Single-impact electrochemistry for the analysis of bacteria is a powerful technique for biosensing applications at the single-cell scale. The sensitivity of this electro-analytical method has been widely demonstrated based on chronoamperometric measurements at an ultramicroelectrode polarized at the appropriate potential of redox species in solution. Furthermore, the most recent studies display a continuous improvement in the ability of this sensitive electrochemical method to identify different bacterial strains with better selectivity. To achieve this, several strategies, such as the presence of a redox mediator, have been investigated for detecting and identifying the bacterial cell through its own electrochemical behavior. Both the blocking electrochemical impacts method and electrochemical collisions of single bacteria with a redox mediator are reported in this review and discussed through relevant examples. An original sensing strategy for virulence factors originating from pathogenic bacteria is also presented, based on a recent proof of concept dealing with redox liposome single-impact electrochemistry. The limitations, applications, perspectives, and challenges of single-impact electrochemistry for bacteria analysis are briefly discussed, based on the most significant published data.

The emergence of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in 2019 caused an increased interest in neutralizing antibody tests to determine the immune status of the population. Standard live-virus-based neutralization assays such as plaque-reduction assays or pseudovirus neutralization tests cannot be adapted to the point-of-care (POC). Accordingly, tests quantifying competitive binding inhibition of the angiotensin-converting enzyme 2 (ACE2) receptor to the receptor-binding domain (RBD) of SARS-CoV-2 by neutralizing antibodies have been developed. Here, we present a new platform using sulforhodamine B encapsulating liposomes decorated with RBD as foundation for the development of both a fluorescent, highly feasible high-throughput (HTS) and a POC-ready neutralizing antibody assay. RBD-conjugated liposomes are incubated with serum and subsequently immobilized in an ACE2-coated plate or mixed with biotinylated ACE2 and used in test strip with streptavidin test line, respectively. Polyclonal neutralizing human antibodies were shown to cause complete binding inhibition, while S309 and CR3022 human monoclonal antibodies only caused partial inhibition, proving the functionality of the assay. Both formats, the HTS and POC assay, were then tested using 20 sera containing varying titers of neutralizing antibodies, and a control panel of sera including prepandemic sera and reconvalescent sera from respiratory infections other than SARS-CoV-2. Both assays correlated well with a standard pseudovirus neutralization test (r = 0.847 for HTS and r = 0.614 for POC format). Furthermore, excellent correlation (r = 0.868) between HTS and POC formats was observed. The flexibility afforded by liposomes as signaling agents using different dyes and sizes can hence be utilized in the future for a broad range of multianalyte neutralizing antibody diagnostics.

Since the last decade, carbon nanomaterials have had a notable impact on different fields such as bioimaging, drug delivery, artificial tissue engineering, and biosensors. This is due to their good compatibility toward a wide range of chemical to biological molecules, low toxicity, and tunable properties. Especially for biosensor technology, the characteristic features of each dimensionality of carbon-based materials may influence the performance and viability of their use. Surface area, porous network, hybridization, functionalization, synthesis route, the combination of dimensionalities, purity levels, and the mechanisms underlying carbon nanomaterial interactions influence their applications in bioanalytical chemistry. Efforts are being made to fully understand how nanomaterials can influence biological interactions, to develop commercially viable biosensors, and to gain knowledge on the biomolecular processes associated with carbon. Here, we present a comprehensive review highlighting the characteristic features of the dimensionality of carbon-based materials in biosensing.

