The Maillard reaction is a complex process in which amine compounds such as amino acids， peptides， and proteins undergo condensation， polymerization， and other reactions with carbonyl compounds such as reducing sugars， ketones， and aldehydes at room temperature or under heating conditions， ultimately producing substances such as melanoidins and aromatic compounds. The processing of traditional Chinese medicine（TCM） often involves heating and the addition of auxiliary materials， providing complete conditions for the occurrence of the Maillard reaction. The Maillard reaction is affected by various factors such as temperature， pH， moisture， substrate， reaction time and pressure， the progress of the reaction also affected by different processing technologies of TCM and the addition of different excipients. The Maillard reaction involves multiple substances， most of which have significant physiological activity or toxicity， affecting the efficacy and pharmacological effects of TCM. It can also produce various flavor substances and browning products that change the flavor and color of TCM. The Maillard reaction mechanism， influencing factors， related components， and the impact of Maillard reaction on various aspects of TCM processing are reviewed from multiple perspectives in this article， providing reference for the further improvement of processing mechanism and quality control of TCM.

OBJECTIVE To provide a reference for the quality control of Hypericum perforatum. METHODS High- performance liquid chromatography （HPLC） was used to establish fingerprints for 20 batches of H. perforatum and determine the contents of its main components： chlorogenic acid， rutin， hyperin， isoquercitrin， avicularin， quercitrin and quercetin. Cluster analysis was conducted using SPSS 26.0 software. The chromaticity values （luminance value L*， red-green value a*， and yellow- blue value b*） of H. perforatum powder were measured using electronic eye. A prediction model for the contents of seven components in H. perforatum based on its appearance chromaticity values was established using machine learning algorithms. The predictive performance of the models was evaluated using root-mean-square-error （RMSE）. RESULTS A total of 16 common peaks were calibrated in the fingerprints of 20 batches of H. perforatum， and 9 peaks were identified， which were chlorogenic acid， rutin， hyperin， isoquercitrin， avicularin， quercitrin， quercetin， hypericin and hyperforin； the similarities of the 20 batches of samples and reference fingerprint ranged from 0.889-0.987. The contents of chlorogenic acid， rutin， hyperin， isoquercitrin， avicularin， quercitrin and quercetin were 0.025%-0.166%， 0.048%-0.339%， 0.082%-0.419%， 0.017%-0.209%， 0.011%-0.134%， 0.020%-0.135%， 0.041%-0.235%， respectively. Cluster analysis results showed that 18 batches of qualified H. perforatum were grouped into three categories， when the Euclidean distance was set to 1.4. L* of the 20 batches of H. perforatum ranged from 62.814 to 75.668， a* ranged from 1.409 to 3.490， and b* ranged from 25.249 to 30.759. RMSE of three prediction models， namely XGBoost， LightGBM， and AdaBoost， ranged from 0.008 to 0.070， indicating good fitting performance. XGBoost model predicted the contents of the other six components with high accuracy， except for rutin. CONCLUSIONS The established fingerprints and content determination methods are accurate， reproducible， and reliable. The content prediction model based on appearance chromaticity values， combined with machine learning algorithms， can be used for the quality control of H. perforatum.

Background Children and adolescents drink sugar-sweetened beverages (SSBs) frequently. Research has confirmed that SSBs associate with weight gain and overweight or obesity. However, it is unclear whether high SSBs intake associates with abnormal changes in physical growth and glucolipid metabolism before causing adverse health outcomes such as overweight and obesity. Early identification of associated health risks of overconsumption of SSBs have important public health implications. Objective To investigate the differences in physical growth and glucolipid metabolism between different SSBs intake frequency groups in normal weight children and adolescents aged 6-17 years, and to evaluate the early effects of SSBs intake on physical growth and glycolipid metabolism before causing overweight and obesity, aiming to provide a scientific basis for the prevention and control of childhood overweight and obesity and related chronic diseases, and for the formulation of policies on the control of SSBs consumption. Methods Data were from the Shanghai Diet and Health Survey (SDHS) among primary and secondary school students. The participants were normal weight children and adolescents aged 6-17 years. Propensity scores were calculated according to energy intake and physical activity factors, after stratifying by age and gender. Participants were 1:1 matched with the closest propensity scores in the high-frequency (≥1 time·d⁻¹) and the low-frequency (≤1 time·week⁻¹) SSBs intake groups. The outcome indicators were physical measurements such as height, weight, percent of body fat, and waist circumference, and metabolic indicators such as fasting blood glucose, total triglycerides, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol. Body mass index (BMI) was calculated. Food frequency questionnaire was used to collect SSBs consumption in the past three months through face-to-face interview. A paired t-test was used to compare the differences in physical and glycolipid metabolic indicators between the high-frequency intake group and the low-frequency intake group of SSBs. Results A total of 431 pairs were obtained. For children and adolescents in grades 6-9, overall height (difference=2.92 cm, P=0.002), weight (difference=2.53 kg, P=0.003), and waist circumference (difference=1.34 cm, P=0.035) were higher in those who consumed SSBs ≥1 time·d⁻¹ than in those who consumed ≤1 time·week⁻¹. For children and adolescents in grades 10-12, overall weight (difference=2.27 kg, P=0.041) was higher in those who consumed SSBs ≥1 time·d⁻¹ than in those who consumed ≤1 time·week⁻¹. Over 95% of the study subjects reported blood glucose and lipid test results within the normal range; but girls in grades 1-5 who consumed SSBs ≥1 time·d⁻¹ had a higher total cholesterol (difference=0.20 mmol·L⁻¹, P=0.027) and low-density lipoprotein cholesterol (difference=0.19 mmol·L⁻¹, P=0.010) than those who consumed ≤1 time·week⁻¹; boys in grades 6-9 who consumed SSBs ≥1 time·d⁻¹ had a lower high-density lipoprotein cholesterol (difference=-0.10 mmol·L⁻¹, P=0.039) than those who consumed ≤1 time·week⁻¹. Conclusion High-frequency intake of SSBs may be associated with higher total cholesterol and low-density lipoprotein cholesterol in normal weight children and adolescents in grades 1-5, and higher weight in normal weight children and adolescents in grades 6-12. There is an urgent need to educate children and adolescents about nutritional health, enhance their ability to make healthy food and beverage choices, and take early interventions to control the intake of SSBs in children.