Naoxintong capsule remodels gut microbiota and ameliorates early-stage atherosclerosis in apolipoprotein E-deficient mice.

BACKGROUND: Naoxintong capsule (NXT) is a compound traditional Chinese medicine prescription with demonstrated effect for the treatment of cardiovascular and cerebrovascular diseases including atherosclerosis (AS). However, the pharmacological mechanisms of NXT in ameliorating early-stage AS are still unclear, especially regarding the role of gut microbiota. PURPOSE: This study is aiming to evaluate the therapeutic effect of NXT against early-stage AS, and further illustrate the potential correlations among AS, gut microbiota, and NXT. METHODS: Thirty-two male ApoE knockout mice (C57BL/6 background) were fed with a high cholesterol diet (HCD) for 4 weeks to establish an early-stage AS model. NXT in two different dosages and simvastatin (Simv) were than administrated for another 8 weeks. Lipid metabolism indicators and inflammation levels were measured with corresponding assay kits. Changes in blood vessels, liver lesions, and intestinal barrier proteins were evaluated with different staining methods. Furthermore, the gut microbiota structure was analyzed using 16S rRNA sequencing technology, while GC-MS was utilized to determine the fecal contents of short-chain fatty acids (SCFAs). RESULTS: Administration of NXT significantly ameliorated obesity, hyperlipidemia, systemic inflammation, vasculopathy, liver injury, and intestinal barrier disorder in AS mice. Administration of NXT also significantly regulated the gut microbiota disturbance and increased the total contents of fecal SCFAs in AS mice. Furthermore, acetic acid content and the relative abundance of Faecalibacterium in feces were proposed as potential therapeutic biomarkers of NXT for AS treatment as indicated via the correlation analysis. CONCLUSION: This study demonstrated that NXT could effectively treat early-stage AS induced by HCD in mice. NXT regulated the gut microbiota and metabolites, maintained intestinal homeostasis, and improved the systemic inflammatory response. These findings may provide robust experimental support for the clinical use of NXT for AS treatment.

High-strength and ultra-tough supramolecular polyamide spider silk fibers assembled via specific covalent and reversible hydrogen bonds.

Achieving ultra-high tensile strength and exceptional toughness is a longstanding goal for structural materials. However, previous attempts using covalent and non-covalent bonds have failed, leading to the belief that these two properties are mutually exclusive. Consequently, commercial fibers have been forced to compromise between tensile strength and toughness, as seen in the differences between nylon and Kevlar. To address this challenge, we drew inspiration from the disparate tensile strength and toughness of nylon and Kevlar, both of which are polyamide fibers, and developed an innovative approach that combines specific intermolecular disulfide bonds and reversible hydrogen bonds to create ultra-strong and ultra-tough polyamide spider silk fibers. Our resulting Supramolecular polyamide spider silk, which has a maximum molecular weight of 1084 kDa, exhibits high tensile strength (1180 MPa) and extraordinary toughness (433 MJ/m3), surpassing Kevlar's toughness 8-fold. This breakthrough presents a new opportunity for the sustainable development of spider silk as an environmentally friendly alternative to synthetic commercial fibers, as spider silk is composed of amino acids. Future research could explore the use of these techniques and fundamental knowledge to develop other super materials in various mechanical fields, with the potential to improve people's lives in many ways. STATEMENT OF SIGNIFICANCE: • By emulating synthetic commercial fibers such as nylon and polyethylene, we have successfully produced supramolecular-weight polyamide spider silk fibers with a molecular weight of 1084 kDa through a unique covalent bond-mediated linear polymerization reaction of spider silk protein molecules. This greatly surpasses the previous record of a maximum molecular weight of 556 kDa. • We obtained supramolecular polyamide spider silk fibers with both high-tensile strength and toughness. The stress at break is 1180 MPa, and the toughness is 8 times that of kevlar, reaching 433 MJ/m3. • Our results challenge the notion that it is impossible to manufacture fibers with both ultra-high tensile strength and ultra-toughness, and provide theoretical guidance for developing environmentally friendly and sustainable structural materials that meet industrial needs.

CT image segmentation of meat sheep Loin based on deep learning.

There are no clear boundaries between internal tissues in sheep Computerized Tomography images, and it is difficult for traditional methods to meet the requirements of image segmentation in application. Deep learning has shown excellent performance in image analysis. In this context, we investigated the Loin CT image segmentation of sheep based on deep learning models. The Fully Convolutional Neural Network (FCN) and 5 different UNet models were applied in image segmentation on the data set of 1471 CT images including the Loin part from 25 Australian White rams and Dolper rams using the method of 5-fold cross validation. After 10 independent runs, different evaluation metrics were applied to assess the performances of the models. All models showed excellent results in terms evaluation metrics. There were slight differences among the results from the six models, and Attention-UNet outperformed others methods with 0.998±0.009 in accuracy, 4.391±0.338 in AVER_HD, 0.90±0.012 in MIOU and 0.95±0.007 in DICE, respectively, while the optimal value of LOSS was 0.029±0.018 from Channel-UNet, and the running time of ResNet34-UNet is the shortest.

