Radiotherapy is a crucial treatment modality for head and neck tumors. However, while effectively killing tumor cells, it significantly disrupts the homeostasis of the oral microecology, which is closely associated with various complications such as radiation-induced oral mucositis. Literature review indicates that as radiotherapy doses accumulate and treatment durations extend, the richness and diversity of the oral microbiota show a declining trend, with the genus Streptococcus decreasing most markedly. In contrast, radiotherapy selectively promotes the proliferation of bacterial phyla such as Proteobacteria and Bacteroidetes, which are rich in opportunistic pathogens. Mechanistically, radiotherapy activates the nuclear factor-kappa B pathway, triggering chronic inflammation and oxidative stress, damaging the epithelial barrier, suppressing local immunity, and causing damage to organs such as the salivary glands. It can also induce systemic diseases via the oral-gut axis, forming a multi-level, interconnected pathogenic network. In terms of interventions, treatment strategies including probiotics and prebiotics have shown promising efficacy against side effects such as radiation-induced oral mucositis. Saliva-based oral microbiota transplantation is an emerging strategy that is expected to become widely utilized for restoring oral microecological balance. Existing interventions provide preliminary pathways for clinical practice, but this field still faces several key scientific questions. The association between oral microecology and systemic diseases remains largely correlative, lacking causal evidence. Furthermore, critical parameters for oral microbiota transplantation, such as donor screening criteria, transplantation protocols, and long-term safety, are not yet well-defined. Therefore, future research should focus on conducting large-scale clinical trials to establish standardized protocols and safety evaluation systems for oral microecological interventions, and explore combined treatment therapies such as probiotics, prebiotics, and microbiota transplantation to advance the development of personalized precision modulation. These will enable more effective management of radiotherapy-induced oral microecological dysbiosis and improve treatment outcomes and quality of life for patients with head and neck tumors.

Objective:To study the relationship between microRNA (miRNA, miR)-675-3p, miR-675-5p, miR-29b-3p, miR-let-7b-3p and fluoride induced articular cartilage injury in rats.Methods:Using the factorial design, thirty 3-week-old specific pathogen free grade male Wistar rats (weighted 125 - 150 g) were selected and randomly divided into a control group, a 25 mg/L fluoride group, and a 50 mg/L fluoride group using a random number table method, with 10 rats in each group. The control group drank distilled water, while the fluoride exposure groups drank distilled water with fluoride ion concentrations of 25 and 50 mg/L, respectively. Five rats were euthanized in each group at 3 and 6 months of feeding, respectively. Visual observation was used to observe the occurrence of dental fluorosis in rats, and fluoride ion selective electrode method was used to detect the fluoride level in blood, urine, and cartilage. Hematoxylin-eosin staining and safranin O-fast green staining were used to observe the pathological changes of articular cartilage, and Mankin score was used to evaluate the grading of cartilage injury. Real-time fluorescence quantitative PCR was used to detect the expression levels of miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p in cartilage.Results:After 3 and 6 months of fluoride exposure, no dental fluorosis was observed in the control group, while rats in the 25 and 50 mg/L fluoride groups showed varying degrees of dental fluorosis. There were statistically significant differences in the levels of blood fluoride (mg/L: 0.11 ± 0.04, 0.57 ± 0.32, 0.29 ± 0.06, 0.07 ± 0.01, 0.31 ± 0.05, 0.38 ± 0.06), urine fluoride (mg/L: 1.81 ± 0.58, 13.18 ± 2.29, 66.11 ± 20.74, 2.35 ± 1.08, 14.79 ± 3.87, 28.32 ± 4.79), and cartilage fluoride (mg/kg: 341.83 ± 44.07, 612.99 ± 174.72, 991.26 ± 227.32, 338.29 ± 72.53, 957.09 ± 195.86, 1 535.53 ± 89.01) among in rats the control group, 25 mg/L fluoride group, and 50 mg/L fluoride group ( F = 7.76, 42.78, 40.54, 23.10, 18.96, 80.81, P < 0.05). In