Sample Preparation Process Research Articles

Simultaneous and sensitive detection of SARS-CoV-2 proteins spike and nucleocapsid based on long-range SERS biosensor

BackgroundEarly diagnosis of SARS-CoV-2 infection is still critical to control COVID-19 outbreak. Traditional polymerase chain reaction, enzyme-linked immunosorbent assay or lateral flow immunoassay performed poorly on detection times, sample preparation process and accuracy. Surface-enhanced Raman scattering (SERS)-based detection has emerged as a powerful analytical technique, which overcomes the above limitations. However, due to the near-field effect of traditional substrate, it is difficult to monitor the binding event of aptamers with proteins. It is obvious that a novel SERS substrate thatsupportedextended and stronger electromagnetic fields was required to hold long-range effects and allow for binding event testing. ResultsDriven by this challenge, we reported a long-range SERS-active substrate, which was built by inserting bowtie nanoaperture arrays in a refractive-index-symmetric environment and Au mirror surfaces, for SARS-CoV-2 protein binding event detection. Then, a double-π structure aptasensor was simply designed through the hybridization of spike (S) and nucleocapsid (N) proteins aptamers, and a corresponding complementary strand. This kind of double-π structure would dissociate when targets proteins S and N existed and led to the SERS responses decreased, which established the detection basis of our system. What's more, due to two Raman labels were involved, both proteins S and N can be sensed simultaneously. Our proposed method showed improved sensitivity with a low limit of detection for multiplex detection (1.6 × 10−16 g/mL for protein S and 1.0 × 10−16 g/mL for protein N) over a wide concentration range. SignificanceThis represents the first long-range SERS apatasensor platform for detection of S and N proteins simultaneously. Our method showed high sensitivity, selectivity, reproducibility, stability and remarkable recoveries in human in saliva and serum samples, which is particularly important for the early diagnostics of COVID as well as for future unknown coronavirus.

Conveniently monitoring aldehyde changes in heated edible oils using miniaturized kapok fiber-supported liquid-phase extraction/in-situ derivatization coupled with liquid chromatography-tandem mass spectrometry

Heating edible oils generates aldehydes, potentially leading to adverse health effects, making their analysis essential for quality control. This study presents a convenient miniaturized kapok fiber-supported liquid-phase extraction/in-situ derivatization method for the simultaneous extraction and derivatization of aldehydes in oils. The method involves placing 150 mg oil into a 1 mL pipette tip packed with 25 mg kapok fiber, adding 150 μL ACN with 1.5 mg mL−1 DNPH, and post 30-minute static extraction, retrieving the extractant with a pipettor for liquid chromatography-tandem mass spectrometry analysis. By optimizing critical parameters through a Box-Behnken design, the method exhibits good linearity (1–500 ng g−1, R2 ≥ 0.991), low detection limits (0.2–1.0 ng g−1), excellent accuracy (95.3–107.1%) and high precisions (relative standard deviation < 7.9%). This method simplifies sample preparation processes, cuts solvent use, and facilitates automation. It effectively identifies ten aldehyde variations in six heated oils, displaying distinct profiles consistent with prior research.

Health risk assessment of heavy metals and predication of water quality indices with using Arc-GIS software: a case study of South Kerman Province

ABSTRACT In many developing countries, including Iran, reservoirs have become essential for providing potable water. This study focused on 20 sample reservoirs in the southern Kerman province, specifically assessing heavy metal contamination. The primary objectives of this research were to determine the concentrations of hazardous heavy metals, such as As, Cr, Pb, and Ni, in the water, and to conduct a Health Risk assessment. The sample preparation process followed the guidelines outlined in the 21st edition of Standard Methods, with reference number A3120. Alarmingly, the average levels of most heavy metals in these reservoirs exceeded the drinking water standards set by both the World Health Organization (WHO) and the U.S. Environmental Protection Agency (EPA). To evaluate water quality, the Water Quality Index (WQI) was employed. Based on this assessment, the water resources in Faryab and Qalaganj were deemed excellent for drinking, while those in Jiroft were classified as good. Furthermore, the findings from the Hazardous Materials Potential Index (HMPI), Heavy Metal Evaluation Index (HMEI), and Extended Water Quality Index (EWQI) were consistent with the trends observed in the WQI. Among these locations, Jiroft had the highest average WQI, scoring 62.5, followed by Faryab and Qalaganj with WQIs of 32.5 and 31.5, respectively. The Total Hazard Quotient (HI) for the metals in the urban drinking water samples from Qalaganj, Jiroft, and Faryab exceeded 1, with values of 5.06, 4.9, and 4.4, respectively. This indicates potential harm to both adults and children. The highest Cancer Risk (CR) values, specifically 3.3 × 10−2, were observed in Jiroft for children exposed to the water dermally, while the lowest levels were found in Faryab among adults exposed to Pb through their skin. In all examined locations, the cumulative cancer risk suggests a medium to extremely high risk. These findings underscore the importance of implementing corrective measures to enhance the quality of drinking water resources.

