receiver operating characteristic curve (ROC curve) was used to analyze the diagnostic efficacy of the plasma CgA，MNs levels and their combination on PHEO. Results Preoperative plasma CgA level of patients in the PHEO group was significantly higher than that in the non-PHEO group ［(647.8±196.2) ng/mL vs (96.4±34.1) ng/mL， t=14.15， P＜0.01］. Compared to the preoperative level, the postoperative plasma CgA in the PHEO group was significantly reduced ［(114.8±60.5) ng/mL vs (647.8±196.2) ng/mL, t=12.78， P＜0.01］. ROC curve analysis results showed that the AUC of CgA and MNs for the diagnosis of PHEO were 0.988 and 0.940, and the cutoff values were 183.1 ng/mL and twice the upper limit of the reference interval,respectively,with sensitivity of 100% and 84.6%, and specificity of 87.1% and 93.5%, respectively; the combined AUC of the two was the highest, at 0.994. Conclusion Plasma CgA levels have a high diagnostic value in patients with PHEO,and can be used as a complementary indicator of plasma MNs for the diagnosis of PHEO to improve diagnostic accuracy."

Purpose – This study aims to ensure the operation safety of high speed trains, it is necessary to carry out nondestructive monitoring of the tensile damage of the gearbox housing material in rail time, yet the traditional tests of mechanical property can hardly meet this requirement. Design/methodology/approach – In this study the acoustic emission (AE) technology is applied in the tensile tests of the gearbox housing material of an high-speed rail (HSR) train, during which the acoustic signatures are acquired for parameter analysis. Afterward, the support vector machine (SVM) classifier is introduced to identify and classify the characteristic parameters extracted, on which basis the SVM is improved and the weighted support vector machine (WSVM) method is applied to effectively reduce the misidentification of the SVM classifier. Through the study of the law of relations between the characteristic values and the tensile life, a degradation model of the gearbox housing material amid tensile is built. Findings – The results show that the growth rate of the logarithmic hit count of AE signals and that of logarithmic amplitude can well characterize the stage of the material tensile process, and the WSVM method can improve the classification accuracy of the imbalanced data to above 94%. The degradation model built can identify the damage occurred to the HSR gearbox housing material amid the tensile process and predict the service life remains. Originality/value – The results of this study provide new concepts for the life prediction of tensile samples, and more further tests should be conducted to verify the conclusion of this research.

Herpes simplex virus (HSV) is the most widely prevalent herpes virus worldwide, and the herpetic encephalitis and genital herpes caused by HSV infection have caused serious harm to human health all over the world. Although many anti-HSV drugs such as nucleoside analogues have been ap-proved for clinical use during the past few decades, important issues, such as drug resistance, toxicity, and high cost of drugs, remain unresolved. Recently, the studies on the anti-HSV activities of marine natural products, such as marine polysaccharides, marine peptides and microbial secondary metabolites are attracting more and more attention all over the world. This review discusses the recent progress in research on the anti-HSV activities of these natural compounds obtained from marine organisms, relating to their structural features and the structure-activity relationships. In addition, the recent findings on the different anti-HSV mechanisms and molecular targets of marine compounds and their potential for therapeutic application will also be summarized in detail.

The existing deep learning based shovel detection methods fail to balance detection speed and precision well. In order to solve the above problem, an improved YOLOv7 model is proposed and applied to mining shovel detection. This model is based on the YOLOv7 model, using a lightweight GhostNet network for feature extraction in the backbone network. This model replaces some ordinary convolutions with lightweight GSConv in the neck network to reduce the number of model parameters and computation, and improve the detection speed of the model. Considering the impact of reduced model parameters on feature information extraction capability after lightweight improvement, the neck network is further improved without increasing computational complexity. The coordinate attention mechanism (CA) is embedded in the extended efficient layer aggregation network (ELAN). The bidirectional feature pyramid network (BiFPN) is used to improve path aggregation network (PANet) to enhance the network's capability to extract feature information. Furthermore, it effectively improves the precision of model detection. The experimental results show that compared with the YOLOv7 model, the improved YOLOv7 model reduces the number of parameters by 75.4%, reduces the number of floating-point operations per second by 82.9%, and improves the detection speed by 24.3%. Compared with other object detection models, the improved YOLOv7 model achieves a good balance between detection speed and precision, meeting the demand for real-time and accurate detection of electric shovels in open-pit coal mine scenarios. It provides favorable conditions for embedding into mobile devices.

