Search

Abstract Objective Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) are considered gold standards for measuring visceral fat area (VFA). However, their relatively high prices and potential radiation exposure limit their widespread use in clinical practice and everyday life. Therefore, our study aims to develop a VFA estimated equation based on sagittal abdominal diameter (SAD) and transverse abdominal diameter (TAD) using anthropometric indexes. To the best of our knowledge, there have been limited studies investigating this aspect thus far. Methods This study was designed as a cross-sectional, retrospective cohort survey. A total of 288 patients (167 males and 121 females) aged 18–80 with type 2 diabetes (T2D) were consecutively collected from a multicenter hospital, and VFA was measured by CT. Subsequently, variables highly correlated with VFA were screened through general linear correlation analysis. A stepwise regression analysis was then conducted to develop a VFA estimated equation. Discrepancies between the estimated and actual VFA values were assessed using the Bland-Altman method to validate the accuracy of the equation. Results In the female T2D population, triglyceride (TG), SAD, TAD were found to be independently correlated with VFA; in the male T2D population, BMI, TG, SAD and TAD showed independent correlations with VFA. Among these variables, SAD exhibited the strongest correlation with VFA (r = 0.83 for females, r = 0.88 for males), followed by TAD (r = 0.69 for females, r = 0.79 for males). Based on these findings, a VFA estimated equation was developed for the T2D population: VFA (male) =-364.16 + 15.36*SAD + 0.77*TG + 9.41*TAD − 5.00*BMI (R2 = 0.75, adjusted R2 = 0.74); VFA(female)=-170.87 + 9.72*SAD-24.29*(TG^-1) + 3.93*TAD (R2 = 0.69, adjusted R2 = 0.68). Both models demonstrated a good fit. The Bland-Altman plot indicated a strong agreement between the actual VFA values and the estimated values, the mean differences were close to 0, and the majority of differences fell within the 95% confidence interval. Conclusions In the T2D population, a VFA estimated equation is developed by incorporating SAD and TAD along with other measurement indices. This equation demonstrates a favorable estimated performance, suggesting to the development of novel and practical VFA estimation models in the future study.

Abstract Background Mesonephric carcinoma (MC) is a very rare tumor with less than 70 cases had been reported. The rarity of MC has restricted its research, resulting in the lack of published guidelines. Objective To summarize the characteristics and construct an external‐validated nomogram to predict the survival of MC patients. Method Sixty‐four qualified patients derived from the Surveillance, Epidemiology, and End Results Plus database, and one patient from the Guangzhou Red Cross Hospital were enrolled. The entire cohort was randomly divided into a development (70%) and a validation cohort (30%). The Kaplan–Meier method and univariate and multivariate Cox regression analyses were applied. Two nomograms were established to predict the 3‐to‐8‐year survival probability of MC patients, which were evaluated by C‐index, ROC curves, DCA curves, and calibration plots. Results The average survival time of MC patients was 84.22 ± 50.66 months. No significant difference was shown among different groups of race, primary site, tumor differentiated grade, and FIGO stages, while different SEER stages did distinguish patients' survival time, which indicated that the SEER stage standards might be a better staging system in the MC patients than FIGO stage (p = .0835). Additional survival analyses showed that MC patients benefited from shorter waiting times to begin treatment, accepting surgery, regional lymph node examination, radiotherapy, and chemotherapy. Two nomograms were established, both of which got satisfied scores in C‐index, ROC curves, DCA curves, and calibration plots. Conclusion Sufficient regional lymph nodes examined, and applying radiotherapy in high‐risk patients are recommended in MC patients. Nomograms established in the present study had good predicting and discriminating capabilities, which would be helpful in patients' individual risk estimation, management, counseling, and follow‐up.

