ObjectiveTo explore the relationship between acne vulgaris and gut microbiota. MethodsA total of 29 clinical cases diagnosed with moderate-to-severe acne vulgaris and 26 healthy individuals as control subjects were recruited. Fecal specimens were collected from all participants， and further analysis of gut microbial communities was performed by leveraging high-throughput sequencing techniques that target the hypervariable regions of 16S rRNA genes. ResultsAssociations between acne vulgaris and alterations in gut microbiota were identified. At the phylum level， the relative abundance of Bacteroidota exhibited a statistically significant elevation in the acne vulgaris cohort when compared with the healthy control group （P<0.01）， while Cyanobacteria was significantly lower in the acne group （P<0.01）. At the genus level， the top five different bacterial taxa in both groups were Bacteroides， Escherichia⁃Shigella， Klebsiella， Roseburia， and Parabacteroides. Among them， Bacteroides， Roseburia， and Parabacteroides were more abundant in acne patients. Linear discriminant analysis identified five biomarkers all belonging to the Bacteroidota phylum in the acne and control groups. These biomarkers belong to the phylum Bacteroidetes. ConclusionThere are significant differences in the composition of intestinal microbiota between acne patients and healthy people. Changes in the richness of specific bacterial genera may become new targets for the diagnosis and treatment of acne.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Objective To develop a platform for reporting medication near miss events and evaluate its application effectiveness,aiming to enhance medication safety of patients.Methods Based on literature review,qualitative interviews,and expert group meetings,a medication near-miss event reporting platform was constructed,including 4 modules:event content filling,event risk grading,event handling,and statistical analysis.50 nurses were conveniently selected from the pediatric ward of a tertiary grade A hospital in Henan Province as the application subjects.The reporting situation and filling duration of medication near miss events,the score of the Medication Near Miss Reporting Disorder Scale,and the incidence of medication near miss events were compared after the application of the platform(from March to August 2023)and before the application(from September 2022 to February 2023).Results The reporting rate of medication near miss events after the application of the platform was higher than that before the application of the platform,and the comparison of the distribution of event nature and occurrence links showed statistically significant differences(P＜0.05).After the application of the platform,the reporting duration of medication near miss events was shorter than that before the application of the platform,and the score of the Medication Near Miss Reporting Disorder Scale was lower than that before the application of the platform.The differences were statistically significant(P＜0.001).There was no statistically significant difference in the incidence of medication near miss events before and after the application of the platform(P=0.241).Conclusion Using this platform can help improve the reporting rate of medication near miss events,reduce the time taken to fill out reports,and minimize reporting barriers for nurses.

Receptor-interacting protein kinase 1 (RIPK1) plays an essential role in regulating the necroptosis and apoptosis in cerebral ischemia-reperfusion (I/R) injury. However, the regulation of RIPK1 kinase activity after cerebral I/R injury remains largely unknown. In this study, we found the downregulation of protein arginine methyltransferase 1 (PRMT1) was induced by cerebral I/R injury, which negatively correlated with the activation of RIPK1. Mechanistically, we proved that PRMT1 directly interacted with RIPK1 and catalyzed its asymmetric dimethylarginine, which then blocked RIPK1 homodimerization and suppressed its kinase activity. Moreover, pharmacological inhibition or genetic ablation of PRMT1 aggravated I/R injury by promoting RIPK1-mediated necroptosis and apoptosis, while PRMT1 overexpression protected against I/R injury by suppressing RIPK1 activation. Our findings revealed the molecular regulation of RIPK1 activation and demonstrated PRMT1 would be a potential therapeutic target for the treatment of ischemic stroke.

Objective To examine the effects of SMAD4 on the proliferation and apoptosis of ovarian granulosa cells in rats with poly-cystic ovary syndrome(PCOS).Methods A PCOS rat model was established using DHEA,and ovarian granulosa cells were extracted and cultured in vitro.The expression of SMAD4 in ovarian granulosa cells was detected by quantitative real-time PCR and Western blot-ting.SMAD4-siRNA was transfected into ovarian granulosa cells from PCOS rats.The expression of SMAD4 mRNA after transfection was determined by quantitative real-time PCR.Western blotting was performed to detect the expression levels of PCNA,BAX,and BCL-2 proteins after transfection.A CCK-8 assay was performed to evaluate cell growth after siRNA interference.Results The HE staining results revealed that the number of ovarian follicular vacuoles increased and that the number of granulosa cell layers and corpus luteum decreased,thus indicating the establishment of a PCOS model.The FSHR positivity rate exceeded 95％.SMAD4 expression in ovarian granulosa cells was higher in the PCOS group than in the control group(P＜0.05).Furthermore,siRNA effectively reduced SMAD4 expression in ovarian granulosa cells of PCOS rats(P＜0.01),promoted proliferation,and inhibited the apoptosis of granulosa cells.Con-clusion The hindered growth of ovarian granulosa cells in PCOS rats may be linked to the overexpression of SMAD4 mRNA,which sug-gests that targeting SMAD4 could be a promising approach for treating ovulatory abnormalities in patients with PCOS.