C50H32Cl6F4N4O4, triclinic, P1‾ $P\overline{1}$ (no. 2), a = 6.6447(6) Å, b = 12.5839(11) Å, c = 14.3335(11) Å, α = 85.845(7)°, β = 85.679(7)°, γ = 85.679(7)°, V = 1188.89(18) Å3, Z = 1, R gt(F) = 0.0605, wR ref(F 2) = 0.1740, T = 200 K.

C49H36N4O4Cl2, triclinic, P1‾$P\overline{1}$ (no. 2), a = 6.3858(2) Å, b = 12.6484(4) Å, c = 12.7115(5) Å, α = 95.986(3)°, β = 102.790(3)°, γ = 95.563(3)°, V = 988.12(6) Å3, Z = 1, Rgt(F) = 0.0603, wRref(F2) = 0.1683, T = 150 K.

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world, which is distinguished by the loss of dopaminergic (DA) neurons in the substantia nigra and the formation of intraneuronal. Numerous studies showed that the damage and dysfunction of mitochondria may play key roles in DA neuronal loss. Thus, it is necessary to seek therapeutic measures for PD targeting mitochondrial function and biogenesis. In this study, through screening the purchased compound library, we found that marine derived vidarabine had significant neuroprotective effects against rotenone (ROT) induced SH-SY5Y cell injury. Further studies indicated that vidarabine pretreatment significantly protected ROT-treated SH-SY5Y cells from toxicity by preserving mitochondrial morphology, improving mitochondrial function, and reducing cell apoptosis. Vidarabine also reduced the oxidative stress and increased the expression levels of PGC-1α, NRF1, and TFAM proteins, which was accompanied by the increased mitochondrial biogenesis. However, the neuroprotective effects of vidarabine were counteracted in the presence of SIRT1-specific inhibitor Ex-527. Besides, vidarabine treatment attenuated the weight loss, alleviated the motor deficits and inhibited the neuronal injury in the MPTP induced mouse model. Thus, vidarabine may exert neuroprotective effects via a mechanism involving specific connections between the SIRT1-dependent mitochondrial biogenesis and its antioxidant capacity, suggesting that vidarabine has potential to be developed into a novel therapeutic agent for PD.

The hygrothermal aging of T800 carbon fiber/epoxy resin composites in seawater environment were studied. The prepared specimens were immersed in artificial seawater 70 ℃, 3.5% NaCl solution for 30, 60 and 90 days for corrosion. The mechanical properties of the materials were analyzed by mass change, surface morphology before and after aging, infrared spectroscopy, dynamic mechanical properties, compression test and interlayer shear test. The results show that the moisture absorption rate of T800 carbon fiber/epoxy resin matrix composites in 3.5% NaCl solution is 0.39%, 0.47%, 0.53%. Good adhesion between unaging sample fiber and matrix, and the damage of the interface between the fiber and the matrix become more serious with the increase of time after aging in 3.5% NaCl solution. The glass transition temperature(Tg) is decreased from 189.16 ℃ to 177.54, 171.88 ℃ and 168.06 ℃ after 30, 60 and 90 days aging. After aging with 3.5%NaCl solution, the maximum compressive failure load of specimens for 30, 60 and 90 days is decreased by 3.2%, 8.4% and 15.3%, respectively, and the compressive strength is decreased by 3.0%, 8.2% and 15.9%, respectively. The maximum interlaminar shear failure load is reduced by 3.0%, 9.2% and 14.9%, and the shear strength is reduced by 3.0%, 9.7% and 16.4%, respectively.

Ischemic stroke (IS) is a prevalent form of stroke and a leading cause of mortality and disability. Recently, cell membrane-derived nanovehicles (CMNVs) derived from erythrocytes, thrombocytes, neutrophils, macrophages, neural stem cells, and cancer cells have shown great promise as drug delivery systems for IS treatment. By precisely controlling drug release rates and targeting specific sites in the brain, CMNVs enable the reduction in drug dosage and minimization of side effects, thus significantly enhancing therapeutic strategies and approaches for IS. While there are some reviews regarding the applications of CMNVs in the treatment of IS, there has been limited attention given to important aspects such as carrier construction, structural design, and functional modification. Therefore, this review aims to address these key issues in CMNVs preparation, structural composition, modification, and other relevant aspects, with a specific focus on targeted therapy for IS. Finally, the challenges and prospects in this field are discussed.