Natural peptides (NPs) are ubiquitous throughout the organism with diversified structures and wide dynamic concentration range, which leads to serious challenge for their comprehensive analysis. Herein, a pseudotargeted peptidomics strategy based on dynamic multiple reaction monitoring (DMRM) with high-throughput data acquisition and accurate quantification was established. Specifically, an in-house software Pep-MRMer was developed for extraction of ions information of peptides, followed by de-redundancy and fusion to construct a transition list. Additionally, retention time (RT) calibration method was optimized by using high content components for effective transference of ion pairs between different detection conditions (e.g., instruments, chromatographic gradients). This strategy was applied for profiling NPs and screening signature peptides for species authentication of Pheretima, a multi-source animal-derived drug widely used in Asian countries. In all, a total of 3307 peptides had excellent quantitative detection after transference. Subsequently, nine signature peptides with extraordinary specificity were screened, identified, and confirmed by comparing with the synthetic standards. Ultimately, a 10 min specific chromatogram based on signature peptides was developed, which realized rapid and accurate identification of Pheretima. Taken together, this research provides a robust strategy for species discrimination of animal-derived drugs without adequate quality control measures.

Aurantii Fructus (AF) and Aurantii Fructus Immaturus (AFI) have been used for thousands of years as traditional Chinese medicine (TCM) with sedative effects. Modern studies have shown that Citrus plants also have protective effects on the nervous system. However, the effective substances and mechanisms of action in Citrus TCMs still remain unclear. In order to explore the pharmacodynamic profiles of identified substances and the action mechanism of these herbs, a comprehensive approach combining ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS/MS) analysis and network pharmacology was employed. Firstly, UNIFI 2.1.1 software was used to identify the chemical characteristics of AF and AFI. Secondly, the SwissTargetPrediction database was used to predict the targets of chemical components in AF and AFI. Targets for neuroprotection were also collected from GeneCards: The Human Gene Database (GeneCards-Human Genes|Gene Database|Gene Search). The networks between targets and compounds or diseases were then constructed using Cytoscape 3.9.1. Finally, the Annotation, Visualization and Integrated Discovery Database (DAVID) (DAVID Functional Annotation Bioinformatics Microarray Analysis) was used for GO and pathway enrichment analysis. The results showed that 50 of 188 compounds in AF and AFI may have neuroprotective biological activities. These activities are associated with the regulatory effects of related components on 146 important signaling pathways, derived from the KEGG (KEGG: Kyoto Encyclopedia of Genes and Genomes), such as neurodegeneration (hsa05022), the Alzheimer’s disease pathway (hsa05010), the NF-kappa B signaling pathway (hsa04064), the hypoxia-inducible factor (HIF)-1 signaling pathway (hsa04066), apoptosis (hsa04210), the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance signaling pathway (hsa01521), and others, by targeting 108 proteins, including xanthine dehydrogenase (XDH), glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B), and glucose-6-phosphate dehydrogenase (G6PD), among others. These targets are thought to be related to inflammation, neural function and cell growth.

Cordyceps sinensis (C. sinensis) is a widely used and highly valuable traditional Chinese medicine. Several dipeptides have been detected in C. sinensis, but current scientific knowledge of its chemical makeup remains limited. In this study, an improved approach that integrates offline two-dimensional liquid chromatography (2D LC) separation, precursor ion list, library screening, and diagnostic ion filtering was established to systematically screen and characterize dipeptides in C. sinensis. Offline 2D LC integrating hydrophilic interaction LC and reverse phase separations was established to eliminate interference and identify the target dipeptides. A library containing the potential 400 dipeptides was created, and a precursor ion list with all theoretical precursor ions was adopted to trigger the MS/MS scan with high sensitivity. To identify dipeptides, the type and connection sequence of amino acids were determined according to the product ions. Ile and Leu residues were differentiated for the first time according to the characteristic ion at m/z 69.07. Ultimately, 170 dipeptides were identified or tentatively characterized from C. sinensis, and most are reported for the first time in this species herein. In addition, the identified dipeptides were also applied for discrimination among the three Cordyceps species, and 11 markers were identified. The obtained results provide a deeper understanding of the chemical basis of C. sinensis.

Abstract NEMO/IKKβ complex is a central regulator of NF-κB signaling pathway, its dissociation has been considered to be an attractive therapeutic target. Herein, using a combined strategy of molecular pharmacological phenotyping, proteomics and bioinformatics analysis, Shikonin (SHK) is identified as a potential inhibitor of the IKKβ/NEMO complex. It destabilizes IKKβ/NEMO complex with IC50 of 174 nM, thereby significantly impairing the proliferation of colorectal cancer cells by suppressing the NF-κB pathway in vitro and in vivo. In addition, we also elucidated the potential target sites of SHK in the NEMO/IKKβ complex. Our study provides some new insights for the development of potent small-molecule PPI inhibitors.