Optimization of extraction-free protocols for SARS-CoV-2 detection using a commercial rRT-PCR assay

In the ongoing global fight against coronavirus disease 2019 (COVID-19), the sample preparation process for real-time reverse transcription polymerase chain reaction (rRT-PCR) faces challenges due to time-consuming steps, labor-intensive procedures, contamination risks, resource demands, and environmental implications. However, optimized strategies for sample preparation have been poorly investigated, and the combination of RNase inhibitors and Proteinase K has been rarely considered. Hence, we investigated combinations of several extraction-free protocols incorporating heat treatment, sample dilution, and Proteinase K and RNase inhibitors, and validated the effectiveness using 120 SARS-CoV-2 positive and 62 negative clinical samples. Combining sample dilution and heat treatment with Proteinase K and RNase inhibitors addition exhibited the highest sensitivity (84.26%) with a mean increase in cycle threshold (Ct) value of + 3.8. Meanwhile, combined sample dilution and heat treatment exhibited a sensitivity of 79.63%, accounting for a 38% increase compared to heat treatment alone. Our findings highlight that the incorporation of Proteinase K and RNase inhibitors with sample dilution and heat treatment contributed only marginally to the improvement without yielding statistically significant differences. Sample dilution significantly impacts SARS-CoV-2 detection, and sample conditions play a crucial role in the efficiency of extraction-free methods. Our findings may provide insights for streamlining diagnostic testing, enhancing its accessibility, cost-effectiveness, and sustainability.

IRINOTECAN-REVIEW OF ANALYTICAL METHODS DEVELOPED FOR PHARMACEUTICAL DOSAGE FORMS AND BIOLOGICAL FLUIDS

Irinotecan (IRI) is utilised as a first line anticancer medication in the cure of cancer having extraordinary ability to block DNA-topoisomerase-I. It is used as a monotherapy and adjunct therapy in the treatment of metastatic colorectal cancer and other cancers, and it differs chemically and pharmacologically from other anticancer medications. The proposed review is divided into two main sections i.e. a) Different analytical methods for estimating irinotecan in pharmaceutical formulations, b) Diverse analytical methods for detecting irinotecan in biological matrices. This work also considers the development of numerous analytical methods based on various parameters, as well as the validation of the methods used. Estimated validation characteristics such as Linearity, Limit of Detection (LOD), and Limit of Quantitation (LOQ) are considered for each. Applying bioanalytical methods, the wavelength of detection, mobile phase, columns, flow rate, retention duration, and sample preparation processes are all evaluated as essential quality variables for estimating Irinotecan.

Arsenic speciation by using emerging sample preparation techniques: a review.

Arsenic is a hazardous element that causes environmental pollution. Due to its toxicological effects, it is crucial to quantify and minimize the hazardous impact on the ecology. Despite the significant advances in analytical techniques, sample preparation is still crucial for determining target analytes in complex matrices. Several factors affect the direct analysis, such as trace-level analysis, advanced regulatory requirements, complexity of sample matrices, and incompatible with analytical instrumentation. Along with the development in the sample preparation process, microextraction methods play an essential role in the sample preparation process. Microextraction techniques (METs) are the newest green approach that replaces traditional sample preparation and preconcentration methods. METs have minimized the limitation of conventional sample preparation methods while keeping all their benefits. METs improve extraction efficacy, are fast, automated, use less amount of solvents, and are suitable for the environment. Microextraction techniques with less solvent consumption, such as solid phase microextraction (SPME) solvent-free methods, and liquid phase microextraction (LPME), are widely used in modern analytical procedures. SPME development focuses on synthesizing new sorbents and applying online sample preparation, whereas LPME research investigates the utilization of new solvents.

