ObjectiveTo explore the application of virtual reality biofeedback training combined with oral localization therapy in dysphagia after oral cancer surgery. MethodsFrom May, 2023 to July, 2024, 86 patients with dysphagia after oral cancer surgery in Zhejiang Provincial People's Hospital were randomly divided into control group (n = 43) and experimental group (n = 43). The control group received conventional swallowing function training, while the experimental group added virtual reality biofeedback training combined with oral positioning therapy, for four weeks. The Standardized Swallowing Function Assessment Scale (SSA), Functional Oral Intake Scale (FOIS) and M.D.Anderson Dysphagia Inventory (MDADI) were used for evaluation before intervention, and two weeks, four weeks and eight weeks after intervention. ResultsFor scores of SSA , the main effects of group (F = 150.190, P < 0.001, η²_p = 0.641) and time (F = 230.870, P < 0.001, η²_p = 0.733), as well as the interaction effect (F = 16.910, P < 0.001, η²_p = 0.168) were all significant. For scores of FOIS, the main effects of group (F = 59.601, P < 0.001, η²_p = 0.415) and time (F = 89.464, P < 0.001, η²_p = 0.516), as well as the interaction effect (F = 7.990, P < 0.001, η²_p = 0.087) were all significant. For scores of MDADI, the main effects of group (F = 33.133, P < 0.001, η²_p = 0.283) and time (F = 49.650, P < 0.001, η²_p = 0.371), as well as the interaction effect (F = 3.224, P = 0.023, η²_p = 0.037) were all significant. ConclusionVirtual reality biofeedback training combined with oral localization therapy could improve the swallowing function, oral feeding ability and overall quality of life of patients with dysphagia after oral cancer surgery.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Diabetic Peripheral Neuropathy （DPN） is one of the most common and harmful complications of type 2 diabetes. DPN's pathogenesis include high blood sugar-induced oxidative stress， inflammation， and mitochondrial dysfunction. These factors are combined to damage nerve fibers， leading to sensory issues， pain， and numbness. Through a coordinated effect， these factors trigger nerve fiber damage and lead to sensory abnormalities， pain and numbness in limbs， and other symptoms， seriously restricting patients' activities of daily living and mobility. Recent research highlights that cellular senescence plays a critical role in DPN. Cellular senescence is manifested by the loss of cell proliferation ability， and further aggravates nerve damage via oxidative stress， mitochondrial dysfunction， autophagy impairment， inflammatory reaction， and other mechanisms， accelerating DPN occurrence and progression. In terms of medical treatment， current methods focus on blood sugar control， pain relief medicine， and microcirculation improvement， while no therapy has been developed based on cellular senescence. In contrast， traditional Chinese medicine （TCM） shows a unique advantage in DPN prevention and treatment via cellular senescence modulation. TCM emphasizes a holistic approach， as well as syndrome differentiation and treatment， effective in anti-aging and nerve damage repair. Recent studies show that TCM active ingredients， including puerarin， ginsenosides， and berberine， can reduce inflammation， oxidative stress， and apoptosis via signaling pathway regulation， thereby slowing cellular senescence to alleviate nerve damage. Furthermore， TCM compounds such as Buyang Huanwutang， Taohong Siwutang， and Huangqi Guizhi Wuwutang exert synergistic effects on cellular senescence-related pathways to improve nerve health and reduce DPN clinical symptoms. Therefore， this paper reviews the literature related to the interaction between cellular senescence and DPN from the perspective of cellular senescence， summarizing the mechanism of DPN and TCM intervention strategies.

