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Scrophularia ningpoensis Hemsl. (SN) is an herbal medicine used as a functional food in China. SN has traditionally been used to treat diabetes mellitus (DM), but its mechanism of action is not well understood. Our previous study indicated that the aqueous extract of SN can reduce hepatic insulin resistance and correct the irregular shape of pancreatic islets in diabetic mice. This study aims to investigate whether the aqueous extract of SN can regulate pyroptosis in pancreatic β-cells and explore its underlying mechanisms. Db/db mice were orally given an aqueous extract of SN for eight weeks. Subsequently, their pancreatic tissues were collected for histopathological analysis and immunoblotting. Rat insulinoma (INS-1) cells were cultured either alone or with the aqueous extract of SN and evaluated for cell viability, pyroptotic body formation, AMP-activated protein kinase (AMPK) activity, the NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) inflammasome and gasdermin D (GSDMD) activation, and reactive oxygen species (ROS) production under high glucose (HG) exposure conditions. The aqueous extract of SN reduced insulitis and pancreatic β-cell death in db/db mice. Increased AMPK phosphorylation and decreased NLRP3 inflammasome and GSDMD activation were observed in pancreatic tissues after administration of the aqueous extract of SN. In vitro, the aqueous extract of SN increased cell viability and AMPK phosphorylation in a concentration-dependent manner. Additionally, the aqueous extract of SN corrected excessive ROS generation, NLRP3 inflammasome and GSDMD activation, and pyroptotic body formation. Inhibition of AMPK negated these beneficial effects of the aqueous extract of SN on INS-1 cells. The study concluded that the aqueous extract of SN alleviates β-cell pyroptosis by inhibiting NLRP3/GSDMD activation in an AMPK-dependent manner.

PURPOSEThis study aimed to verify whether the use of the Kaiser score can improve the diagnostic performance in breast magnetic resonance imaging (MRI) for suspicious lesions and avoid further invasive diagnostic approaches.METHODSThis retrospective study enrolled 97 patients who underwent breast MRI before undergoing breast biopsy or surgery. Evaluations were conducted on all MRI images individually by 2 radiologists using the Kaiser score. Neither radiologist had the knowledge of the final histopathological diagnosis. The ability of the Kaiser score in diagnosis was established via a receiver performing characteristic (ROC) analysis, which was measured by the area under the ROC curve (AUC). Youden index was used to define the optimal cutoff value. Kaiser score categories were dichotomized into positive (cutoff score > 4) and negative scores (cutoff score ≤ 4). Cohen’s kappa coefficient was used to analyze the inter-rater agreement.RESULTSHistopathology revealed 56 malignant and 41 benign lesions. The AUC for all lesions evaluated by the Kaiser score was 0.992 (95% CI: 0.981-1.0) and 0.958 (95% CI: 0.920-0.996) for 2 radiologists, respectively. Inter-rater agreement of the dichotomized Kaiser score was excellent (κ=0.894, P < .001). A total of 20 lesions (33.8%) previously categorized as BI-RADS 4 were reduced to BI-RADS 2/3 (19 benign lesions and 1 malignant lesion).CONCLUSIONThe Kaiser score is a valuable auxiliary diagnostic tool for improving the diagnostic ability of radiologists, whose experiences in breast MRI are diverse. In some cases, the application of the Kaiser score could possibly avoid unnecessary breast biopsies.

The rapid development of digital technology has injected new vitality into green technological innovation within manufacturing enterprises. Proper application of digital technology during the innovation process can propel global sustainable development. Using Chinese publicly traded manufacturing firms as a sample, this study employed a constructed digital technology innovation network and OLS models to unveil the mechanisms through which digital technology application affects green technological innovation. This research reveals a significant positive impact of the breadth and depth of digital technology applications on companies’ green technological innovation performance. Green human resource allocation serves as an intermediary in this relationship. Furthermore, the embeddedness and structural embeddedness of the digital technology innovation network play a significantly positive moderating role in the relationship between digital technology applications and green human resource allocation. This discovery provides a theoretical foundation for how companies can harness digital technology to promote green innovation within China’s digital strategy. It aids manufacturing enterprises in optimizing digital technology applications, improving green human resource allocation, and facilitating the development of digital technology innovation networks, advancing more sustainable development and contributing to global environmental goals.