Fast Forward: Optimized Sample Preparation and Fluorescent Staining for Microplastic Detection

The fast, affordable, and standardized detection of microplastics (MP) remains one of the biggest challenges in MP research. Comparable data are essential for appropriate risk assessments and the implementation of laws and limit values. The fluorescent staining of MP in environmental samples is a possible solution to this problem. This study investigates the optimization of a sample preparation process (hydrogen peroxide digestion) and the staining process (temperature, concentration, time, surfactants as staining aids) for using a specifically developed fluorescent dye for MP detection. The optimization is performed by comparing the sample preparation process and staining of MP from different polymers and natural particles. Further, the suitability of the optimized process for the detection of fluoropolymers and tire abrasion was tested. The results show that the optimized method (increased temperature and optimized stain concentration) can detect microplastics reliably with a total sample preparation and measurement time of 2.5–3 h per sample, reaching recovery rates of 93.3% (polypropylene) to 101.7% (polyester). Moreover, two of the three tested fluoropolymers could be detected reliably. Tire abrasion could not be detected with the here presented method, as the black color leads to strong quenching. A long-term study measuring the MP pollution in the effluent of a municipal wastewater treatment plant compared the optimized and original processes and confirmed the stability of the improved method for routine measurements and contamination control.

Validated HPLC method for simultaneous quantitative determination of dimethylcurcumin and resveratrol in pluronic-F127 nanomicelles: Formulation with enhanced anticancer efficacy

Nano-micelles offer a promising vehicle for the delivery various therapeutically significant biologicals. Development of convenient and efficient chromatographic methods for the quantitative determination of the active pharmaceutical ingredients in such systems is of immense importance. In this study pluronic-F-127 nano-micelles were prepared and loaded with dimethylcurcumin (DMC) and resveratrol (Res). A simple, convenient and effective HPLC method was developed for the quantitative estimation of DMC and Res in the polymeric nano-micelles through a single injection. A reverse-phase ACE® C18 column (250 mm × 4.6 mm) was used with a gradient mobile phase system consisting of 1 % MeOH and 0.1 % H3PO4:100 % acetonitrile at 1 mL/min flow rate with UV detection for Res, and fluorescence detector for DMC. The calibration curves generated for both the compounds were found linear with r2 values of 1.000 over a concentration range of 2–25 µg/mL with low limit of detection (LOD) values of 0.37 and 0.16 µg/mL for DMC and Res respectively and limit of quantification (LOQ) values of 1.23 and 0.55 µg/mL for DMC and Res respectively. Similarly, accuracy was found in a range of 98.80 -102.47 % for DMC and 100.58–101.77 % for Res. Furthermore, the within-run precisions (%RSD) were 0.073 - 0.444% for DMC and 0.159 - 0.917% for Res, while between-run precisions (%RSD) were 0.344 - 1.47 for DMC and 0.458 - 1.651 for Res. Moreover, the DMC with Res co-loaded nanomicelles showed higher activity against MCF-7 and MDA-MB 231 compared to DMC and Res alone. Overall, this study presented a simple, convenient, precise and accurate method for the quantitative determination of DMC and Res in polymeric nano-micelles which have anticancer potential.•A simple HPLC for the quantitative determination of DMC and Res in nanomicelles having anti-cancer potential.•Non complicate with high degree of recoveries of sample preparation process.•This method can be used to determine a mixture of DMC and Res in pharmaceutical formulation in single injection.

