o-phenylenediamine Derived Fluorescent Carbon Quantum dots for Detection of Hg(II) in Environmental Water.

With the expansion of human activities, the consequent influx of mercury (Hg) into the food chain and the environment is seriously threatening human life. Herein, nitrogen and sulfur co-doped fluorescent carbon quantum dots (yCQDs) were prepared via a hydrothermal method using o-phenylenediamine (OPD) and taurine as precursors. The morphological characteristics as well as spectral features of yCQDs indicated that the photoluminescence mechanism should be the molecular state fluorophores of 2, 3-diaminophenothiazine (oxOPD), which is the oxide of OPD. The as-synthesized yCQDs exhibited sensitive recognition of Hg2+. According to the investigation in combination of UV-Vis absorption spectra, time-resolved fluorescence spectra and quantum chemical calculations, the abundant functional groups on the surface of yCQDs allowed Hg2+ to bind with yCQDs through various interactions, and the formed complexes significantly inhibited the absorption of excitation light, resulting in the static fluorescence quenching of yCQDs. The proposed yCQDs was utilized for Hg2+ sensing with the limit of detection calculated to be 4.50 × 10- 8 M. Furthermore, the recognition ability of yCQDs for Hg2+ was estimated in tap water, lake water and bottled water, and the results indicated that yCQDs have potential applications in monitoring Hg2+.

Non-enzymatic Detection of Uric Acid in Serum and Urine by Fluorescent and Visual Dual-Mode Sensor Based on 3-aminophenylboric Acid Functionalized Carbon Dots.

Herein, we developed a sophisticated dual-mode sensor that utilized 3-aminophenylboric acid functionalized carbon dots (APBA-CDs) to accurately detect uric acid (UA). Our innovative process involved synthesizing APBA-CDs that emitted at 369 nm using a one-step hydrothermal method with 3-aminophenylboric acid and L-glutamine as precursors, ethanol and deionized water as solvents. Once UA was introduced to the APBA-CDs, the fluorescence of the system became visibly quenched. The results of Zeta potential, Fourier transformed infrared (FTIR) spectra, fluorescence lifetime, and other characteristics were analyzed to determine that the reaction mechanism was static quenching. This meant that after UA was mixed with APBA-CDs, it combined with the boric acid function on the surface to form complexes, resulting in a decrease in fluorescence intensity and a blue shift in the absorption peak at about 295 nm in the Ultraviolet-visible (UV-vis) absorption spectra. We were pleased to report that we have successfully used the dual-reading platform to accurately detect UA in serum and human urine. It provided a superior quantitative and visual analysis of UA without the involvement of enzymes. We firmly believe that our innovative dual-mode sensor has immense potential in the fields of biosensing and health monitoring.

Nitrogen and Sulfur co-doped Carbon dots as an "on-off-on" Fluorescent Sensor for the Detection of Hg2+ and Ampicillin.

Herein, a fluorescent "on-off-on" nanosensor based on N,S-CDs was developed for highly precise and sensitive recognition of Hg2+ and ampicillin (AMP). Nitrogen and sulfur co-doped carbon dots with blue fluorescence were synthesized by one-pot hydrothermal method using ammonium citrate and DL-methionine as precursors. N,S-CDs exhibited a surface abundant in -OH, -COOH, and -NH2 groups, aiding in creating non-fluorescent ground state complexes when combined with Hg2+, leading to the suppression of N,S-CDs' fluorescence. Subsequent to additional AMP application, the mixed system's fluorescence was restored. Based on this N,S-CDs sensing system, the thresholds for detection for AMP and Hg2+ were discovered to be 0.121 µM and 0.493 µM, respectively. Furthermore, this methodology proved effective in identifying AMP in real samples of tap and lake water, yielding satisfactory results. Consequently, in the area of bioanalysis in intricate environmental sample work, the sensing system showed tremendous promise.

Investigation of the Application and Mechanism of Nitrogen and Phosphorus Co-doped Carbon Dots for Mercury Ion Detection.

