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In this paper, a temperature measurement system with NTC (Negative Temperature Coefficient) thermistors was designed. An MCU (Micro Control Unit) primarily operates by converting the voltage value collected by an ADC (Analog-to-Digital Converter) into the resistance value. The temperature value is then calculated, and a DAC (Digital-to-Analog Converter) outputs a current of 4 to 20 mA that is linearly related to the temperature value. The nonlinear characteristics of NTC thermistors pose a challenging problem. The nonlinear characteristics of NTC thermistors were to a great extent solved by using a resistance ratio model. The high precision of the NTC thermistor is obtained by fitting it with the Hoge equation. The results of actual measurements suggest that each module works properly, and the temperature measurement accuracy of 0.067 °C in the range from −40 °C to 120 °C has been achieved. The uncertainty of the output current is analyzed and calculated with the uncertainty of 0.0014 mA. This type of system has broad potential applications in industry fields such as the petrochemical industry.

To enrich the technical means of quality control of Torreya, the qualitative analysis model of storage time and conditions of Torreya grandis was established by near infrared spectroscopy. Additionally, a quantitative analysis model for protein and fat content of Torreya was established using chemometric methods. After preprocessing the spectra and selecting feature wavelengths, a convolutional neural network (CNN) model based on genetic algorithm (GA) and multiplicative scatter correction (MSC) algorithm was developed, achieving an identification accuracy of 99.2% in distinguishing Torreya with different storage times and conditions. Furthermore, partial least squares (PLS), radial basis function neural network (RBF), and extreme learning machine (ELM) models were established and compared. Competitive adaptive reweighted sampling (CARS) was used as a spectral feature selection method, resulting in 41 and 56 selected features for protein and fat content, respectively, significantly improving computational efficiency. The results showed that the D2-CARS-PLS model with second derivative (D2) preprocessing and CARS method was the optimal model, achieving good prediction performance for protein and fat content of Torreya with coefficients of determination (R2) of 0.977 and 0.984, respectively. The findings demonstrated the potential of near-infrared spectroscopy technology for rapid and non-destructive detection of Torreya nut quality, providing a reliable analytical method for Torreya nut quality assessment.

In the tumor microenvironment, transforming growth factor β (TGF-β) contributes to neutrophil development toward a pro-tumor phenotype; however, the molecular mechanism by which this occurs remains unclear. Therefore, we explored the role of TGF-β in N2 neutrophil polarization and the subsequent effect on oral leukoplakia/oral squamous cell carcinoma (OL/OSCC) cells. The TGF-β-stimulated N2 culture supernatant promoted the proliferation of OL/OSCC cells. Analysis of the N2 supernatant using a cytokine array revealed significantly upregulated expression of soluble forms of receptor for advanced glycation end products (RAGE). TGF-β was found to induce the expression of RAGE and matrix metalloproteinase 9 (MMP9) in neutrophils. Additionally, MMP9 treatment could cleave RAGE and promote its secretion by neutrophils, thereby promoting cancer cell proliferation. In an established mouse model of oral cancer using 4NQO, RAGE were found to be highly expressed. Importantly, neutralizing antibodies against RAGE significantly inhibited oral cancer progression in mice. Analysis of clinical data from the TCGA database revealed that RAGE and MMP9 are highly expressed in head and neck squamous cell carcinoma (HNSCC) and that RAGE expression is significantly positively correlated with neutrophil infiltration. In conclusion, our results indicate that TGF-β promotes N2 neutrophil polarization through upregulation of soluble RAGE (sRAGE) secretion, leading to OSCC cell proliferation. Our findings also suggest that the sRAGE formed during N2 polarization may be a potential therapeutic target in OL/OSCC.