Rapid Determination of Cr3+ and Mn2+ in Water Using Laser-Induced Breakdown Spectroscopy Combined with Filter Paper Modified with Gold Nanoclusters.

Excessive emissions of heavy metals not only cause environmental pollution but also pose a direct threat to human health. Therefore, rapid and accurate detection of heavy metals in the environment is of great significance. Herein, we propose a method based on laser-induced breakdown spectroscopy (LIBS) combined with filter paper modified with bovine serum albumin-protected gold nanoclusters (LIBS-FP-AuNCs) for the rapid and sensitive detection of Cr3+ and Mn2+. The filter paper modified with AuNCs was used to selectively enrich Cr3+ and Mn2+. Combined with the multi-element detection capability of LIBS, this method achieved the simultaneous rapid detection of Cr3+ and Mn2+. Both elements showed linear ranges for concentrations of 10-1000 µg L-1, with limits of detection of 7.5 and 9.0 µg L-1 for Cr3+ and Mn2+, respectively. This method was successfully applied to the determination of Cr3+ and Mn2+ in real water samples, with satisfactory recoveries ranging from 94.6% to 105.1%. This method has potential application in the analysis of heavy metal pollution.

Green Fruit Detection with a Small Dataset under a Similar Color Background Based on the Improved YOLOv5-AT.

Green fruit detection is of great significance for estimating orchard yield and the allocation of water and fertilizer. However, due to the similar colors of green fruit and the background of images, the complexity of backgrounds and the difficulty in collecting green fruit datasets, there is currently no accurate and convenient green fruit detection method available for small datasets. The YOLO object detection model, a representative of the single-stage detection framework, has the advantages of a flexible structure, fast inference speed and excellent versatility. In this study, we proposed a model based on the improved YOLOv5 model that combined data augmentation methods to detect green fruit in a small dataset with a background of similar color. In the improved YOLOv5 model (YOLOv5-AT), a Conv-AT block and SA and CA blocks were designed to construct feature information from different perspectives and improve the accuracy by conveying local key information to the deeper layer. The proposed method was applied to green oranges, green tomatoes and green persimmons, and the mAPs were higher than those of other YOLO object detection models, reaching 84.6%, 98.0% and 85.1%, respectively. Furthermore, taking green oranges as an example, a mAP of 82.2% was obtained on the basis of retaining 50% of the original dataset (163 images), which was only 2.4% lower than that obtained when using 100% of the dataset (326 images) for training. Thus, the YOLOv5-AT model combined with data augmentation methods can effectively achieve accurate detection in small green fruit datasets under a similar color background. These research results could provide supportive data for improving the efficiency of agricultural production.

Long-range infrared absorption spectroscopy and fast mass spectrometry for rapid online measurements of volatile organic compounds from black tea fermentation.

Fermentation is the key process to determine the quality of black tea. Traditional physical and chemical analyses are time consuming, it cannot meet the needs of online monitoring. The existing rapid testing techniques cannot determine the specific volatile organic compounds (VOCs) produced at different stages of fermentation, resulting in poor model transferability; therefore, the current degree of black tea fermentation mainly relies on the sensory judgment of tea makers. This study used proton transfer reaction mass spectrometry (PTR-MS) and fourier transform infrared spectroscopy (FTIR) combined with different injection methods to collect VOCs of the samples, the rule of change of specific VOCs was clarified, and the extreme learning machine (ELM) model was established after principal component analysis (PCA), the prediction accuracy reached 95% and 100%, respectively. Finally, different application scenarios of the two technologies in the actual production of black tea are discussed based on their respective advantages.

Simple and sensitive determination of Cr (III), Cu (II) and Pb (II) in tea infusions using AgNPs-modified resin combined with laser-induced breakdown spectroscopy.

The detection of heavy metals in tea infusions is important because of the potential health risks associated with their consumption. Existing highly sensitive detection methods pose challenges because they are complicated and time-consuming. In this study, we developed an innovative and simple method using Ag nanoparticles-modified resin (AgNPs-MR) for pre-enrichment prior to laser-induced breakdown spectroscopy for the simultaneous analysis of Cr (III), Cu (II), and Pb (II) in tea infusions. Signal enhancement using AgNPs-MR resulted in amplification with limits of detection of 0.22 µg L-1 for Cr (III), 0.33 µg L-1 for Cu (II), and 1.25 µg L-1 for Pb (II). Quantitative analyses of these ions in infusions of black tea from various brands yielded recoveries ranging from 83.3% to 114.5%. This method is effective as a direct and highly sensitive technique for precisely quantifying trace concentrations of heavy metals in tea infusions.