Here, we report on the feasibility of using quantitative NMR and ultra-microbalances for additional measurements of the mass of poly-ethylene terephthalate (PET) particles in a reference material (RM). The microplastic (MP) PET particles were immobilised in solid NaCl following freeze-drying of a 1-ml NaCl suspension. The particles ranged from 30 to about 200 µm (Feretmin). In a 3-day process, more than 500 such units of PET particles in the NaCl carrier were prepared and later used in a large-scale inter-laboratory comparison. The homogeneity of PET in the salt carrier over these 500 units had previously been evaluated with respect to the mass of PET using an ultra-microbalance. In addition to the original results obtained by weighing, two independent results of quantitative 1H-NMR have been obtained for further investigation of this reference material together with one additional set of weighing data. The NMR data were used for confirmation of the weighed amount of PET (as weighing is non-specific for PET). Average masses of 0.293 ± 0.04 mg and 0.286 ± 0.03 mg of PET were obtained using two different ultra-microbalances (14% RSD for n = 14 and 9% RSD for n = 4, respectively). The corresponding 1H-NMR data was 0.300 ± 0.02 mg of PET (6.7% RSD for n = 5) and 0.345 ± 0.04 mg of PET (12.5% RSD for n = 14), respectively. The average mass of PET obtained by 1H-NMR measurements was in agreement with the weighed amounts within their standard deviations. A mean value of 0.306 mg PET with an expanded uncertainty of 0.058 mg (± 19% relative) was calculated, and it is traceable to the SI system of measurements. Measurement of PET by quantitative 1H-NMR spectroscopy is also reported for a water sample. The PET contained in one RM sample was transferred to 1 L of water to mimic a drinking water sample for microplastics.

Histone proteins are essential to the regulation of the eukaryotic genome. Histone post-translational modifications (PTMs) and single-molecule combinations of these modifications (proteoforms) allow for the regulation of many DNA-templated processes, most notably transcription. Histone H4 is a part of the core histone octamer, which packages DNA into nucleosomes. Top-down proteomics allows for the inquiry of the epigenetic landscape with proteoform-level specificity. Although these approaches are well-demonstrated ex vivo, our knowledge of in vivo histone proteoform biology remains sparse. Here, we demonstrate the first in vivo quantitative top-down analysis of histone H4 and analyze the forebrains and hindbrains of differently aged mice. This reveals novel differences between the mouse forebrain and hindbrain and region-specific changes during adolescence in histone H4 PTMs and proteoforms. At 25 days of age (P25), histone H4 of the hindbrain is more acetylated than the forebrain. At 47 days of age (P47), there are fewer significant differences in histone H4 PTMs and their combinations between regions. Histone H4 of the forebrain is more acetylated in P47 than in P25 forebrains. Hindbrains exhibit the opposite difference with histone H4 of the P25 hindbrain being more acetylated than that of P47 hindbrains. These differences are mainly driven by less abundant hyperacetylated proteoforms. Transcription of histone acetyltransferases such as p300, CBP, and HAT1 is known to be higher in cortical neurons, consistent with the observed acetylation levels. Lysine 20 methylation (K20me1, K20me2, and K20me3) is notably invariant with brain region and age difference.

Hydrogen peroxide (H2O2) is considered a significant biomarker in various diseases and could induce deleterious health problems at irregular physiological concentrations. Therefore, developing a simple, efficient biocompatible nanoprobe for trace amount H2O2 detection with high sensitivity and specificity is of great help for early diagnosis and therapeutics. Herein, we designed amphiphilic poly(styrene-co-maleic anhydride) (PMSA)-encapsulated nanoclusters composed of upconversion nanoparticles (UCNPs) and manganese dioxide nanoparticles (MnO2 NPs) at a specific ratio to produce a near-infrared (NIR) excited luminescent nanoprobe for H2O2 detection. Our results revealed that the MnO2 NPs tended to experience catalytic decomposition when exposed to H2O2, while the UCNPs were retained inside the PSMA encapsulation, causing recovery of the UCNP emission band at 470 nm in accordance with H2O2 concentration. This luminescence recovery was linearly dependent on H2O2 concentrations, yielding a limit of detection (LOD) of 20 nM. The easy-to-interpret H2O2 nanoprobe also proved high selectivity in the presence of other interfering substances, and biocompatibility and water-dispersibility, making it an ideal candidate for real-time detection of disease-related H2O2 in living organisms.

