In silico and in vivo discovery of antioxidant sea cucumber peptides with antineurodegenerative properties.

Since oxidative stress is often associated with neurodegenerative diseases, antioxidants are likely to confer protection against neurodegeneration. Despite an increasing number of food-derived peptides being identified as antioxidants, their antineurodegenerative potentials remain largely unexplored. Here, a sea cucumber peptide preparation - the peptide-rich fraction of <3 kDa (UF<3K) obtained by ultrafiltration from Apostichopus japonicus protein hydrolyzate - was found to protect PC12 cells and Caenorhabditis elegans from neurodegeneration by reducing oxidative stress and apoptosis, demonstrating its in vitro and in vivo neuroprotective effects. As many food-originated peptides are cryptides (cryptic peptides - short amino acid sequences encrypted in parent proteins) released in quantities by protein hydrolysis, UF<3K was subjected to sequencing analysis. As expected, a large repertoire of peptides were identified in UF<3K, establishing a sea cucumber cryptome (1238 peptides in total). Then 134 peptides were randomly selected from the cryptome (>10%) and analyzed for their antioxidant activities using a number of in silico bioinformatic programs as well as in vivo experimental assays in C. elegans. From these results, a novel antioxidant peptide - HoloPep#362 (FETLMPLWGNK) - was shown to not only inhibit aggregation of neurodegeneration-associated polygluatmine proteins but also ameliorate behavioral deficits in proteotoxicity nematodes. Proteomic analysis revealed an increased expression of several lysosomal proteases by HoloPep#362, suggesting proteostasis maintenance as a mechanism for its antineurodegenerative action. These findings provide an insight into the health-promoting potential of sea cucumber peptides as neuroprotective nutraceuticals and also into the importance of training in silico peptide bioactivity prediction programs with in vivo experimental data.

The protective role of oily fish intake against type 2 diabetes: insights from a genetic correlation and Mendelian randomization study.

Background and aims: Previous research has underscored the association between oily fish intake and type 2 diabetes (T2DM), yet the causality remains elusive. Methods: A bidirectional univariable Mendelian Randomization (MR) analysis was employed to evaluate the causal effects of oily fish and non-oily fish intake on T2DM. Replication analysis and meta-analysis were conducted to ensure robust results. Multivariable MR analysis was utilized to assess confounders, and further mediation MR analysis discerned mediating effects. Linkage Disequilibrium Score (LDSC) analysis was undertaken to compute genetic correlations. Inverse variance weighted (IVW) was the primary method, complemented by a series of sensitivity analyses. Results: The LDSC analysis unveiled a significant genetic correlation between oily fish intake and T2DM (Genetic correlation: -0.102, p = 4.43 × 10-4). For each standard deviation (SD) increase in genetically predicted oily fish intake, the risk of T2DM was reduced by 38.6% (OR = 0.614, 95% CI 0.504 ~ 0.748, p = 1.24 × 10-6, False Discovery Rate (FDR) = 3.72 × 10-6). The meta-analysis across three data sources highlighted a persistent causal association (OR = 0.728, 95% CI 0.593 ~ 0.895, p = 0.003). No other causal effects were identified (all p > 0.5, FDR > 0.5). The main outcomes remained consistent in most sensitivity analyses. Both MVMR and mediation MR analyses emphasized the mediating roles of triglycerides (TG), body mass index (BMI), and 25-hydroxyvitamin D (25OHD) levels. Conclusion: To encapsulate, there's an inverse association between oily fish intake and T2DM risk, suggesting potential benefits of oily fish intake in T2DM prevention.

Modification Strategies for Development of 2D Material-Based Electrocatalysts for Alcohol Oxidation Reaction.

2D materials, such as graphene, MXenes (metal carbides and nitrides), graphdiyne (GDY), layered double hydroxides, and black phosphorus, are widely used as electrocatalyst supports for alcohol oxidation reactions (AORs) owing to their large surface area and unique 2D charge transport channels. Furthermore, the development of highly efficient electrocatalysts for AORs via tuning the structure of 2D support materials has recently become a hot area. This article provides a critical review on modification strategies to develop 2D material-based electrocatalysts for AOR. First, the principles and influencing factors of electrocatalytic oxidation of alcohols (such as methanol and ethanol) are introduced. Second, surface molecular functionalization, heteroatom doping, and composite hybridization are deeply discussed as the modification strategies to improve 2D material catalyst supports for AORs. Finally, the challenges and perspectives of 2D material-based electrocatalysts for AORs are outlined. This review will promote further efforts in the development of electrocatalysts for AORs.