A preparation technology of volatile components in Linggui Zhugan decoction based on the transfer of cinnamaldehyde and its anti-gastric ulcer effect

PurposeThis study aims to preserve the volatile components of Linggui Zhugan (LGZG) decoction, offering an experimental foundation for subsequent preparations efforts. MethodsTwo modern sample preparation processes were compared with the traditional method approach using HPLC fingerprints. After identifying the main volatile components in LGZG aqueous decoction, the inclusion method of inclusion compounds (IC-LGZG) was established and optimized at laboratory, pilot and production scales. Characterization, stability testing of IC-LGZG, and experiments on gastric ulcer rats were conducted to validate the transferability of chemical composition and pharmaceutical efficacy. ResultsThe study focused on preserving the volatile components in LGZG modern preparations. HPLC analysis revealed cinnamaldehyde (CA) as the main volatile component in LGZG decoction. The optimized IC-LGZG preparation involved heating aromatic water to 40 °C, adding 20 g/L of β-Cyclodextrin (β-CD), keeping warm and stirring at 300 r for 30 min. This process exhibited good repeatability across different verification tests at varying scales. IC-LGZG obtained effectively transferred CA molecules into the β-CD molecules via encapsulation, remaining stable when stored in sealed and dark conditions. Finally, CA, IC-LGZG and M−LGZG (a mixture of IC-LGZG and water-soluble extract powder) effectively prevented the formation of gastric ulcer by mitigating reductions in IL-10, SOD and the increase of TNF-α, NO, MDA in serum. ConclusionThe IC-LGZG prepared using this process successfully transfers volatile components, both chemically and pharmacologically, making it suitable for modern preparations of LGZG.

Erratum: Optimizing Sample Preparation Process for Transmission Electron Microscopy of Neuromuscular Junctions in Drosophila Larvae.

An erratum was issued for:Optimizing Sample Preparation Process for Transmission Electron Microscopy of Neuromuscular Junctions in Drosophila Larvae. The Authors section was updated from: Gan Guangming1,2 Sheng Qingyuan3 Ou Yutong1 Chen Mei1 Zhang Chenchen1 1The School of Medicine, Southeast University, 2The Key Laboratory of Developmental Genes and Human Disease, Southeast University, 3The School of Life Science and Technology, Southeast University Corresponding Authors:Gan Guangming to: Gan Guangming1,2 Sheng Qingyuan3 Ou Yutong1 Chen Mei3 Zhang Chenchen1 1The School of Medicine, Southeast University, 2The Key Laboratory of Developmental Genes and Human Disease, Southeast University, 3The School of Life Science and Technology, Southeast University Corresponding Authors:Gan Guangming,Sheng Qingyuan.

Identification of Location and Geometry of Invisible Internal Defects in Structures using Deep Learning and Surface Deformation Field

On‐site inspection of invisible subsurface defects in multiscale structural materials by conventional nondestructive testing (NDT) methods, such as X‐ray and ultrasound, requires complex sample preparation and data acquisition processes. Moreover, the inspected area is very small. Herein, a simple, inexpensive, and ultrasensitive NDT method for identifying and classifying the geometries of subsurface defects using commercial cameras, digital image correlation software, and object detection (OD) algorithms is developed. Three OD algorithms—Faster region‐based convolutional neural network (Faster R‐CNN), Mask R‐CNN, and you‐only‐look‐once (YOLO)v3—are evaluated for their ability to locate defects and identify defect geometries. Specifically, bounding boxes of two sizes (large and small) are applied to the regions of defect‐induced perturbations in strain tensors, which serve as virtual representatives of invisible subsurface defects. The performance of the proposed approach is validated on test datasets of known and unknown defect types. The experimental results confirm that the proposed approach can effectively utilize the surface deformation field information to accurately and reliably locate and identify subsurface defects. The method is nondestructive and low cost, enables real‐time detection, is robust against noise‐dominated deformation fields, and can be applied to various structural deformations. The method is therefore suitable for multiscale structural health monitoring and characterization of internal defects in materials.