In low-voltage distribution systems, the load types are complex, so traditional detection methods cannot effectively identify series arc faults. To address this problem, this paper proposes an arc fault detection method based on multimodal feature fusion. Firstly, the different mode features of the current signal are extracted by mathematical statistics, Fourier transform, wavelet packet transform, and continuous wavelet transform. The different modal features include one-dimensional features, such as time-domain features, frequency-domain features, and wavelet packet energy features, and two-dimensional features of time-spectrum images. Secondly, the extracted features are preprocessed and prioritized for importance based on different machine learning algorithms to improve the feature data quality. The features of higher importance are input into an arc fault detection model. Finally, an arc fault detection model is constructed based on a one-dimensional convolutional network and a deep residual shrinkage network to achieve high accuracy. The proposed detection method has higher detection accuracy and better performance compared with the arc fault detection method based on single-mode features.

BackgroundStroke is one of the leading causes of mortality across the world. However, there is a paucity of information regarding mortality rates and associated risk factors in patients with acute ischemic stroke (AIS) undergoing endovascular thrombectomy (EVT). In this study, we aimed to clarify these issues and analyzed previous publications related to mortality in patients treated with EVT.MethodsWe analyzed the survival of 245 consecutive patients treated with mechanical thrombectomy for AIS for which mortality information was obtained. Early mortality was defined as death occurring during hospitalization after EVT or within 7 days following hospital discharge from the stroke event.ResultsEarly mortality occurred in 22.8% of cases in this cohort. Recanalization status (modified thrombolysis in cerebral infarction, mTICI) (p = 0.002), National Institute of Health Stroke Scale Score (NIHSS) score 24-h after EVT (p < 0.001) and symptomatic intracerebral hemorrhage (sICH) (p < 0.001) were independently associated with early mortality. Age, sex, cardiovascular risk factors, NIHSS score pre-treatment, Alberta Stroke Program Early CT Score (ASPECTS), stroke subtype, site of arterial occlusion and timing form onset to recanalization did not have an independent influence on survival. Non-survivors had a shorter hospitalization (p < 0.001) but higher costs related to their hospitalization and outpatient care.ConclusionThe recanalization status, NIHSS score 24-h after EVT and sICH were predictors of early mortality in AIS patients treated with EVT.

Accurate identification of the botanical origins of Rhizoma Alismatis (RA) is pivotal to its precise clinical usage. We herein present a strategy, by integrating untargeted metabolomics, data cross validation, absolute quantification, and vector machine model, for species discrimination and source recognition of Rhizoma Alismatis for the first time. An ultra-high-performance liquid chromatography/LTQ-Orbitrap mass spectrometry with precursor ions list-including data-dependent acquisition approach was developed for metabolite profiling. Holistic, continuous, and pattern recognition chemometrics could make it feasible to unveil forty-one markers, with “multi-duplicated and traceability samples comparison” cross validation to narrow down to twelve robust markers, some of which were further validated by absolute quantification. A support vector machine model was eventually developed to distinguish these two species and predict origins of commercially available varieties. This was the first report on systematic comparison and discrimination of two original species of RA. This integral strategy, in contrast to conventional approaches, renders more convincing data supporting for the discovery of multi-source chemical makers of traditional Chinese medicines (TCM).

Jujube fruit was well-loved and praised by the broad masses due to its delicious taste, abundant nutritional value, and medicinal properties. Few studies reported the quality evaluation and gut microbiota regulation effect of polysaccharides of jujube fruits from different producing areas. In the present study, multi-level fingerprint profiling, including polysaccharides, oligosaccharides, and monosaccharides, was established for the quality evaluation of polysaccharides from jujube fruits. For polysaccharides, the total content in jujube fruits ranged from 1.31% to 2.22%, and the molecular weight distribution (MWD) ranged from 1.14 × 105 to 1.73 × 106 Da. The MWD fingerprint profiling of polysaccharides from eight producing areas was similar, but the profile of infrared spectroscopy (IR) showed differentiation. The characteristic signals were screened and used to establish a discrimination model for the identification of jujube fruits from different areas, and the accuracy of identification reached 100.00%. For oligosaccharides, the main components were galacturonic acid polymers (DP, 2–4), and the profile of oligosaccharides exhibited high similarity. The monosaccharides, GalA, Glc, and Ara, were the primary monosaccharides. Although the fingerprint of monosaccharides was semblable, the composing proportion of monosaccharides revealed significant differences. In addition, the polysaccharides of jujube fruits could regulate the gut microbiota composition and possess potential therapeutic effects on dysentery and nervous system diseases.