Multifunctional compounds may form different prototropic isomers under different conditions, which are known as protomers/deprotomers. In biological systems, these protomer/deprotomer isomers affect the interaction modes and conformational landscape between compounds and enzymes and thus present different biological activities. Study on protomers/deprotomers is essentially the study on the acidity/basicity of each intramolecular functional group and its effect on molecular structure. In recent years, the combination of mass spectrometry (MS) and computational chemistry has been proven to be a powerful and effective means to study prototropic isomers. MS-based technologies are developed to discriminate and characterize protomers/deprotomers to provide structural information and monitor transformations, showing great superiority than other experimental methods. Computational chemistry is used to predict the thermodynamic stability of protomers/deprotomers, provide the simulated MS/MS spectra, infrared spectra, and calculate collision cross-section values. By comparing the theoretical data with the corresponding experimental results, the researchers can not only determine the protomer/deprotomer structure, but also investigate the structure-activity relationship in a given system. This review covers various MS methods and theoretical calculations and their devotion to isomer discrimination, structure identification, conformational transformation, and phase transition investigation of protomers/deprotomers.

A novel matrix certified reference material (CRM) for clenbuterol in mutton (GBW 10216) was developed to assist measurement and risk monitoring of clenbuterol in mutton. The candidate CRM raw samples were obtained by oral administration of clenbuterol and investigating the pharmacokinetics of clenbuterol in sheep. A high-precision isotope dilution coupled with liquid chromatography tandem mass spectrometry (LC-ID-MS/MS) method was established and assigned the value of clenbuterol in mutton powder through combined detection of nine inter-laboratories. The certified value with expanded uncertainty was 21.1 ± 2.2 μg/kg (k = 2, 95% confidence) for clenbuterol in mutton. The prepared matrix CRM was sufficiently homogeneous between and within bottles. The long-term stability of clenbuterol in mutton powder was evaluated for 12 months at -20℃ and short-term stability for 7 days at 4℃ and 50℃. The uncertainties originating from characterization, homogeneity, and stability were systematically analyzed and evaluated. The prepared matrix CRM can be applied for proficiency testing and nationwide risk monitoring programs to guarantee the accuracy and comparability of clenbuterol measurement results in mutton.

The detection of emerging contaminants (ECs) and understanding their ecotoxicity has brought new challenges to water pollution control. Triclosan (TCS), as an emerging contaminant, is a commonly used antibacterial agent widely present in the environment. Microdialysis (MD), as a sampling technique, can overcome some of the deficiencies of traditional approaches to sampling, using sources such as blood, urine, tissue, and target organs, in terms of invasiveness, time from collection to analysis, and possible changes during sample preparation. In this study, we coupled MD with analysis using UHPLC-QTOF/MS to identify the endogenous metabolites in the liver as biomarkers of the exposure of living crucian carp to TCS. The identified biomarkers were then quantified using UHPLC-MS/MS to continuously monitor the effect of TCS on endogenous metabolites in the liver of living crucian carp, which contributes to a better understanding of the toxicological effect of TCS. The experimental results demonstrated that TCS exposure interfered with the metabolic pathways of amino acids (L-isoleucine and L-histidine), purines (xanthine and hypoxanthine), and small nerve molecules (acetylcholine and choline).

Cortisol is a crucial hormone involving many physiological processes. Hence, cortisol detection is essential. This review highlights the key progress made on wearable electrochemical sensors using antibodies. It covers the design, principle, and electroanalytical methodology for detecting cortisol noninvasively. This article also analyzes and collects the analytical performances of electrochemical cortisol sensors. The development of these sensors continues to face challenges such as biofouling, sample management, sensitivity, flexibility, stability, and recognition layer performance. It is also necessary to develop a sensitive electrode and material. This article also presents potential strategies for designing antibody electrodes and provides examples of sensing systems. Additionally, it discusses the challenges in translating research into practical applications.

Polarized light microscopy (PLM) is a common but critical method for pharmaceutical crystallinity characterization, which has been widely introduced for research purposes or drug testing and is recommended by many pharmacopeias around the world. To date, crystallinity characterization of pharmaceutical solids is restricted to laboratories due to the relatively bulky design of the conventional PLM system, while little attention has been paid to on-site, portable, and low-cost applications. Herein, we developed a smartphone-based polarized microscope with an ultra-miniaturization design ("hand-held" scale) for these purposes. The compact system consists of an optical lens, two polarizers, and a tailor-made platform to hold the smartphone. Analytical performance parameters including resolution, imaging quality of interference color, and imaging reproducibility were measured. In a first approach, we illustrated the suitability of the device for pharmaceutical crystallinity characterization and obtained high-quality birefringence images comparable to a conventional PLM system, and we also showed the great promise of the device for on-site characterization with high flexibility. In a second approach, we employed the device as a proof of concept for a wider application ranging from liquid crystal to environmental pollutants or tissues from plants. As such, this smartphone-based hand-held polarized light microscope shows great potential in helping pharmacists both for research purposes and on-site drug testing, not to mention its broad application prospects in many other fields.