Discrete and Balanced Spectral Clustering With Scalability.

Spectral Clustering (SC) has been the main subject of intensive research due to its remarkable clustering performance. Despite its successes, most existing SC methods suffer from several critical issues. First, they typically involve two independent stages, i.e., learning the continuous relaxation matrix followed by the discretization of the cluster indicator matrix. This two-stage approach can result in suboptimal solutions that negatively impact the clustering performance. Second, these methods are hard to maintain the balance property of clusters inherent in many real-world data, which restricts their practical applicability. Finally, these methods are computationally expensive and hence unable to handle large-scale datasets. In light of these limitations, we present a novel Discrete and Balanced Spectral Clustering with Scalability (DBSC) model that integrates the learning the continuous relaxation matrix and the discrete cluster indicator matrix into a single step. Moreover, the proposed model also maintains the size of each cluster approximately equal, thereby achieving soft-balanced clustering. What's more, the DBSC model incorporates an anchor-based strategy to improve its scalability to large-scale datasets. The experimental results demonstrate that our proposed model outperforms existing methods in terms of both clustering performance and balance performance. Specifically, the clustering accuracy of DBSC on CMUPIE data achieved a 17.93% improvement compared with that of the SOTA methods (LABIN, EBSC, etc.).

Danhong injection improves neurological function in rats with ischemic stroke by enhancing neurogenesis and activating BDNF/AKT/CREB signaling pathway.

Danhong injection (DHI) is a traditional Chinese medicine injection that promotes blood circulation and removes blood stasis and has been widely used in the treatment of stroke. Many studies have focused on the mechanism of DHI in acute ischemic stroke (IS); however, few studies have thoroughly explored its role during recovery. In this study, we aimed to determine the effect of DHI on long-term neurological function recovery after cerebral ischemia and explored the related mechanisms. Middle cerebral artery occlusion (MCAO) was used to establish an IS model in rats. The efficacy of DHI was assessed using neurological severity scores, behaviors, cerebral infarction volume and histopathology. Immunofluorescence staining was performed to assess hippocampal neurogenesis. An in vitro oxygen-glucose deprivation/reoxygenation (OGD/R) cell model was constructed and western-blot analyses were performed to verify the underlying mechanisms. Our results showed that DHI treatment greatly reduced the infarct volume, promoted neurological recovery and reversed brain pathological changes. Furthermore, DHI promoted neurogenesis by increasing the migration and proliferation of neural stem cells, and enhancing synaptic plasticity. Moreover, we found that the pro-neurogenic effects of DHI were related to an increase in brain-derived neurotrophic factor (BDNF) expression and the activation of AKT/CREB, which were attenuated by ANA-12 and LY294002, the inhibitors of the BDNF receptor and PI3K. These results suggest that DHI improves neurological function by enhancing neurogenesis and activating the BDNF/AKT/CREB signaling pathways.

Rapid identification and quantitative determination of chemical compositions in Buyang Huanwu decoction based on HPLC-Q-Exactive mass spectrometry.

OBJECTIVE: To establish an analytical method for rapid identification of chemical compositions and quantitative determination of major compositions in Buyang Huanwu decoction (BYHWD) based on high performance liquid chromatography-quadrupole orbitrap mass spectrometry (HPLC-Q-Exactive MS) and high performance liquid chromatography-ultraviolet detection (HPLC-UV). METHODS: The mass spectrometry information was collected in Full MS/dd-MS 2 negative ion mode with HPLC-Q-Exactive MS system; the chemical compositions of BYHWD were subsequently annotated with Compound Discoverer 3.0 software and a self-built in-house compound library. Eight major compositions (paeoniflorin, gallic acid, hydroxysafflor yellow A, ferulic acid, calycosin-7-glucoside, ononin, calycosin, formononetin) were picked out and their contents were quantitatively determined with HPLC-UV analysis. RESULTS: A total of 178 compounds in BYHWD were tentatively identified. The results of HPLC-UV quantitative analysis showed that 8 compositions had a good linear relationship in their respective concentration range ( R 2≥0.9990), the relative standard deviations (RSD) of precision and stability were all less than 15%, and the recovery rate RSD was between 1.6% and 2.4%. CONCLUSIONS: The method established in this study can realize the rapid identification and accurate quantification of the major compositions in BYHWD. Paeoniflorin, hydroxysafflor yellow A and gallic acid may be used as quality control markers.

Naoxintong Capsule Alternates Gut Microbiota and Prevents Hyperlipidemia in High-Fat-Diet Fed Rats.