Quantitative determination of multi-class bioactive constituents for quality control of Yiqi Jiangzhi Granules.

Objective: To establish a reliable and sensitive method for evaluating quality of Yiqi Jiangzhi Granules (YQJZG). Methods: Ultra performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS) was employed for simultaneous determination of eight marker components. Separation was performed on an AQUITY UPLC® HSS T3 column, the mobile phase consisted of acetonitrile as the organic phase and 0.1% (volume percentage) formic acid as the aqueous. Eight marker components, ginsenoside Rg1 (GRg1), ginsenoside Re (GRe), ginsenoside Rb1 (Gb1), typhaneoside (TEO), isorhamnetin-3-O-neohespeidoside (IN), hesperidin (HPD), aurantio-obtusin-6-O-ß-D-glucoside (AG) and curcumin (CCM), were detected by multiple reaction monitoring (MRM) mode. The Chinese Pharmacopoeia (2020 edition) was regarded as the guidance document for this method validation. Results: The method showed good linearity (R 2 ≥ 0.9990). The relative standard deviation (RSD) values for the instrument precision, intermediate precision and repeatability were less than 2.91%, 2.88%, and 3.54%, respectively. The average recovery varied from 91.08% to 103.89%, with RSD below 3.81%. Sample solutions were found to be stable within 24 h at 4 °C (RSD < 2.85%). Eight marker components were successfully determined from three batches of YQJZG. Conclusion: The proposed UPLC-ESI-MS/MS method was found to be simple, fast and sensitive, and can be used for the routine quality assessment of YQJZG. Simultaneously, this method may provide a new and powerful tool of quality control for other traditional Chinese medicine analogous formulae.

Cryptochlorogenic acid and its metabolites ameliorate myocardial hypertrophy through a HIF1α-related pathway.

Cryptochlorogenic acid (4-CQA) is a phenolic acid that has antioxidant and anti-inflammatory activities. Our preliminary study found that 4-CQA has a good effect on isoproterenol (ISO)-induced myocardial hypertrophy, while the mechanism remains largely unknown. This study aimed at delineating the metabolites and metabolic pathways of 4-CQA using liquid mass spectrometry and molecular biotechnology, exploring possible active metabolites and the mechanism of myocardial hypertrophy amelioration in H9c2 cells, and finally, investigating the pharmacokinetics of 4-CQA and its active metabolites in vivo. In summary, 56 potential effective metabolites were distinguished in rat urine, feces, plasma samples and heart tissue after intragastric administration of 4-CQA, and the main metabolic reaction types of 4-CQA included hydrogenation, methylation, glucuronidation, sulfation, hydration and their composite reactions in in vivo biotransformation. Besides, 4-CQA and its main active metabolites, caffeic acid and 4-O-feruloylquinic acid, significantly ameliorated pathological cardiac hypertrophy of H9c2 cells treated with ISO based on the Akt/mTOR/HIF-1α pathway. In addition, this study demonstrated that the prototype drugs 4-CQA and 4-O-ferulylquinic acid generally exhibit similar pharmacokinetic characteristics and caffeic acid presents relatively late peak time and low peak concentration in rats, which make them suitable candidate drugs.

SPINK2 is a prognostic biomarker related to immune infiltration in acute myeloid leukemia.

