Polyol‐enhanced dispersive liquid–liquid microextraction coupled with gas chromatography and nitrogen phosphorous detection for the determination of organophosphorus pesticides from aqueous samples,fruit juices,and vegetables

Polyol‐enhanced dispersive liquid–liquid microextraction has been proposed for the extraction and preconcentration of some organophosphorus pesticides from different samples. In the present study, a high volume of an aqueous phase containing a polyol (sorbitol) is prepared and then a disperser solvent along with an extraction solvent is rapidly injected into it. Sorbitol showed the best results and it was more effective on the extraction recoveries of the analytes than inorganic salts such as sodium chloride, potassium chloride, and sodium sulfate. Under the optimum extraction conditions, the method showed low limits of detection and quantification within the ranges of 12–56 and 44–162 pg/mL, respectively. Enrichment factors and extraction recoveries were in the ranges of 2799–3033 and 84–92%, respectively. The method precision was evaluated at a concentration of 10 ng/mL of each analyte, and relative standard deviations were found to be less than 5.9% for intraday (n = 6) and less than 7.8% for interday (n = 4). Finally, some aqueous samples were successfully analyzed using the proposed method and four analytes (diazinon, dimethoate, chlorpyrifos, and phosalone) were determined, some of them at ng/mL level.     

DMA-80测汞仪直接测定固体样品中的汞

利用DMA-80测汞仪直接测定固体样品中的汞,采用升温加热直接进行热分解、金汞齐反应,采用长、短双检测池,可直接测定固体、液体样品,汞含量在0.n~600.0ng/g范围内的样品都能准确地测定,每个样品测定时间约为5min。测定结果证明方法具有可靠性。     

Correlation‐assisted nearest shrunken centroid classifier with applications for high dimensional spectral data

High throughput data are frequently observed in contemporary chemical studies. Classification through spectral information is an important issue in chemometrics. Linear discriminant analysis (LDA) fails in the large‐p‐small‐n situation for two main reasons: (1) the sample covariance matrix is singular when p > n and (2) there is an accumulation of noise in the estimation of the class centroid in high dimensional feature space. The Independence Rule is a class of methods used to overcome these drawbacks by ignoring the correlation information between spectral variables. However, a strong correlation is an essential characteristic of spectral data. We proposed a new correlation‐assisted nearest shrunken centroid classifier (CA‐NSC) to incorporate correlation information into the classification. CA‐NSC combines two sources of information [class centroid (mean) and correlation structure (variance)] to generate the classification. We used two real data analyses and a simulation study to verify our CA‐NSC method. In addition to NSC, we also performed a comparison with the soft independent modeling of class analogy (SIMCA) approach, which uses only correlation structure information for classification. The results show that CA‐NSC consistently improves on NSC and SIMCA. The misclassification rate of CA‐NSC is reduced by almost half compared with NSC in one of the real data analyses. Generally, correlation among variables will worsen the performance of NSC, even though the discriminatory information contained in the class centroid remains unchanged. If only correlation structure information is used (as in the case of SIMCA), the result will be satisfactory only when the correlation structure alone can provide sufficient information for classification. Copyright © 2015 John Wiley & Sons, Ltd.     

Robustness quantification method for network intrusion detection models

Deep learning techniques have been successfully applied to network intrusion detection tasks, but as in the case of autonomous driving and face recognition, the reliability of the system itself has become a pressing issue. Robustness is a key attribute to determine whether a deep learning system is secure and reliable, and we also choose to explore the security of intrusion detection models from a new perspective of robustness quantification. In this paper, we focus on the intrusion detection model based on long and short-term memory, and use a fine-grained linear approximation method to derive a more accurate robustness bound on the nonlinear activation function with tighter linear constraints. We can use this bound to quantitatively measure the robustness of the detection model and determine whether the model is susceptible to the influence of adversarial samples. In our experiments, we test networks with various structures on the MNIST dataset, and the results show that our proposed method can effectively deduce the robustness bounds of output elements, and has good scalability and applicability.     

基于酶循环放大的DNA生物传感器用于检测食管鳞状细胞癌生物标志物蛋白PDGF-BB

食管鳞状细胞癌（ESCC）患者发病早期由于体内的肿瘤标志物种类少且含量低,难以在患病早期发现疾病从而快速反应并有效治疗。因此,找到一种合适的标志物对其进行快速高效检测是研究者亟待解决的问题。血小板衍生生长因子（PDGF－BB）在恶性肿瘤的早期诊断中具有极其重要的地位。该文基于酶循环放大荧光光谱设计了一种用于PDGF－BB检测的DNA生物传感器,利用特定位点剪切酶,实现了信号放大,检出限由1 fmol/L降至1 amol/L,大大提高了检测的灵敏度。该方法通过检测血液中PDGF－BB浓度,从而实现对ESCC的简单、快速、高效诊断,在生物化学和医学应用上具有重要价值。     