Upon the current requirement of the extreme weather forecast and service, we developed two improved prediction schemes (that is, schemeⅠ and scheme Ⅱ) based on the ECMWF-IFS model (EC model) and the model output statistics (MOS) method on the basis of the Anolog Ensemble (AnEn) method. First, taking the EC model forecasts from 2016 to 2018 and their corresponding observations as the training dataset, the overall performance of schemeⅠ, scheme Ⅱ, and AnEn for the extreme temperature and wind speed in Beijingfrom January 1 to December 31 in 2019 is tested and evaluated against the observations at 364 stations. The results show that the prediction accuracy of schemeⅠ and scheme Ⅱ is better than that of AnEn for both extreme temperature (T) and wind speed (VM), particularly for scheme Ⅱ. Second, according to the 2nd and 98th percentiles, the thresholds of extreme low temperature (Tm) and extreme high temperature (TM) at the different stations in Beijing are -22.3 ℃ and 38.8 ℃, respectively. The overall prediction results of schemeⅠ and scheme Ⅱ for T in this region show that the two schemes are significantly improved compared to AnEn, and their mean absolute errors (EMA) are reduced by 11.90% and 21.43%, respectively. Similarly, according to the 98th percentile, the VM threshold of each station in Beijing is set at 20.3 m·s-1, and the EMA of VM forecast with schemeⅠ and scheme Ⅱ is reduced by 23.08% and 26.52%, respectively, compared with AnEn. Finally, the prediction results of Tm, TM and VM at each station in Beijing show that schemeⅠ and scheme Ⅱ have improved in T and VM on the basis of AnEn, and more than 94% of stations show that scheme Ⅱ has better performance. In addition, the spatial distributions of prediction accuracy of T and VM show that the two improved schemes have better performance on the prediction of T and VM in the mountainous areas than in the plain areas.

【Objective】 Frost heave is a hazard damaging canals constructed in frozen soils with shallow groundwater table. Taking trapezoidal canals with arc bottoms as an example, this paper investigated the mechanisms underlying the formation of frost heave and its dependance on groundwater table depth. 【Method】 The analysis was based on the Winkler assumption and that the height of the arc was much less than overall depth of the canal. We proposed a method to calculate the variation of normal force over the frost heave force, as well as the distribution of tangential freezing force over the curved segments of the canal linings. A mechanical model was constructed to analyze the damages caused by frost heave. 【Result】 The transverse difference in the distribution of the sectional internal force and the frost heave force both increased as the depth of groundwater table decreased. The effect of groundwater table depth on distribution of the sectional internal force and frost heave force decreased as the depth of the groundwater table increased. Adequate time and source for water recharge and transversely uneven distribution of frost heave force are the main cause of frost heave damage to the canals. 【Conclusion】 The proposed model describes the mechanical characteristic of the canals due the impact of frost heave reasonably well, and the calculated are accurate and reliable. The proposed method and results provide a tool to help design canals to improve the resistance against frost heave damages.

Based on hourly station precipitation data and ECMWF ERA5 reanalysis data from 2009 to 2019, this paper explores the temporal variations and spatial distribution of short–duration heavy rainfall (SDHR) induced by North China cold vortices (NCCV) over the Beijing-Tianjin-Hebei (BTH) region, and comparatively analyzes the characteristic of environmental parameters and then choose some predictors to make probability forecasting for short–duration heavy rainfall induced by North China cold vortices. Results show that short–duration heavy rainfall has obviously interannual, monthly and diurnal variations. Areas of high short–duration heavy rainfall frequency caused by North China cold vortices exhibit eastward movement, which generally locate along the mountain areas of the Beijing-Tianjin-Hebei region in the afternoon, and moves to the coastal areas of the Beijing-Tianjin-Hebei region after midnight. In general, short–duration heavy rainfall induced by North China cold vortices mainly occurs in 16:00–21:00 and around 02:00–05:00, showing a delayed peak time and a secondary peak time in recent years. Besides, short–duration heavy rainfall caused by North China cold vortices occurs fewer but more extremely over the northwestern and southern parts of the Beijing-Tianjin-Hebei region, more frequently and extremely over the border area of the Beijing-Tianjin-Hebei region, and more frequently but with moderate intensity over the coastal area of the Beijing-Tianjin-Hebei region. By comparing the distribution characteristics of some physical parameters for three categories of no precipitation, ordinary precipitation, and short–duration heavy rainfall weather induced by North China cold vortices, it is found that moisture and atmospheric instability conditions have great significance for the occurrence of short–duration heavy rainfall caused by North China cold vortices. Probability forecast for short–duration heavy rainfall caused by North China cold vortices is made based on ingredient method and fuzzy logic algorithms. The result shows the products have good performance, further implying the significance of the environmental parameters for forecasting short–duration heavy rainfall caused by North China cold vortices.