BACKGROUND: Serine peptidase inhibitor Kazal type 2 (SPINK2) has been reported to be involved in certain cancers. We conducted an in-depth investigation on the role and mechanism of SPINK2 in acute myeloid leukemia (AML). METHODS: The relationship between SPINK2 expression and AML clinicopathologic characteristics was determined using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Concomitantly, we used Kaplan-Meier survival analysis, as well as univariate and multivariate regression analyses to evaluate SPINK2 as a prognostic marker of AML. Additionally, we annotated the enrichment and function of SPINK2 using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Sets Enrichment Analysis (GSEA). The CIBERSORT algorithm was used to analyze the relationship between SPINK2 expression and immune infiltration. RESULTS: SPINK2 expression was significantly higher in AML patients compared to healthy individuals (P<0.001). The area under receiver operating characteristic curve in the GSE9476 dataset was 0.660, whereas that in the Genotype-Tissue Expression (GTEx) and TCGA datasets was 0.935. In addition, GSEA also showed that several pathways were enriched in the group with high SPINK2 expression, such as PI3K-AKT signaling, PD-L1 expression, and checkpoint pathways. Analysis of immune infiltration showed that SPINK2 expression was correlated with certain immune infiltrating cells. Cox multivariate analysis revealed that the level of SPINK2 was an independent risk factor for the progression of AML (P<0.001). Moreover, age, M1, M5, M6, and CytoRisk-Poor also affected the progression of AML (P<0.05). The C-index of the nomogram in our internal validation was 0.702. CONCLUSION: The high expression of SPINK2 in AML suggests that SPINK2 may play an important role in the immune microenvironment and thus could be a biomarker for diagnosis and prognosis of AML.

Investigation of mouse hepatitis virus strain A59 inactivation under both ambient and cold environments reveals the mechanisms of infectivity reduction following UVC exposure.

The surface contamination of SARS-CoV-2 is becoming a potential source of virus transmission during the pandemic of COVID-19. Under the cold environment, the infection incidents would be more severe with the increase of virus survival time. Thus, the disinfection of contaminated surfaces in both ambient and cold environments is a critical measure to restrain the spread of the virus. In our study, it was demonstrated that the 254 nm ultraviolet-C (UVC) is an efficient method to inactivate a coronavirus, mouse hepatitis virus strain A59 (MHV-A59). The inactivation rate to MHV-A59 coronavirus was up to 99.99% when UVC doses were 2.90 and 14.0 mJ/cm2 at room temperature (23 °C) and in cold environment (-20 °C), respectively. Further mechanistic study demonstrated that UVC could induce spike protein damage to partly impede virus attachment and genome penetration processes, which contributes to 12% loss of viral infectivity. Additionally, it can induce genome damage to significantly interrupt genome replication, protein synthesis, virus assembly and release processes, which takes up 88% contribution to viral inactivation. With these mechanistic understandings, it will greatly contribute to the prevention and control of the current SARS-CoV-2 transmissions in cold chains (low temperature-controlled product supply chains), public area such as airport, school, and warehouse.

[Calibration on chromone reference extract and application on quality control of Saposhnikoviae Radix].

The calibration of chromone reference extract(CRE) was conducted and a quality control method of Saposhnikoviae Radix(SR) was established based on CRE. Meanwhile, the quality control system of SR was improved and the feasibility of using reference extract as a substitute for single reference substance in quality control of Chinese medicine was discussed. In this study, the content of the prepared CRE was calibrated with prim-O-glucosylcimifugin, cimifugin, 4'-O-ß-D-glucosyl-5-O-methylvisamminol, and secO-glucosylhamaudol as indicators. Subsequently, an HPLC analytical method was developed to determine the content of four chromones in 20 batches of SR samples based on the CRE with known content as the standard substance. T-test was used for the comparison of the determination results of the two methods(single chemical component and CRE as reference substances, respectively), and the P values of prim-O-glucosylcimifugin, cimifugin, 4'-O-ß-D-glucosyl-5-O-methylvisamminol, and sec-O-glucosylhamaudol were 0. 16,0. 39, 0. 14, and 0. 42. The results demonstrated that there was no significant difference between the two methods. This study initially verified the feasibility that the CRE could be used as a substitute for single reference substance in quality control of SR. In conclusion,this study is expected to provide a scientific basis and a new research model for the application of reference extract in the quality control of Chinese medicine.

A Lightweight Localization Strategy for LiDAR-Guided Autonomous Robots with Artificial Landmarks.