Unveiling the hidden impact: How biodegradable microplastics influence CO2 and CH4 emissions and Volatile Organic Compounds (VOCs) profiles in soil ecosystems.

Biodegradable plastics promise eco-friendliness, yet their transformation into microplastics (bio-MPs) raises environmental alarms. However, how those bio-MPs affect the greenhouse gases (GHGs) and volatile organic compounds (VOCs) in soil ecosystems remains largely unexplored. Here, we investigated the effects of diverse bio-MPs (PBAT, PBS, and PLA) on GHGs and VOCs emission in typical paddy or upland soils. We monitored the carbon dioxide (CO2) and methane (CH4) fluxes in-situ using the self-developed portable optical gas sensor and analyzed VOC profiles using a proton-transfer reaction mass spectrometer (PTR-MS). Our study has revealed that, despite their biodegradable nature, bio-MPs do not always promote soil GHG emissions as previously thought. Specifically, PBAT and PLA significantly increased CO2 and CH4 emissions up to 1.9-7.5 and 115.9-178.5 fold, respectively, compared to the control group. While PBS exhibited the opposite trend, causing a decrease of up to 39.9% for CO2 and up to 39.9% for CH4. In addition, different types of bio-MPs triggered distinct soil VOC emission patterns. According to the Mann-Whitney U-test and Partial Least Squares Discriminant Analysis (PLS-DA), a recognizable VOC pattern associated with different bio-MPs was revealed. This study claims the necessity of considering polymer-specific responses when assessing the environmental impact of Bio-MPs, and providing insights into their implications for climate change.

Rapid Determination of Different Ripening Stages of Occidental Pears (Pyrus communis L.) by Volatile Organic Compounds Using Proton-Transfer-Reaction Mass Spectrometry (PTR-MS).

Determination of Occidental pear (Pyrus communis) ripening is difficult because the appearance of Occidental pears does not change significantly during the ripening process. Occidental pears at different ripening stages release different volatile organic compounds (VOCs), which can be used to determine fruit ripeness non-destructively and rapidly. In this study, VOCs were detected using proton-transfer-reaction mass spectrometry (PTR-MS). Notably, data were acquired within 1 min. Occidental pears harvested at five separate times were divided into three ripening stages: unripe, ripe, and overripe. The results showed that the composition of VOCs differed depending on the ripening stage. In particular, the concentrations of esters and terpenes significantly increased during the overripe stage. Three ripening stages were clearly discriminated by heatmap clustering and principal component analysis (PCA). This study provided a rapid and non-destructive method to evaluate the ripening stages of Occidental pears. The result can help fruit farmers to decide the optimum harvest time and hence reduce their economic losses.

Gas Imaging with Uncooled Thermal Imager.

Gas imaging has become one of the research hotspots in the field of gas detection due to its significant advantages, such as high efficiency, large range, and dynamic visualization. It is widely used in industries such as natural gas transportation, chemical, and electric power industries. With the development of infrared detector technology, uncooled thermal imagers are undergoing a developmental stage of technological advancement and widespread application. This article introduces a gas imaging principle and radiation transfer model, focusing on passive imaging technology and active imaging technology. Combined with the actual analysis, the application scenarios using uncooled thermal imaging cameras for gas imaging measurement are analyzed. Finally, the limitations and challenges of the development of gas imaging technology are analyzed.

Detection of volatile organic compounds in adulterated tea using Fourier transform infrared spectroscopy and Proton-transfer-reaction mass spectrometry.

Aroma is a key factor used to evaluate tea quality. Illegal traders usually add essence to expired or substandard tea to improve its aroma so as to gain more profit. Traditional physical and chemical testing methods are time-consuming and costly. Furthermore, rapid detection techniques, such as near-infrared spectroscopy and machine vision, can only be used to detect adulterated powdered solid essences in tea. In this study, proton-transfer reaction mass spectrometry (PTR-MS) and Fourier-transform infrared spectroscopy (FTIR) were employed to detect volatile organic compounds (VOCs) in samples, and rapid detection of different tea adulterated liquid essence was achieved. The prediction accuracies of PTR-MS and FTIR reached over 0.941 and 0.957, respectively, and the minimum detection limits were lower than the actual used values in both. In this study, the different application scenarios of the two technologies are discussed based on their performance characteristics.

