OBJECTIVE: To establish and optimize in vitro lipolysis model, and then to study griseofuvin(GRI) distribution during in vitro lipolysis of self-nanoemulsifying drug delivery systems(SNEDDSs). METHODS: The lipolysis rate and extent of triglyceride (TG)were two index for in vitro lipolysis model optimization. The partitioning of GRI into lipolysis phases (aqueous phase, pellet phase, lipid phase) was exploited to investigate the impact of structure and lipid loaded of TG on GRI distribution of SNEDDSs in vitro lipolysis. RESULTS: The optimal lipolysis model at the start of the experiment was as follows: 800 U · mL^-1 Pancreatin extract, 5/1.25 mmol · L^-1 NaTDC/PC micelle and 50 mmol · L^-1 Trizma maleate. The addition way of Ca²⁺ for medium chain triglyceride (MCT) and long chain triglyceride (LCT) were fixed addition 5 mmol · L^-1 and continuous addition 0.008 mmol · min^-1, respectively. With the same amount of TG in SNEDDSs, percent content of GRI in aqueous phase of LCT-SNEDDS was higher than MCT-SNEDDS. When TG loaded doubled, GRI in aqueous phase of LCT-SNEDDS significantly increased by 32.4%, and which of MCT-SNEDDS raised only 5.7%, respectively. CONCLUSION: The lipolysis rate and extent of TG were correlated with its structure and composition of TG and in vitro lipolysis model. Compared to GRI-SNEDDS without lipolysis, during in vitro lipolysis GRI had transferred to aqueous phase, pellet phase and lipid phase from which was only dispersed in emulsion droplet. And the distribution of GRI during in, vitro lipolysis depended on the composition and loading rate of TG in SNEDDS. These results may provide useful references to study the absorption mechanism of SNEDDS.

Objective To explore the effect of therapeutic-oriented communication on relieving preoperative anxiety of patients with thyroid tumor.Methods Totals of 83 patients with thyroid tumor who meet the inclusion criterion were divided into intervention group ( n =42 ) and control group ( n =41 ) by odd and even hospitalization number.Control group received conventional treatment and care while intervention group received the traditional care plus therapeutic-oriented communication.Self-Rating Anxiety Scale (SAS) were used to investigate the anxiety status before and after intervention among these patients.Results There was no difference in the average SAS scores between two groups before intervention( P ＞0.05 ),the average SAS score in intervention group was significantly lower than that of control group after intervention [ ( 39.62 ± 4.08 ) vs (46.41 ± 3.54 ) ;t =- 8.097,P ＜ 0.01 ].Conclusions Therapeutic-oriented communication play an active role in alleviating anxiety of patients with thyroid tumors,and can effectively improve the patient' s mental health.

Objective To optimize the short tandem repeats(STR)which link closely to survival motor neuron(SMN)and have redundant polymorphism information contents,and to use these STR in the prenatal diagnosis of spinal muscular atrophy(SMA).Methods Eleven STR loci(D5S435,D5F153, DSF151,D5S637,D5S1413,D5S125,D5S464,D5S1556,DSF149,D5S351,MAP1B-5')were amplified by PCR.Then the PCR products were detected by polyacrylamide gel electrophoresis(PAGE)and analyzed by silver staining.STR loci were evaluated and optimized by their PIC values.PCR-PAGE and gene scan were combined to make genetic link analysis for SMA families based on the optimized STR.Results Three STR loci(D5S435,DSF149 and D5S351)were selected with 8,19 and 18 polymorphic fragments detected respectively in 100 normal individuals.Their PIC values were 0.84,0.91 and 0.92 respectively.Four carriers and 2 normal individuals were detected from 6 SMA families with linkage analysis by using the 3 STR.Conclusion This genetic diagnosis system based on the 3 STR loci can provide rapid prenatal diagnosis for SMA families,can eliminate maternal blood contamination,and also can discriminate carriers from normal individuals in the fetuses,which makes the prenatal diagnosis system of SMA perfect.