Objective To examine the effects of SMAD4 on the proliferation and apoptosis of ovarian granulosa cells in rats with poly-cystic ovary syndrome(PCOS).Methods A PCOS rat model was established using DHEA,and ovarian granulosa cells were extracted and cultured in vitro.The expression of SMAD4 in ovarian granulosa cells was detected by quantitative real-time PCR and Western blot-ting.SMAD4-siRNA was transfected into ovarian granulosa cells from PCOS rats.The expression of SMAD4 mRNA after transfection was determined by quantitative real-time PCR.Western blotting was performed to detect the expression levels of PCNA,BAX,and BCL-2 proteins after transfection.A CCK-8 assay was performed to evaluate cell growth after siRNA interference.Results The HE staining results revealed that the number of ovarian follicular vacuoles increased and that the number of granulosa cell layers and corpus luteum decreased,thus indicating the establishment of a PCOS model.The FSHR positivity rate exceeded 95％.SMAD4 expression in ovarian granulosa cells was higher in the PCOS group than in the control group(P＜0.05).Furthermore,siRNA effectively reduced SMAD4 expression in ovarian granulosa cells of PCOS rats(P＜0.01),promoted proliferation,and inhibited the apoptosis of granulosa cells.Con-clusion The hindered growth of ovarian granulosa cells in PCOS rats may be linked to the overexpression of SMAD4 mRNA,which sug-gests that targeting SMAD4 could be a promising approach for treating ovulatory abnormalities in patients with PCOS.

Objective To develop a platform for reporting medication near miss events and evaluate its application effectiveness,aiming to enhance medication safety of patients.Methods Based on literature review,qualitative interviews,and expert group meetings,a medication near-miss event reporting platform was constructed,including 4 modules:event content filling,event risk grading,event handling,and statistical analysis.50 nurses were conveniently selected from the pediatric ward of a tertiary grade A hospital in Henan Province as the application subjects.The reporting situation and filling duration of medication near miss events,the score of the Medication Near Miss Reporting Disorder Scale,and the incidence of medication near miss events were compared after the application of the platform(from March to August 2023)and before the application(from September 2022 to February 2023).Results The reporting rate of medication near miss events after the application of the platform was higher than that before the application of the platform,and the comparison of the distribution of event nature and occurrence links showed statistically significant differences(P＜0.05).After the application of the platform,the reporting duration of medication near miss events was shorter than that before the application of the platform,and the score of the Medication Near Miss Reporting Disorder Scale was lower than that before the application of the platform.The differences were statistically significant(P＜0.001).There was no statistically significant difference in the incidence of medication near miss events before and after the application of the platform(P=0.241).Conclusion Using this platform can help improve the reporting rate of medication near miss events,reduce the time taken to fill out reports,and minimize reporting barriers for nurses.

Objective To explore the effect of FBXW7 on ferroptosis in head and neck squamous cell carcinoma.Methods Head and neck squamous cell lines HN4 and HN6 were cultured in vitro.FBXW7 and SOX2 overexpression plasmids were constructed,and the plasmids were stably transfected into cell lines.The overexpression transfection efficiency was verified at the transcription level and protein level by qRT-PCR and Western blot experiments,respectively.The lipid peroxidation levels of head and neck squamous cell carcinoma cells with overexpressing FBXW7 were verified by measuring malondialdehyde(MDA),glutathione(GSH),and reactive ox-ygen species(ROS)levels.After treating cells with ferroptosis inhibitor Fer-1,the changes in cell viability were further detected to ver-ify the effect of FBXW7 on ferroptosis.The effect of transfection of the overexpressed plasmid on cellular pathways was detected by Western blot.Results HN4 and HN6 cell lines showed increased levels of lipid peroxidation after overexpression of FBXW7,and the ferroptosis inhibitor Fer-1 was able to effectively reverse the ferroptosis induced by overexpression of FBXW7.Western blot assay results showed that overexpression of FBXW7 reduced the expression of c-Myc,SOX2 and SLC7A11.Conclusion FBXW7 regulates the ex-pression of SOX2-SLC7A11 by degrading c-Myc,thereby effectively regulating ferroptosis in HNSCC.