Liquid biopsies have significance for early colon cancer screening and improving patient survival. Recently, several researchers have applied surface-enhanced Raman spectroscopy (SERS) for the label-free and non-invasive detection of serum. Most of these studies performed the assay using a mixture of noble metal nanoparticles (NMNPs) with serum. However, SERS analysis of serum remains a challenge in terms of reproducibility and stability, as NMNPs tend to aggregate when mixed with serum, resulting in a non-uniform distribution of hot spots. Here, we report on the non-invasive identification of colon cancer (CC) using an internal standard (IS)-calibrated label-free serum SERS assay in combination with machine learning. Serum SERS spectra of 50 CC patients and 50 health volunteers have been obtained using silver nanoparticle (Ag NP) colloid and mercaptopropionic acid-modified Ag NPs (Ag NPs-MPA) as the SERS substrates. Decision tree (DT), random forest (RF), and principal component and linear discriminant analysis (PCA-LDA) algorithms were utilized to establish the diagnosis model for SERS spectra data classifying. The results show that the RF model provides a high diagnostic accuracy compared to PCA-LDA. Following calibration with IS molecules, high diagnostic accuracy of over 90% and 100% specificity can be achieved with DT, RF, and PCA-LDA algorithms to differentiate between cancer and normal groups. The results from this exploratory work demonstrate that serum SERS detection combined with multivariate statistical methods and IS calibration has great potential for the non-invasive and label-free detection of CC.

Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) studies on trace element concentration and their spatial distribution in CaC2O4-matrix urinary stones are important but powerfully rely on matrix-matched external calibration. In this work, CaC2O4 precipitate CaOx-1 which was doped with Mg, Cr, Mn, Fe, Co, Cu, Zn, and Sr was prepared by the homogeneous co-precipitation method. It had a homogeneous distribution of major (RSD of 0.46%) and trace elements (RSD of 1.83-6.92%) due to the negligible concentration difference compared with that prepared by the heterogeneous co-precipitation method. Based on this, an analytical method for quantitative determination of elemental concentration in CaC2O4-matrix samples was established using CaOx-1 as a calibration standard, and the accuracy of this method was assessed by calibrating the elemental concentration in another synthetic CaC2O4 precipitate CaOx-2 with relative deviation (Dr) from - 11.43% (Mn) to 9.76% (Mg). Finally, a methodology for quantitative imaging of Mg, Cr, Mn, Fe, Co, Cu, Zn, and Sr in urinary stones via LA-ICP-MS was developed. From the elemental distributional maps, an annular texture can be found for Mg, Cu, Zn, and Sr, which corresponds to the annular white and brown texture in the real urinary stone. A homogeneous distribution of Fe and low concentrations of Cr and Co were found throughout the stone, while Mn was highly concentrated in the margin of the stone. All these results demonstrate that quantitative distribution patterns of Mg, Cr, Mn, Fe, Co, Cu, Zn, and Sr can be obtained by LA-ICP-MS using CaOx-1 as a calibration standard, which can provide potential evidence for urological and other medical studies.