基质辅助激光解析/电离飞行时间质谱(MALDI-TOF MS)在微生物鉴定中的应用*

基质辅助激光解析/电离飞行时间质谱(MALDI-TOF MS)是一种新型软电离生物质谱,具有检测速度快、操作简便、结果准确等优点,目前已成为可靠的微生物快速鉴定技术。就工作流程而言,与常规生化方法相比,MALDI-TOF MS可以将微生物鉴定的时间缩短为一天甚至更短。对于具有抗生素耐药性的微生物,使用MALDI-TOF MS鉴定也有很好的准确性。在病毒鉴定中,MALDI-TOF MS也可以发挥作用,已有报道将MALDI-TOF MS和机器学习(ML)分析方法结合来检测鼻拭子中SARS-CoV-2。此外,MALDI-TOF MS还可用于细菌的无光谱库鉴定。目前,MALDI-TOF MS正通过与其他技术(例如傅里叶红外光谱FTIR)相结合进一步扩大微生物鉴定范围。     

Rational Design of Ratiometric Fe3+ Fluorescent Probes Based on FRET Mechanism

As the most abundant transition metal element in mammals, iron(Fe) plays a vital role in life activities. It is of great significance to study the variation of Fe³⁺ level in living organisms. In virtue of the advantages of high sensitivity, good selectivity and low damage to living systems, the fluorescence detection of Fe³⁺ has attracted much attention. Compared with the intensity-based fluorescent probe, the ratiometric fluorescent probe has less interference of environmental and can realize quantitative detection. In this study, four ratiometric Fe³⁺ fluorescent probes, R1, R2, R3 and R4_, were designed and synthesized using fluorescence resonance energy transfer(FRET) mechanism to achieve quantitative detection of Fe³⁺. In the FRET systems, 1,8-naphthalimide fluorophore derivatives were adopted as donors while rhodamine B derivatives were selected as receptors. The connection sites of the donor and acceptor in R3 and R4 are different from those in R1 and R2. All the four probes showed good response and selectivity to Fe³⁺. The energy transfer efficiencies of R3 and R4 were obviously higher than those of R1 and R2. This work provided a promising strategy for the development of fluorescent ratiometic Fe³⁺sensors.     

Bipolar Electrode-based Electrochromic Devices for Analytical Applications – A Review

Bipolar electrode-based (BPE-based) electrochromic devices have garnered increasing attention in the past decade. These BPE-based electrochromic devices have been used for analytical health monitoring, point-of-care (POC) diagnostics, and chemical sensing. In this review, we highlight recent progress made regarding BPE-based electrochromic devices constructed for these analytical applications. Various, available electrochromic materials are summarized in the first section, after which the different device types (e. g., paper-based and self-powered) are discussed. Biological- and chemical-based analytical demonstrations of these devices are then reviewed. Finally, we conclude this review with a perspective on the future developments of BPE-based electrochromic devices in analytical applications.     

Synthesis,characterization and applications of schiff base chemosensor for determination of Cu2+ ions

A novel thiazole-based Schiffbase chemosensor SB1 with N- and O- donor atoms was synthesized and characterized by different techniques (UV–vis, ¹³C NMR, ¹H NMR, and FT-IR analysis). The chemosensor SB1 was used for the determination of Cu²⁺ ions in various samples. The significant spectral changes in absorption spectra of chemosensor SB1 at 220 and 416 nm and the color change from light yellow to yellowish-brown indicate high selectivity and sensitivity towards Cu²⁺ ions as compared to other cations (Na⁺, K⁺, Ag⁺, Zn²⁺, Ni²⁺, Pb²⁺, Mn²⁺, Mg²⁺, Co²⁺, Cd²⁺, Sn²⁺, Hg²⁺, Cr³⁺, Fe^3+, and Al³⁺). The sensing mechanism of SB1 was investigated through various techniques such as FT-IR, UV–vis and ¹H NMR titration experiment and further confirmed by DFT computational studies. The 2:1 binding mode between SB1 and Cu²⁺ ions was confirmed by Job‘s plot using UV–vis spectrophotometry. The limit of detection (LOD) and limit of quantification (LOQ) were found to be 0.015 and 0.0471 µg mL^?1, respectively. The percent recovery of Cu²⁺ from various environmental samples was found to be 95.00–103.33% at various levels. These obtained results demonstrate that chemosensor SB1 is a cost-effective, facile, selective, sensitive, and colorimetric sensing platform to detect trace amounts of Cu²⁺ ions in variousenvironmental and agricultural samples.