the 50 mg/L fluoride group, there were statistically significant differences in the levels of urine fluoride and cartilage fluoride of rats exposed for different times ( t = 4.45, - 3.80, P < 0.05). The Mankin score grading for cartilage injury showed that at 3 months of fluoride exposure, there were 4, 0, and 0 rats with normal cartilage in the control group, 25 mg/L fluoride group, and 50 mg/L fluoride group, 1, 4, and 1 rats with mild injury, and 0, 1, and 4 rats with moderate injury, respectively. At 6 months of fluoride exposure, there were 4, 0, and 0 rats with normal cartilage in the control group, 25 mg/L fluoride group, and 50 mg/L fluoride group, 1, 3, and 0 rats with mild injury, 0, 1, and 3 rats with moderate injury, and 0, 1, and 2 rats with severe injury, respectively. Real-time fluorescence quantitative PCR results showed that fluoride exposure dose had individual effects on the expression of miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p in cartilage ( F = 8.68, 7.97, 9.34, 10.14, P < 0.05). There was no individual effect of fluoride exposure time on the expression of miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p in cartilage ( F = 0.00, 0.15, 0.63, 0.53, P > 0.05). However, there was no interaction effect between fluoride exposure time and dose on the above-mentioned miRNA ( F = 0.68, 0.05, 0.22, 0.24, P > 0.05). The correlation analysis results showed that miR-675-3p and miR-675-5p in cartilage were negatively correlated with blood fluoride, urine fluoride, and cartilage fluoride ( r = - 0.37, - 0.42, - 0.56, - 0.53, - 0.57, - 0.53, P < 0.05), while miR-29b-3p and miR-let-7b-3p were positively correlated with urine fluoride and cartilage fluoride ( r = 0.58, 0.40, 0.48, 0.47, P < 0.05). The results of ordered logistic regression analysis showed that miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p were influencing factors of dental fluorosis grading ( OR = 0.13, 0.04, 1.55, 2.58, P < 0.05) and Mankin score grading ( OR = 0.04, 0.06, 1.41, 1.58, P < 0.05). Conclusion:MiR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p may be involved in the process of fluoride induced articular cartilage injury.

Objective: To investigate the association between the parent-child relationship with depression among junior high school students, as well as the dual moderating effect of teacher support and gender, so as to provide a reference for depression interventions at family, school, and individual levels. Methods: In November 2024, a cluster sampling design was used to recruit 1 229 students from two junior high schools in Chengdu, Sichuan Province as participants. The survey employed the Interpersonal Relations Scale, the Patient Health Questionnaire-9 for depression, and the Students Perceived Teacher Support Behavior Questionnaire. Spearman s rank correlation analyses were used to examine the associations among the parent-child relationship, teacher support, gender, and depression. Through linear regression analysis, the dual moderating effects of teacher support and gender on the association between parent-child relationship and depression in middle school students were evaluated. Results: Scores for the parent-child relationship and for teacher support among middle school students were (4.03±1.00) and (4.23±0.86), respectively, and the depression score was 1.13 (1.00, 1.63). Parent-child relationships and teacher support showed positive correlations,while both the parent-child relationship and teacher support were negatively correlated with depression among junior high school students ( r =0.25, -0.55, -0.29, all P <0.01). Linear regression analyses showed that teacher support and gender jointly moderated the association between the parent-child relationship and depression. Further simple slopes analyses revealed that the negative impact of the parent-child relationship on depression was stronger in girls, peaking under low teacher support conditions ( β =-0.61); among boys, a negative effect was also present but weaker ( β =-0.48) (both P <0.05). Conclusion Teacher support and gender jointly moderated the association between the parent-child relationship and depression among junior high school students; girls depression are more closely linked to the quality of the parent-child relationship, while boys are more sensitive to changes in teacher support.

