Altered executive control network and default model network topology are linked to acute electronic cigarette use: A resting-state fNIRS study.

In recent years, electronic cigarettes (e-cigs) have gained popularity as stylish, safe, and effective smoking cessation aids, leading to widespread consumer acceptance. Although previous research has explored the acute effects of combustible cigarettes or nicotine replacement therapy on brain functional activities, studies on e-cigs have been limited. Using fNIRS, we conducted graph theory analysis on the resting-state functional connectivity of 61 male abstinent smokers both before and after vaping e-cigs. And we performed Pearson correlation analysis to investigate the relationship between alterations in network metrics and changes in craving. E-cig use resulted in increased degree centrality, nodal efficiency, and local efficiency within the executive control network (ECN), while causing a decrease in these properties within the default model network (DMN). These alterations were found to be correlated with reductions in craving, indicating a relationship between differing network topologies in the ECN and DMN and decreased craving. These findings suggest that the impact of e-cig usage on network topologies observed in male smokers resembles the effects observed with traditional cigarettes and other forms of nicotine delivery, providing valuable insights into their addictive potential and effectiveness as aids for smoking cessation.

Muscle oxygenation and pain in different types of temporomandibular disorders.

OBJECTIVES: Studies exploring variations in peripheral muscle oxygenation and pressure pain thresholds (PPT) of masticatory muscles in individuals with Temporomandibular Disorders (TMDs) are limited. The purpose of this study was to compare variations in peripheral oxygenation of the masseter muscle; PPT of the masseter and temporal muscles and correlate peripheral muscle oxygenation and PPT of the masseter muscle in individuals with different types of TMDs. MATERIALS AND METHODS: Cross-sectional study involving 116 participants classified into three groups: muscle group (MG, n = 32), joint group (JG, n = 30) and muscle-joint group (MJG, n = 54). Individuals aged 26.97 ± 6.93, 68.97% female, 31,03% males were included. All participants were evaluated using the Diagnostic Criteria for Temporomandibular Disorders, Near-infrared spectroscopy (NIRS) for peripheral muscle oxygenation and pressure algometer for PPT. RESULTS: There was no difference in masseter muscle oxygenation among groups. In the masseter muscle, a weakly positive correlation was observed between PPT and variation in tissue saturation index in the MG (rho = 0.365) and JG (rho = 0.317). In addition, the MJG expressed lower PPT (p = 0.004) than JG, demonstrating that MJG had more pain in this muscle. CONCLUSIONS: MJG have lower PPT in the masseter muscle. Although the PPT is dependent on the type of TMDs, the correlation between PPT and oxygenation is weak. All TMDs groups evaluated (MG, JG, MJG) showed hemodynamic similarities of the masseter muscle. CLINICAL RELEVANCE: Understanding pain thresholds and the hemodynamic behavior of the masticatory muscles contributes to a more assertive physiotherapeutic assessment in TMDs, serving as a basis for careful and individualized interventions.

Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.

The improper storage of seeds can potentially compromise agricultural productivity, leading to reduced crop yields. Therefore, assessing seed viability before sowing is of paramount importance. Although numerous techniques exist for evaluating seed conditions, this research leveraged hyperspectral imaging (HSI) technology as an innovative, rapid, clean, and precise nondestructive testing method. The study aimed to determine the most effective classification model for watermelon seeds. Initially, purchased watermelon seeds were segregated into two groups: One underwent sterilization in a dehydrator machine at 40°C for 36 h, whereas the other batch was stored under favorable conditions. Watermelon seeds' spectral images were captured using an HSI with a charge-coupled device camera ranging from 400 to 1000 nm, and the segmented regions of all samples were measured. Preprocessing techniques and wavelength selection methods were applied to manage spectral data workload, followed by the implementation of a support vector machine (SVM) model. The initial hybrid-SVM model achieved a predictive accuracy rate of 100%, with a test set accuracy of 92.33%. Subsequently, an artificial bee colony (ABC) optimization was introduced to enhance model precision. The results indicated that, with kernel parameters (c, g) set at 13.17 and 0.01, respectively, and a runtime of 4.19328 s, the training and evaluation of the dataset achieved an accuracy rate of 100%. Hence, it was practical to utilize HSI technology combined with the PCA-ABC-SVM model to detect different watermelon seeds. As a result, these findings introduce a novel technique for accurately forecasting seed viability, intended for use in agricultural industrial multispectral imaging. PRACTICAL APPLICATION: The traditional methods for determining the condition of seeds primarily emphasize aesthetics, rely on subjective assessment, are time-consuming, and require a lot of labor. On the other hand, HSI technology as green technology was employed to alleviate the aforementioned problems. This work significantly contributes to the field of industrial multispectral imaging by enhancing the capacity to discern various types of seeds and agricultural crop products.