Non-destructive and in-situ detection of shrimp freshness using mid-infrared fiber-optic evanescent wave spectroscopy.

There is strong interest in non-destructive and rapid determination of food freshness in food research. In this study, mid-infrared (MIR) fiber-optic evanescent wave (FOEW) spectroscopy was applied to monitor shrimp freshness through the evaluation of protein, chitin, and calcite contents in conjunction with a Partial Least Squares Discriminant Analysis (PLS-DA) model. Shrimp shells were wiped with a micro fiber-optic probe to obtain a FOEW spectrum which quickly and nondestructively allowed evaluation of the shrimp freshness. Peaks for proteins, chitin, and calcite, which are closely related to shrimp freshness, were detected and quantified. Compared with the standard indicator for evaluating shrimp freshness (total volatile basic nitrogen), the PLS-DA model gave recognition rates for shrimp freshness using calibration and validation sets of the FOEW data of 87.27%, 90.28%, respectively. Our results show that FOEW spectroscopy is a feasible method for non-destructive and in-site detection of shrimp freshness.

Oil content analysis of corn seeds using a hand-held Raman spectrometer and spectral peak decomposition algorithm.

Rapid, non-destructive and reliable detection of the oil content of corn seeds is important for development of high-oil corn. However, determination of the oil content is difficult using traditional methods for seed composition analysis. In this study, a hand-held Raman spectrometer was used with a spectral peak decomposition algorithm to determine the oil contents of corn seeds. Mature and waxy Zhengdan 958 corn seeds and mature Jingke 968 corn seeds were analyzed. Raman spectra were obtained in four regions of interest in the embryo of the seed. After analysis of the spectra, a characteristic spectral peak for the oil content was identified. A Gaussian curve fitting spectral peak decomposition algorithm was used to decompose the characteristic spectral peak of oil at 1657 cm-1. This peak was used to determine the Raman spectral peak intensity for the oil content in the embryo and differences in the oil contents among seeds of varying maturity and different varieties. This method is feasible and effective for detection of corn seed oil.

Rapid identification of artificial fragrant rice based on volatile organic compounds: From PTR-MS to FTIR.

The volatile organic compounds (VOCs) released from foods can reflect their internal properties. Artificial fragrant rice (AFR) is a fraudulent food product in which the flavor of low-quality rice is artificially enhanced by addition of essence. In this study, proton-transfer reaction mass spectrometry, long optical path gas phase FTIR spectroscopy and fiber optic evanescent wave were used to analyze the characteristic mass-charge ratios signal and infrared fingerprint signal of four essence which may be used to make AFR, and the prepared AFR samples with different essence levels (0.001 %-0.3 %) were used to verify the detection performance of the detection methods. The results show that the three detection methods effectively identified AFR containing the minimum recommended dose of essence (≥0.1 %, w/w). The above detection methods can provide detection results in real time without complex sample pretreatment and provide options as rapid screening methods for food regulatory authorities to identify AFR.

Protein arginine methyltransferase 8 regulates ferroptosis and macrophage polarization in spinal cord injury via glial cell-derived neurotrophic factor.

