Modeling and Optimization of Artificial Neural Network and Response Surface Methodology in Ultra-high-Pressure Extraction of Artemisia argyi Levl. et Vant and its antifungal activity

Using terahertz spectroscopy to quantify bioactive flavonoids in Moxa Wool as predictor of rheumatoid arthritis treatment outcomes

BACKGROUND

Moxibustion, a traditional Chinese medicine practice, employs Moxa Wool, derived from Artemisia argyi. Flavonoids, the key pharmacological constituents in Moxa Wool, are known for their anti-inflammatory and analgesic properties. The purity of Moxa Wool, particularly its flavonoid content, directly influences the efficacy of moxibustion treatments. However, quantifying these bioactive flavonoids accurately and non-destructively has been a challenge.

PURPOSE

This study introduces terahertz spectroscopy as a non-destructive optical detection method for qualitative detection and quantitative analysis of flavonoids in Moxa Wool. By establishing a mathematical model between spectral signals and clinical efficacy, a reliable correlation between flavonoid concentration and the therapeutic effect of moxibustion can be established, providing a potential predictive model for the treatment outcomes of rheumatoid arthritis.

STUDY DESIGN

We adopted terahertz spectroscopy technology and combined it with terahertz metamaterial biosensors to achieve rapid, efficient, and non-destructive testing of the quality of Moxa Wool. This method reduces the detection time from hours to minutes while lowering the sample detection limit, overcoming the limitations of traditional detection methods in pharmacological research.

METHODS

Through terahertz metamaterial biosensors, rapid detection of the purity of Moxa Wool has been achieved. A combination of molecular simulation and terahertz spectroscopy was used to quantitatively analyze the flavonoid content in different purities of Moxa Wool. To ensure accuracy, the quantitative results of flavonoids obtained by terahertz spectroscopy were validated using high-performance liquid chromatography (HPLC). In addition, moxibustion treatment was performed on rats with rheumatoid arthritis using Moxa Wool, and medical indicator information was recorded. A mathematical analysis model was established to evaluate the correlation between flavonoid content and analgesic and anti-inflammatory effects.

RESULTS

Terahertz spectroscopy analysis shows that there is a direct correlation between the flavonoid content in moxibustion and the absorption peak intensity. The maximum R2 in the model analysis is 0.98, indicating a high accuracy in predicting the purity of Moxa Wool. These results were also validated by HPLC. In a rat model, the purity of 30:1 Moxa Wool samples showed a 50 % decrease in TNF-α, IL-1β, and IL-6 levels during treatment compared to low-purity samples, significantly reducing inflammation markers and pain symptoms. Meanwhile, The PLS prediction model established a correlation between terahertz-detected flavonoid levels and treatment outcomes (PWL and IL-1β). The maximum R2 in the model is 0.91, indicating a high correlation between flavonoid levels and the anti-inflammatory and analgesic effects of moxibustion treatment.

CONCLUSION

This study not only demonstrates the effectiveness of terahertz spectroscopy in the pharmacological quantification of bioactive compounds but also establishes a novel predictive model for the efficacy of moxibustion in rheumatoid arthritis treatment. It underscores the potential of integrating traditional medicine insights with advanced technology to enhance therapeutic strategies in pharmacology.

Enhanced production of acetic acid through bioprocess optimization employing response surface methodology and artificial neural network

In this study, acetic acid bacteria (AAB) are isolated from fruit waste and cow dung on the basis of acetic acid production potential. The AAB were identified based on halo-zones produced in the Glucose-Yeast extract-Calcium carbonate (GYC media) agar plates. In the current study, maximum acetic acid yield is reported to be 4.88 g/100 ml from the bacterial strain isolated from apple waste. With the help of RSM (Response surface methodology) tool, glucose and ethanol concentration and incubation period, as independent variable showed the significant effect of glucose concentration and incubation period and their interaction on the AA yield. A hypothetical model of artificial neural network (ANN) was also used to compare the predicted value from RSM. Acetic acid production through the biological route can be the sustainable and clean approach to utilizing food waste in circular economy approach.

Optimization of High-Pressure-Assisted Extraction of Cadmium and Lead from Kelp (Laminaria japonica) Using Response Surface Methodology

Kelp (Laminaria japonica) is a popular and nutritious sea vegetable, but it has a strong biosorption capacity for heavy metals. The high content of cadmium (Cd) and lead (Pb) is a threat to the quality of kelp. The objective of this study was to investigate the effects of high-pressure-assisted extraction (HPAE) conditions on Cd and Pb removal efficiency from kelp. Pressure intensity (0.1-200 MPa), the number of HPAE cycles (one to five) and acetic acid concentration (0-10%) were optimized using response surface methodology. The pressure intensity had the most significant positive effects on Cd and Pb removal efficiency, while the correlation between acetic acid concentration and removal efficiency was positive for Cd and negative for Pb. The optimum conditions for the removal of Cd and Pb were attained at 188 MPa, with four cycles and with an acetic acid concentration of 0%. At optimum conditions, the experimental values of removal efficiency were 61.14% (Cd) and 70.97% (Pb), and this was consistent with the predicted value, confirming the validity of the predictive model.