This paper proposes and implements a lightweight, "real-time" localization system (SORLA) with artificial landmarks (reflectors), which only uses LiDAR data for the laser odometer compensation in the case of high-speed or sharp-turning. Theoretically, due to the feature-matching mechanism of the LiDAR, locations of multiple reflectors and the reflector layout are not limited by geometrical relation. A series of algorithms is implemented to find and track the features of the environment, such as the reflector localization method, the motion compensation technique, and the reflector matching optimization algorithm. The reflector extraction algorithm is used to identify the reflector candidates and estimates the precise center locations of the reflectors from 2D LiDAR data. The motion compensation algorithm predicts the potential velocity, location, and angle of the robot without odometer errors. Finally, the matching optimization algorithm searches the reflector combinations for the best matching score, which ensures that the correct reflector combination could be found during the high-speed movement and fast turning. All those mechanisms guarantee the algorithm's precision and robustness in the high speed and noisy background. Our experimental results show that the SORLA algorithm has an average localization error of 6.45 mm at a speed of 0.4 m/s, and 9.87 mm at 4.2 m/s, and still works well with the angular velocity of 1.4 rad/s at a sharp turn. The recovery mechanism in the algorithm could handle the failure cases of reflector occlusion, and the long-term stability test of 72 h firmly proves the algorithm's robustness. This work shows that the strategy used in the SORLA algorithm is feasible for industry-level navigation with high precision and a promising alternative solution for SLAM.

Machine learning-based genetic diagnosis models for hereditary hearing loss by the GJB2, SLC26A4 and MT-RNR1 variants.

BACKGROUND: Hereditary hearing loss (HHL) is the most common sensory deficit, which highly afflicts humans. With gene sequencing technology development, more variants will be identified and support genetic diagnoses, which is difficult for human experts to diagnose. This study aims to develop a machine learning-based genetic diagnosis model of HHL-related variants of GJB2, SLC26A4 and MT-RNR1. METHODS: This case-control study included 1898 subjects, among which 1354 were HHL patients and 544 were carriers. Risk assessment models were established based on variants at 144 sites in three genes related to HHL by building six machine learning (ML) models. We compared the ML models with the genetic risk score (GRS) and expert interpretation (EI) to verify the clinical performance. FINDINGS: Among the six ML models, the support vector machine (SVM) showed the best performance. For the prediction of HHL-related gene sites in subjects with variants, the area under the receiver operating characteristic (AUC) of the SVM model was 0.803 (0.680-0.814) in the 10-fold stratified cross-validation and 0.751 (0.635-0.779) in external validation. The predicted results were better than both EI and GRS. Furthermore, 11 sites were identified as the smallest feature set that can be accurately predicted. INTERPRETATION: The developed SVM model has great potential to be an efficient and effective tool for HHL prediction when high throughput sequencing data are available. FUNDING: This study was supported by the National Key Research and Development Program (2017YFC1001800).

[Study on scrophulariaceae radix reference extract and its application in quality control of Scrophulariae Radix].

By establishing the preparation process of Scrophulariaceae Radix reference extract(SRRE) and calibrating it, we discussed its feasibility as a substitute for single reference substance in the quality control of Scrophulariae Radix. The SRREs were prepared by solvent extraction method and chromatographic separation technology, and then calibrated with the reference substances of harpagide, angoroside C and harpagoside. The HPLC content determination method of Scrophulariae Radixl was established with SRREs of the known content and the reference substances of harpagide, angoroside C and harpagoside respectively as the control ones. Then the content of three components in Scrophulariae Radix was determined, and the t-test method was used to compare the results of the two methods. With SRRE as references, harpagide, angoroside C and harpagoside were in a good linear relationship(r≥0.999 8) within each range, and the average recovery rate was 98.55% to 100.6%. The t-test results showed that the P values of two determination methods were 0.493, 0.155 and 0.171 for harpagide, angoroside C and harpagoside respectively, indicating no significant diffe-rence between the two methods of content determination. The SRRE can be used as a substitute for the reference in the quality control of Scrophulariaceae Radix. The SRRE can replace the corresponding reference substance for the quality control of Scrophulariae Radix. The results of this study provide new methods and new ideas for the quality evaluation of Scrophulariae Radix, and provide a scientific basis for the application of reference extracts in the quality research of traditional Chinese medicine.

[Construction of "2R network pharmacology" research method for effective components of traditional Chinese medicine based on "prediction of dominant components-screening of potential targets"].