Altered glycan levels in serum have been associated with increased risk of cancer. In this study, we have developed and validated a HPLC-based method to analyze monosaccharide composition (D-mannose, Glucosamine, Galactosamine, Glucuronic acid, D-glucose, D-galactose, D-xylose, L-fucose) in human serum, with L-rhamnose, being used as internal standard. Monosaccharides obtained from hydrolyzed serum samples were derivatized by 1-Phenyl-3-methyl-5-pyrazolone. A ZORBAX XDB-C18 column(150×4.6mm) was used for chromatographic separation with 100 mM ammonium acetate buffer (NH4Ac-HAc, PH=5.5, solvent A), acetonitrile (ACN, solvent B) as a mobile phase. The calibration standard curves for the eight monosaccharides showed good linearity over the range of 2.5-500μg/mL with R2 > 0.995. The relative standard deviation values for intra-day and inter-day precision were ≤ 5.49%. Recovery was 69.01-108.96%. We observed that this column exhibited high specificity and selectivity to separate monosaccharides from serum. This method was then applied to quantitatively analyze the serum monosaccharide levels in 30 patients with endometrial cancer and 30 matched healthy controls. Statistical analysis indicated that the serum monosaccharide levels were significantly higher in patients compared with healthy controls (P value< 0.0001). Overall, we report here a simple, reliable, low-cost, and reproducible HPLC method for the separation and quantification monosaccharides in the human serum, which has potential value to serve as a screening marker for endometrial cancer.

Ensemble prediction systems (EPSs) serve as a popular technique to provide probabilistic precipitation prediction in short- and medium-range forecasting. However, numerical models still suffer from imperfect configurations associated with data assimilation and physical parameterization, which can lead to systemic bias. Even state-of-the-art models often fail to provide high-quality precipitation forecasting, especially for extreme events. In this study, two deep-learning-based models—a shallow neural network (NN) and a deep NN with convolutional layers (CNN)—were used as alternative post-processing approaches to further improve the probabilistic forecasting of precipitation over China with 1–7 lead days. A popular conventional method—the censored and shifted gamma distribution-based ensemble model output statistics (CSG EMOS)—was used as the baseline. Re-forecasts run using a frozen EPS—Global Ensemble Forecast System version 12—were collected as the raw ensembles spanning from 2000 to 2019. The re-forecast data were generated once per day and consisted of one control run and four perturbed members. We used the calendar year 2018 as the validation period and 2019 as the testing period, and the remaining 18 years of data were used for training. According to the results, in terms of the continuous ranked probability score (CRPS) and the Brier score, the CNN model significantly outperforms the shallow NN model, as well as the CSG EMOS approach and the raw ensemble, especially for heavy or extreme precipitation events (those exceeding 50 mm/day). A remarkable degradation was seen when reducing the size of training samples from 18 years of data to two years. The spatial distribution of the CRPS shows that the stations in central China were better calibrated than those in other regions. With a lead time of 1 day, the CNN model was found to be superior to the other models (in terms of the CRPS) at 74.5% of the study stations. These results indicate that deep NNs can serve as a promising approach to the statistical post-processing of probabilistic precipitation forecasting.

Severe wind events which occur in the metropolis of Beijing in China bring major catastrophes. Characteristics of severe winter and spring wind events over Beijing during the past 40 years have been analyzed. An artificial intelligence-based method is adopted to categorize the favorable large-scale circulation patterns and dominant weather systems. Four categories are concluded and compared to each other in terms of distributions of geopotential height at 500 hPa, temperature at 500 hPa, sea level pressure and their corresponding anomalies in 1979–2019. It is found that the first category (T1) which is dominated by strong cold trough at upper levels with strong cold-core high locating at surface is the most conducive circulation pattern, while the fourth category (T4) which is controlled by weak trough and strong ridge with strong low cyclone at surface is the least one. The second and third categories, represented by T2 and T3, are under the control of strong cold trough and warm ridge at upper levels with weak high at surface, and of weak trough and strong ridge with strong low cyclone at surface, respectively. Characteristics and differences under different backgrounds of global temperatures are analyzed by separating the past 40years into two distinct periods. The decreasing trends of intensities of the trough and ridge, the temperature at 500hPa, together with the surface systems, are found to be responsible for the decrease in severe wind events in T1, T2 and T3 in the last 20 years, while T4 is distinct to the other three categories with little change in its circulation pattern, and thus continues contributing to the severe wind events over Beijing. The results found in this study with the usage of an AI-based algorithm will benefit for the operational forecasting for extreme wind events over Beijing.

