Quantification of antibiotics in food by octahedral gold-silver nanocages-based SERS sensor coupling multivariate calibration.

The abuse of antibiotics has caused gradually increases drug-resistant bacterial strains that pose health risks. Herein, a sensitive SERS sensor coupled multivariate calibration was proposed for quantification of antibiotics in milk. Initially, octahedral gold-silver nanocages (Au@Ag MCs) were synthesized by Cu2O template etching method as SERS substrates, which enhanced the plasmonic effect through sharp edges and hollow nanostructures. Afterwards, five chemometric algorithms, like partial least square (PLS), uninformative variable elimination-PLS (UVE-PLS), competitive adaptive reweighted sampling-PLS (CARS-PLS), random frog-PLS (RF-PLS), and convolutional neural network (CNN) were applied for TTC and CAP. RF-PLS performed optimally for TTC and CAP (Rc = 0.9686, Rp = 0.9648, RPD = 3.79 for TTC and Rc = 0.9893, Rp = 0.9878, RPD = 5.88 for CAP). Furthermore, the detection limit of 0.0001 µg/mL for both TTC and CAP was obtained. Finally, satisfactory (p > 0.05) results were obtained with the standard HPLC method. Therefore, SERS combined RF-PLS could be applied for fast, nondestructive sensing of TTC and CAP in milk.

Acute skin toxicity and self-management ability among Chinese breast cancer radiotherapy patients: a qualitative study.

OBJECTIVES: Radiation dermatitis is the most common reaction to radiotherapy, almost all breast cancer patients receive radiotherapy on an outpatient basis. Currently, there are no studies on the experience of radiation dermatitis and the ability to self-manage it. Therefore, we aimed to use qualitative approaches to gain a deeper understanding of the actual experiences and self-management ability in order to provide a reference for further improving the effectiveness of self-management and to optimize symptom management strategies. METHODS: A descriptive qualitative study was conducted using purposive sampling to select 17 breast cancer patients undergoing radiotherapy. Semi-structured interviews were conducted from September to November 2023. The Colaizzi seven-step analysis method was used to classify the data into summarized themes. RESULTS: Four themes were identified from the interview responses: (1) multiple self-reported skin symptoms in breast cancer patients with radiation dermatitis; (2) the multidimensional impact on patient's quality of life, especially pruritus, ulceration; (3) the ability to self-manage radiation dermatitis: strong mental toughness, positive response, and self-doubt; (4) challenges faced: concerns about radiotherapy side effects and recurrence, targeted symptom management and continuity of care after the radiotherapy. CONCLUSIONS: Healthcare professionals should consider patients' self-reported symptoms when assessing radiation dermatitis. For pruritus and pain, we can enhance precision symptom management to improve patients' quality of life. By utilizing information technology tools, we can increase breast cancer patients' ability and confidence in managing radiation dermatitis effectively while enhancing accurate symptom management during radiotherapy.

Flexible SERS sensor using AuNTs-assembled PDMS film coupled chemometric algorithms for rapid detection of chloramphenicol in food.

The misuse of chloramphenicol (CAP) has led to the development of drug-resistant strains that pose significant threats to public health. Here, we propose a universal flexible surface-enhanced Raman spectroscopy (SERS) sensor utilizing gold nanotriangles (AuNTs) and polydimethylsiloxane (PDMS) film for rapid detection of CAP in food samples. Initially, AuNTs@PDMS with unique optical and plasmonic properties were used to collect spectra of CAP. Afterward, four chemometric algorithms were executed and compared. Accordingly, random frog-partial least squares (RF-PLS) exhibited optimum results with correlation coefficient of prediction (Rp = 0.9802) and the lowest root-mean-square error of prediction (RMSEP = 0.348 µg/mL). Furthermore, the sensor's efficacy to detect CAP in milk samples was confirmed, and the findings were compatible with the conventional HPLC approach (P > 0.05). Therefore, the proposed flexible SERS sensor could effectively be used to monitor milk quality and safety.

A Novel Colorimetric Sensor Array Coupled Multivariate Calibration Analysis for Predicting Freshness in Chicken Meat: A Comparison of Linear and Nonlinear Regression Algorithms.