Optimization of the decolorization conditions of Rose Bengal by using Aspergillus niger TF05 and a decolorization mechanism

Aspergillus niger TF05 was applied to decolorize Rose Bengal dye. The effects of carbon source, nitrogen source, metal ion and spore concentration on Rose Bengal treatment with A. niger TF05 were studied. A Plackett–Burman design (PBD) and a uniform design (UD) were used to optimize the decolorization conditions of A. niger TF05 and enhance its decolorization effect. The mechanism of Rose Bengal decolorization by A. niger TF05 was examined by analysing degradation products via UV–visible light spectroscopy, IR spectroscopy and GC-MS. The best decolorization effect was achieved in the single factor test with glucose and ammonium chloride as carbon and nitrogen sources, respectively. Mg²⁺ was an essential ion that could improve the mould ball state and adsorption efficiency if the spore concentration was maintained at 10⁶ spores ml^–1. The optimal decolorization conditions obtained using the PBD and UD methods were 11.5 g l⁻¹ glucose, 6.5 g l⁻¹ ammonium chloride, 0.4 g l⁻¹ magnesium sulphate, pH 5.8, 28 °C, 140 r.p.m. rotational speed, 0.18 g l⁻¹ dye concentration, 0.5 ml of inocula and 120 h decolorization time. Under these conditions, the maximum decolorization rate was 106%. Spectral analysis suggested that the absorption peak of the product changed clearly after decolorization; GC-MS analysis revealed that the intermediate product tetrachlorophthalic anhydride formed after decolorization. The combined use of the PBD and UD methods can optimize multi-factor experiments. A. niger TF05 decolorized Rose Bengal during intracellular enzymatic degradation after adsorption.

Optimization of Total Monomeric Anthocyanin (TMA) and Total Phenolic Content (TPC) Extractions from Red Cabbage (Brassica oleracea var. capitata f. rubra): Response Surface Methodology versus Artificial Neural Network

The aim of this study was to investigate the influence of solvent type, ultrasonic frequency, extraction time and temperature on the total phenolic content (TPC) and total monomeric anthocyanin (TMA) extraction from red cabbage (Brassica oleracea var. capitata f. rubra) using the response surface methodology (RSM) and artificial neural network. The red cabbage has been used as TPC and TMA sources due to its low cost and highly availability during all the year. The experimental data for the extraction of TPC and TMA were fitted to second-order polynomial models with higher regression coefficients than 0.902. The optimal conditions (in dry matter) for highest TPC extraction (7,049.5 mg gallic acid equivalent/kg) are: methanol as solvent, 3.60 kHz ultrasonic frequency at 67.6 °C for 59.6 min, while for TMA optimal extraction (0.3 mg/g) 2-propanol was used as solvent, 45 kHz ultrasonic frequency at 69.2 °C for 20.80 min. The artificial neural network (ANN) is better than RSM to predict the TPC and TMA extraction from red cabbage.

DNA Barcode for Identifying Folium Artemisiae Argyi from Counterfeits

Folium Artemisiae Argyi is an important herb in traditional Chinese medicine. It is commonly used in moxibustion, medicine, etc. However, identifying Artemisia argyi is difficult because this herb exhibits similar morphological characteristics to closely related species and counterfeits. To verify the applicability of DNA barcoding, ITS2 and psbA-trnH were used to identify A. argyi from 15 closely related species and counterfeits. Results indicated that total DNA was easily extracted from all the samples and that both ITS2 and psbA-trnH fragments can be easily amplified. ITS2 was a more ideal barcode than psbA-trnH and ITS2+psbA-trnH to identify A. argyi from closely related species and counterfeits on the basis of sequence character, genetic distance, and tree methods. The sequence length was 225 bp for the 56 ITS2 sequences of A. argyi, and no variable site was detected. For the ITS2 sequences, A. capillaris, A. anomala, A. annua, A. igniaria, A. maximowicziana, A. princeps, Dendranthema vestitum, and D. indicum had single nucleotide polymorphisms (SNPs). The intraspecific Kimura 2-Parameter distance was zero, which is lower than the minimum interspecific distance (0.005). A. argyi, the closely related species, and counterfeits, except for Artemisia maximowicziana and Artemisia sieversiana, were separated into pairs of divergent clusters by using the neighbor joining, maximum parsimony, and maximum likelihood tree methods. Thus, the ITS2 sequence was an ideal barcode to identify A. argyi from closely related species and counterfeits to ensure the safe use of this plant.