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties with communication and social interaction, restricted and repetitive behaviors. Previous studies have indicated that individuals with ASD exhibit early and lifelong attention deficits, which are closely related to the core symptoms of ASD. Basic visual attention processes may provide a critical foundation for their social communication and interaction abilities. Therefore, this study explores the behavior of children with ASD in capturing attention to changes in topological properties. MethodsOur study recruited twenty-seven ASD children diagnosed by professional clinicians according to DSM-5 and twenty-eight typically developing (TD) age-matched controls. In an attention capture task, we recorded the saccadic behaviors of children with ASD and TD in response to topological change (TC) and non-topological change (nTC) stimuli. Saccadic reaction time (SRT), visual search time (VS), and first fixation dwell time (FFDT) were used as indicators of attentional bias. Pearson correlation tests between the clinical assessment scales and attentional bias were conducted. ResultsThis study found that TD children had significantly faster SRT (P<0.05) and VS (P<0.05) for the TC stimuli compared to the nTC stimuli, while the children with ASD did not exhibit significant differences in either measure (P>0.05). Additionally, ASD children demonstrated significantly less attention towards the TC targets (measured by FFDT), in comparison to TD children (P<0.05). Furthermore, ASD children exhibited a significant negative linear correlation between their attentional bias (measured by VS) and their scores on the compulsive subscale (P<0.05). ConclusionThe results suggest that children with ASD have difficulty shifting their attention to objects with topological changes during change detection. This atypical attention may affect the child’s cognitive and behavioral development, thereby impacting their social communication and interaction. In sum, our findings indicate that difficulties in attentional capture by TC may be a key feature of ASD.

Objective:To understand the potential characteristics of decision-making preparation in outpatient hypertensive patients based on latent profile analysis, to identify the influencing factors of different categories of decision-making preparation levels, and to explore the performance of different decision-making preparation types in facilitation of patients involvement in treatment decision-making.Methods:Through a cross-sectional study, 350 hypertensive patients attending outpatient clinics in five different types of healthcare institutions (general hospitals, specialised hospitals and community hospitals) in Tianjin during January to May 2024 who met the inclusion and exclusion criteria were selected by the convenience sampling method as study subjects. General Information Questionnaires, Preparation for Decision Making Scale, and Facilitation of Patient Involvement Scale were used for investigation.Results:Totally 350 valid questionnaires [178 males and 172 females aged 25-89(57.24 ± 13.39)years old] were collected. The decision-making preparation score of outpatient hypertensive patients was (64.19 ± 18.69). The latent profile analysis results showed that the decision-making preparation of outpatient hypertensive patients could be divided into three potential categories: decision-making information scarcity type accounted for 20.0%(70/350), decision-making balance negotiation type accounted for 39.7%(139/350), and decision-making preparation adequacy type accounted for 40.3%(141/350). The results of multiple Logistic regression analysis showed that age, medical insurance type, occupation, and children′s condition were the influencing factors for the potential categories of decision-making preparation in outpatient hypertensive patients (all P<0.05). Age [less than 35 years old: OR(95% CI)=0.127(0.020-0.796)], occupation [on the job: OR(95% CI)=2.010 (1.034-3.906)], were the influencing factors of decision-making balance negotiation group (all P<0.05). Medical insurance type [basic medical insurance for urban employees: OR(95% CI)=0.372(0.193-0.720)], occupation [on the job: OR(95% CI)=2.500(1.270-4.920)], children′s condition[junior and senior high school: OR(95% CI)=0.391(0.190-0.802)] were the influencing factors of decision-making preparation adequacy group (all P<0.05). Conclusions:The level of promoting patient participation among outpatients with hypertension is relatively high, and there are differences in the perceived degree of promoting patient participation among patients with different types of decision preparation.It is recommended that medical staff provide decision-making related information based on the characteristics of different decision-making preparation categories of patients, encourage patients to actively participate in decision-making, and construct targeted decision support plans.

Aim To explore the mechanism of Con-grong Shujing granule(CSGs)in the treatment of Par-kinson's disease(PD)by network pharmacology,mo-lecular docking and parallel reaction monitoring(PRM)technology.Methods The active components of CSGs and the target genes of Parkinson's disease were obtained through the database.The intersection targets of drugs and diseases were selected to construct the"drug-active ingredient-target"and protein interac-tion network.The intersection target genes were impor-ted into David database for GO and KEGG enrichment analysis,and the main components were docked with key targets.27 SD rats were randomly divided into the normal group(n=9),model group(n=9)and treat-ment group(n=9).On day 1,7 and 14 of treatment,PRM analysis was used to detect the changes in the specific peptides of key target proteins in the substantia nigra of rats.Results The main components of CSGs wereTanshialdehyde,Baicalein,Quercetin and Kaempferol.The most important targets for the treat-ment of PD were TP53,AKT1,EGFR,HSP90 AA1 and STAT3.KEGG analysis mainly enriched MAPK,PI3K-Akt and neurotrophic factor signaling pathway.The molecular docking between core components and core targets showed that the binding of drugs and targets had good activity.PRM analysis of key proteins found that the target peptide expression levels of ASK1,JNK1 and JNK3 were different among groups(P＜0.05).Con-clusion CSGs can alleviate ERS,inhibit apoptosis and play a neural protective role through the ASK1-JNK pathway.