Hemodynamics of short-duration light-intensity physical exercise in the prefrontal cortex of children: a functional near-infrared spectroscopy study.

Identifying the types of exercise that enhance cerebral blood flow is crucial for developing exercise programs that enhance cognitive function. Nevertheless, few studies have explored the amount of light-intensity, short-duration exercises that individuals can easily perform on cerebral blood flow, particularly in children. We examined the effects of these exercises on the hemodynamics of the prefrontal cortex (PFC) using functional near-infrared spectroscopy. Participants comprised 41 children (aged 12.1 ± 1.5 years, 37% female) who engaged in seven light-intensity exercises, with each movement performed in two patterns lasting 10 or 20 s. Changes in oxygenated hemoglobin (oxy-Hb) levels at rest and during exercise were compared using analysis of covariance, with sex and age as covariates. Significant increases in oxy-Hb were observed in multiple regions of the PFC during all forms of exercise (including dynamic and twist stretching [66.6%, 8/12 regions, η2 = 0.07-0.27], hand and finger movements [75.0%, 9/12 regions, η2 = 0.07-0.16], and balance exercises (100.0%, 6/6 regions, η2 = 0.13-0.25]), except for static stretching with monotonic movements. This study implies that short-duration, light-intensity exercises, provided that they entail a certain degree of cognitive and/or physical demands, can activate the PFC and increase blood flow.

Effects of acute aerobic exercise on resting state functional connectivity of motor cortex in college students.

This study intends to inspect the effects of acute aerobic exercise (AE) on resting state functional connectivity (RSFC) in motor cortex of college students and the moderating effect of fitness level. METHODS: 20 high fitness level college students and 20 ordinary college students were recruited in public. Subjects completed 25 min of moderate- and high-intensity acute aerobic exercise respectively by a bicycle ergometer, and the motor cortex's blood oxygen signals in resting state were monitored by functional Near Infrared Spectroscopy (fNIRS, the Shimadzu portable Light NIRS, Japan) in pre- and post-test. RESULTS: At the moderate intensity level, the total mean value of RSFC pre- and post-test was significantly different in the high fitness level group (pre-test 0.62 ± 0.18, post-test 0.51 ± 0.17, t(19) = 2.61, p = 0.02, d = 0.58), but no significant change was found in the low fitness level group. At the high-intensity level, there was no significant difference in the difference of total RSFC between pre- and post-test in the high and low fitness group. According to and change trend of 190 "edges": at the moderate-intensity level, the number of difference edges in the high fitness group (d = 0.58, 23) were significantly higher than those in the low fitness group (d = 0.32, 15), while at high-intensity level, there was a reverse trend between the high fitness group (d = 0.25, 18) and the low fitness group (d = 0.39, 23). CONCLUSIONS: moderate-intensity AE can cause significant changes of RSFC in the motor cortex of college students with high fitness, while high fitness has a moderating effect on the relationship between exercise intensity and RSFC. RSFC of people with high fitness is more likely to be affected by AE and show a wider range of changes.

Near-infrared nanosensors enable optical imaging of oxytocin with selectivity over vasopressin in acute mouse brain slices.