As a source of vital nutrients for the normal functioning of the body, chicken meat plays an important role in promoting good health. This study examines the occurrence of total volatile basic nitrogen (TVB-N) as an index for evaluating freshness, using novel colorimetric sensor arrays (CSA) in combination with linear and nonlinear regression models. Herein, the TVB-N was determined by steam distillation, and the CSA was fabricated via the use of nine chemically responsive dyes. The corresponding dyes utilized, and the emitted volatile organic compounds (VOCs) were found to be correlated. Afterwards, the regression algorithms were applied, assessed, and compared, with the result that a nonlinear model based on competitive adaptive reweighted sampling coupled with support vector machines (CARS-SVM) achieved the best results. Accordingly, the CARS-SVM model provided improved coefficient values (Rc = 0.98 and Rp = 0.92) based on the figures of merit used, as well as root mean square errors (RMSEC = 3.12 and RMSEP = 6.75) and a ratio of performance deviation (RPD) of 2.25. Thus, this study demonstrated that the CSA paired with a nonlinear algorithm (CARS-SVM) could be employed for fast, noninvasive, and sensitive detection of TVB-N concentration in chicken meat as a major indicator of freshness in meat.

Stimuli-responsive SERS biosensor for ultrasensitive tetracycline sensing using EDTA-driven PEI@CaCO3 microcapsule and CS@FeMMs.

In this work, a stimuli-responsive SERS biosensor was fabricated for tetracycline (TTC) by "signal-on" strategy using (EDTA)-driven polyethyleneimine grafted calcium carbonate (PEI@CaCO3) microcapsule and chitosan-Fe magnetic microbeads (CS@FeMMs). Initially, aptamer conjugated magnetic-bead CS@FeMMs@Apt with superparamagnetism and excellent biocompatibility was employed as capture probe, which facilitated the rapid and easy magnetic separation. Subsequently, the PEI cross-linked layer and aptamer network layer were constructed onto the outer layer of CaCO3@4-ATP microcapsule to form sensing probes (PEI@CaCO3@4-ATP@Apt) via the layer-by-layer assembly method. In the presence of TTC, a sandwich SERS-assay was exploited by aptamer recognition induced target-bridged strategy. When the solution of EDTA was added, the core layer of CaCO3 would be dissolved quickly, destroying the microcapsule to release 4-ATP. The released 4-ATP could be quantitatively monitored by dripping the supernatant onto the AuNTs@PDMS SERS platform, resulting in a strong Raman "signal-on". Under the optimal conditions, a good linear relationship was established with a correlation coefficient (R2) of 0.9938 and a LOD of 0.03 ng/mL. Additionally, the application capacity of the biosensor to detect TTC was also affirmed in food matrixes, and the results were consistent with the standard ELISA method (P > 0.05). Hence, this SERS biosensor affords extensive application prospects for TTC detection with multiple merits such as high sensitivity, environment friendliness, and high stability.

Identification of volatile compounds and metabolic pathway during ultrasound-assisted kombucha fermentation by HS-SPME-GC/MS combined with metabolomic analysis.

The current work combines headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC/MS) with multivariate analysis fusion metabonomics for examining metabolite profile changes. The correlation with metabolic pathways during the fermentation of kombucha tea were comprehensively explored. For optimizing the fermentation process, ultrasound-assisted factors were explored. A total of 132 metabolites released by fermented kombucha were detected by HS-SPME-GC/MS. We employed the principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to present the relationship between aroma components and fermentation time, of which the first two principal components respectively accounted for 60.3% and 6.5% of the total variance. Multivariate statistical analysis showed that during the fermentation of kombucha tea, there were significant differences in the phenotypes of metabolites in the samples, and 25 characteristic metabolites were selected as biomarkers. Leaf alcohol was first proposed as the characteristic volatile in the fermentation process of kombucha. Furthermore, we addressed the generation pathways of characteristic volatiles, their formation mechanisms, and the transformational correlation among them. Our findings provide a roadmap for future kombucha fermentation processing to enhance kombucha flavor and aroma.