Objective:To explore the types and characteristics of self-management behaviors among stroke patients, as well as to analyze the influencing factors associated with these different types, providing a reference for developing intervention programs aimed at enhancing self-management behaviors in stroke patients.Methods:This study adopted a cross-sectional survey design. The stroke inpatients were selected through convenience sampling from the Department of Neurology at Huashan Hospital, Fudan University between October 2023 and August 2024. Data collection was conducted using the following instruments: the General Information Questionnaire, Stroke Self-Management Behavior Rating Scale, Self-Efficacy for Managing Chronic Disease 6-Item Scale, Stroke Health Knowledge Questionnaire, Social Support Rating Scale, Generalized Anxiety Disorder Scale, Patient Health Questionnaire-9, and the modified Rankin Scale. Stroke patients' self-management behaviors were categorized using systematic cluster analysis, and disordered multi-class Logistic regression was employed to identify the influencing factors associated with each category.Results:Finally, 210 stroke patients were enrolled, there were 148 males and 62 females, aged (60.82 ± 13.05) years. The total score of self-management behavior in stroke patients was (144.18 ± 23.24) points, with a score rate of 56.54%. Systematic cluster analysis identified four distinct self-management behaviors patterns: consistent implementers (25.71%, 54/210); unrealistically optimistic(54.76%, 115/210); optimistically proactive (13.81%, 29/210); and passive and resigned (5.71%, 12/210). Disordered multi-class Logistic regression analysis indicated that higher scores in stroke-related health knowledge were associated with a greater likelihood of being categorized as stable practice type and optimistic proactive type ( OR=1.130, 1.254, both P<0.05). Conversely, increased levels of depression correlate with a higher probability of being classified as passive waiting type ( OR=0.684, 0.722, 0.540, all P<0.05). Additionally, lower modified Rankin Scale scores were linked to an increased tendency to fall into the categories of stable practice type and blind optimism type ( OR=19.759, 23.148, both P<0.05). Conclusions:The self-management behaviors of stroke patients are generally suboptimal and exhibited distinct classification features. Significant differences are observed in stroke health knowledge, depression, and the modified Rankin Scale scores among the four patient types. Healthcare professionals should tailor intervention measures to the characteristics of each type to enhance patients' self-management capacity.

Lung cancer exhibits the highest incidence and mortality rates among cancers globally,with a five-year overall survival rate alarmingly below 20％.Targeting autophagy,though a controversial therapeutic strategy,is extensively employed in clinical practice.Current research is actively pursuing various therapeutic strategies using small molecules to exploit the dual function of autophagy.Nevertheless,the pivotal question of enhancing or inhibiting autophagy in cancer therapy merits further attention.This review aims to provide a comprehensive overview of the mechanisms of autophagy in lung cancer.It also explores recent advances in targeting cytotoxic autophagy and inhibiting protective autophagy with small molecules to induce cell death in lung cancer cells.Notably,most autophagy-targeting drugs,primarily natural small molecules,have demonstrated that activating cytotoxic autophagy effectively induces cell death in lung cancer,as opposed to inhibiting protective autophagy.These insights contribute to identifying druggable targets and drug candidates for potential autophagy-related lung cancer therapies,offering promising approaches to combat this disease.

Ovairan steroid cell tumor, not otherwise specified is a rare type of ovarian sex cord-stromal tumor, accounting for<0.1% of all ovarian tumors. This article analyzes the diagnosis and treatment process, clinical manifestations, diagnosis and differential diagnosis, immunohistochemistry, treatment, and prognosis of a case of ovarian SCT-NOS.