Genital herpes is a common sexually transmitted disease mainly caused by herpes simplex virus type 2 (HSV-2), which can increase the risk of HIV transmission and is a major health problem in the world. Thus, it is of great significance to develop new anti-HSV-2 drugs with high efficiency and low toxicity. In this study, the anti-HSV-2 activities of PSSD, a marine sulfated polysaccharide, was deeply explored both in vitro and in vivo. The results showed that PSSD had marked anti-HSV-2 activities in vitro with low cytotoxicity. PSSD can directly interact with virus particles to inhibit the adsorption of virus to the cell surface. PSSD may also interact with virus surface glycoproteins to block virus-induced membrane fusion. Importantly, PSSD can significantly attenuate the symptoms of genital herpes and weight loss in mice after gel smear treatment, as well as reducing the titer of virus shedding in the reproductive tract of mice, superior to the effect of acyclovir. In summary, the marine polysaccharide PSSD possesses anti-HSV-2 effects both in vitro and in vivo, and has potential to be developed into a novel anti-genital herpes agent in the future.

IntroductionEarly diagnosis could lead to a cure of colorectal cancer (CRC). Since CRC is related to aging and lifestyles, we tested if the environmental information-enriched monosaccharide composite (MC) of circulating glycans could serve as an early diagnostic biomarker for CRC. Meanwhile, we evaluated its role in predicting prognosis.MethodsHPAEC-PAD was used to quantify glycan monosaccharide compositions from a total of 467 serum samples including CRC patients, colorectal adenoma (CRA) patients and healthy individuals. Two diagnostic model was constructed by logistic regression analysis. The diagnostic performance of the two models was verified in the retrospective validation group and the prospective validation group. The prognostic performance of the model was assessed by survival analysis.ResultsThe concentrations of monosaccharides in serum were significantly higher in CRA and CRC patients than in healthy individuals. Two diagnostic models were constructed: MC1 was used to distinguish between healthy individuals and CRC; MC2 was used to distinguish between healthy individuals and CRA. Area under receptor operating characteristic curve (AUC) of MC2 and MC1 was 0.8025 and 0.9403 respectively. However, the AUC of CEA between healthy individuals and CRC was 0.7384. Moreover, in early stage of CRC (without lymph node metastasis), the positive rates of CEA and MC1 were 28% and 80%, respectively. The follow-up data showed that the increased MC1 value was associated with poor survival in patients with CRC (p=0.0010, HR=5.30).DiscussionThe MC1 model is superior to CEA in the diagnosis of CRC, especially in the early diagnosis. MC1 can be used for predicting prognosis of CRC patients, and elevated MC1 values indicate poor survival.

Abstract Background Patchouli alcohol (PA) is a tricyclic sesquiterpene extracted from Pogostemonis Herba, which is a traditional Chinese medicine used for therapy of inflammatory diseases. Recent studies have shown that PA has various pharmacological activities, including anti-bacterial and anti-viral effects. Methods In this study, the anti-influenza virus (IAV) activities and mechanisms were investigated both in vitro and in vivo. The inhibitory effects of PA against IAV in vitro were evaluated by plaque assay and immunofluorescence assay. The neuraminidase inhibition assay, hemagglutination inhibition (HI) assay, and western blot assay were used to explore the anti-viral mechanisms. The anti-IAV activities in vivo were determined by mice pneumonia model and HE staining. Results The results showed that PA significantly inhibited different IAV strains multiplication in vitro, and may block IAV infection through inactivating virus particles directly and interfering with some early stages after virus adsorption. Cellular PI3K/Akt and ERK/MAPK signaling pathways may be involved in the anti-IAV actions of PA. Intranasal administration of PA markedly improved mice survival and attenuated pneumonia symptoms in IAV infected mice, comparable to the effects of Oseltamivir. Conclusions Therefore, Patchouli alcohol has the potential to be developed into a novel anti-IAV agent in the future.