This paper describes the design and construction of dual microfluidic paper-based analytical devices (dual-μPADs) as a lab-on-paper platform involving a "do-it-yourself" fabrication protocol. The device comprises a colorimetric and electrochemical module to obtain a dual-mode signal readout sensing strategy. A 3D pen polymeric resin was used to prepare graphite carbon-based electrodes and hydrophobic barriers on paper substrates. The proposed carbon-based ink was employed to manufacture electrodes on paper based on a stencil-printing approach, which were further characterized by electrochemical and morphological analyses. The analytical performance of the dual-μPADs was simultaneously evaluated for lactate, pH, nitrite, and salivary amylase (sAA) analysis. To demonstrate the proof-of-concept, saliva samples collected from both healthy individuals and those with periodontitis were successfully tested to demonstrate the feasibility of the proposed devices. Samples collected from individuals previously diagnosed with periodontitis showed high levels of nitrite and sAA (> 94 μmol L-1 and > 610 U mL-1) in comparison with healthy individuals (≤ 16 μmol L-1 and 545 U mL-1). Moreover, periodontitis saliva resulted in acid solution and almost null lactate levels. Notably, this protocol supplies a simple way to manufacture dual-μPADs, a versatile platform for sensitive detecting of biomarkers in saliva playing a crucial role towards the point-of-care diagnosis of periodontal disease.

This work details the enzymatic generation of fluorescence nanomaterials and the use of this optical signal as the analytical parameter for the quantification of the substrate. More specifically, fluorescent copper nanoclusters have been obtained during the enzymatic reaction of tyramine oxidase and tyramine in the presence of Cu(II); the fluorescence intensity being proportional to the concentration of tyramine. The nanoclusters obtained show fluorescence at 445 nm by being excited at 320 nm and have been characterized by TEM, EDX, and XPS. The formation mechanism has also been studied, suggesting that under the optimal conditions (0.1 M MES buffer and pH = 6), the formation of the nanoclusters is due to the reducing properties of the product of the enzymatic reaction (p-hydroxybenzaldehyde) in MES buffer. The method shows a linear relationship with the concentration of tyramine in the range from 1.0·10-5 to 2.5·10-4 M, a RSD of 3% (n = 5) and a LOD of 6.3·10-6 M. The method has been applied to the determination of tyramine in sausage with good results.

Arginine methylation is involved in many important biological processes. PRMT1 is a major arginine methyltransferase in mammalian cells and is highly conserved in eukaryotes. It catalyzes the methylation of various of substrates, including histones, and PRMT1 has been reported to be overexpressed in many cancers, indicating that it is a potential therapeutic target. No tool for efficient methylation level detection in living cells has been available to date. In this work, we designed and constructed a gene-encoded fluorescence resonance energy transfer (FRET) fluorescent sensor for detecting dimethylation levels in living cells and evaluated its functional efficiency both in vitro and in living cells. Both site-directed mutagenesis and PRMT1 inhibition experiments verified that the fluorescent sensor responded to changes in PRMT1 activity and to different PRMT1-induced methylation levels in vitro. Finally, we verified that this optimized methyl sensor responded sensitively to changes in methylation levels in living cells by overexpressing and inhibiting PRMT1, which makes it a useful tool for real-time imaging of arginine methylation. As a new tool for detecting arginine dimethylation levels in living cells, the designed FRET sensor is very important for posttranslational studies and may show a wide range of applications.

It is well known that the processing method of herbal medicine has a complex impact on the active components and clinical efficacy, which is difficult to measure. As a representative herb medicine with diverse processing methods, Radix Paeoniae Alba (RPA) and its processed products differ greatly in clinical efficacy. However, in some cases, different processed products are confused for use in clinical practice. Therefore, it is necessary to strictly control the quality of RPA and its processed products. Giving that the time-consuming and laborious operation of traditional quality control methods, a comprehensive strategy of near-infrared (NIR) spectroscopy combined with multivariate algorithms was proposed. This strategy has the advantages of being rapid and non-destructive, not only qualitatively distinguishing RPA and various processed products but also enabling quantitative prediction of five bioactive components. Qualitatively, the subspace clustering algorithm successfully differentiated RPA and three processed products, with an accuracy rate of 97.1%; quantitatively, interval combination optimization (ICO), competitive adaptive reweighted sampling (CARS), and competitive adaptive reweighted sampling combined with successive projections algorithm (CARS-SPA) were used to optimize the PLS model, and satisfactory results were obtained in terms of wavelength selection. In conclusion, it is feasible to use NIR spectroscopy to rapidly evaluate the effect of processing methods on the quality of RPA, which provides a meaningful reference for quality control of other herbal medicines with numerous processing methods.