Background: Platform work offers flexibility and autonomy to workers, but there are concerns about the impacts of excessive labor control exercised by digital platforms using algorithmic management. This study assessed the level of labor control exerted by digital platforms and explored its associations with psychosocial work conditions and workers' mental well-being. Methods: A total of 487 location-based platform workers in Taiwan, encompassing ride-hailing, delivery, and house chore services, participated in this questionnaire survey. A 5-item scale was created to assess platform-mediated labor control. Psychosocial work conditions, including demands, job control, work rewards, and mental well-being, including burnout and self-rated mental health status, were assessed using validated instruments. Cronbach's α and principal component analysis were employed to assess the validity of the labor control scale. Logistic regression analysis and path analysis were conducted to investigate the relationship between labor control and workers' mental health. Results: Exploratory factor analyses confirmed the structural validity and the internal consistency of the scale. Logistic regression models revealed that higher levels of labor control were associated with an increased risk of burnout and poorer mental health. Path analyses further indicated that higher labor control through digital platforms raised mental health risks by increasing job demands. Conclusion Algorithmic management is associated with increased stress among platform workers as they try to meet the platform's performance metrics.

Background: Platform work offers flexibility and autonomy to workers, but there are concerns about the impacts of excessive labor control exercised by digital platforms using algorithmic management. This study assessed the level of labor control exerted by digital platforms and explored its associations with psychosocial work conditions and workers' mental well-being. Methods: A total of 487 location-based platform workers in Taiwan, encompassing ride-hailing, delivery, and house chore services, participated in this questionnaire survey. A 5-item scale was created to assess platform-mediated labor control. Psychosocial work conditions, including demands, job control, work rewards, and mental well-being, including burnout and self-rated mental health status, were assessed using validated instruments. Cronbach's α and principal component analysis were employed to assess the validity of the labor control scale. Logistic regression analysis and path analysis were conducted to investigate the relationship between labor control and workers' mental health. Results: Exploratory factor analyses confirmed the structural validity and the internal consistency of the scale. Logistic regression models revealed that higher levels of labor control were associated with an increased risk of burnout and poorer mental health. Path analyses further indicated that higher labor control through digital platforms raised mental health risks by increasing job demands. Conclusion Algorithmic management is associated with increased stress among platform workers as they try to meet the platform's performance metrics.

Background: Platform work offers flexibility and autonomy to workers, but there are concerns about the impacts of excessive labor control exercised by digital platforms using algorithmic management. This study assessed the level of labor control exerted by digital platforms and explored its associations with psychosocial work conditions and workers' mental well-being. Methods: A total of 487 location-based platform workers in Taiwan, encompassing ride-hailing, delivery, and house chore services, participated in this questionnaire survey. A 5-item scale was created to assess platform-mediated labor control. Psychosocial work conditions, including demands, job control, work rewards, and mental well-being, including burnout and self-rated mental health status, were assessed using validated instruments. Cronbach's α and principal component analysis were employed to assess the validity of the labor control scale. Logistic regression analysis and path analysis were conducted to investigate the relationship between labor control and workers' mental health. Results: Exploratory factor analyses confirmed the structural validity and the internal consistency of the scale. Logistic regression models revealed that higher levels of labor control were associated with an increased risk of burnout and poorer mental health. Path analyses further indicated that higher labor control through digital platforms raised mental health risks by increasing job demands. Conclusion Algorithmic management is associated with increased stress among platform workers as they try to meet the platform's performance metrics.

Background: Platform work offers flexibility and autonomy to workers, but there are concerns about the impacts of excessive labor control exercised by digital platforms using algorithmic management. This study assessed the level of labor control exerted by digital platforms and explored its associations with psychosocial work conditions and workers' mental well-being. Methods: A total of 487 location-based platform workers in Taiwan, encompassing ride-hailing, delivery, and house chore services, participated in this questionnaire survey. A 5-item scale was created to assess platform-mediated labor control. Psychosocial work conditions, including demands, job control, work rewards, and mental well-being, including burnout and self-rated mental health status, were assessed using validated instruments. Cronbach's α and principal component analysis were employed to assess the validity of the labor control scale. Logistic regression analysis and path analysis were conducted to investigate the relationship between labor control and workers' mental health. Results: Exploratory factor analyses confirmed the structural validity and the internal consistency of the scale. Logistic regression models revealed that higher levels of labor control were associated with an increased risk of burnout and poorer mental health. Path analyses further indicated that higher labor control through digital platforms raised mental health risks by increasing job demands. Conclusion Algorithmic management is associated with increased stress among platform workers as they try to meet the platform's performance metrics.