In this study, wind forecasts derived from the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environmental Prediction (NCEP), the Japan Meteorological Agency (JMA) and the United Kingdom Meteorological Office (UKMO) are evaluated for lead times of 1–7 days at the 10 m and multiple isobaric surfaces (500 hPa, 700 hPa, 850 hPa and 925 hPa) over North China for 2020. The straightforward multimodel ensemble mean (MME) method is utilized to improve forecasting abilities. In addition, the forecast errors are decomposed to further diagnose the error sources of wind forecasts. Results indicated that there is little difference in the performances of the four models in terms of wind direction forecasts (DIR), but obvious differences occur in the meridional wind (U), zonal wind (V) and wind speed (WS) forecasts. Among them, the ECMWF and NCEP showed the highest and lowest abilities, respectively. The MME effectively improved wind forecast abilities, and showed more evident superiorities at higher levels for longer lead times. Meanwhile, all of the models and the MME manifested consistent trends of increasing (decreasing) errors for U, V and WS (DIR) with rising height. On the other hand, the main source of errors for wind forecasts at both 10 m and isobaric surfaces was the sequence component (SEQU), which rose rapidly with increasing lead times. The deficiency of the less proficient NCEP model at the 10 m and isobaric surfaces could mainly be attributed to the bias component (BIAS) and SEQU, respectively. Furthermore, the MME tended to produce lower SEQU than the models at all layers, which was more obvious at longer lead times. However, the MME showed a slight deficiency in reducing BIAS and the distribution component of forecast errors. The results not only recognized the model forecast performances in detail, but also provided important references for the use of wind forecasts in business departments and associated scientific researches.

C33H28N10O, triclinic, P1̄ (no. 2), a = 14.7148(9) Å, b = 15.5185(10) Å, c = 16.1128(9) Å, α = 113.219(6)°, β = 96.735(5)°, γ = 115.259(6)°, V = 2872.0(3) Å3, Z = 4, Rgt(F) = 0.0426, wRref(F2) = 0.1108, T = 150(2) K.

C38H39N13O8Zn, monoclinic, P21/c (no. 14), a = 13.0155(7) Å, b = 32.7011(14) Å, c = 9.8464(4) Å, β = 110.228(1)°, V = 3932.4(3) Å3, Z = 4, Rgt(F) = 0.0476, wRref(F2) = 0.1358, T = 150(2) K.

[Introduction] The paper aims to reduce the intermittent, random, uncontrollable effects of DERs capacity represented by wind and solar energy, and to participate in the competition in the power market, a community-based energy Internet model is proposed. [Method] Considering a community-based energy Internet model consisting of a virtual power plant (VPP) cluster consisting of a wind farm, a photovoltaic power station, and a load, interconnecting a single VPP, and based on the balance of supply and demand within a single VPP, the surplus power game sharing through VPP clusters, and finally trading with the electricity market to achieve reverse sales. [Results] The results we obtained demonstrate that the goal of maximizing the benefits of community-based energy Internet, and adding demand response (DR) to achieve the purpose of saving electricity for users. [Conclusion] This work through the community energy Internet demonstration project, the VPP operation strategy model is proposed, and the feasibility of verifying the power generation strategy in different scenarios is established through the established benefits, which indicates the direction for the construction and transaction of the community energy Internet.

Agaro-oligosaccharides, hydrolysates of agarose isolated from red algae, were reported to possess various biological functions and activities, including anti-bacteria, anti-inflammatory and anti-oxidative properties. In this study, the potential neuroprotective effects and underlying molecular mechanisms of agaro-oligosaccharides against neurotoxicity induced by 6-hydroxydopamine in SH-SY5Y cells were explored. The results indicated that pretreatment with agaro-oligosaccharide monomers especially agaropentaose (AOP) considerably enhanced the cell viability and the activities of antioxidant enzymes in SH-SY5Y cells treated by 6-hydroxydopamine. In addition, AOP markedly reduced intracellular reactive oxygen species level and inhibited the loss of mitochondrial membrane potential. Moreover, NF-κB and p38MAPK signaling pathways associated with neuroinflammation were significantly down-regulated by pretreatment with AOP. These findings reflected the protective effects and mechanisms of AOP against neurologic damage in SH-SY5Y cells induced by 6-hydroxydopamine. Hence the marine-derived agaropentaose merits further study as a novel functional food additive or therapeutic agent against some neuronal diseases.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Background/Aims: Genistein is a natural isoflavone enriched in soybeans. It has beneficial effects for patients with mucopolysaccharidose type III through inhibiting glycosaminoglycan biosynthesis. However, other studies indicate that genistein does not always inhibit glycosaminoglycan biosynthesis. Methods: To understand the underlying molecular mechanisms, CHOK1, CHO3.1, CHO3.3, and HCT116 cells were treated with genistein and the monosaccharide compositions and quantity of all glycans from the cell lysate were measured after thorough acid hydrolysis followed by HPLC analysis. In addition, the glycosaminoglycan disaccharide compositions were obtained by stable isotope labeling coupled with LC/MS analysis. Results: Genistein treatment reduced the amount of glycans but increased the amount of glycosaminoglycans in HCT116 cells. In contrast, genistein treatment reduced both glycan and glycosaminoglycan quantities in CHOK1, CHO3.1, and CHO3.3 cells in addition to differential changes in glycosaminoglycan disaccharide compositions. Conclusion: Genistein treatment reduced overall glycan quantity but glycosaminoglycan quantities were either increased or decreased in a cell type-dependent manner.