In this paper, we obtained nitrogen and phosphorus co-doped carbon dots through a hydrothermal method using o-phenylenediamine and citric acid in a 40% phosphoric acid environment. The carbon dots emitted fluorescence at 476 nm under excitation at 408 nm and exhibited good selectivity and high sensitivity towards mercury ions. These carbon dots showed excellent dispersibility in water and maintained stable fluorescence even in high concentration salt environments. The interaction between mercury ions and functional groups on the carbon dots surface through electrostatic interaction resulted in static quenching. Simultaneously, by detecting the lifetime and transient absorption spectra of the carbon dots, we observed that the coordination of mercury ions with the carbon dots broadened the band structure of the carbon dots, and the existing photoinduced electron transfer process increased the non-radiative transition channel. The combined effect of dynamic quenching and static quenching significantly reduced the fluorescence intensity of the carbon dots at 476 nm. The carbon dots exhibited linear detection of mercury ions in the range of 0.01-1 µM, with a detection limit as low as 0.0245 µM. In terms of practical water environmental detection applications, these carbon dots were able to effectively detect mercury ions in tap water and lake water, demonstrating their broad application prospects in the field of environmental metal analysis.

Dual-mode colorimetric and fluorescent detection of cobalt ions based on N, B co-doped carbon quantum dots and p-phenylenediamine derived nanoparticles.

Nitrogen, boron co-doped carbon quantum dots (gCQDs), and a coloration probe (PPD-NPs) with response to cobalt ions (Co2+) were prepared by using 4-hydroxyphenylboric acid as the common precursor, with ethylenediamine and p-phenylenediamine (PPD) adopted as nitrogen-doped reagents, respectively. A noticeable brown-to-purple color change can be observed with the addition of Co2+, and a broad absorption band emerges at 535 nm. At the same time, gCQDs, which is introduced as the fluorescence signal source, will be significantly quenched due to the enhanced inner filtration effect, induced by the overlap between the emission spectrum of gCQDs and the emerging absorption band. Therefore, a colorimetric/fluorescent dual-mode sensing probe for Co2+ is constructed by combining the recognition unit PPD-NPs and the fluorescent gCQDs into PPD-NP/gCQD. Under the optimized experimental conditions, the calculated limits of detection are 1.51 × 10-7 M and 3.75 × 10-7 M for the colorimetric mode and the fluorescence mode, respectively, well qualified for the determination of Co2+ maximum permitted level in drinking water. The feasibility of the proposed method has been verified in tap water, lake water, and black tea samples.

Flavor classification and year prediction of Chinese Baijiu by time-resolved fluorescence.

Baijiu is a traditional and popular Chinese liquor with enormous sale potential, which is affected by factors such as flavor and storage time. Chinese Baijiu is a complex and transparent mixture that makes analyzing difficult. The utility of time-resolved fluorescence helped to develop a new method to analyze Baijiu. Forty-two Baijiu samples among six brands with three flavors were prepared, and their fluorescence spectra were analyzed with an excitation light of 374.2 nm. Hexanoic acid and ethyl butyrate were found to have an impact on Baijiu fluorescence. The properties of lifetimes in Baijiu were investigated, and its mechanism was studied by calculations through density function theory. Using parameters of fluorescence lifetimes, Baijiu samples were classified according to their flavors. Additionally, the correlations between fluorescence lifetimes and storage time of Baijiu in Luzhou flavor were obtained, leading to a reliable and efficient method to establish the year forecast model of Chinese Baijiu with a mean error of 2.79 months. It also provides an important reference of the utility of time-resolved fluorescence for quantitative research of multi-component systems.

Highly Fluorescent Green Carbon Dots as a Fluorescent Probe for Detecting Mineral Water pH.

In this report, high-brightness green carbon dots were successfully prepared using 3,5-diaminobenzoic acid as the sole precursor and synthesized in one step using a solvothermal strategy. Under the excitation of 365 nm ultraviolet light, the quantum yield of carbon dots is as high as 53.8%. Experiments revealed that the carbon dots are highly carbonized and the surface is rich in amino and carboxyl groups. The synthesized carbon dots have good water solubility, and are resistant to ions and temperature. The fluorescence intensity of CDs is sensitive to pH changes and is linearly correlated with the pH in the near-neutral range (pH = 6.0 to 9.0). Our experiments showed that carbon dots were sensitive and accurate fluorescent probes for measuring the pH value of drinking water, which could provide an effective method for measuring the pH value of water in the future.