Modifikasi Hammer Mill Sample Divider Untuk Penyederhanaan Fungsi Dengan Desain Ulang Pada PT. BV

This study was conducted at PT. BV whose activities are in the coal mining sector, where there is a sample preparation process which aims to minimize the presence of impurities that will interfere with the coal analysis process. In the process there are two important tools used, namely the Hammer Mill and the Rotary Sample Divider. If we look at the use of these two separate tools, they are not efficient in terms of time, space and human resources, as a result the sample results are not optimal. So it is necessary to redesign the Hammer Mill machine and the Rotary Sample Divider machine by combining the two machines in one design, so that their function is simpler and more efficient, and also produces homogeneity in the coal samples to be analyzed. It is hoped that by combining the 2 tools used into one, we can overcome the lack of efficiency in sample preparation and get maximum results. The analysis used to identify problems uses a fishbone diagram to support identification, exploration, and depicts in detail all the causes related to this problem. The result of the redesign is a modified Hammer Mill Sample Divider that is more efficient and produces homogeneous coal samples to be analyzed. Apart from that, testing data on the sample preparation process using a modified Hammer Mill Sample Divider machine showed that the total testing time for 10 samples was obtained with an average time of 12.55 minutes, a maximum time limit of 14.02 minutes and a minimum time of 10.8 minutes and with the re-design of the Hammer Mill Sample Divider can minimize costs, use of human resources and time.. Keywords: Coal, Efficient, Hammer mill, Re-desain, Rotary sample divider, Sample preparation

Recent Progress of Metal-Organic Framework-Assisted Sensing System for Point-of-Care Antibiotics Detection in Food Industry; a Mini Review

Antibiotics (ANBs) are essential for animal health and are used for treatment, prevention, and growth promotion. However, ANB use in animals can lead to antibiotic residue in food products, which can cause various side effects. These include the transfer of ANB-resistant bacteria to humans, immunopathological effects, allergies, and even carcinogenicity. The most significant adverse effect is the transfer of ANB-resistant bacteria to humans due to the mobile properties of resistance. Therefore, timely detection is the best approach to prevent the spread of downsides of these compounds. Various methods exist for measuring ANB concentrations, such as LC-MS, high-performance liquid chromatography, capillary electrophoresis, thin-layer chromatography, and enzyme-linked immunoassay. However, complicated sample preparation processes and expensive equipment are often considered obstacles to their prevalent usage. Emerging technologies like Metal-Organic Frameworks (MOFs) offer a simpler, quicker, and more cost-effective solution for detecting veterinary drugs in animal-derived food samples. This investigation first reviews some conventional methods for ANB recognition, including microbiological, immunological, and laboratory-based procedures. Then, Sensor-based analytical methods and their advantages and disadvantages were discussed. Finally, the recent progress in ANB detection approaches using MOF-based sensors in food products was investigated. MOFs have become a topic of great interest due to their remarkable properties. These include high surface areas that can be easily modified, defined porosity, lightweight, adjustable pore sizes, ordered structures, and impressive mechanical strength. The performance of MOFs is superior to traditional chemosensory materials due to their ability to adjust properties. Various sensing systems based on MOFs have been reported, including photoelectrochemical, electrochemiluminescence, electrochemical, and quartz crystal microbalance. As discussed in this review, sensors based on MOFs have emerged as reliable alternatives for fast and routine detection in clinical and environmental analysis and food safety control. Various MOF-based materials have been used for detecting antibiotics, and their advantages and limitations have been critically evaluated for future applications in diagnosing antibiotics in food products.

Direct extraction with acetonitrile of hemp seed oil for the analysis of pesticides by using comprehensive two-dimensional gas chromatography-triple quadrupole mass spectrometry

The method herein described involves a rapid and limited-volume (0.5 mL of acetonitrile) solvent-extraction sample preparation process, for pesticide determination in hemp seed oil. The extraction method was characterized by the absence of both clean-up or pre-concentration steps. The extracts were directly analyzed through cryogenic-modulation comprehensive two-dimensional gas chromatography coupled to triple quadrupole mass spectrometry. The novelty characterizing the present research [compared to a previous one (Arena et al., 2023)] is related to the extension of the number of pesticides (97), and to the investigation of a more challenging matrix, contained in a vegetable oil of increasing interest among consumers.Linearity, limits of detection and quantification, accuracy, precision, recovery, and matrix effect were measured. Particular emphasis was devoted to the matrix effect, with the co-extracted matrix amount defined. Three international regulations (Canada, California, Europe) were considered, and the obtained limits of quantification were found to be too high in five (Canada) and twelve (Europe) cases, for a total number of 15 pesticides.The analysis of ten commercial samples showed the presence of seven pesticide residues in four of them, at concentration levels ranging from 0.02 to 0.98 mg kg−1, with most over the regulation residue limits.

