Early detection of gray blight in tea leaves and rapid screening of resistance varieties by hyperspectral imaging technology.

BACKGROUND: Gray blight (GB) is a significant disease of tea leaves, posing a severe threat to both the yield and quality. In this study, the process of leaf infection by a pathogenic isolate of the GB disease (DDZ-6) was simulated. Hyperspectral images of normal leaves, infected leaves without symptoms, and infected leaves with mild and moderate symptoms were collected. Combining convolution neural network (CNN), long short-term memory (LSTM), and support vector machine (SVM) algorithms, the early detection model of GB disease, and the rapid screening model of resistant varieties were established. The generality of this method was verified by collecting datasets under field conditions. RESULTS: The visible red-light band demonstrated a pronounced responsiveness to GB disease, with three sensitive bands identified through rigorous screening processes utilizing uninformative variable elimination (UVE), competitive adaptive reweighted sampling (CARS), and the successive projections algorithm (SPA). The 693, 727, and 766 nm bands emerged as highly sensitive indicators of GB. Under ideal conditions, the CARS-LSTM model excelled in early detection of GB, achieving an accuracy of 92.6%. However, under field conditions, the combination of 693 and 727 nm bands integrated with a CNN provided the most effective early detection model, attaining an accuracy of 87.8%. For screening tea varieties resistant to GB, the SPA-LSTM model excelled, achieving an accuracy of 82.9%. CONCLUSION: This study provides a core algorithm for a GB disease instrument with detection capabilities, which is of great importance for the early prevention of GB disease in tea plantations. © 2024 Society of Chemical Industry.

A ratiometric fluorescent dark box and smartphone integrated portable sensing platform based on hydrogen bonding induction for on-site determination of enrofloxacin.

Enrofloxacin (ENR) residues in animal-derived food and water threaten human health. Simple, low-cost and on-site detection methods are urgently needed. Blue emitting carbon quantum dots (CQDs) and orange rhodamine B (RhB) were used as recognition and reference signals, respectively, to construct a ratiometric fluorescence sensor. After the addition of ENR, the color of the sensor changed from orange to blue because hydrogen bonding induced a considerable increase in CQDs fluorescence. Based on this mechanism, a simple and low cost on-site portable sensing platform was constructed, which integrated a stable UV light strip and a smartphone with voice-controlled phototaking function and an RGB app. The t-test results of spiked ENR recoveries for diluted milk, honey and drinking water revealed no significant differences between the ratiometric fluorescent sensor and portable sensing platform. Thus, this portable sensing platform provides a novel strategy for on-site quantification of quinolone antibiotics in foodstuffs and environmental water.

Mitochondria-targeted sonodynamic modulation of neuroinflammation to protect against myocardial ischemia‒reperfusion injury.

Sympathetic hyperactivation and inflammatory responses are the main causes of myocardial ischemia‒reperfusion (I/R) injury and myocardial I/R-related ventricular arrhythmias (VAs). Previous studies have demonstrated that light-emitting diodes (LEDs) could modulate post-I/R neuroinflammation, thus providing protection against myocardial I/R injury. Nevertheless, further applications of LEDs are constrained due to the low penetration depth (<1 cm) and potential phototoxicity. Low-intensity focused ultrasound (LIFU), an emerging noninvasive neuromodulation strategy with deeper penetration depth (∼10 cm), has been confirmed to modulate sympathetic nerve activity and inflammatory responses. Sonodynamic therapy (SDT), which combines LIFU with sonosensitizers, confers additional advantages, including superior therapeutic efficacy, precise localization of neuronal modulation and negligible side effects. Herein, LIFU and SDT were introduced to modulate post-myocardial I/R neuroinflammation to protect against myocardial I/R injury. The results indicated that LIFU and SDT inhibited sympathetic neural activity, suppressed the activation of astrocytes and microglia, and promoted microglial polarization towards the M2 phenotype, thereby attenuating myocardial I/R injury and preventing I/R-related malignant VAs. These insights suggest that LIFU and SDT inspire a noninvasive and efficient neuroinflammatory modulation strategy with great clinical translation potential thus benefiting more patients with myocardial I/R in the future. STATEMENT OF SIGNIFICANCE: Myocardial ischemia-reperfusion (I/R) may cause I/R injury and I/R-induced ventricular arrhythmias. Sympathetic hyperactivation and inflammatory response play an adverse effect in myocardial I/R injury. Previous studies have shown that light emitting diode (LED) can regulate I/R-induced neuroinflammation, thus playing a myocardial protective role. However, due to the low penetration depth and potential phototoxicity of LED, it is difficult to achieve clinical translation. Herein, we introduced sonodynamic modulation of neuroinflammation to protect against myocardial I/R injury, based on mitochondria-targeted nanosonosensitizers (CCNU980 NPs). We demonstrated that sonodynamic modulation could promote microglial autophagy, thereby preventing myocardial I/R injury and I/R-induced ventricular arrhythmias. This is the first example of sonodynamic modulation of myocardial I/R-induced neuroinflammation, providing a novel strategy for clinical translation.