Oxytocin plays a critical role in regulating social behaviors, yet our understanding of its function in both neurological health and disease remains incomplete. Real-time oxytocin imaging probes with spatiotemporal resolution relevant to its endogenous signaling are required to fully elucidate oxytocin's role in the brain. Herein, we describe a near-infrared oxytocin nanosensor (nIROXT), a synthetic probe capable of imaging oxytocin in the brain without interference from its structural analogue, vasopressin. nIROXT leverages the inherent tissue-transparent fluorescence of single-walled carbon nanotubes (SWCNT) and the molecular recognition capacity of an oxytocin receptor peptide fragment to selectively and reversibly image oxytocin. We employ these nanosensors to monitor electrically stimulated oxytocin release in brain tissue, revealing oxytocin release sites with a median size of 3 µm in the paraventricular nucleus of C57BL/6 mice, which putatively represents the spatial diffusion of oxytocin from its point of release. These data demonstrate that covalent SWCNT constructs, such as nIROXT, are powerful optical tools that can be leveraged to measure neuropeptide release in brain tissue.

Exploring the dynamics of prefrontal cortex in the interaction between orienteering experience and cognitive performance by fNIRS.

Sporting experience plays a pivotal role in shaping exercise habits, with a mutually reinforcing relationship that enhances cognitive performance. The acknowledged plasticity of cognition driven by sports necessitates a comprehensive examination. Hence, this study delves into the dynamic intricacies of the prefrontal cortex, exploring the impact of orienteering experience on cognitive performance. Our findings contribute empirical evidence regarding the functional activation of specific brain regions bridging the nexus between experiential factors and cognitive capabilities. In this cross-sectional study, a cohort of forty-nine athletes was enrolled to meticulously examine behavioral variances and prefrontal cortex dynamics among orienteering athletes of varying experience levels across diverse non-specialized scenarios. These investigations involved the utilization of functional near-infrared spectroscopy (fNIRS) to detect alterations in oxygenated hemoglobin (HbO2). The high-experience expert group exhibited neurological efficiency, demonstrating significantly diminished brain activation in the dorsolateral prefrontal, left ventral lateral prefrontal, and right orbitofrontal regions compared to the low-experience group. Within the low-experience novice group, superior performance in the spatial memory task was observed compared to the mental rotation task, with consistently lower reaction times across all conditions compared to the high-experience group. Notably, cerebral blood oxygenation activation exhibited a significant reduction in the high-experience expert group compared to the low-experience novice group, irrespective of task type. The dorsolateral prefrontal lobe exhibited activation upon task onset, irrespective of experience level. Correct rates in the spatial memory task were consistently higher than those in the mental rotation task, while brain region activation was significantly greater during the mental rotation task than the spatial memory task." This study elucidates disparities in prefrontal cortex dynamics between highly seasoned experts and neophyte novices, showcasing a cognitive edge within the highly experienced cohort and a spatial memory advantage in the inexperienced group. Our findings contribute to the comprehension of the neural mechanisms that underlie the observed cognitive advantage and provide insights into the forebrain resources mobilized by orienteering experience during spatial cognitive tasks."

Prefrontal cortex oxygenation during a mentally fatiguing task in normoxia and hypoxia.

Mental fatigue (MF) and hypoxia impair cognitive performance through changes in brain hemodynamics. We want to elucidate the role of prefrontal cortex (PFC)-oxygenation in MF. Twelve participants (22.9 ± 3.5 years) completed four experimental trials, (1) MF in (normobaric) hypoxia (MF_HYP) (3.800 m; 13.5%O2), (2) MF in normoxia (MF_NOR) (98 m; 21.0%O2), (3) Control task in HYP (CON_HYP), (4) Control in NOR (CON_NOR). Participants performed a 2-back task, Digit Symbol Substitution test and Psychomotor Vigilance task before and after a 60-min Stroop task or an emotionally neutral documentary. Brain oxygenation was measured through functional Near Infrared Spectroscopy. Subjective feelings of MF and physiological measures (heart rate, oxygen saturation, blood glucose and hemoglobin) were recorded. The Stroop task resulted in increased subjective feelings of MF compared to watching the documentary. 2-back accuracy was lower post task compared to pre task in MF_NOR and CON_NOR, while no differences were found in the other cognitive tasks. The fraction of inspired oxygen did not impact feelings of MF. Although performing the Stroop resulted in higher subjective feelings of MF, hypoxia had no effect on the severity of self-reported MF. Additionally, this study could not provide evidence for a role of oxygenation of the PFC in the build-up of MF.