Rapid Sample Enrichment, Novel Derivatization, and High Sensitivity for Determination of 3-Chloropropane-1,2-diol in Soy Sauce via High-Performance Liquid Chromatography-Tandem Mass Spectrometry.

A novel, simplified derivatization method and a rapid sample preparation process using carbon yarn as a sorbent for the determination of 3-chloropropane-1,2-diol (3-MCPD) in soy sauce via high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was developed. 3-MCPD was first enriched and purified with carbon yarn and then eluted with a methanol-water solution. Subsequently, the analyte underwent derivatization with p-(dimethylamino)-phenol for sensitive detection via HPLC-MS/MS. The limit of detection and the limit of quantitation for 3-MCPD were validated to be 0.5 and 1.0 μg/kg, respectively. Spiking experiments showed recoveries between 83 and 94%, with a relative standard deviation of ≤10%. The method was further validated with a certified reference material. Furthermore, 11 real soy sauce samples from local markets were tested by using this method. These results reveal the widespread 3-MCPD contamination. Consequently, this study offers a preferable alternative for the sensitive, accurate, and precise determination of 3-MCPD in soy sauce.

A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM.

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules (≤50 kDa) remain challenging targets due to their intrinsic low signal to noise ratio. Methods to help resolve small proteins have been applied but development of similar approaches to aid in structural determination of small, structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5-5.0 Å. While lacking the detail of true high-resolution maps, these maps are suitable for model building and preliminary structure determination. We demonstrate this method helped faithfully recover the structure of several RNA elements of known structure, and that it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a robust system to aid in RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

Cannabigerol (CBG) signal enhancement in its analysis by gas chromatography coupled with tandem mass spectrometry

PurposeAccording to recent reports, cannabigerol (CBG) concentration level in blood and body fluids may have forensic utility as a highly specific albeit insensitive biomarker of recent cannabis smoking. While the analytical sensitivity of cannabidiol (CBD), Δ9-tetrahydrocannabinol (Δ9-THC), cannabichromene (CBC) or cannabinol (CBN) estimation by gas chromatography-mass spectrometry (GC–MS) is similar and sufficiently high, it is exceptionally low in the case of CBG (ca. 25 times lower than for the other mentioned cannabinoids). The purpose of this study is to explain the reasons for the extremely low analytical sensitivity of GC–MS in estimating CBG and to present possible ways of its improvement.MethodsNuclear magnetic resonance (NMR) data and GC–MS responses to CBG and its various derivatization and transformation products were studied.ResultsThe validation data of individual derivatives of CBG and its transformation products were established. CBG silylation/acylation or hydration allows to decrease LOD about 3 times, whereas the formation of pyranic CBG derivative leads to 10-times decrease of LOD. The paper enriches the literature of the subject by providing MS and NMR spectra, not published so far, for derivatives of CBG and its transformation products. The most likely cause of low GC–MS response to CBG is also presented.ConclusionsThe presented results shows that although the signal increase of CBG can be obtained through its derivatization by silylation and/or acylation, the greatest increase is observed in the case of its cyclization to the pyranic CBG form during the sample preparation process. The CBG cyclization procedure is very simple and workable in estimating this cannabinoid in blood/plasma samples.Graphical abstract

B-178 Clinical Routine Ultrasensitive LC-MS/MS Method Development for Analysis of 17β-Estradiol in Human Serum