Glutamate and GABA imbalance promotes neuronal apoptosis in hippocampus after stress.

BACKGROUND: People who experience traumatic events have an increased risk of post-traumatic stress disorder (PTSD). However, PTSD-related pathological changes in the hippocampus and prefrontal cortex remain poorly understood. MATERIAL AND METHODS: We investigated the effect of a PTSD-like animal model induced by severe stress. The experimental rats received 20 inescapable electric foot shocks in an enclosed box for a total of 6 times in 3 days. The physiological state (body weight and plasma corticosterone concentrations), emotion, cognitive behavior, brain morphology, apoptosis, and balance of gamma-aminobutyric acid (GABA) and glutamate in the hippocampus and prefrontal cortex were observed. Cell damages were examined with histological staining (HE, Nissl, and silver impregnation), while apoptosis was analyzed with flow cytometry using an Annexin V and propidium iodide (PI) binding and terminal deoxynucleotidyl transferase mediated-dUTP nick end labeling (TUNEL) method. RESULTS: In comparison with the sham litter-mates, the stressed rats showed decreased body weight, inhibition of hypothalamic-pituitary-adrenal (HPA) axis activation, increase in freezing response to trauma reminder, hypoactivity and anxiety-like behaviors in elevated plus maze and open field test, poor learning in Morris water maze, and shortened latency in hot-plate test. There were significant damages in the hippocampus but not in the prefrontal cortex. Imbalance between glutamate and GABA was more evident in the hippocampus than in the prefrontal cortex. CONCLUSIONS: These results suggest that neuronal apoptosis in the hippocampus after severe traumatic stress is related to the imbalance between glutamate and GABA. Such modifications may resemble the profound changes observed in PTSD patients.

Aboveground Biomass Mapping and Analysis of Spatial Drivers in the Qinghai-Xizang Plateau Permafrost Zone: A Case Study of the Beilu River Basin.

Aboveground biomass (AGB) serves as a crucial measure of ecosystem productivity and carbon storage in alpine grasslands, playing a pivotal role in understanding the dynamics of the carbon cycle and the impacts of climate change on the Qinghai-Xizang Plateau. This study utilized Google Earth Engine to amalgamate Landsat 8 and Sentinel-2 satellite imagery and applied the Random Forest algorithm to estimate the spatial distribution of AGB in the alpine grasslands of the Beiliu River Basin in the Qinghai-Xizang Plateau permafrost zone during the 2022 growing season. Additionally, the geodetector technique was employed to identify the primary drivers of AGB distribution. The results indicated that the random forest model, which incorporated the normalized vegetation index (NDVI), the enhanced vegetation index (EVI), the soil-adjusted vegetation index (SAVI), and the normalized burn ratio index (NBR2), demonstrated robust performance in regards to AGB estimation, achieving an average coefficient of determination (R2) of 0.76 and a root mean square error (RMSE) of 70 g/m2. The average AGB for alpine meadows was determined to be 285 g/m2, while for alpine steppes, it was 204 g/m2, both surpassing the regional averages in the Qinghai-Xizang Plateau. The spatial pattern of AGB was primarily driven by grassland type and soil moisture, with q-values of 0.63 and 0.52, and the active layer thickness (ALT) also played a important role in AGB change, with a q-value of 0.38, demonstrating that the influences of ALT should not be neglected in regards to grassland change.

Classification and identification of tea diseases based on improved YOLOv7 model of MobileNeXt.

To address the issues of low accuracy and slow response speed in tea disease classification and identification, an improved YOLOv7 lightweight model was proposed in this study. The lightweight MobileNeXt was used as the backbone network to reduce computational load and enhance efficiency. Additionally, a dual-layer routing attention mechanism was introduced to enhance the model's ability to capture crucial details and textures in disease images, thereby improving accuracy. The SIoU loss function was employed to mitigate missed and erroneous judgments, resulting in improved recognition amidst complex image backgrounds.The revised model achieved precision, recall, and average precision of 93.5%, 89.9%, and 92.1%, respectively, representing increases of 4.5%, 1.9%, and 2.6% over the original model. Furthermore, the model's volum was reduced by 24.69M, the total param was reduced by 12.88M, while detection speed was increased by 24.41 frames per second. This enhanced model efficiently and accurately identifies tea disease types, offering the benefits of lower parameter count and faster detection, thereby establishing a robust foundation for tea disease monitoring and prevention efforts.