Simultaneous quantification of total flavonoids and phenolic content in raw peanut seeds via NIR spectroscopy coupled with integrated algorithms.

Peanuts are nutritionally valuable for both humans and animals due to their high content of flavonoids and phenolic compounds. Herein, we explored the potential of near-infrared (NIR) spectroscopy coupled with efficient variable selection algorithms for quantitative prediction of total flavonoids (TFC) and total phenolics content (TPC) in raw peanut seeds. Spectrophotometrically, the reference results of the extracts for TFC and TPC were analysed and recorded. The integrated application of the synergy interval coupled competitive adaptive reweighted sampling-partial least squares (Si-CARS-PLS) were used for prediction. The model performance appraisal was based on the correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD). The Si-CARS-PLS performed optimally for TFC (Rp = 0.9137, RPD = 2.49) and TPC (Rp = 0.9042, RPD = 2.31), respectively. Moreover, the model (Si-CARS-PLS) was found to have an acceptable fit for the analytes under study since it achieved 0.88 for TFC and 0.86 for TPC based on the external validation. Therefore, these results showed that NIR coupled with Si-CARS-PLS could be used for the quantitative prediction of flavonoids and phenolic contents in raw peanut seeds.

Intelligent evaluation of free amino acid and crude protein content in raw peanut seed kernels using NIR spectroscopy paired with multivariable calibration.

Given the nutritional importance of peanuts, this study examined the free amino acid (FAA) and crude protein (CP) content in raw peanut seeds. Near-infrared spectroscopy (NIRS) was employed in combination with variable selection algorithms after successful reference data analysis using colorimetric and Kjeldahl methods. Ensuing the application of partial least squares (PLS) as a full spectral model, the genetic algorithm (GA), bootstrapping soft shrinkage (BOSS), uninformative variable elimination (UVE), and random frog (RF) models were tested and assessed. A comparison of correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) was performed to appraise the performance of the built models. Using RF-PLS, an unsurpassed outcome was achieved for FAA (Rp = 0.937, RPD = 3.38) and CP (Rp = 0.9261, RPD = 3.66). These findings demonstrated that NIR in combination with RF-PLS could be utilized for quantitative, rapid, and nondestructive prediction of FAA and CP in raw peanut seed samples.

A target-responsive release SERS sensor for sensitive detection of tetracycline using aptamer-gated HP-UiO-66-NH2 nanochannel strategy.

In this study, a target-responsive release Surface-enhanced Raman scattering (SERS) sensor was developed for sensitive detection of tetracycline (TTC) using aptamer-gated HP-UiO-66-NH2 nanochannel strategy. The hierarchically porous zirconium-based metal-organic frameworks (HP-UiO-66-NH2 MOFs) with high surface areas and the conjugated π-electron system were first synthesized and served as the nanocontainers. The methylene blue (MB) and gold nanoparticles (AuNPs) were then loaded in the pores of HP-UiO-66-NH2 as the signal probes and capping agent, respectively. Thereafter, aptamer was assembled on the surface of HP-UiO-66-NH2 based on the π-π stacking interaction. In the presence of TTC, the aptamer "molecular gate" was opened, resulting in the "cargo release" of MB and AuNPs. Hence, the amount of TTC could be determined by monitoring the change of SERS intensity of the supernatant. Under the optimal conditions, a good linear correlation between SERS intensity (886 cm-1) and TTC concentration was observed with the concentration from 0.01 to 10000 ng/mL, resulting in a relatively low detection limit of 0.01 ng/mL. Moreover, this method showed a promising practical application in spiked real samples (milk and pork) with recoveries of 93.23-108.79%, which confirmed its great potential in antibiotic detection.

Highly-anisotropic plasmons in two-dimensional hyperbolic copper borides.