Activation changes in patients with post-stroke cognitive impairment receiving intermittent theta burst stimulation: A functional near-infrared spectroscopy study.

BACKGROUND: Intermittent theta burst stimulation (iTBS) has demonstrated efficacy in patients with cognitive impairment. However, activation patterns and mechanisms of iTBS for post-stroke cognitive impairment (PSCI) remain insufficiently understood. OBJECTIVE: To investigate the activation patterns and potential benefits of using iTBS in patients with PSCI. METHODS: A total of forty-four patients with PSCI were enrolled and divided into an iTBS group (iTBS and cognitive training) or a control group (cognitive training alone). Outcomes were assessed based on the activation in functional near-infrared spectroscopy (fNIRS), as well as Loewenstein Occupational Therapy Cognitive Assessment (LOTCA) and the modified Barthel Index (MBI). RESULTS: Thirty-eight patients completed the interventions and assessments. Increased cortical activation was observed in the iTBS group after the interventions, including the right superior temporal gyrus (STG), left frontopolar cortex (FPC) and left orbitofrontal cortex (OFC). Both groups showed significant improvements in LOTCA and MBI after the interventions (p < 0.05). Furthermore, the iTBS group augmented superior improvement in the total score of MBI and LOTCA compared to the control group, especially in visuomotor organization and thinking operations (p < 0.05). CONCLUSION: iTBS altered activation patterns and improved cognitive function in patients with PSCI. The activation induced by iTBS may contribute to the improvement of cognitive function.

NIR-II Fluorescent Probes for Fluorescence-Imaging-Guided Tumor Surgery.

Second near-infrared (NIR-II) fluorescence imaging is the most advanced imaging fidelity method with extraordinary penetration depth, signal-to-background ratio, biocompatibility, and targeting ability. It is currently booming in the medical realm to diagnose tumors and is being widely applied for fluorescence-imaging-guided tumor surgery. To efficiently execute this modern imaging modality, scientists have designed various probes capable of showing fluorescence in the NIR-II window. Here, we update the state-of-the-art NIR-II fluorescent probes in the most recent literature, including indocyanine green, NIR-II emissive cyanine dyes, BODIPY probes, aggregation-induced emission fluorophores, conjugated polymers, donor-acceptor-donor dyes, carbon nanotubes, and quantum dots for imaging-guided tumor surgery. Furthermore, we point out that the new materials with fluorescence in NIR-III and higher wavelength range to further optimize the imaging results in the medical realm are a new challenge for the scientific world. In general, we hope this review will serve as a handbook for researchers and students who have an interest in developing and applying fluorescent probes for NIR-II fluorescence-imaging-guided surgery and that it will expedite the clinical translation of the probes from bench to bedside.

Impact of repetitive transcranial magnetic stimulation on cortical activity: a systematic review and meta-analysis utilizing functional near-infrared spectroscopy evaluation.