OBJECTIVE: To explore the influence of protein arginine methyltransferase 8 (PRMT8) regulating glial cell-derived neurotrophic factor (GDNF) on neuron ferroptosis and macrophage polarization in spinal cord injury (SCI). METHODS: A rat model of SCI was established through an injury induced by an external force. Basso, Beattie, and Bresnahan score, hematoxylin and eosin staining, and immunofluorescence were used, respectively, to detect changes in rat locomotion, spinal cord histopathology, and NeuN expression in the spinal cord. Iron content in the spinal cord and levels of malondialdehyde and glutathione were measured using detection kits. Transmission electron microscopy was used to reveal the morphological characteristics of mitochondria. Western blotting was performed to detect PRMT8, GDNF, cystine/glutamate transporter XCT, glutathione peroxidase 4, 4-hydroxynonenal, heme oxygenase-1, inducible nitric oxide synthase (iNOS), CD16, and arginase 1 (Arg1). The expression levels of iNOS and Arg1 in the spinal cord were visualized by immunofluorescence. ELISA was performed to measure the expression levels of IL-6, IL-1ß, and TNF-α. Rat dorsal root ganglion (DRG) neurons and RMa-bm rat macrophages were treated with lipopolysaccharide under hypoxic conditions. The viability and iron content of the neurons were detected using Cell Counting Kit-8 and a specific probe, respectively. Flow cytometry and immunofluorescence were used to assess macrophage polarization. Chromatin immunoprecipitation was used to identify the binding of PRMT8 to the GDFN promoter. RESULTS: Neuronal ferroptosis and M1 macrophage polarization were promoted, and PRMT8 expression was downregulated in SCI. PRMT8 overexpression exerted therapeutic effects on injured DRG neurons and RMa-bm cells. Moreover, PRMT8 overexpression inhibited ferroptosis and M1 macrophage polarization in rats with SCI. PRMT8 promoted GDNF expression by catalyzing H3K4 methylation. Knockdown of GDNF counteracted the therapeutic effects of PRMT8 overexpression. CONCLUSION: Overexpression of PRMT8 may inhibit ferroptosis and M1 macrophage polarization by increasing GDNF expression, thereby alleviating SCI.

MicroRNA-181a-5p Curbs Osteogenic Differentiation and Bone Formation Partially Through Impairing Runx1-Dependent Inhibition of AIF-1 Transcription.

BACKGRUOUND: Evidence has revealed the involvement of microRNAs (miRNAs) in modulating osteogenic differentiation, implying the promise of miRNA-based therapies for treating osteoporosis. This study investigated whether miR-181a-5p influences osteogenic differentiation and bone formation and aimed to establish the mechanisms in depth. METHODS: Clinical serum samples were obtained from osteoporosis patients, and MC3T3-E1 cells were treated with osteogenic induction medium (OIM) to induce osteogenic differentiation. miR-181a-5p-, Runt-related transcription factor 1 (Runx1)-, and/or allograft inflammatory factor-1 (AIF-1)-associated oligonucleotides or vectors were transfected into MC3T3-E1 cells to explore their function in relation to the number of calcified nodules, alkaline phosphatase (ALP) staining and activity, expression levels of osteogenesis-related proteins, and apoptosis. Luciferase activity, RNA immunoprecipitation, and chromatin immunoprecipitation assays were employed to validate the binding relationship between miR-181a-5p and Runx1, and the transcriptional regulatory relationship between Runx1 and AIF-1. Ovariectomy (OVX)-induced mice were injected with a miR-181a-5p antagonist for in vivo verification. RESULTS: miR-181a-5p was highly expressed in the serum of osteoporosis patients. OIM treatment decreased miR-181a-5p and AIF-1 expression, but promoted Runx1 expression in MC3T-E1 cells. Meanwhile, upregulated miR-181a-5p suppressed OIM-induced increases in calcified nodules, ALP content, and osteogenesis-related protein expression. Mechanically, miR-181a-5p targeted Runx1, which acted as a transcription factor to negatively modulate AIF-1 expression. Downregulated Runx1 suppressed the miR-181a-5p inhibitor-mediated promotion of osteogenic differentiation, and downregulated AIF-1 reversed the miR-181a-5p mimic-induced inhibition of osteogenic differentiation. Tail vein injection of a miR-181a-5p antagonist induced bone formation in OVX-induced osteoporotic mice. CONCLUSION: In conclusion, miR-181a-5p affects osteogenic differentiation and bone formation partially via the modulation of the Runx1/AIF-1 axis.

Detection of heavy metal ions using laser-induced breakdown spectroscopy combined with filter paper modified with PtAg bimetallic nanoparticles.