Hyperbolic materials have wide application prospects, such as all-angle negative refraction, sub-diffraction imaging and nano-sensing, owning to the unusual electromagnetic response characteristics. Compared with artificial hyperbolic metamaterials, natural hyperbolic materials have many advantages. Anisotropic two-dimensional (2D) materials show great potential in the field of optoelectronics due to the intrinsic in-plane anisotropy. Here, the electronic and optical properties of two hyperbolic 2D materials, monolayer CuB6 and CuB3, are investigated using first-principles calculations. They are predicted to have multiple broadband hyperbolic windows with low loss and highly-anisotropic plasmon excitation from infrared to ultraviolet regions. Remarkably, plasmon propagation along the x-direction is almost forbidden in CuB3 monolayer. The hyperbolic windows and plasmonic properties of these 2D copper borides can be effectively regulated by electron (or hole) doping, which offers a promising strategy for tuning the optical properties of the materials.

The Impact of Green Credit on the Green Innovation Level of Heavy-Polluting Enterprises-Evidence from China.

This article uses the "Green Credit Guidelines" promulgated in 2012 as an example to construct a quasi-natural experiment and uses the double difference method to test the impact of the implementation of the "Green Credit Guidelines" on the green innovation activities of heavy-polluting enterprises. The study found that, in comparison to non-heavy polluting enterprises, the implementation of green credit policies inhibited the green innovation of all heavy-polluting enterprises. In the analysis of heterogeneity, this restraint effect did not differ significantly due to the nature of property rights and the company's size. The mechanism test showed that green credit policy limits the efficiency of business investment and increases the cost of financing business debt. Eliminating corporate credit financing, particularly long-term borrowing, negatively impacts the green innovation behavior of listed companies.

Simultaneous quantification of deoxymyoglobin and oxymyoglobin in pork by Raman spectroscopy coupled with multivariate calibration.

Because of the nutritional advantages and customer acceptance, it is vital to ensure pork meat quality. This study examined the quantification of myoglobin proportions (deoxymyoglobin and oxymyoglobin) by coupling Raman spectroscopy with efficient variables selection chemometrics. Prior to acquiring Raman spectroscopic data, the fractions of myoglobin were determined. Afterward, multivariate calibration methods like partial least square (PLS), competitive adaptive reweighted sampling (CARS-PLS), genetic algorithm-PLS (GA-PLS), and random frog-PLS (RF-PLS) were applied and evaluated. The models' performance was assessed using correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD). The RF-PLS model achieved optimal results for both deoxymyoglobin and oxymyoglobin, with Rp = 0.8936; RMSEP = 2.91 and RPD = 1.97 for the former and Rp = 0.9762; RMSEP = 1.23 and RPD = 4.47 for the latter, respectively. Therefore, this work demonstrated that Raman spectroscopy paired with RF-PLS could be employed for nondestructive, fast, and easy detection of deoxymyoglobin and oxymyoglobin.

Identification of characteristic volatiles and metabolomic pathway during pork storage using HS-SPME-GC/MS coupled with multivariate analysis.

Previous researches have been conducted evaluating the volatile compounds of pork. However, data regarding the changes in volatiles and metabolic pathways during pork storage were inadequately investigated. Herein, a headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC/MS) coupled multivariate analysis was proposed for characterizing the profiles of volatile compounds and metabolic pathways during pork storage. A total of 37 metabolites, including aldehydes, ketones, alcohols etc. were successfully identified. Multivariate statistical analysis revealed a substantial variation in metabolite phenotype among samples over the pork storage period, with 12 characteristic metabolites and 5 potential characteristic metabolites screened as biomarkers. Moreover, three metabolomic pathways analysis and transformation between each other (thermal reactions, lipid metabolism and amino acid metabolism) reveals the underlying mechanisms of metabolites change of pork. Therefore, the present study may provide insight into future understanding of the variation in the pork metabolite profiles.

Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis.

Two key parameters (acidity and peroxide content) for evaluation of the oxidation level in crude peanut oil have been studied. The titrimetric analysis was carried out for reference data collection. Then, near-infrared spectroscopy in combination with chemometric algorithms such as partial least square (PLS); bootstrapping soft shrinkage-PLS (BOSS-PLS); uninformative variable elimination-PLS (UVE-PLS), and competitive-adaptive reweighted sampling-PLS (CARS-PLS) were attempted and assessed. The correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to individually evaluate the performance of the models. Optimum results were noticed with CARS-PLS, 0.9517 ≤ Rc ≤ 0.9670, 0.9503 ≤ Rp ≤ 0.9637, 0.0874 ≤ RMSEP ≤ 0.5650, and 3.14 ≤ RPD ≤ 3.64. Therefore, this affirmed that the near-infrared spectroscopy coupled with CARS-PLS could be used as a simple, fast, and non-invasive technique for quantifying acid value and peroxide value in crude peanut oil.

