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Nanostructures possessing plasmonic and magnetic properties can enhance the transverse magneto-optical Kerr effect (TMOKE) by exciting surface plasmon resonances (SPRs). This provides a promising platform for magneto-optical SPR sensors with significantly improved sensing performance. Here, we propose a high-performance magneto-optical SPR sensor, which consists of a bilayer Au/Co grating placed on a gold film. By tuning the structural parameters, a Fano-like TMOKE spectrum with a linewidth of only 0.0135 nm and an amplitude approaching the theoretical maximum is obtained. We attribute the optimal TMOKE signal achieved by the sensor to the critical coupling concept which is associated with the trade-off between scattering and intrinsic decay rates of the system. The optimized nanostructure sensor demonstrates a sensitivity of 1432 nm/RIU to refractive index fluctuations as small as 0.0001 in air, and all figures of merit (FOM) up to 105 RIU−1, making it suitable for gas sensor fabrication. [ABSTRACT FROM AUTHOR]

Background There is growing evidence that pre-hospital use of metformin reduces mortality in patients with diabetes and sepsis; however, the effect of metformin on clinical outcomes in patients with diabetes and sepsis remains controversial. Therefore, there is a need for a systematic review and Meta-analysis of existing studies to further evaluate whether metformin can improve mortality and other clinical outcomes in patients with diabetes and sepsis. Objective To systematically evaluate the effects of pre-hospital metformin use on mortality, initial plasma lactate level and organ dysfunction in patients with diabetes and sepsis. Methods PubMed, Embase, Cochrane Library, Web of Science, Scopus, China Biomedical Literature Service System, Wanfang Data, CNKI and other databases were searched by computer for Chinese and English literature on the effects of pre-hospital metformin use on clinical outcomes in patients with sepsis and diabetes from inception to March 15, 2023. The test group (MET group) involved adult patients with diabetes and sepsis received pre-hospital metformin use, and the control group (NM group) involved adult patients with diabetes and sepsis who did not receive pre-hospital metformin use. After screening, data extraction and literature quality evaluation were conducted by two researchers, Meta-analysis was performed using RevMan 5.3 software. Results A total of 12 papers were included in this study, involving 12 320 patients with diabetes and sepsis, with Newcastle-Ottawa Scale (NOS) scores of 7-8. The results of Meta-analysis showed that the mortality rate (OR=0.61, 95%CI=0.46 to 0.80, P

In order to rapidly and non-destructively detect gastrodin and 4-hydroxybenzyl alcohol in Rhizoma Gastrodiae, near infrared spectral data of the dried tuber of Gastrodia elata Bl. f. glauca S. Chow were collected in the wavelength range of 900–1 700 nm. First, convolutional smoothing (SG) and standard normal variable transformation (SNV) were used for spectral data preprocessing. Second, feature wavelength extraction was carried out by competitive adaptive reweighted sampling (CARS) and iteratively retains informative variables (IRIV). According to the results of establishing least squares support vector machine (LSSVR) model based on feature wavelength, the best method of feature wavelength extraction was selected. In order to improve the accuracy of the model, this study introduced the artificial rabbits optimization (ARO) algorithm to optimize the regularization parameter γ and the kernel function density σ2 in LSSVR and the superiority of ARO to particle swarm optimization (PSO) and grey wolf optimizer (GWO) was evaluated. The results showed that the ARO algorithm was superior to PSO and GWO in in terms of optimization speed and ability. The best prediction models for gastrodin and 4-hydroxybenzyl alcohol were CARS-ARO-LSSVR, with prediction correlation coefficient (R2p) of 0.969 6 and 0.957 7, and root mean square error of prediction (RMSEP) of 0.014 and 0.020, respectively. Therefore, this study shows that near-infrared spectroscopy can be used for quantitative detection of active components in Rhizoma Gastrodiae, which provides a theoretical basis for the development of rapid detection devices for Rhizoma Gastrodiae.

In order to identify Panax notoginseng powders from different root parts, an electronic nose and gas chromatography-mass spectrometry (GC-MS) were used to analyze the volatile components of the whole root powder, rhizome powder, taproot powder, lateral root powder and fibrous root powder of P. notoginseng. The data obtained were analyzed by multiple comparison. The statistical learning method was used to extract eight time-domain features from the response curves of the electronic nose, and correlation analysis was carried out. Three feature selection algorithms were used to reduce the dimension of the feature data. Classification models were built using support vector machine (SVM), least square support vector machine (LSSVM) or extreme learning machine (ELM) based on the original feature data or the three kinds of feature selection data. The grey wolf optimization (GWO) algorithm was introduced to optimize the parameters gam and sig2 in the classification model. The results showed that a total of 31 volatile compounds were detected in the five P. notoginseng powders. The best GWO-IRIV-LSSVM model could effectively distinguish the electronic nose data, with 97.5% accuracy for the test set. Moreover, the volatile composition of the five samples differed mainly in terms of the contents of total volatiles, alkanes, and aromatic compounds, which was consistent with the results of GC-MS. The method used in this study can be used for the detection of high-quality P. notoginseng powder from geo-authentic production areas mixed with low-quality P. notoginseng powder.

The time-modulated active medium with linear independent frequency conversion method has been demonstrated to enable wave orientation and reconstruction. However, due to the symmetric scattering field, this technique requires intricate microcircuit designs. To overcome this limitation, this paper proposes a tunable piezoelectric metasurface based on acoustic black holes (ABHs) to redirect flexural wave reflections. The system can convert an incident flexural wave into a reflected wave of any direction and frequency. This is accomplished through the linear time modulation of the sensing signal, which breaks the constraints of Snell's law inherent in traditional designs and is insensitive to the incident amplitude. The coupling of the ABH damping system with a linear independent frequency conversion mechanism allows for the conversion of an incident flexural wave into a reflected wave in any direction and frequency while also eliminating the influence of second harmonic reflection on the wave field and simplifying the time modulation circuit. In addition, this paper demonstrates arbitrary angle reflection, focusing, beam splitting, and frequency conversion of the incident wave. By improving the flexibility of elastic wave manipulation, this paper introduces a new approach for active control of elastic waves and provides a design method that can be employed in a variety of applications ranging from vibration protection of engineering structures to vibration sensing and evaluation. [ABSTRACT FROM AUTHOR]

Peripheral neuropathy is a common complication during treatment of multiple myeloma, which affecting the prognosis and patients’ quality of life. Effective prevention, treatment and nursing interventions have been proved to reduce the incidence of multiple myeloma complicated by peripheral neuropathy. This paper reviewed the studies on nursing of multiple myeloma complicated by peripheral neuropathy in perspectives of risk factors, prevention, treatment and nursing interventions, in order to provide reference for clinical nursing practice. (多发性骨髓瘤周围神经病变(MMPN)是多发性骨髓瘤(MM)治疗过程中常见的并发症之一, 严重影响患者的生活质量及预后, 有效的预防措施、治疗方法和护理干预均能有效降低MMPN的发生率。本研究从MMPN的危险因素、预防、治疗及护理干预措施进行综述, 旨在为MMPN患者的护理提供参考依据和实践指导。)