The rapid and sensitive detection of heavy metal ions is important for environment and human health. Hence, the rapid and sensitive detection of multiple heavy metals simultaneously has become a critical issue. Here, we propose a method based on laser-induced breakdown spectroscopy (LIBS) combined with filter paper modified with PtAg bimetallic nanoparticles (BNPs) (LIBS-FP-PtAgBNPs) for the ultrasensitive detection of Hg2+, Cr3+, and Pb2+. The PtAgBNPs-modified filter paper was used to efficiently and specifically adsorb Hg, Cr, and Pb, and LIBS was used to detect the Hg, Cr, and Pb simultaneously. The limits of detection for Hg, Cr, and Pb were 0.5 µg/L (2.5 nM), 8 µg/L (0.15 µM), and 2 µg/L (9 nM), respectively. Furthermore, this method was successfully applied to determine the concentrations of Hg, Cr, and Pb in real spiked water samples. Compared with other methods based on nanoparticle sensing, LIBS-FP-PtAgBNPs is simpler to use and can achieve highly efficient enrichment, rapid separation, and sensitive detection of heavy metal ions. The optimal detections of Hg, Cr, and Pb were achieved in the pH range of 1-6. The developed method provides a new avenue to realize the rapid and sensitive detection of trace heavy metals in the environment.

A Real-Time Detection Method of Hg2+ in Drinking Water via Portable Biosensor: Using a Smartphone as a Low-Cost Micro-Spectrometer to Read the Colorimetric Signals.

This paper reported a real-time detection strategy for Hg2+ inspired by the visible spectrophotometer that used a smartphone as a low-cost micro-spectrometer. In combination with the smartphone's camera and optical accessories, the phone's built-in software can process the received light band image and then read out the spectral data in real time. The sensor was also used to detect gold nanoparticles with an LOD of 0.14 µM, which are widely used in colorimetric biosensors. Ultimately, a gold nanoparticles-glutathione (AuNPs-GSH) conjugate was used as a probe to detect Hg2+ in water with an LOD of 1.2 nM and was applied successfully to natural mineral water, pure water, tap water, and river water samples.

In situ detection of fruit spoilage based on volatile compounds using the mid-infrared fiber-optic evanescent wave spectroscopy.

Volatile compounds such as ethanol released from fruit can be rapidly detected using Fourier Transform Infrared spectroscopy based on a long-path gas cell. However, this method relies on a long optical path length and requires pumping fruit volatiles into the gas cell. This can lead to the volatile compounds being contaminated and not detectable in situ. Fiber optic evanescent wave spectroscopy (FOEW) is not influenced by the path length so can detect materials (solid, liquid and gas phase) rapidly in situ, using only a few millimeters of optical fiber. In the present study, a spiral silver halide FOEW sensor with a length of approximately 21 mm was used to replace a long-path gas cell to explore the feasibility of identifying volatile compounds released from grapes in situ. The absorption peaks of ethanol in the volatile compounds were clearly found in the FOEW spectra and their intensity gradually increased as the storage time of the grapes increased. PCA analysis of these spectra showed clear clustering at different storage times (1-3, 4-5 and 6-7 d), revealing that the concentration of the ethanol released from the grapes changed significantly with time. The qualitative model established by PLS-DA algorithm could accurately classify grape samples as "Fresh," "Slight spoilage," or "Severe spoilage". The accuracy of the calibration and validation sets both were 100.00%. These changes can therefore be used for rapidly identifying fruit deterioration. Compared with the method used in a previous study by the authors, this method avoids using a pumping process and can thus identify volatile compounds and hence monitor deterioration in situ and on-line by placing a very short optical fiber near the fruit.

Electric Field-Induced Specific Preconcentration to Enhance DNA-Based Electrochemical Sensing of Hg2+ via the Synergy of Enrichment and Self-Cleaning.

Efficient preconcentration is critical for sensitive and selective electrochemical detection of metal ions, but rapid specific enrichment with depressed absorption of interfering ions at the electrode is challenging. Here, we proposed an electric field-induced specific preconcentration to boost the analytical performance of DNA-based electrochemical sensors for Hg2+ detection. As for such preconcentration, a positive external electric field was first used to enrich Hg2+ at an electrode assembled with T-rich DNA, thus boosting T-Hg2+-T recognitions. The following applied inverse electric field strips the nonspecifically absorbed Hg2+ and other interfering ions, thus depressing matrix interferences via self-cleaning. Based on this principle, we designed a portable device to realize programmable control of electric fields; a T-Hg2+-T recognition-based electrochemical sensor was thus fabricated as a model platform to assess the feasibility of electric field-induced preconcentration. The experimental results revealed that such a strategy decreased the time of T-Hg2+-T-based recognition from 60 to 20 min and led to detection with better reproducibility by depressing the influence of free Hg2+ as well as interfering ions. This strategy offered Hg2+ detection limits of 0.01 pM─three-fold better than that without preconcentration─within 22 min. The proposed preconcentration strategy offers a new way to enhance the analytical performance of sensing at the solid-liquid interface.