Fabricating a nano-bionic sensor for rapid detection of H2S during pork spoilage using Ru NPs modulated catalytic hydrogenation conversion.

Rapid, sensitive and on-site monitoring of meat spoilage is highly essential for food safety. Hydrogen sulfide (H2S) a typical volatile, produced during enzymatic hydrolysis is considered as a reliable marker for evaluating meat freshness. Herein, a novel nano-bionic sensor based on the superior catalytic activity of ruthenium nanoparticles (Ru NPs) has been fabricated for H2S quantification. The activity sites of Ru NPs were poisoned in the presence of H2S, thereby affecting its catalytic efficiency via reducing the degradation of azo dye. The developed nano-bionic sensor achieved a selective response toward H2S, with capability for on-site surveillance of the pork freshness in the linear range (0-1800 nM). A higher correlation was obtained between the H2S content and the total viable count during the 9-period pork spoilage process (R2 = 0.9633 and 0.9769). Moreover, the proposed method exhibits high selectivity in the presence of other characteristic volatiles encountered during the pork storage process.

Anomalous plasmons in a two-dimensional Dirac nodal-line Lieb lattice.

Plasmons in two-dimensional (2D) Dirac materials feature an interesting regime with a tunable frequency, and long propagating length and lifetime, but are rarely achieved in the visible light regime. Using a tight-binding (TB) model in combination with first-principles calculations, we investigated plasmon modes in a 2D Lieb lattice with a Dirac nodal-line electronic structure. In contrast to conventional 2D plasmons, anomalous plasmons in the Lieb lattice exhibit the unique features of a carrier-density-independent frequency, being Landau-damping free in a wide-range of wave vectors, a high frequency, and high subwavelength confinement. Remarkably, by using first-principles calculations, we proposed a candidate material, 2D Be2C monolayer, to achieve these interesting plasmon properties. The plasmons in the Be2C monolayer can survive up to the visible frequency region and propagate to large momentum transfer that has rarely been reported. The anomalous plasmons revealed in the Lieb lattice offer a promising platform for the study of 2D plasmons as well as the design of 2D plasmonic materials.

Trends in the Retinal Nerve Fiber Layer Thickness Changes with Different Degrees of Visual Field Defects.

PURPOSE: To explore the disease progression of primary open-angle glaucoma (POAG) in individuals with different degrees of VF defects by analyzing the trends in retinal nerve fiber layer (RNFL) changes at each stage. METHODS: A total of 39 patients (77 eyes) were divided into three groups based on the severity of glaucomatous visual field (VF) loss: the first group included patients with mild baseline VF defects (mild group; n = 21 eyes). The second group included patients with moderate VF defects (moderate group; n = 18 eyes). The third group included patients with severe baseline VF defects (severe group; n = 38 eyes). For all patients, slit-lamp biomicroscopy of the anterior and posterior segments and detailed fundus and optic disc inspections were performed, the intraocular pressure (IOP) was measured by Goldman tonometry, best-corrected visual acuity (BCVA) was measured, the RNFL thickness was measured by OCT, and the VF was assessed by the Octopus perimeter. All the groups were followed up postoperatively for 18 months. RESULTS: The mean RNFL thickness was recorded for all the visits. Using simple linear regression analysis, we found that the R 2 values of the three groups were 0.988, 0.982, and 0.814, respectively, and the slopes of mean RNFL thickness changes for mild, moderate, and severe baseline VF defects were -0.088, -0.082, and -0.015, respectively. Moreover, we used simple linear regression analysis to explore whether and how the speed of RNFL thinning differs across groups. The R 2 values of the three groups were 0.982, 0.978, and 0.805, respectively, and the slopes for mild, moderate, and severe baseline VF defects were 0.089, 0.085, and 0.017, respectively. CONCLUSION: The rate of RNFL thinning is linear; RNFL thinning is the fastest in individuals with mild baseline VF defects, followed by those with moderate baseline VF defects. In individuals with severe VF defects, changes in the RNFL thickness do not appropriately reflect the progression of the disease. The clinical trial is registered with ChiCTR2000028975.