(NH4)2RuCl6 is an important precursor in the synthesis of Ru powder with high-purity requirement. In this study, high-purity (>99.999 wt%) micro-sized (NH4)2RuCl6 pieces were synthesized by distillation and precipitation from crude Ru powder. Then, the thermal decomposition behavior of the (NH4)2RuCl6 pieces was investigated. The decomposition process included two stages. First, (NH4)2RuCl6 was decomposed from 255.0°C to 314.0°C, with the endothermic peak located at 309.4°C. At this stage, HCl and NH3 were released, while the dense micro-pieces were transformed to loosened micro-pieces due to the thermal decomposition. Then, the solid phase [(NH3)4Ru3Cl12] kept decomposing from 314.0°C to 352.7°C, HCl and N2 were released, and agglomerated Ru particles were achieved. Thermogravimetric analysis-differential thermal analysis-mass spectrum coupling (TG-DTA-MS) was used to monitor the thermal decomposition process and identify the released gaseous phases, respectively. The solid phases in different stages were characterized by high-temperature X-ray diffraction (HTXRD). A good understanding of the processing and thermal decomposition of (NH4)2RuCl6 is crucial in the creation of Ru products.

Background/Aims: Bleomycin is a clinically used anti-cancer drug that produces DNA breaks once inside of cells. However, bleomycin is a positively charged molecule and cannot get inside of cells by free diffusion. We previously reported that the cell surface negatively charged glycosaminoglycans (GAGs) may be involved in the cellular uptake of bleomycin. We also observed that a class of positively charged small molecules has Golgi localization once inside of the cells. We therefore hypothesized that bleomycin might perturb Golgi-operated GAG biosynthesis. Methods: We used stable isotope labeling coupled with LC/MS analysis of GAG disaccharides simultaneously from bleomycin-treated and non-treated cancer cells. To further understand the cytotoxicity of bleomycin and its relationship to GAGs, we used sodium chlorate to inhibit GAG sulfation and commercially available GAGs to compete for cell surface GAG/bleomycin interactions in seven cell lines including CHO745 defective in both heparan sulfate and chondroitin sulfate biosynthesis. Results: we discovered that heparan sulfate GAG was significantly undersulfated and the quantity and disaccharide compositions of GAGs were changed in bleomycin-treated cells in a concentration- and time-dependent manner. We revealed that bleomycin-induced cytotoxicity was directly related to cell surface GAGs. Conclusion: GAGs were targeted by bleomycin both at cell surface and at Golgi. Thus, GAGs might be the biological relevant molecules that might be related to the bleomycin-induced fibrosis in certain cancer patients, a severe side effect with largely unknown molecular mechanism.

The effects of Mg and Ag contents on the corrosion resistance of Al-Cu-Mg-Ag alloy were investigated by intergranular corrosion (IGC) testing. The corrosion mechanism of the alloys with different chemical composition was discussed by transmission electron microscopy (TEM) and electrochemical analyses. The results indicate with increasing Mg and Ag content, the age hardening rate of the alloy increases. The size of the strengthening phases Ω decreases with increasing Mg content whereas phase volume fraction increases. More solution atoms are consumed to form the precipitation on the grain boundaries of the alloy with higher Mg content, which increases the potential difference between precipitation free zone (PFZ) and the matrix and subsequently, the IGC resistance of Al-Cu-Mg-Ag alloy decreases. Increasing the Ag content, the main strengthening phases transform from great amounts of θ' with less Ω to plentiful Ω with less θ'. The variation of Ag content hardly affects the potential of PFZ, and the corrosion resistance of the alloy depends mainly on the width of PFZ. With increasing Ag content, the precipitations on the grain boundaries are refined; the width of PFZ decreases and correspondingly, the corrosion passageway becomes narrow. The IGC resistance of Al-Cu-Mg-Ag alloy is enhanced with increasing Ag content.