Enzyme-modulated photothermal immunoassay of chloramphenicol residues in milk and egg using a self-calibrated thermal imager.

Highly sensitive and accurate detection of chloramphenicol is of paramount importance for food safety. Herein, an enzyme-modulated photothermal immunosensor that uses a self-calibrated thermal imaging system (SCTIS) as signal read-out was developed for detecting chloramphenicol. In this immunosensor, alkaline phosphatase was used as a modulator of the photothermal conversion. It could hydrolyze the substrate into ascorbic acid, thereby reducing oxidized 3,3',5,5'-tetramethylbenzidine, which exhibited a near-infrared laser-driven photothermal effect. For precise temperature measurement, the SCTIS was designed by using the temperature compensation of a ceramic chip to enable real-time self-calibration of the temperature. This SCTIS-based immunosensor could detect chloramphenicol with a LOD of 9 pg/mL in 2 h, and relative standard derivations from 3.95% to 13.58%. The average recoveries in milk and egg samples ranged from 76% to 114%. This versatile sensing strategy can detect various targets by altering recognition elements, thus has wide applicability in food safety testing and monitoring.

A biosensor based on a thermal camera using infrared radiance as the signal probe.

Flexible-type signal probes and their detection methods are increasingly being applied in biosensors. Among these, temperature-based signal probes represent a novel research direction. These sensors convert immunoassay signals into temperature signals, which are then detected using a thermometer or thermal infrared reader. However, from a physical viewpoint, we know that the temperature measured directly using a thermal infrared camera is the infrared radiance temperature, which is proportional to both the true temperature and emissivity. Herein, we design a novel sensing method that uses infrared radiance rather than true temperature as the signal probe. We convert the immunoassay to an infrared radiation temperature measurement by controlling an aluminum plate in constant temperature whose infrared radiation temperature varied significantly with immunoassay-based the amount of the target. We then develop two readout systems: one is based on a scientific-grade infrared camera, and the other uses a smartphone-based thermal camera, which is more portable, flexible, and can be used as an in-pocket sensor. The sensors are verified via detecting exemplary biomarker human IgG, and show excellent quantitative model performances in 0-100 ng mL-1 concentration range with the detection limit estimated as low as 0.54 ng mL-1. The excellent quantitative results demonstrate the powerful detection performance of this sensing method.

Facilitative role of circPVT1 in osteogenic differentiation potentials of bone marrow mesenchymal stem cells from patients with osteoporosis through the miR-30d-5p/ITGB3 axis.

OBJECTIVE: The critical role of circular RNAs (circRNAs) in osteoporosis (OP) has been highlighted. We tried to explore the role of circPVT1 in OP in relation to microRNA-30d-5p (miR-30d-5p) and ITGB3. METHODS: After bone marrow collection, bone marrow mesenchymal stem cells (BMSCs) were isolated and identified. Then, Pearson coefficient was used to analyze the correlation among circPVT1, miR-30d-5p and ITGB3, and the binding sites were predicted and verified. Gain- and loss-of function assays in circPVT1, miR-30d-5p and ITGB3 were performed to analyze their effect on osteogenic differentiation of BMSCs. RESULTS: The osteogenic differentiation of BMSCs from OP patients was significantly decreased, and reduced circPVT1 expression was found in the BMSCs from OP patients. Overexpression of circPVT1 stimulated the formation of calcified nodules, increased alkaline phosphatase activity, and enhanced the expression of osteogenic marker genes in the BMSCs from OP patients. Additionally, circPVT1 expression was negatively correlated with miR-30d-5p, and miR-30d-5p was negatively correlated with ITGB3 in OP patients. Mechanically, circPVT1 regulated the osteogenic differentiation potential of BMSCs by relieving the inhibition of miR-30d-5p on ITGB3 through the competitive endogenous RNA mechanism. CONCLUSION: Our study highlighted a circPVT1/miR-30d-5p/ITGB3 axis in regulating osteogenic differentiation potential of BMSCs from OP patients.