BACKGROUND: Repeated transcranial magnetic stimulation (rTMS) could induce alterations in cortical excitability and promote neuroplasticity. To precisely quantify these effects, functional near-infrared spectroscopy (fNIRS), an optical neuroimaging modality adept at detecting changes in cortical hemodynamic responses, has been employed concurrently alongside rTMS to measure and tailor the impact of diverse rTMS protocols on the brain cortex. OBJECTIVE: This systematic review and meta-analysis aimed to elucidate the effects of rTMS on cortical hemodynamic responses over the primary motor cortex (M1) as detected by fNIRS. METHODS: Original articles that utilized rTMS to stimulate the M1 cortex in combination with fNIRS for the assessment of cortical activity were systematically searched across the PubMed, Embase, and Scopus databases. The search encompassed records from the inception of these databases up until April, 2024. The assessment for risk of bias was also conducted. A meta-analysis was also conducted in studies with extractable raw data. RESULTS: Among 312 studies, 14 articles were eligible for qualitative review. 7 studies were eligible for meta-analysis. A variety of rTMS protocols was employed on M1 cortex. In inhibitory rTMS, multiple studies observed a reduction in the concentration of oxygenated hemoglobin [HbO] at the ipsilateral M1, contrasted by an elevation at the contralateral M1. Meta-analysis also corroborated this consistent trend. Nevertheless, certain investigations unveiled diminished [HbO] in bilateral M1. Several studies also depicted intricate inhibitory or excitatory interplay among distinct cortical regions. CONCLUSION: Diverse rTMS protocols led to varied patterns of cortical activity detected by fNIRS. Meta-analysis revealed a trend of increasing [HbO] in the contralateral cortices and decreasing [HbO] in the ipsilateral cortices following low frequency inhibitory rTMS. However, due to the heterogeneity between studies, further research is necessary to comprehensively understand rTMS-induced alterations in brain activity.

Investigation of hemispheric asymmetry in Alzheimer's disease patients during resting state revealed BY fNIRS.

Alzheimer's disease (AD) is characterized by the gradual deterioration of brain structures and changes in hemispheric asymmetry. Meanwhile, healthy aging is associated with a decrease in functional hemispheric asymmetry. In this study, functional connectivity analysis was used to compare the functional hemispheric asymmetry in eyes-open resting-state fNIRS data of 16 healthy elderly controls (mean age: 60.4 years, MMSE (Mini-Mental State Examination): 27.3 ± 2.52) and 14 Alzheimer's patients (mean age: 73.8 years, MMSE: 22 ± 4.32). Increased interhemispheric functional connectivity was found in the premotor cortex, supplementary motor cortex, primary motor cortex, inferior parietal cortex, primary somatosensory cortex, and supramarginal gyrus in the control group compared to the AD group. The study revealed that the control group had stronger interhemispheric connectivity, leading to a more significant decrease in hemispheric asymmetry than the AD group. The results show that there is a difference in interhemispheric functional connections at rest between the Alzheimer's group and the control group, suggesting that functional hemispheric asymmetry continues in Alzheimer's patients.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging During Rehabilitation Following Stroke: A Review.

Stroke is a cerebrovascular disease that impairs blood supply to localized brain tissue regions due to various causes. This leads to ischemic and hypoxic lesions, necrosis of the brain tissue, and a variety of functional disorders. Abnormal cortical activation and functional connectivity occur in the brain after a stroke, but the activation patterns and functional reorganization are not well understood. Rehabilitation interventions can enhance functional recovery in stroke patients. However, clinicians require objective measures to support their practice, as outcome measures for functional recovery are based on scale scores. Furthermore, the most effective rehabilitation measures for treating patients are yet to be investigated. Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method that detects changes in cerebral hemodynamics during task performance. It is widely used in neurological research and clinical practice due to its safety, portability, high motion tolerance, and low cost. This paper briefly introduces the imaging principle and the advantages and disadvantages of fNIRS to summarize the application of fNIRS in post-stroke rehabilitation.

A near-infrared plasmonic biosensor for detection of morphine and codeine in biological samples based on the end-to-end assembly of modified gold nanorods.