Pest recognition in microstates state: an improvement of YOLOv7 based on Spatial and Channel Reconstruction Convolution for feature redundancy and vision transformer with Bi-Level Routing Attention.

Introduction: In order to solve the problem of precise identification and counting of tea pests, this study has proposed a novel tea pest identification method based on improved YOLOv7 network. Methods: This method used MPDIoU to optimize the original loss function, which improved the convergence speed of the model and simplifies the calculation process. Replace part of the network structure of the original model using Spatial and Channel reconstruction Convolution to reduce redundant features, lower the complexity of the model, and reduce computational costs. The Vision Transformer with Bi-Level Routing Attention has been incorporated to enhance the flexibility of model calculation allocation and content perception. Results: The experimental results revealed that the enhanced YOLOv7 model significantly boosted Precision, Recall, F1, and mAP by 5.68%, 5.14%, 5.41%, and 2.58% respectively, compared to the original YOLOv7. Furthermore, when compared to deep learning networks such as SSD, Faster Region-based Convolutional Neural Network (RCNN), and the original YOLOv7, this method proves to be superior while being externally validated. It exhibited a noticeable improvement in the FPS rates, with increments of 5.75 HZ, 34.42 HZ, and 25.44 HZ respectively. Moreover, the mAP for actual detection experiences significant enhancements, with respective increases of 2.49%, 12.26%, and 7.26%. Additionally, the parameter size is reduced by 1.39 G relative to the original model. Discussion: The improved model can not only identify and count tea pests efficiently and accurately, but also has the characteristics of high recognition rate, low parameters and high detection speed. It is of great significance to achieve realize the intelligent and precise prevention and control of tea pests.

Boric acid-functionalized silver nanoparticles as SERS substrate for sensitive and rapid detection of fructose in artificial urine.

The accurate detection of fructose in human urine can help prevent and screen for diseases such as fructokinase deficiency and hereditary fructose intolerance. Surface-enhanced Raman spectroscopy (SERS) is an analytical technique with selectivity and high sensitivity, which has been widely applied to the detection of targets with complex backgrounds. In this work, 4-mercaptophenylboronic acid (4-MPBA) was modified on the surface of silver nanoparticles (AgNPs) under mild conditions to obtain a boronic acid-functionalized SERS substrate for the detection of fructose in artificial urine. The detection mechanism was based on the deboronization reaction of 4-MPBA on the surface of AgNPs, which was induced by fructose, and the Raman signal of the generated thiophenol (TP) molecules was significantly enhanced by the silver nanoparticles, with a linear increase in SERS peak intensity at 1570 cm-1. We achieved the detection limits of 0.084 µmol/L in water and 0.535 µmol/L in urine by this method. The relative standard deviation (RSD) in the recovery experiments of urine ranged from 1.01 % to 2.22 %, and the whole detection time was less than 10 min, which indicated that this method is highly reliable for fructose detection and has a good prospect in bioassay and clinical medicine.

Detection of melamine by using carboxyl-functionalized Ag-COF as a novel SERS substrate.

Melamine, a nitrogen-containing organic molecule, has received widespread attention as it had been illegally added in dairy products to increase the content of nitrogen, leading to kidney stones in healthy people after long-term ingestion. Based on SERS technology and Covalent Organic Framework (COF) materials, we developed carboxyl-functionalized Ag-COF-COOH materials as SERS substrates for the detection of melamine adulteration. Using COF material as a ligand can effectively reduce the influence of interferents in milk. In addition, we investigated two causes of melamine SERS enhancement: the ordered arrangement of Ag NPs and the strong interaction between the substrate and the melamine. The linear range was 1-20 µg/L and the limit of detection (LOD) was 0.68 µg/L in liquid milk due to the high sensitivity and reliability of this method. The results show that this new SERS substrate has great potential for applications in the food surveillance industry.