Flavonoids derived from citrus plants are favored by phytomedicinal researchers due to their wide range of biological activities, and relevant studies have been sustained for 67 years (since the first paper published in 1955). In terms of a scientometric and critical review, the scientometrics of related papers, chemical structures, and pharmacological action of citrus flavonoids were comprehensively summarized. The modern pharmacological effects of citrus flavonoids are primarily focused on their anticancer activities (such as breast cancer, gastric cancer, lung cancer, and liver cancer), neuroprotective effects (such as anti-Alzheimer’s disease, Parkinson’s disease), and metabolic diseases. Furthermore, the therapeutic mechanism of cancers (including inducing apoptosis, inhibiting cell proliferation, and inhibiting cancer metastasis), neuroprotective effects (including antioxidant and anti-inflammatory), and metabolic diseases (such as non-alcoholic fatty liver disease, type 2 diabetes mellitus) were summarized and discussed. We anticipate that this review could provide an essential reference for anti-cancer and neuroprotective research of citrus flavonoids and provide researchers with a comprehensive understanding of citrus flavonoids.

Elastic–plastic numerical analysis of the spinning process of SA-372 steel is used in high-pressure hydrogen storage to analyze high-pressure hydrogen storage cylinders with high precision and excellent hydrogen embrittlement resistance. The spinning process of SA-372 steel used to form such a cylinder with a pressure of 100 MPa is investigated through elastic–plastic finite element analysis. The variations in the stress, strain, pressure, temperature, and wall thickness during the spinning processes are comprehensively examined, and the optimized processing parameters are determined based on the numerical analysis results. Finally, these optimal parameters are used to conduct actual spin-forming experiments. The numerical results are found to be in excellent agreement with the experimental results, which verifies the feasibility and effectiveness of the proposed elastic–plastic numerical analysis model for the optimization of spinning process parameters. Furthermore, the hydrogen embrittlement test based on ISO 11114-4:2005 method A proves that the cylinder shoulder has a good hydrogen embrittlement resistance.

Electronic nose (E-nose) and ultra-high-performance liquid chromatography (UHPLC) were simultaneously developed for quality evaluation and diversity research of A. mongholicus. Instrumental data were subjected to principal component analysis (PCA) and discriminant factor analysis (DFA) to rapidly distinguish A. mongholicus derived from different main producing regions in China. E-nose results showed that A. mongholicus that originated from main producing areas (Gansu, Shanxi, and Inner Mongolia in China) could be accurately classified into three groups through PCA and DFA. The response values of samples from Inner Mongolia and Shanxi were similar, and better than those of the samples from Gansu. Identification by the E-nose was verified through UHPLC analysis, and the content of the main ingredient was consistent with the response value of A. mongholicus. In conclusion, E-nose and UHPLC combined with chemometrics can be used as reliable techniques to distinguish the geographic origins of A. mongholicus effectively, and evaluate the quality of traditional Chinese herbs.

A permanent magnet synchronous motor (PMSM) has advantages in applications such as electric vehicles and all-electric-aircraft because of its inherent characteristics of high power density. In order to further improve its power density, this paper proposes a novel rotor structure with a magnetic stripe, based on the “dual stator + Halbach array” topology of the PMSM, which leads to a PMSM with greater power density. Then, this paper proposes characteristic parameters such as the external air gap proportional coefficient K1 and the internal air gap proportional coefficient K2 of the novel rotor structure, and establishes the torque analysis model of the novel rotor structure and the corresponding motor. Simulation results show that the novel rotor structure can increase the average torque. Then, this paper establishes an optimization model, in which K1 and K2 are taken as optimization variables, a torque fluctuation of no more than 5% is set as a constraint, and the maximum average torque is set as the optimization goal. The results show that the optimized novel rotor structure with magnetic stripe can significantly improve the torque performance of the PMSM, and the optimization method proposed is efficient.