Chinese traditional medicine compound is the main form of Chinese medicine clinical application. The elucidation of the effective components of traditional Chinese medicine is one of the key scientific issues to promote the modernization of traditional Chinese medicine. At present, there are many research ideas on the effective components of traditional Chinese medicine compounds. By analyzing the current status and existing problems of existing research ideas, the author proposes a "double reduction network pharmacology"(2 R network pharmacology) research method based on "prediction of dominant components-potential target selection". Chemical components with good properties were selected by ADMET property prediction technology, and compared with the blood components and target organ components to determine the dominant components with potential therapeutic effect, that is "reducing constituents"; the potential core regulatory pathway of traditional Chinese medicine compound was enriched by RNA-Seq technology combined with network database, and then the target of traditional Chinese medicine compound was mined based on the signal pathway, that is "reducing targets". To improve the efficiency and accuracy of effective component screening, the network relationship of "component target" was established by the related technology of network pharmacology. The purpose of this study is to provide practical research ideas and methods for clarifying the effective components of traditional Chinese medicine, revealing the law of compatibility of traditional Chinese medicine and clarifying the target of drug action.

Image-Guided Core Needle Biopsy of Adipocytic Tumors: Diagnostic Accuracy and Concordance With Final Surgical Pathology.

OBJECTIVE. Diagnostic accuracy of core needle biopsy (CNB) for adipocytic tumors can be low because of sampling error from these often large, heterogeneous lesions. The purpose of this study was to evaluate the diagnostic accuracy of image-guided CNB for various adipocytic tumors in comparison with excisional pathology. MATERIALS AND METHODS. Adipocytic tumors (n = 77) of all adult patients undergoing image-guided CNB and subsequent surgical excision of an adipocytic tumor at a tertiary referral center between 2005 and 2019 were studied. To determine concordance, we compared pathologic diagnoses based on CNB to the reference standard of pathologic diagnoses after surgical excision. Tumors were divided into three categories (benign lipomatous tumors [lipoma, lipoma variants, hibernomas], atypical lipomatous tumors [ALTs] or well-differentiated liposarcomas [WDLs], and higher grade liposarcomas [myxoid, dedifferentiated, pleomorphic]), and diagnostic accuracy was calculated for each category. RESULTS. In 73 of 77 adipocytic tumors (95%), diagnosis at CNB and diagnosis after excision were concordant. Accuracy of diagnosis was poorer for ALTs and WDLs than for the other two categories, and the difference was statistically significant (p < .002). For the 29 benign lipomatous tumors and the 27 higher-grade liposarcomas, diagnoses at CNB and after excision were concordant in all cases (100%). Seventeen of the 21 tumors (81%) diagnosed as ALTs or WDLs at CNB had a concordant diagnosis after excision; four of the 21 were upgraded (dedifferentiated liposarcoma, n = 3; myxoid liposarcoma, n = 1). CONCLUSION. CNB provides high diagnostic accuracy for adipocytic tumors, particularly for benign lipomatous tumors and higher grade liposarcomas. However, though still high at 81%, diagnostic accuracy of CNB is not as high for tumors diagnosed as ALTs or WDLs. Awareness of this limitation is important when determining management, particularly of cases of ALT or WDL for which surgery is not planned.

Video Based Shuffling Step Detection for Parkinsonian Patients Using 3D Convolution.

Parkinson's Disease (PD) is a common neurodegenerative disease which impacts millions of people around the world. In clinical treatments, freezing of gait (FoG) is used as the typical symptom to assess PD patients' condition. Currently, the assessment of FoG is usually performed through live observation or video analysis by doctors. Considering the aging societies, such a manual inspection based approach may cause serious burdens on the healthcare systems. In this study, we propose a pure video-based method to automatically detect the shuffling step, which is the most indistinguishable type of FoG. Firstly, the RGB silhouettes which only contain legs and feet are fed into the feature extraction module to obtain multi-level features. 3D convolutions are used to aggregate both temporal and spatial information. Then the multi-level features are aggregated by the feature fusion. Skip connections are implemented to reserve information of high resolution and period-wise horizontal pyramid pooling is utilized to fuse both global context and local features. To validate the efficacy of our method, a dataset containing 268 normal gait samples and 362 shuffling step samples is built, on which our method achieves an average detection accuracy of 90.8%. Besides shuffling step detection, we demonstrate that our method can also assess the severity of walking abnormity. Our proposal facilitates a more frequent assessment of FoG with less manpower and lower cost, leading to more accurate monitoring of the patients' condition.

Deciphering the effective combinatorial components from Si-Miao-Yong-An decoction regarding the intervention on myocardial hypertrophy.