Al2O3@Ag composite structure as SERS substrate for sensitive detection of sodium thiocyanate.

Sodium thiocyanate (NaSCN) can be added to fresh milk to enhance the sterilization ability of the lactoperoxidase system (LP system) in milk, extending shelf life. However, excessive intake of NaSCN can be harmful to human health because it can prevent absorption of iodine leading to disease. Also NaSCN can be used as a marker to distinguish smokers from non-smokers. In this work, we successfully synthesized meatball-like Al2O3@Ag composite structures as surface-enhanced Raman scattering (SERS) substrates using a simple wet chemical method adapted to conventional laboratory conditions. The substrate exhibited strong SERS enhancement for NaSCN. Under the optimal experiment conditions, we obtained a detection limit of 0.28 µg L-1 and a quantification limit of 1 µg L-1, R2 = 0.992. Based on the analysis of the intensity of SERS characteristic peak, the substrate had good reproducibility and uniformity. In summary, the Al2O3@Ag composite structure achieved sensitive SERS detection of NaSCN. Combining the facile and low-cost methods, we believe that the SERS detection method developed in this work can be used as a potential candidate for biosensing applications in the future.

Nitrogen-doped carbon dots with bright fluorescence for highly sensitive detection of Fe3+ in environmental waters.

In this study, we synthesized stable nitrogen-doped carbon dots by a simple and economical one-step hydrothermal method using l-cysteine and anhydrous ethylenediamine as precursors. The prepared carbon dots have bright and stable blue light emission near 383 nm and can be used as fluorescent probes to detect the concentration of Fe3+ in environmental waters. It was demonstrated that due to intermolecular electrostatic interaction, a non-fluorescent complex N-CDs/Fe3+ is formed by coordination of Fe3+ with amino and carboxyl functional groups on the surface of carbon dots. Therefore, in combination with internal filtration effect, the fluorescence of carbon dots can be quenched in the presence of Fe3+, and the degree of quenching is linearly related to the concentration of Fe3+. The limit of detection in deionized water was as low as 0.069 µM with R2 of 0.998 and a linear range of 0.3 to 20 µM. In addition, satisfactory recoveries were achieved for the determination of Fe3+ in environmental water samples. The method is reliable, with highly sensitivity and selectivity, and has potential for practical applications in environmental metal analysis.

Multi-response gelation based on the molecular assembly of Sudan I dye derivatives for phase selective gelators and chemosensors.

Sudan I dye-based smart low molecular weight gelators with/without a perfluoroalkyl group have been successfully synthesized and characterized by rheological measurements, scanning electron microscopy (SEM), IR, and NMR spectroscopies. The gelation behaviors in response to temperature, pH changes, metal cations, and UV-vis light irradiation are investigated. Compounds 1 and 2 could selectively sense the Cu2+ cation in the presence of other metal cations. Moreover, compound 2 with a perfluoroalkyl group shows phase selective gelation ability. This work also provides a valuable reference for exploiting photosensitive materials as chemosensors.

Sensitive determination of Norfloxacin in milk based on ß-cyclodextrin functionalized silver nanoparticles SERS substrate.

The norfloxacin (NFX) residue in milk will increase human resistance to drugs and pose a threat to public health. In this work, a highly sensitive method for detection of NFX was developed based on surface enhanced Raman spectroscopy (SERS) using ß-cyclodextrin functionalized silver nanoparticles (ß-CD-AgNPs) as substrate. The unique spatial size and hydrophilicity of ß-CD on the surface of AgNPs could selectively capture the target molecule (NFX) through some weak interactions, including hydrogen-bond interaction, electrostatic interaction, etc. The interactions were characterized by the UV-Vis absorption spectroscopy, fluorescence spectroscopy, Zeta potential and DLS. The Raman signal of NFX is largely enhanced when anchored by ß-CD on the surface of AgNPs due to SERS effect. Through a series of experiments and analysis, the limit of detection (LOD) in standard solution and spiked milk were calculated to be 3.214 pmol/L and 5.327 nmol/L. The correlation coefficients (R2) were 0.986 and 0.984, respectively. For milk sample determination of NFX, the recovery was 101.29% to 104.00% with the relative standard deviation (RSD) from 2.986% to 9.136%. To sum up, this developed SERS strategy is sensitive and specific to detect NFX in milk, it has practical application value and prospects.