The analytical determination of opiates in biological samples is a critical mission and remains a challenge for almost all judicial and clinical drug testing panels due to their high abuse potential. Based on the high sensitivity of the longitudinal surface plasmon resonance (LSPR) peak of gold nanorods (AuNRs), we successfully developed a novel and simple refractive index sensing platform for detection of morphine (MOR) and codeine (COD) by means of 2-amino-5-mercapto-1,3,4-thiadiazole functionalized gold nanorods (AMTD-AuNRs) in aqueous solution, which is, to the best of our knowledge, the first report on the assay of MOR and COD using AuNRs. AMTD molecules strongly anchor onto the tips of AuNRs via the mercapto group and subsequent hydrogen-bonding interactions between AMTD and the analytes induced end-to-end chain assembly of AuNRs and a consequent decrease of the LSPR absorption band at 850 nm along with a bathochromic shift and emergence of a new hybridized plasmon mode at 1050 nm which was characterized using a Vis-NIR spectrophotometer. After systematic optimization, the absorbance ratio (A1050/A850) was proportional to the concentration of MOR in the ranges of 0.08-5 µM and 0.2-8 µM for COD without any significant effect from possible interferents. Furthermore, detection limits of 40 and 62 nM were achieved for MOR and COD, respectively, which are much lower than the cut-off level of 2000 ng mL-1 for opiates in urine samples set by the Substance and Abuse Mental Health Services Administration (SAMHSA). Eventually, as proof-of-applicability, human urine and blood serum samples spiked with MOR and COD were analyzed and excellent recoveries ranging from 94.4 to 108.9% were obtained, demonstrating the successful applicability of the designed refractive index probe in real biological specimens.

What is the most effective analytical method for quantification and identification of microplastics in contaminated soils?

The increasing concern over microplastics (MPs) contamination in agricultural soils due to excessive plastic use is a worldwide concern. The objective of this study was to determine which analytical technique is most effective for the analysis of MPs in agricultural soils. Near-infrared spectroscopy (NIR), scanning electron microscopy (SEM), multispectral analysis, and X-ray diffraction were used to analyze sections of clay soil containing varying percentages of virgin white MPs from 0 to 100%. X-ray analysis only detected MPs at high concentrations (20%). However, NIR at 2.300 nm and multispectral analysis at 395 nm demonstrated greater accuracy and sensitivity in distinguishing between all MPs levels. SEM revealed that MPs have an amorphous structure that is distinct from crystalline soil, potentially influencing their interactions with other soil constituents. These findings highlight the value of NIR and multispectral analysis in accurately identifying and measuring MPs in soil. Efficient management plans rely on increased awareness of MPs' environmental impact.

On-farm NIR sensor for milk analysis: Exploitation of bias monitoring and bias correction.

Long-term studies have shown a bias drift over time in the prediction performance of near-infrared spectroscopy measurement systems. This bias drift generally requires extra laboratory reference measurements to detect and correct for this bias. Since these reference measurements are expensive and time consuming, there is a need for advanced methodologies for bias drift monitoring and correction without the need for taking extra samples. In this study, we propose and validate a method to monitor the bias drift and two methods to tackle it. The first method requires no extra measurements and uses a modified version of Partial Least Squares Regression to estimate and correct the bias. This method is based on the assumption that the mean concentration of the predicted component remains constant over time. The second method uses regular bulk milk measurements as a reference for bias correction. This method compares the measured concentrations of the bulk milk to the volume-weighted average concentrations of individual milk samples predicted by the sensor. Any difference between the actual and calculated bulk milk composition is then used to perform a bias correction on the predictions by the sensor system. The effectiveness of these methods to improve the component prediction was evaluated on data originating from a custom-built sensor that automatically measures the NIR reflectance and transmittance spectra of raw milk on the farm. We evaluate the practical use case where models for predicting the milk composition are trained upon installation of the sensor at the farm, and later used to predict the composition of subsequent samples over a period of more than 6 months. The effectiveness of the fully unsupervised method was confirmed when the mean concentration of the milk samples remained constant, while the effectiveness reduced when this was not the case. The bulk milk correction method was effective when all relevant samples for the component were measured by the sensor and included in the analyzed bulk milk, but is less effective when samples included in the bulk which are not measured by the sensor system. When the necessary conditions are met, these methods can be used to extend the lifetime of deployed prediction models by significantly reducing the bias on the predicted values.

Differentiation of Listeria monocytogenes serotypes using near infrared hyperspectral imaging.