ETHNOPHARMACOLOGICAL RELEVANCE: Si-Miao-Yong-An decoction (SMYAD), a classical traditional Chinese medicine (TCM) formula, has been used to treat various cardiovascular diseases in clinics. AIM OF THE STUDY: The aim of this study is to investigate the effective combinatorial components from SMYAD and its mechanism regarding the intervention on myocardial hypertrophy. MATERIALS AND METHODS: SMYAD constituents absorbed in rat plasma and heart were identified using UHPLC Q-Exactive-Orbitrap MS/MS. The identified constituents in SMYAD were further analyzed using ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction and molecular docking. The effective constituents were identified using isoproterenol (ISO)-induced H9c2 cardiomyocyte hypertrophy, and neochlorogenic acid (NCA), chlorogenic acid (CA), cryptochlorogenic acid (CCA), isochlorogenic acid C (ICAC), angoroside C (AGDC), isochlorogenic acid A (ICAA), sweroside (SRD), and harpagide (HPD) in SMYAD extract were quantified by HPLC for compatibility. Finally, anti-hypertrophic activities of candidate effective combinatorial components, which were prepared according to the determined molar concentration ratio of effective constituents using reference substance solution, were analyzed using immunofluorescence staining and Quantitative real-time PCR. The expression levels of PI3Kα, p-ERK, p-Akt, Akt, p-mTOR, mTOR and HIF-1α were measured using Western blot. RESULTS: 32 prototypes of SMYAD were identified from plasma and heart tissue of rat. Combining with ADMET prediction, 31 dominant constituents were focused. Based on HIF-1 pathway identified in preliminary result, 17 targets were focused, which were used to dock with 31 constituents. 27 constituents were therefore hit as the potential effective constituents of SMYAD in inhibiting myocardial hypertrophy. Bioactivity evaluation showed that NCA, CA, CCA, ICAC, AGDC, ICAA, SRD, and HPD significantly inhibited the increase of H9c2 cell surface area induced by ISO. Except for ICAA and AGDC, the remaining 6 effective constituents, showing a certain inhibitory effect on ISO-induced ANP mRNA overexpression at high and low concentrations, participated in compatibility based on the molar concentration ratio determined by HPLC. Effective combinatorial components composed of the 6 effective constituents (effective combinatorial components ABC) showed significant inhibitory effect on the increase of cell surface area, and the overexpression of ANP and ß-MHC mRNA in H9c2 cells induced by ISO. Moreover, effective combinatorial components ABC significantly inhibited the protein overexpressions of p-Akt, p-mTOR and HIF-1α. Based on the results, we put forward the strategy of "Focusing constituents" and "Focusing targets" for the effective constituents research of TCM formula. CONCLUSION: Effective combinatorial components ABC composed of NCA, CA, CCA, ICAC, SRD and HPD from SMYAD inhibited ISO-induced cardiomyocyte hypertrophy and down-regulated expression of ANP and ß-MHC mRNA through the inactivation of Akt/mTOR/HIF-1α pathway.

Effects of metformin on lipopolysaccharide-induced depressive-like behavior in mice and its mechanisms.

Metformin, an AMPK activator, is a widely used medicine for type II diabetes, which has been considered to exert the anti-inflammatory effects. It has been reported that inflammation plays an important role in the pathogenesis of depression. Lipopolysaccharide (LPS) is often utilized to induce depressive-like behavior in mice with respect to recent studies. However, whether metformin alleviates the symptoms of depressive-like behaviors and its mechanisms remain unexplored. The present study investigates whether metformin alleviates LPS-induced depressive-like behavior in mice and aims to explore the mechanisms. We first treated adult mice with LPS (0.83 mg/kg, intraperitoneal) to induce depressive-like behavior model for 24 hours after treatment with or without metformin. Then, the effects of metformin on depressive-like behaviors were detected by tail suspension test and forced swim test. Moreover, quantitative RT-PCR was used to determine the mRNA expression levels of lipocalin 2 (Lcn-2) and inflammatory molecules including IL-1ß, IL-6 and von Willebrand factor (vWF), which are concerned with inflammation and Lcn-2. It was shown that LPS-induced mouse depressive-like behaviors, as indicated by the increased time of immobility in tail suspension test and forced swim test, were reversed by metformin. It was also shown that LPS increased the mRNA expression levels of Lcn-2 and inflammation-related molecules such as IL-1ß in the amygdala tissue, which could be alleviated by metformin. Taken together, metformin mitigates LPS-induced depressive-like behavior in mice by regulating the expression level of Lcn-2 and inflammation-related molecules, including IL-1ß, IL-6 and vWF.Video abstract: http://links.lww.com/WNR/A568.