Gentianae Radix et Rhizome (Longdan in Chinese, GRR) in Chinese Pharmacopoeia is derived from the dried roots and rhizomes of Gentiana scabra and G. rigescens, that have long been used for heat-clearing and damp-drying in the medicinal history of China. However, the characterization of the chemical components of two species and the screening of chemical markers still remain unsolved. In current research, the identification and characterization of chemical components of two species was performed using ultra-high-performance liquid chromatography (UHPLC) coupled with linear ion trap-Orbitrap (LTQ-Orbitrap) mass spectrometry. Subsequently, the chemical markers of two species were screened based on metabolomics and multivariate statistical analysis. In total, 87 chemical constituents were characterized in G. scabra (65 chemical constituents) and G. rigescens (51 chemical constituents), with 29 common chemical constituents being discovered. Thereafter, 11 differential characteristic components which could differentiate the two species were designated with orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF) iterative modeling. Finally, seven characteristic components identified as (+)-syringaresinol, lutonarin, trifloroside, 4-O-β-d-glu-trifloroside, 4″-O-β-d-glucopyranosy1-6′-O-(4-O-β-d-glucaffeoyl)-linearroside, macrophylloside a and scabraside were selected as the chemical markers for the recognition of two Gentiana species. It was implied that the results could distinguish the GRR derived from different botanical sources, and also be beneficial in the rational clinical use of GRR.

Characterization and determination of metabolites to monitor metabolic pathways play a paramount role in evaluating the efficacy and safety of medicines. However, the separation and quantification of metabolites are rather difficult due to their limited contents in vivo, especially in the case of Chinese medicine, due to its complexity. In this study, an effective and convenient method was developed to simultaneously quantify bufalin and its nine metabolites (semi-quantitation) in rat plasma after an oral administration of 10 mg/kg to rats. The prototype and metabolites that were identified were subsequently quantified using positive electrospray ionization in multiple reaction monitoring (MRM) mode with transitions of m/z 387.4→369.6 and 387.4→351.3 for bufalin, m/z 513.7→145.3 for IS, and 387.4→369.6, 419.2→365.2, and 403.2→349.2 for the main metabolites (3-epi-bufalin, dihydroxylated bufalin, and hydroxylated bufalin, respectively). The method was validated over the calibration curve range of 1.00−100 ng/mL with a limit of quantitation (LOQ) of 1 ng/mL for bufalin. No obvious matrix effect was observed, and the intra- and inter-day precisions, as well as accuracy, were all within the acceptable criteria in this method. Then, this method was successfully applied in metabolic profiling and a pharmacokinetic study of bufalin after an oral administration of 10 mg/kg to rats. The method of simultaneous determination of bufalin and its nine metabolites in rat plasma could be useful for pharmacokinetic−pharmacodynamic relationship research of bufalin, providing experimental evidence for explaining the occurrence of some adverse effects of Venenum Bufonis and its related preparations.

The mass spectrometry (MS) has been widely used for profiling chemical components of traditional Chinese medicine (TCM). However, there are few studies reporting quality control of TCM based on mass spectrometry fingerprint (MSF) due to its complicated operation and high cost. The aim of this study was to extend the application of MSF for quality evaluation of TCM. In this study, an MSF based on single quadrupole mass spectrometry method was established, and was successfully used for the quality control of Venenum bufonis (VB), a famous TCM which was used clinically for cancer treatment in China. The results showed that the superiority of MSF for more chemical information exposure and the finding of more potential chemical markers (eight versus four) compared with the traditional photo-diode array (a kind of ultra violet detector, PDA). Besides, the performance of MSF was also validated by similarity and principle component analysis (PCA) of MS data acquired on two other mass spectrometry (low-resolution, triple quadrupole, QQQ, and high-resolution, quadruple time-of-flight, Q-TOF), showing high consistency with QQQ and Q-TOF, but robustness with few parameters’ settings. Based on our study, MSF could be widely applied for the quality control of TCM.