SERS Detection of Benzoic Acid in Milk by Using Ag-COF SERS Substrate.

Benzoic acid, which has a pivotal role in food additive, is prohibited to add as a preservative in dairy products. China, Brazil, and other countries have proposed standard methods to detect the addition of benzoic acid in food. Surface-enhanced Raman scattering (SERS) is an upcoming spectral detection technique, which has been widely used in the field of material analysis with the advantages of non-invasive, fast detection speed and complex environment with little interference. To detect the illegal use of benzoic acid in dairy industry, we developed Ag-COF (covalent-organic framework) material as SERS substrate to detect benzoic acid in liquid milk. The great enhancement ability of Ag-COF substrate is controlled by the addition of acetic acid and complex interplay between COF material and benzoic acid. This detection method has high sensitivity and reliability that allows us to achieve limit of detection (LOD) of 0.13 µg/mL in milk and 0.00372 µg/mL in water by applying this method. In experiment on recovery rate of real samples, the detection time is less than 15 minutes and the relative standard deviation (RSD) ranged from 2.82% to 5.69%. Therefore, this method has practical significance of the detection of benzoic acid in dairy products.

A fluorescent probe based on FRET effect between carbon nanodots and gold nanoparticles for sensitive detection of thiourea.

Illegal abuse results in the presence of thiourea (TU) in soil, wastewater, and even fruits, which is harmful for the environment and human health. It has urgent practical significance to design an efficient and reliable probe for TU detection. Herein, a sensitive fluorescent probe with off-on response for harmful TU was reported. The probe was designed with fluorescent carbon nanodots (CNDs) and gold nanoparticles (AuNPs) based on fluorescence resonance energy transfer (FRET) effect. Firstly, the CNDs were pre-combined with AuNPs and the fluorescence of CNDs was quenched due to the FRET effect. Upon addition of TU, the fluorescence of CNDs recovered due to the unbinding of CNDs and AuNPs, since the coordination interaction between TU and AuNPs is stronger than the electrostatic interaction among CNDs and AuNPs. Under the optimum parameters, a linear relationship was found between the relative fluorescence intensity of the probe and the concentration of TU in the range of 5.00 × 10-8-1.00 × 10-6 M (R2 = 0.9958), with the limit of detection (LOD) calculated to be 3.62 × 10-8 M. This proposed method is easy to operate and has excellent selectivity and sensitivity for TU, which can be effectively applied in environmental water and compound fruit-vegetable juice.

Quantifying links between stroke and risk factors: a study on individual health risk appraisal of stroke in a community of Chongqing.

The objective of this study is to investigate the risk factors of stroke in a community in Chongqing by setting quantitative criteria for determining the risk factors of stroke. Thus, high-risk individuals can be identified and laid a foundation for predicting individual risk of stroke. 1,034 cases with 1:2 matched controls (2,068) were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road and Ciqikou. Participants were interviewed with a uniform questionnaire. The risk factors of stroke and the odds ratios of risk factors were analyzed with a logistic regression model, and risk exposure factors of different levels were converted into risk scores using statistical models. For men, ten risk factors including hypertension (5.728), family history of stroke (4.599), and coronary heart disease (5.404), among others, were entered into the main effect model. For women, 11 risk factors included hypertension (5.270), family history of stroke (4.866), hyperlipidemia (4.346), among others. The related risk scores were added to obtain a combined risk score to predict the individual's risk of stoke in the future. An individual health risk appraisal model of stroke, which was applicable to individuals of different gender, age, health behavior, disease and family history, was established. In conclusion, personal diseases including hypertension, diabetes mellitus, etc., were very important to the prevalence of stoke. The prevalence of stroke can be effectively reduced by changing unhealthy lifestyles and curing the positive individual disease. The study lays a foundation for health education to persuade people to change their unhealthy lifestyles or behaviors, and could be used in community health services.