Antimicrobial resistance (AMR) is a major threat to global health due to the wide use of antibacterial drugs. Multiple studies show that the pharmacokinetic/pharmacodynamic (PK/PD) studies of antibiotics are an approach to prevent/delay AMR. The pharmacokinetic parameters of antibiotics are the basis of PK/PD studies, and therapeutic drug monitoring (TDM) is the key method to obtain pharmacokinetic information. We developed an ultra-performance liquid chromatography–tandem mass spectrometry to determine 18 antibacterial drugs (piperacillin, cefazolin, cefuroxime, cefoperazone, ceftriaxone, cefepime, aztreonam, meropenem, imipenem, levofloxacin, moxifloxacin, azithromycin, clindamycin, tigecycline, linezolid, vancomycin, voriconazole and caspofungin) in human plasma for practical clinical usage. Samples were prepared using protein precipitation with methanol. Chromatographic separation was accomplished in 6 min on a BEH C18 column (2.1 × 100 mm, 1.7 µm) using a gradient elution of acetonitrile and 0.1% formic acid in water at a flow rate of 0.3 ml/min. The electrospray ionization source interface was operated in the positive and negative ionization modes. Inter- and intra-day precision, accuracy, recovery, matrix effect, and stability were validated according to the Food and Drug Administration guidance. The correlation coefficients of calibration curves were all greater than 0.99. The accuracies of the 18 antibacterial drugs ranged from 89.1% to 112.4%. The intra-day precision of the analytes ranged from 1.4% to 9.3% and the inter-day precision from 2.1% to 7.2%. The matrix effects ranged from 93.1% to 105.8% and the extraction recoveries ranged between 90.1% and 109.2%. The stabilities of the 18 antibacterial drugs in plasma were evaluated by analyzing three different concentrations following storage at three storage conditions. All samples displayed variations less than 15.0%. The validated method was successfully applied to routine clinical TDM for 231 samples.

The application of nanomaterials (NMs) in agriculture has become a global concern in recent years. However, studies on their effects on plants are still limited. Here, we conducted a seed germination experiment for 5 days and a hydroponics experiment for 14 days to study the effects of silicon dioxide NMs(nSiO2) and silicon carbide NMs(nSiC) (0,10, 50, 200 mg/L) on rice (Oryza sativa L.). Bulk SiO2 (bSiO2) and sodium silicate (Na2SiO3) were used as controls. The results showed that nSiO2 and nSiC increased the shoot length (11–37%, 6–25%) and root length (17–87%, 59–207%) of germinating seeds, respectively, compared with the control. Similarly, inter-root exposure to nSiO2, bSiO2, and nSiC improved the activity of aboveground catalase (10–55%, 31–34%, and 13–51%) and increased the content of trace elements magnesium, copper, and zinc, thus promoting the photosynthesis of rice. However, Na2SiO3 at a concentration of 200 mg/L reduced the aboveground and root biomass of rice by 27–51% and 4–17%, respectively. This may be because excess silicon not only inhibited the activity of root antioxidant enzymes but also disrupted the balance of mineral elements. This finding provides a new basis for the effect of silica-based NMs promotion on seed germination and rice growth.

To ensure food safety, the current agricultural development has put forward requirements for improving nutritional quality and reducing the harmful accumulation of agricultural chemicals. Nano-enabled sustainable agriculture and food security have been increasingly explored as a new research frontier. Nano-fertilizers show the potential to be more efficient than traditional fertilizers, reducing the amount used while ensuring plant uptake, supplying the inorganic nutrients needed by plants, and improving the process by which plants produce organic nutrients. Other agricultural uses of nanotechnology affect crop productivity and nutrient quality in addition to nano-fertilizers. This article will review the research progress of using nanomaterials to improve nutritional quality in recent years and point out the focus of future research.

Abstract Ice accretion on wind turbine blades is one of the major faults affecting the operational safety and power generation efficiency of wind turbines. Current icing detection methods are based on either meteorological observing system or extra condition monitoring system. Compared with current methods, icing detection using the intrinsic supervisory control and data acquisition (SCADA) data of wind turbines has plenty of potential advantages, such as low cost, high stability, and early icing detection ability. However, there have not been deep investigations in this field at present. In this paper, a novel intelligent wind turbine blade icing detection method based on the wind turbine SCADA data is proposed. This method consists of three processes: SCADA data preprocessing, automatic feature extraction, and ensemble icing detection model construction. Specifically, deep autoencoders network is employed to learn multilevel fault features from the complex SCADA data adaptively. And the ensemble technique is utilized to make full use of all the extracted features from different hidden layers of the deep autoencoders network to build the ensemble icing detection model. The effectiveness of the proposed method is validated using the data collected from actual wind farms. The experimental results reveal that the proposed method is able to not only adaptively extract valuable fault features from the complex SCADA data, but also obtains higher detection accuracy and generalization capability compared with conventional machine learning models and individual deep learning model.