Among the severe foodborne illnesses, listeriosis resulting from the pathogen Listeria monocytogenes exhibits one of the highest fatality rates. This study investigated the application of near infrared hyperspectral imaging (NIR-HSI) for the classification of three L. monocytogenes serotypes namely serotype 4b, 1/2a and 1/2c. The bacteria were cultured on Brain Heart Infusion agar, and NIR hyperspectral images were captured in the spectral range 900-2500 nm. Different pre-processing methods were applied to the raw spectra and principal component analysis was used for data exploration. Classification was achieved with partial least squares discriminant analysis (PLS-DA). The PLS-DA results revealed classification accuracies exceeding 80 % for all the bacterial serotypes for both training and test set data. Based on validation data, sensitivity values for L. monocytogenes serotype 4b, 1/2a and 1/2c were 0.69, 0.80 and 0.98, respectively when using full wavelength data. The reduced wavelength model had sensitivity values of 0.65, 0.85 and 0.98 for serotype 4b, 1/2a and 1/2c, respectively. The most relevant bands for serotype discrimination were identified to be around 1490 nm and 1580-1690 nm based on both principal component loadings and variable importance in projection scores. The outcomes of this study demonstrate the feasibility of utilizing NIR-HSI for detecting and classifying L. monocytogenes serotypes on growth media.

Data fusion of near-infrared and mid-infrared spectroscopy for rapid origin identification and quality evaluation of Lonicerae japonicae flos.

A data fusion strategy based on near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were developed for rapid origin identification and quality evaluation of Lonicerae japonicae flos (LJF). A high-level data fusion for origin identification was formed using the soft voting method. This data fusion model achieved accuracy, log-loss value and Kappa value of 95.5%, 0.347 and 0.910 on the prediction set. The spectral data were converted to liquid chromatography data using a data fusion model constructed by the weighted average algorithm. The Euclidean distance and adjusted cosine similarity were used to evaluate the similarity between the converted and the real chromatographic data, with results of 247.990 and 0.996, respectively. The data fusion models all performed better than the models constructed using single data. This indicates that multispectral data fusion techniques have a wide range of application prospects and practical value in the quality control of natural products such as LJF.

Rapid-response near-infrared fluorescence probe for colorimetric detection of HClO and its applications in environmental monitoring and biological imaging.

As a crucial endogenous reactive oxygen species, hypochlorous acid (HClO) plays an indispensable role in numerous physiological and pathological processes. Additionally, it serves as a biomarker closely associated with inflammation and liver injury. The utilization of near-infrared fluorescence probes has surged in recent years for live biological imaging, owing to their minimal tissue damage and potent tissue penetration capabilities. In this work, a novel near-infrared fluorescence probe MB-HPD was synthesized to sensitively detect HClO. Probe MB-HPD exhibits remarkable selectivity, high sensitivity (14.3 nM), and rapid response towards HClO (20 s). Probe MB-HPD has demonstrated successful application in the imaging of HClO within cells and zebrafish. Remarkably, it has proven to be effective for detecting HClO within environmental samples, as well as imaging HClO in mice models of arthritis and APAP-induced liver injury. These findings indicate the broad applicability of probe MB-HPD, offering a promising avenue for designing highly selective near-infrared fluorescence probes suitable for real-time HClO monitoring.

Rapid non-destructive monitoring and quality assessment of the fumigation process of Shanxi aged vinegar based on Vis-NIR hyperspectral imaging combined with multiple chemometric algorithms.

The quality of the grains during the fumigation process can significantly affect the flavour and nutritional value of Shanxi aged vinegar (SAV). Hyperspectral imaging (HSI) was used to monitor the extent of fumigated grains, and it was combined with chemometrics to quantitatively predict three key physicochemical constituents: moisture content (MC), total acid (TA) and amino acid nitrogen (AAN). The noise reduction effects of five spectral preprocessing methods were compared, followed by the screening of optimal wavelengths using competitive adaptive reweighted sampling. Support vector machine classification was employed to establish a model for discriminating fumigated grains, and the best recognition accuracy reached 100%. Furthermore, the results of partial least squares regression slightly outperformed support vector machine regression, with correlation coefficient for prediction (Rp) of 0.9697, 0.9716, and 0.9098 for MC, TA, and AAN, respectively. The study demonstrates that HSI can be employed for rapid non-destructive monitoring and quality assessment of the fumigation process in SAV.