Background: Platform work offers flexibility and autonomy to workers, but there are concerns about the impacts of excessive labor control exercised by digital platforms using algorithmic management. This study assessed the level of labor control exerted by digital platforms and explored its associations with psychosocial work conditions and workers' mental well-being. Methods: A total of 487 location-based platform workers in Taiwan, encompassing ride-hailing, delivery, and house chore services, participated in this questionnaire survey. A 5-item scale was created to assess platform-mediated labor control. Psychosocial work conditions, including demands, job control, work rewards, and mental well-being, including burnout and self-rated mental health status, were assessed using validated instruments. Cronbach's α and principal component analysis were employed to assess the validity of the labor control scale. Logistic regression analysis and path analysis were conducted to investigate the relationship between labor control and workers' mental health. Results: Exploratory factor analyses confirmed the structural validity and the internal consistency of the scale. Logistic regression models revealed that higher levels of labor control were associated with an increased risk of burnout and poorer mental health. Path analyses further indicated that higher labor control through digital platforms raised mental health risks by increasing job demands. Conclusion Algorithmic management is associated with increased stress among platform workers as they try to meet the platform's performance metrics.

Objective To prepare the survival motor neuron(SMN)polyclonal antibody and explore the localization of SMN protein in transfected cells and its expression in skeletal muscles of patients with spinal muscular atrophy(SMA).Methods A prokaryotic expressional plasmid named pET-28? (+)/SMN was constructed and SMN-His fusion protein was induced.The fusion protein was used to immunize New Zealadd rabbits to prepare SMN polyclonal antibody.A eukaryotic expressional plasmid named pcDNA3.1/myc-HisB-SMN was constructed and used to transfect CHO cells.Skeletal muscles were collected from 3 patients with bone fracture who were regarded as normal controls, and 3 SMA patients of type Ⅰ, 3 of type Ⅱ and 3 of type Ⅲ who were ascertained by genetic analysis.Western-blotting and immunofluorescence stain were applied to study the expression of SMN in transfected CHO cells and skeletal muscles of normal individuals and SMA patients.Results Correct pET-28a(+)/SMN prokaryotic expressive plasmid was constructed and SMN-His fusion protein was obtained from E coli BL21 transformed with pET-28a(+)/SMN.Then, rabbit anti-human full-length SMN polyclonal antibody of high specificity and sensitivity was obtained from rabbits immunized by SMN-His fusion protein.SMN proteins were shown diffusedly locating in the cytoplasm and nucleus of CHO cells transfected with pcDNA3.1/myc-HisB-SMN plasmid and mainly accumulating around the nucleus.The results of Western-blotting were as follows:the average ratio of SMN band density to glyceraldehyde phosphate dehydrogenase(GAPDH)band density (SMN/GAPDH)is 0.619 in skeletal muscles from normal controls, the average values of SMN/GAPDH in skeletal muscle from SMA patients of type Ⅲ and Ⅱ were 0.347 and 0.340 respectively, which were lower than that of normal controls.However, the average values of SMN/GAPDH in skeletal muscle from SMA patients of type I was only 0.079, which was quite lower than that of normal controls.Conclusions The rabbit anti-human full-length SMN polyclonal antibody is of high specificity and sensitivity, which makes the basis for the research of SMN function and SMA pathogenesis.There may be a correlation between the SMN level in skeletal muscle and the severity of disease.

Objective To explore the effect of Rational Emotive Therapy on depression and anxiety of patients with breast cancer. Methods A total of 82 patients with breast cancer were divided into the observation group (42 cases) and the contrast group (40 cases). They were investigated before and after the psychotherapy with Self-rating Depression Scale (SDS) and self-rating Anxiety Scale (SAS). Results The scores between the two groups were similar before intervention (P > 0. 05). while, after the psychotherapy, there were significant differences in each item of SDS and SAS (P <0. 01). Conclusions Rational Emotive Therapy is proved to be effective to improve the psychological status and promote healthy behaviors among breast cancer patients.