[Identification of compounds in Lycii Cortex by UPLC-LTQ-Orbitrap-MS].

This experiment was performed to analyze and identify the chemical constituents of Lycii Cortex by UPLC-LTQ-OrbitrapMS. The analysis was performed on a Waters Xbridge Shield RP18( 4. 6 mm×250 mm,5 µm) column with the mobile phase of 0. 1%formic acid( A)-acetonitrile( B) under gradient conditions at a flow rate of 1. 0 m L·min-1 and the temperature maintained at 35 ℃ ．Electrospray ionization ion trap time-off light multistage mass spectrometry was applied for qualitative analysis under positive and negative ion modes. The results indicated that 55 compounds consisted of 39 phenolic amides,6 organic acids,3 cyclic peptides,2 coumarins and 5 others. In conclusion,an UPLC-LTQ-Orbitrap-MS method was established to qualitative analysis of Lycii Cortex in this study,and the fragmentation rules of phenolic amides were summarized,which provides a good foundation for further study of Lycii Cortex.

Ratiometric fluorescence detection of riboflavin based on fluorescence resonance energy transfer from nitrogen and phosphorus co-doped carbon dots to riboflavin.

Fluorescent nitrogen and phosphorus co-doped carbon dots (NPCDs) were prepared via a hydrothermal method with citric acid and O-phosphorylethanolamine as precursors. The overlap between the absorption spectrum of riboflavin and the fluorescence emission spectrum of the NPCDs and the relative proximity of the NPCDs to riboflavin due to hydrogen bonding facilitated the formation of a NPCDs/riboflavin fluorescence resonance energy transfer (FRET) system. Thus, a ratiometric fluorescence method for the detection of riboflavin based on the formation of this NPCDs/riboflavin FRET system was developed. The method displayed a sensitive and selective response to riboflavin in the range 0.5-50 µmol/L with a detection limit of 0.17 µmol/L. It was also found to be suitable for the detection of riboflavin in milk and riboflavin pharmaceutical tablets. Graphical abstract Illustration of the preparation of NPCDs and the ratiometric fluorescence detection of riboflavin using the NPCDs/riboflavin FRET system.

Intrinsic catalytic activity of rhodium nanoparticles with respect to reactive oxygen species scavenging: implication for diminishing cytotoxicity.

Noble metal nanoparticles (NPs) and their hybrids have demonstrated a strong potential to mimic the catalytic activity of natural enzymes and diminish oxidative stress. There is a large space to explore the intrinsic catalytic activity of Rh NPs with respect to reactive oxygen species (ROS) scavenging. We found that Rh NPs can quench H2O2, •OH, O2•-, 1O2 and inhibit lipid peroxidation under physiological conditions. In vitro cell experiments proved that Rh NPs have great biocompatibility and protect cells from oxidative damage caused by H2O2. This study can provide important insights that could inform future biological applications.

Arrhythmia Recognition and Classification Using ECG Morphology and Segment Feature Analysis.

In this work, arrhythmia appearing with the presence of abnormal heart electrical activity is efficiently recognized and classified. A novel method is proposed for accurate recognition and classification of cardiac arrhythmias. Firstly, P-QRS-T waves is segmented from ECG waveform; secondly, morphological features are extracted from P-QRS-T waves, and ECG segment features are extracted from the selected ECG segment by using PCA and dynamic time warping(DTW); finally, SVM is applied to the features and automatic diagnosis results is presented. ECG data set used is derived from the MIT-BIH in which ECG signals are divided into the four classes: normal beats(N), supraventricular ectopic beats (SVEBs), ventricular ectopic beats (VEBs) and fusion of ventricular and normal (F). Our proposed method can distinguish N, SVEBs, VEBs and F with an accuracy of 97.80 percent. The sensitivities for the classes N, SVEBs, VEBs and F are 99.27, 87.47, 94.71, and 73.88 percent and the positive predictivities are 98.48, 95.25, 95.22 and 86.09 percent respectively. The detection sensitivity of SVEBs and VEBs has a better performance by combining proposed features than by using the ECG morphology or ECG segment features separately. The proposed method is compared with four selected peer algorithms and delivers solid results.