Background: Naoxintong Capsule (NXT) is a formulated Traditional Chinese Medicine (TCM) widely applied in the treatment of cardiovascular and metabolic diseases, most of which are closely related to hyperlipidemia as a major risk factor. Given the current limited understandings to the role of gut microbiota in the lipid-lowering effect of NXT and other TCM products, this study investigated the regulation of gut microbiota and lipid metabolism by NXT, and their potential relationship. Methods: The chemical components of NXT were firstly analyzed with HPLC-MS method. In high fat diet (HFD)-fed rat models, as well as normal rats as control, the histopathological and biochemical changes of serum and liver were examined, including total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C). In addition, the gut microbiota community was analyzed using 16S rRNA sequencing technique, the fecal levels of gut microbiota related metabolites, including bile acids (BAs) and short chain fatty acids (SCFAs) were determined with HPLC-MS. The correlations of the clinical indicators and gut microbiota related indicators were then investigated statistically. Results: The results showed that NXT exerted potential preventive effect on hyperlipidemia. Specifically, NXT significantly reduced the body weight, TC, TG and LDL-C in serum, increased HDL-C in serum, reduced the TC and TG in liver, as well as protected liver. The body weight, serum lipid levels and liver function were all significantly alleviated. The gut microbiota of the HFD-fed rats was reconstituted with supplementation of NXT. The fecal levels of gut microbiota related metabolites, including BAs and SCFAs were also altered. The correlation between the gut microbiota and clinical/metabolomic parameters was then studied. As the result, the amount of propionic aicd, Firmicutes/Bacteroidetes ratio (F/B) and the relative abundance of Collinsella in feces are the most possibly potential therapeutic biomarkers of NXT. Conclusion: NXT was effective in regulation of gut microbiota and prevention of hyperlipidemia in HFD fed rats. The present work might provide novel insights into the anti-hyperlipidemia effect of TCM and afford new scientific evidence for clinical application of TCM.

Discrete and Parameter-Free Multiple Kernel k-Means.

The multiple kernel k -means (MKKM) and its variants utilize complementary information from different sources, achieving better performance than kernel k -means (KKM). However, the optimization procedures of most previous works comprise two stages, learning the continuous relaxation matrix and obtaining the discrete one by extra discretization procedures. Such a two-stage strategy gives rise to a mismatched problem and severe information loss. Even worse, most existing MKKM methods overlook the correlation among prespecified kernels, which leads to the fusion of mutually redundant kernels and bad effects on the diversity of information sources, finally resulting in unsatisfying results. To address these issues, we elaborate a novel Discrete and Parameter-free Multiple Kernel k -means (DPMKKM) model solved by an alternative optimization method, which can directly obtain the cluster assignment results without subsequent discretization procedure. Moreover, DPMKKM can measure the correlation among kernels by implicitly introducing a regularization term, which is able to enhance kernel fusion by reducing redundancy and improving diversity. Noteworthily, the time complexity of optimization algorithm is successfully reduced, through masterly utilizing of coordinate descent technique, which contributes to higher algorithm efficiency and broader applications. What's more, our proposed model is parameter-free avoiding intractable hyperparameter tuning, which makes it feasible in practical applications. Lastly, extensive experiments conducted on a number of real-world datasets illustrated the effectiveness and superiority of the proposed DPMKKM model.

Metal ions stabilize a dimeric molten globule state between the open and closed forms of malic enzyme.

Malic enzyme is a tetrameric protein with double dimer quaternary structure. In 3-5 M urea, the pigeon cytosolic NADP(+)-dependent malic enzyme unfolded and aggregated into various forms with dimers as the basic unit. Under the same denaturing conditions but in the presence of 4 mM Mn(2+), the enzyme existed exclusively as a molten globule dimer in solution. Similar to pigeon enzyme (Chang, G. G., T. M. Huang, and T. C. Chang. 1988. Biochem. J. 254:123-130), the human mitochondrial NAD(+)-dependent malic enzyme also underwent a reversible tetramer-dimer-monomer quaternary structural change in an acidic pH environment, which resulted in a molten globule state that is also prone to aggregate. The aggregation of pigeon enzyme was attributable to Trp-572 side chain. Mutation of Trp-572 to Phe, His, Ile, Ser, or Ala abolished the protective effect of the metal ions. The cytosolic malic enzyme was completely digested within 2 h by trypsin. In the presence of Mn(2+), a specific cutting site in the Lys-352-Gly-Arg-354 region was able to generate a unique polypeptide with M(r) of 37 kDa, and this polypeptide was resistant to further digestion. These results indicate that, during the catalytic process of malic enzyme, binding metal ion induces a conformational change within the enzyme from the open form to an intermediate form, which upon binding of L-malate, transforms further into a catalytically competent closed form.