Objective To evaluate the clinical efficacy of a novel sleep-aid decoction in treating elderly insomnia patients with different traditional Chinese medicine (TCM) constitutional types, and its effects on neurotransmitter and inflammatory factor levels. Methods A total of 200 patients with four different TCM constitutions-peaceful, Qi-deficient, Yin-deficient, and Yang-deficient-were recruited. Peripheral blood neurotransmitter and inflammatory factor levels were measured for variations among insomnia patients across different constitutions. These patients were treated using the novel sleep-aid decoction, the effects of which were evaluated based on changes in neurotransmitters and inflammatory factors. Results Compared to the peaceful constitution group, insomnia patients with Qi-deficient, Yin-deficient, and Yang-deficient constitutions exhibited significantly elevated baseline levels of neurotransmitters (5-HT, GABA) and inflammatory factors (IL-6, TNF-α, IL-1β, CRP). Following the treatment, the Qi-deficient and Yin-deficient groups showed a marked increase in 5-HT levels, restored balance of Glu, GABA, and melatonin, and significant reductions in IL-6 and TNF-α levels. The overall effective rate was 83.5%, with optimal efficacy observed in the Qi-deficient (97.72%) and Yin-deficient (95.34%) groups. Conclusion The novel sleep-aid decoction is effective in treating insomnia in elderly patients, with the best results observed in the Qi-deficient and Yin-deficient constitution groups.
Humans ; Sleep Initiation and Maintenance Disorders/blood* ; Aged ; Male ; Female ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Middle Aged ; Tumor Necrosis Factor-alpha/blood* ; Sleep Aids, Pharmaceutical/therapeutic use* ; Anti-Inflammatory Agents/therapeutic use* ; Interleukin-6/blood* ; Interleukin-1beta/blood* ; Neurotransmitter Agents/blood* ; Aged, 80 and over ; C-Reactive Protein/metabolism*

Objective To analyze the prescription patterns of Professor Chen Bin in treating chronic superficial gastritis(CSG)with data mining methods.Methods Prescription data from effective medical records of outpatients with CSG treated by Professor Chen Bin at the First Affiliated Hospital of Guangzhou University of Chinese Medicine from October of 2022 to April of 2023 were collected.R language,SPSS,and IBM SPSS Modeler were used to perform frequency statistics,association rule analysis,and systematic cluster analysis on the prescription data,and then the medication and prescription patterns of Professor Chen Bin in treating CSG were explored.Results A total of 64 outpatient prescriptions formulated by Professor Chen Bin were included,involving 95 Chinese herbal medicines.The top 10 frequently-used herbs were Glycyrrhizae Radix et Rhizoma Praeparata cum Melle(Zhigancao),Bupleuri Radix(Chaihu),Pinelliae Rhizoma Praeparatum(Fabanxia),Jujubae Fructus(Dazao),Zingiberis Rhizoma(Ganjiang),Codonopsis Radix(Dangshen),Scutellariae Radix(Huangqin),Paederiae Herba(Jishiteng),Citri Reticulatae Pericarpium(Chenpi),and Taraxaci Herba(Pugongying).Most of the herbs were warm,cold,and mild in nature,and were sweet in flavor.And the herbs mainly had the meridian tropism of spleen,stomach,and liver meridians,and had the primary therapeutic effects of strengthening the spleen and replenishing qi,regulating qi,and resolving dampness.Based on the results of association rule analysis,a total of 21 core herb combinations were screened out,and cluster analysis yielded 4 clustered prescriptions.Combining the results of high-frequency herb statistics and cluster analysis and based on the traditional Chinese medicine theory,the core herbs for treating CSG was identified as Zhigancao,Chaihu,Fabanxia,Dazao,Ganjiang,Dangshen,Huangqin,Jishiteng,Chenpi,and Pugongying.Conclusion In treating CSG,Professor Chen Bin adheres to the treatment principle of replenishing qi and regulating the pivot,and the therapeutic methods of regulating qi movement,strengthening the spleen and harmonizing the stomach are applied with Xiaochaihu Decoction as the fundamental prescriptions.His view of treatment by focusing on the spleen and stomach,emphasizing the combination of herbs with cold and warm properties and based on syndrome differentiation will provide a reference for the clinical application of traditional Chinese medicine in treating CSG.