Effect of one comprehensive education course to lower anxiety and depression among Chinese breast cancer patients during the postoperative radiotherapy period - one randomized clinical trial.

BACKGROUND: We investigated the effectiveness of one education course to lower the severity of anxiety and depression symptoms among breast cancer (BC) patients during radiotherapy (RT). METHODS: All 290 one-sided BC patients were evenly randomized into intervention or control arm. "Intervention" patient was additionally provided with one three-hour course on psychological stresses and management skills. Changes of anxiety and depression score and their 3-level severity category ('normal', 'borderline' and 'abnormal' scored 0-7, 8-10 and 11-21, respectively) from HADS questionnaire over RT were evaluated by multivariable linear and ordinal logistic regressions. RESULTS: Response rates were 94 and 100% by "intervention" and "control" arm, respectively. Means of score changes by "intervention" and "control" (n = 145) were + 0.59 (SD = 2.47) and + 0.11 (SD = 2.55) for anxiety and + 0.81 (SD = 2.81) and + 0.45 (SD = 2.77) for depression scores, respectively. 'Abnormal' anxiety and depression patients were 4.1 and 6.9% at baseline and 4.8 and 6.9% at end of RT at 'control' arm; those rates were 6.6 and 7.4%, and 8.8 and 10.3% at 'intervention' arm, respectively. Both changes on anxiety and depression measurements between two arms were all insignificant (p > 0.20). CONCLUSIONS: One education course did not reduce the score and severity of anxiety and depression symptoms over RT period. TRIAL REGISTRATION: Chinese Clinical Trial Registry #: ChiCTR-IIR-16008818 at www.chictr.org.cn .

Strategies to achieve high-solids enzymatic hydrolysis of dilute-acid pretreated corn stover.

Three strategies were presented to achieve high solids loading while maximizing carbohydrate conversion, which are fed-batch, splitting/thickening, and clarifier processes. Enzymatic hydrolysis was performed at water insoluble solids (WIS) of 15% using washed dilute-acid pretreated corn stover. The carbohydrate concentration increased from 31.8 to 99.3g/L when the insoluble solids content increased from 5% to 15% WIS, while the final carbohydrate conversion was decreased from 78.4% to 73.2%. For the fed-batch process, a carbohydrate conversion efficiency of 76.8% was achieved when solid was split into 60:20:20 ratio, with all enzymes added first. For the splitting/thickening process, a carbohydrate conversion of 76.5% was realized when the filtrate was recycled to simulate a steady-state process. Lastly, the clarifier process was evaluated and the highest carbohydrate conversion of 81.4% was achieved. All of these results suggests the possibility of enzymatic hydrolysis at high solids to make the overall conversion cost-competitive.

Comparison of sodium carbonate-oxygen and sodium hydroxide-oxygen pretreatments on the chemical composition and enzymatic saccharification of wheat straw.

Pretreatment of wheat straw with a combination of sodium carbonate (Na2CO3) or sodium hydroxide (NaOH) with oxygen (O2) 0.5MPa was evaluated for its delignification ability at relatively low temperature 110°C and for its effect on enzymatic hydrolysis efficiency. In the pretreatment, the increase of alkali charge (as Na2O) up to 12% for Na2CO3 and 6% for NaOH, respectively, resulted in enhancement of lignin removal, but did not significantly degrade cellulose and hemicellulose. When the pretreated solid was hydrolyzed with a mixture of cellulases and hemicellulases, the sugar yield increased rapidly with the lignin removal during the pretreatment. A total sugar yield based on dry matter of raw material, 63.8% for Na2CO3-O2 and 71.9% for NaOH-O2 was achieved under a cellulase loading of 20FPU/g-cellulose. The delignification efficiency and total sugar yield from enzymatic hydrolysis were comparable to the previously reported results at much higher temperature without oxygen.