C29H22N2O2, triclinic, P1̅ (no. 2), a = 22.4995(6) Å, b = 9.9370(3) Å, c = 21.6466(6) Å, β = 115.941(1)°, V = 4352.1(2) Å3, Z = 4, Rgt(F) = 0.0487, wRref(F2) = 0.1473, T = 296 K.

The washout position has great effects on the perception fidelity and the movement of the motion simulator. In this paper, the main square error of sensation between simulator and vehicle is determined, and the fidelity of the occupant and the platform motion performance as a basis to build a model for a single occupant optimal washout position measurement. Then, considering the features of the multi-occupant motion simulator, a concept of the task’s master-crew is proposed, the multi-occupant optimal washout position measurement model is built. Then an anti-aircraft simulator for three occupants is taken as an example of a multi-occupant simulator and the optimal washout position measurement model is studied. Considering that the basic PSO algorithm has shortcomings such as easy aging and falling into local extreme value, a modified algorithm is designed called Adaptive Chaos PSO algorithm and applied to the resolution of the models. The results showed that the optimal position can make the simulator trainer have a more realistic sensation and maintain the safety of the platform, and that the Adaptive chaos PSO algorithm can effectively solve the shortcomings of PSO and is very useful in the resolution of the model.

Through understanding and comprehension of working principle and structure layout of polyurethane sponge cutting machine, we conduct design and remolding on modeling and appearance of current product. Based on methods such as aesthetic principles of artistic modeling, modular design methods, modeling design methods of mechanical product, remolding and design of overall appearance of machines are studied to realize more modern aesthetics and visual impact of new appearance and promotion of the product’s outward appearance quality.

On the purpose of deepening method research of perceptual analysis, based on the description of the relationship between perceptual design and rational design, the importance of perceptual design in modern product design is clarified. To strengthen the emotional expression of the product, the study focuses on sort perceptual design method with the background of perceptual design internalization and equivalent theory. Taking the perceptual design as the bond, how the method located sensibility in product design is analyzed. By taking advantage of formal beauty rule, more perceptual elements are added into product design to summarize the method and principle based on the product perceptual design.

Astaxanthin, a carotenoid extensively found in marine organisms and increasingly used as a dietary supplement, has been reported to have neuroprotective effect. In this study, the neuroprotective effects and mechanisms of astaxanthin against glutamate-induced neurotoxicity were explored. The results showed that pretreatment with astaxanthin inhibited neuronal PC12 cell death induced by L-glutamate and reduced the production of reactive oxygen species (ROS) significantly. Astaxanthin prevented glutamate-induced apoptosis by depressing the elevation of Bax/Bcl-2 ratio, caspase-3 activation and Ca2+ influx. Moreover, the loss of mitochondrial membrane potential (MMP) as well as the activation of ROS associated NF-κB and MAPK pathways were also inhibited upon treatment with astaxanthin. Therefore, the neuroprotective effects reflected the ability of astaxanthin in the regulation of multiple signaling pathways that protect mitochondria as well as cellular damage induced by L-glutamate. Thus, astaxanthin has the potential to be used as a prophylactic or remediation agent against neuronal disorders.

Chitosan oligosaccharides (COSs), depolymerized products of chitosan composed of β-(1→4) d-glucosamine units, have broad range of biological activities such as antitumour, antifungal, and antioxidant activities. In this study, peracetylated chitosan oligosaccharides (PACOs) and N-acetylated chitosan oligosaccharides (NACOs) were prepared from the COSs by chemcal modification. The structures of these monomers were identified using NMR and ESI-MS spectra. Their antagonist effects against glutamate-induced PC12 cell death were investigated. The results showed that pretreatment of PC12 cells with the PACOs markedly inhibited glutamate-induced cell death in a concentration-dependent manner. The PACOs were better glutamate antagonists compared to the COSs and the NACOs, suggesting the peracetylation is essential for the neuroprotective effects of chitosan oligosaccharides. In addition, the PACOs pretreatment significantly reduced lactate dehydrogenase release and reactive oxygen species production. It also attenuated the loss of mitochondrial membrane potential. Further studies indicated that the PACOs inhibited glutamate-induced cell death by preventing apoptosis through depressing the elevation of Bax/Bcl-2 ratio and caspase-3 activation. These results suggest that PACOs might be promising antagonists against glutamate-induced neural cell death.