Objective:To study the relationship between microRNA (miRNA, miR)-675-3p, miR-675-5p, miR-29b-3p, miR-let-7b-3p and fluoride induced articular cartilage injury in rats.Methods:Using the factorial design, thirty 3-week-old specific pathogen free grade male Wistar rats (weighted 125 - 150 g) were selected and randomly divided into a control group, a 25 mg/L fluoride group, and a 50 mg/L fluoride group using a random number table method, with 10 rats in each group. The control group drank distilled water, while the fluoride exposure groups drank distilled water with fluoride ion concentrations of 25 and 50 mg/L, respectively. Five rats were euthanized in each group at 3 and 6 months of feeding, respectively. Visual observation was used to observe the occurrence of dental fluorosis in rats, and fluoride ion selective electrode method was used to detect the fluoride level in blood, urine, and cartilage. Hematoxylin-eosin staining and safranin O-fast green staining were used to observe the pathological changes of articular cartilage, and Mankin score was used to evaluate the grading of cartilage injury. Real-time fluorescence quantitative PCR was used to detect the expression levels of miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p in cartilage.Results:After 3 and 6 months of fluoride exposure, no dental fluorosis was observed in the control group, while rats in the 25 and 50 mg/L fluoride groups showed varying degrees of dental fluorosis. There were statistically significant differences in the levels of blood fluoride (mg/L: 0.11 ± 0.04, 0.57 ± 0.32, 0.29 ± 0.06, 0.07 ± 0.01, 0.31 ± 0.05, 0.38 ± 0.06), urine fluoride (mg/L: 1.81 ± 0.58, 13.18 ± 2.29, 66.11 ± 20.74, 2.35 ± 1.08, 14.79 ± 3.87, 28.32 ± 4.79), and cartilage fluoride (mg/kg: 341.83 ± 44.07, 612.99 ± 174.72, 991.26 ± 227.32, 338.29 ± 72.53, 957.09 ± 195.86, 1 535.53 ± 89.01) among in rats the control group, 25 mg/L fluoride group, and 50 mg/L fluoride group ( F = 7.76, 42.78, 40.54, 23.10, 18.96, 80.81, P < 0.05). In the 50 mg/L fluoride group, there were statistically significant differences in the levels of urine fluoride and cartilage fluoride of rats exposed for different times ( t = 4.45, - 3.80, P < 0.05). The Mankin score grading for cartilage injury showed that at 3 months of fluoride exposure, there were 4, 0, and 0 rats with normal cartilage in the control group, 25 mg/L fluoride group, and 50 mg/L fluoride group, 1, 4, and 1 rats with mild injury, and 0, 1, and 4 rats with moderate injury, respectively. At 6 months of fluoride exposure, there were 4, 0, and 0 rats with normal cartilage in the control group, 25 mg/L fluoride group, and 50 mg/L fluoride group, 1, 3, and 0 rats with mild injury, 0, 1, and 3 rats with moderate injury, and 0, 1, and 2 rats with severe injury, respectively. Real-time fluorescence quantitative PCR results showed that fluoride exposure dose had individual effects on the expression of miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p in cartilage ( F = 8.68, 7.97, 9.34, 10.14, P < 0.05). There was no individual effect of fluoride exposure time on the expression of miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p in cartilage ( F = 0.00, 0.15, 0.63, 0.53, P > 0.05). However, there was no interaction effect between fluoride exposure time and dose on the above-mentioned miRNA ( F = 0.68, 0.05, 0.22, 0.24, P > 0.05). The correlation analysis results showed that miR-675-3p and miR-675-5p in cartilage were negatively correlated with blood fluoride, urine fluoride, and cartilage fluoride ( r = - 0.37, - 0.42, - 0.56, - 0.53, - 0.57, - 0.53, P < 0.05), while miR-29b-3p and miR-let-7b-3p were positively correlated with urine fluoride and cartilage fluoride ( r = 0.58, 0.40, 0.48, 0.47, P < 0.05). The results of ordered logistic regression analysis showed that miR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p were influencing factors of dental fluorosis grading ( OR = 0.13, 0.04, 1.55, 2.58, P < 0.05) and Mankin score grading ( OR = 0.04, 0.06, 1.41, 1.58, P < 0.05). Conclusion:MiR-675-3p, miR-675-5p, miR-29b-3p, and miR-let-7b-3p may be involved in the process of fluoride induced articular cartilage injury.