Abstract Background The increasing clinical demand for the measurement of circulating 17β-Estradiol at very low concentrations consolidates the need of highly sensitive and specific analytical methodologies. These assays are suitable in situations such as antiestrogen therapy monitoring (use of aromatase inhibitor in breast cancer treatment); diagnosis of suspect inherited sex-steroid metabolic disorders; diagnosis of precocious and delayed puberty in female; hormone replacement therapy in postmenopausal women; and estrogen deficiency in men. Time-consuming methods and lack of sensitivity are common in the quantification of 17β-Estradiol in serum by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The strategy of chemical derivatization is common for analysis of estrogens because it enhances specificity and sensitivity, but this approach becomes laborious in the sample preparation process. For the purpose of solving these analytical challenges, the aim of this work was developing a reliable, sensitive and low-cost LC-MS/MS method without derivatization for clinical routine analysis. Methods Isotope-labeled internal standard 17β-Estradiol-D5 were added to calibrators, quality controls (QC) and serum samples before a liquid-liquid extraction with the organic solvent Diethyl Ether. After reconstitution, the extracts were injected into a Biphenyl column 50 × 2.1 mm, 2,6 µm, chromatographic separated by solvent gradient (Ammonium Fluoride in Water – Acetonitrile) and detected in positive electrospray ionization mode. The analytical method was validated using reference material grade standards and spiked QCs in charcoal stripped pool patient serum at 4 levels by the assessment of linearity, limit of quantification (LoQ), precision inter and intra-assay, accuracy, carryover, method comparison, cross-reactivity and stability (freeze-thawing cycles, bench top, postoperative and stock solution). Results The method has been validated with the analytical measurement range of 2–500 pg/mL. It was successfully optimized to achieve low levels of 17β-Estradiol as proposed with limit of quantitation of 2 pg/mL. Within-run and between-run precision (coefficient of variation) study yielded 1.3%–7.2% and accuracy within 95.7%–112.1%. No carryover, matrix effect and significant cross-reactivity was observed. Estradiol was found to be stable in serum samples under 3 freeze/thawing cycles, 4 h at ambient temperature and 72 h after extraction procedure in auto-injector. The stability of stock solutions was tested in −20 °C freezer and remained stable for 1 month. Method comparison between two reference laboratories (LC-MS/MS method) was performed and the results showed acceptable data for regression statistics (slope (a) = 0.9184; intercept (b) = −0.1576), t-test statistics (bias = 8.5%) and difference plot. Conclusion An ultrasensitive and derivatization-free LC-MS/MS method was developed and it may be beneficial for patients with endocrine disorders associated with estradiol levels.

Observation and research on surface crack structure of coal based on electronic scanning technology

Based on the background of the 2 # coal seam mainly mined by Caojiatan Coal Mine in Yulin Mining Area in northern Shaanxi, this paper adopts the Scanning electron microscope test method to obtain the fracture size and structural characteristics of coal samples through the process of sample preparation drying testing analysis. After testing, the cracks in the main coal seam samples of Yulin mining area in northern Shaanxi show irregular distribution, with small branch cracks mainly derived from larger main cracks. The closed form crack structure is a wedge-shaped structure, while the open form crack width is in an disordered state. Some cracks have no fixed width or size, and the main crack width range is 90μm~617μm, the width range of branch fine cracks is 0-21 μm; It can provide basic support for the application of water injection dust reduction engineering in the later stage.

Feasibility of using Vis-NIR spectroscopy and PXRF spectrometry to estimate regional soil cadmium concentration

Conventionally, soil cadmium (Cd) measurements in the laboratory are expensive and time-consuming, involving complex processes of sample preparation and chemical analysis. This study aimed to identify the feasibility of using sensor data of visible near-infrared reflectance (Vis-NIR) spectroscopy and portable X-ray fluorescence spectrometry (PXRF) to estimate regional soil Cd concentration in a time- and cost-saving manner. The sensor data of Vis-NIR and PXRF, and Cd concentrations of 128 surface soils from Yunnan Province, China, were measured. Outer-product analysis (OPA) was used for synthesizing the sensor data and Granger-Ramanathan averaging (GRA) was applied to fuse the model results. Artificial neural network (ANN) models were built using Vis-NIR data, PXRF data, and OPA data, respectively. Results showed that: (1) ANN model based on PXRF data performed better than that based on Vis-NIR data for soil Cd estimation; (2) Fusion methods of both OPA and GRA had higher predictive power (R2) = 0.89, ratios of performance to interquartile range (RPIQ) = 4.14, and lower root mean squared error (RMSE) = 0.06, in ANN model based on OPA fusion; R2 = 0.88, RMSE = 0.06, and RPIQ = 3.53 in GRA model) than those based on either Vis-NIR data or PXRF data. In conclusion, there exists a great potential for the combination of OPA fusion and ANN to estimate soil Cd concentration rapidly and accurately.