The aim of this study was to evaluate the therapeutic effects of Bletilla striata polysaccharide (BSP) on wound healing in diabetes mellitus (DM) and to explore the underlying mechanisms. DM mouse models were induced by high fat-diet feeding combined with low-dose streptozocin injection. To establish diabetic foot ulcer (DFU) models, DM mice were wounded on the dorsal surface. Subsequently, mice were treated with vehicle or BSP for 12 days and wound healing was monitored. The effects of BSP on the production of interleukin-1β (IL-1β), tumor necrosis factor-α, macrophages infiltration, angiogenesis, the activation of nucleotide-binding and oligomerization (NACHT) domain, leucine-rich repeat (LRR), and pyrin domain (PYD)-containing protein 3 (NLRP3) inflammasome, and insulin sensitivity in wound tissues were subsequently evaluated. Separated- and cultured- bone marrow-derived macrophages (BMDMs) and cardiac microvascular endothelial cells (CMECs) were isolated from mice and used to investigate the effects of BSP on cell viability, reactive oxygen species (ROS) generation, NLRP3 inflammasome activation and insulin sensitivity in vitro following exposure to high glucose (HG). BSP administration accelerated diabetic wound healing, suppressed macrophage infiltration, promoted angiogenesis, suppressed NLRP3 inflammasome activation, decreased IL-1β secretion, and improved insulin sensitivity in wound tissues in DM mice. In vitro, co-treatment with BSP protected against HG-induced ROS generation, NLRP3 inflammasome activation, and IL-1β secretion in BMDMs, and improved cell viability and decreased ROS levels in CMECs. Moreover, in HG exposed BMDMs-CMECs cultures, BSP treatment suppressed NLRP3 inflammasome activation and IL-1β secretion in BMDMs, and improved cell viability and insulin sensitivity in CMECs. Furthermore, treatment with IL-1β almost completely suppressed the beneficial effects of BSP on the NLRP3 inflammasome, IL-1β secretion, and insulin sensitivity in HG-treated BMDMs-CMECs. BSP promotes DFU healing through inhibition of the HG-activated NLRP3 inflammasome.

The recognition of defects in the solder paste printing process significantly influences the surface-mounted technology (SMT) production quality. However, defect recognition via inspection by a machine has poor accuracy, resulting in a need for the manual rechecking of many defects and a high production cost. In this study, we investigated SMT product defect recognition based on multi-source and multi-dimensional data reconstruction for the SMT production quality control process in order to address this issue. Firstly, the correlation between features and defects was enhanced by feature interaction, selection, and conversion. Then, a defect recognition model for the solder paste printing process was constructed based on feature reconstruction. Finally, the proposed model was validated on a SMT production dataset and compared with other methods. The results show that the accuracy of the proposed defect recognition model is 96.97%. Compared with four other methods, the proposed defect recognition model has higher accuracy and provides a new approach to improving the defect recognition rate in the SMT production quality control process.

In this study, the cold rolling microstructure and static recrystallization mechanism of the high strength titanium alloy Ti-3.5Al-5Mo-6V-3Cr-2Sn-0.5Fe were systematically investigated. Results show that the cold rolling microstructure is mainly composed of the elongated deformed β grains containing micro-shear bands. After annealing at 815 °C for 2 min, the fine SRXed grains are observed, mainly concentrated in the micro-shear band, the grain boundary and the interior of the deformed grain. The sub-grain structure obtained by static recovery inside the deformed grain produces continuous SRX during the annealing treatment. Meanwhile, geometric and discontinued SRXed grains are also observed in the large deformed β grain and at the trigeminal grain boundaries, respectively. Many ultra-fine grains appear inside the micro-shear band, exhibiting a phenomenon of the micro-shear band assisting SRX. With the increase in the annealing holding time, the elongated β grains are significantly refined and the degree of recrystallization is continuously improved. In addition, the recrystallization behavior also results in a significant change in the fiber texture. With the extension of the annealing holding time, the rolling texture type evolves gradually, with the {111} γ-fiber texture to weak α-fiber, γ-fiber, and Goss-fiber.

Angoroside C is a phenylpropanoid glycoside compound isolated from the dried root of Scrophularia ningpoensis Hemsl., which possesses the effects of preventing ventricular remodeling, reducing pulmonary oedema, and reducing blood pressure, as well as having the properties of anti-platelet aggregation, hepatoprotection and anti-nephritis, etc. However, few investigations have been conducted on the absorption, distribution, metabolism, and excretion (ADME) study of angoroside C. Thus, a fast ultra-high performance liquid chromatography-tandem quadrupole mass spectrometry (UPLC-MS/MS) method was established for the determination of angoroside C and its metabolite ferulic acid in rat plasma and tissue homogenate. The two analytes were extracted from the biosamples using a simple protein precipitation with acetonitrile. The developed method was validated and successfully applied to the pharmacokinetics, bioavailability and tissue distribution study after the intragastric administration of angoroside C (100 mg/kg) or the intravenous administration of angoroside C (5 mg/kg), respectively. The results showed that angoroside C can be absorbed extremely quickly (Tmax = 15 min), can be eliminated very rapidly (t1/2 = 1.26 h), and its oral bioavailability is only about 2.1%. Furthermore, angoroside C was extensively distributed in all main organs (liver, heart, spleen, lung, kidney, and brain), and the highest concentration was detected in the lung 15 min after oral administration. This paper also indicated that angoroside C could be converted to the active metabolite ferulic acid in vivo. The maximum concentrations of ferulic acid in the kidney occurred at 6 h after oral administration. In summary, this study explored some of the pharmacokinetic characteristics of angoroside C in vivo, and the data produced could provide a basis for the further investigation of angoroside C.