Objective:To investigate the status quo of cognitive frailty in elderly patients with heart failure and analyze its influencing factors, so as to provide evidence for healthcare professionals to formulate effective intervention strategies.Methods:A total of 330 elderly patients with heart failure admitted to the First Affiliated Hospital of the University of South China and the Second Affiliated Hospital of the University of South China from October 2023 to January 2024 were selected as the study objects by convenience sampling method. General data questionnaire, Frailty Phenotype, Montreal Cognitive Assessment, Clinical Dementia Rating Scale, Geriatric Depression Scale-15 and Short Form Mini Nutritional Assessment were used for a sectional investigation. Random forest algorithm was used to rank the importance of variables and binary logistic regression was combined to explore the influencing factors of elderly patients with heart failure.Results:According to the evaluation criteria of cognitive frailty, 330 elderly patients with heart failure were divided into cognitive frailty group (124 cases) and non-cognitive frailty group (206 cases). The incidence of cognitive frailty was 37.6% (124/330). Among which, the median age of the cognitive frailty group was 73 years old, with 63 males and 61 females. The median age of the non-cognitive frailty group was 71 years old, with 117 males and 89 females. The random forest results showed that the top 7 variables in importance ranking were weekly intellectual activity, frequency of physical exercise, age, educational levels, depression status, cardiac function grade and risk of malnutrition. Binary logistic regression analysis showed that weekly intellectual activity ( OR=0.076, 95% CI 0.027-0.216), requency of physical exercise ( OR=0.184, 95% CI 0.079-0.430), age ( OR=1.173, 95% CI 1.077-1.277), educational levels ( OR=0.283, 95% CI 0.143-0.559), depression status ( OR=4.440, 95% CI 1.451-13.585), cardiac function grade ( OR=3.030, 95% CI 1.673-5.489) and risk of malnutrition ( OR=3.833, 95% CI 1.530-9.602) were the main influencing factors (all P<0.05). Conclusions:The incidence of cognitive frailty in elderly patients with heart failure is high. Healthcare professionals ought to focus on the screening and assessing of cognitive frailty in elderly patients with heart failure, and formulate effective intervention strategies by considering the above influencing factors to mitigate the occurrence of cognitive frailty.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Objective:To investigate the status quo of cognitive frailty in elderly patients with heart failure and analyze its influencing factors, so as to provide evidence for healthcare professionals to formulate effective intervention strategies.Methods:A total of 330 elderly patients with heart failure admitted to the First Affiliated Hospital of the University of South China and the Second Affiliated Hospital of the University of South China from October 2023 to January 2024 were selected as the study objects by convenience sampling method. General data questionnaire, Frailty Phenotype, Montreal Cognitive Assessment, Clinical Dementia Rating Scale, Geriatric Depression Scale-15 and Short Form Mini Nutritional Assessment were used for a sectional investigation. Random forest algorithm was used to rank the importance of variables and binary logistic regression was combined to explore the influencing factors of elderly patients with heart failure.Results:According to the evaluation criteria of cognitive frailty, 330 elderly patients with heart failure were divided into cognitive frailty group (124 cases) and non-cognitive frailty group (206 cases). The incidence of cognitive frailty was 37.6% (124/330). Among which, the median age of the cognitive frailty group was 73 years old, with 63 males and 61 females. The median age of the non-cognitive frailty group was 71 years old, with 117 males and 89 females. The random forest results showed that the top 7 variables in importance ranking were weekly intellectual activity, frequency of physical exercise, age, educational levels, depression status, cardiac function grade and risk of malnutrition. Binary logistic regression analysis showed that weekly intellectual activity ( OR=0.076, 95% CI 0.027-0.216), requency of physical exercise ( OR=0.184, 95% CI 0.079-0.430), age ( OR=1.173, 95% CI 1.077-1.277), educational levels ( OR=0.283, 95% CI 0.143-0.559), depression status ( OR=4.440, 95% CI 1.451-13.585), cardiac function grade ( OR=3.030, 95% CI 1.673-5.489) and risk of malnutrition ( OR=3.833, 95% CI 1.530-9.602) were the main influencing factors (all P<0.05). Conclusions:The incidence of cognitive frailty in elderly patients with heart failure is high. Healthcare professionals ought to focus on the screening and assessing of cognitive frailty in elderly patients with heart failure, and formulate effective intervention strategies by considering the above influencing factors to mitigate the occurrence of cognitive frailty.