Objective:To develop a network-structured clinical pathway grouping rule based on the principles and methods of China healthcare security diagnosis related groups(CHS-DRG), for references for optimizing clinical pathway management.Methods:From August to November 2024, this study constructed a network-structured clinical pathway management framework, followed the grouping principles of CHS-DRG, and developed a network-structured clinical pathway grouping rule through literature analysis and expert discussions. 54 clinical specialists from the sample hospital were organized and grouped according to the rule for the normal magnification cases(139 218 cases) of DRG medical insurance settlement in the hospital in 2023. Using a stratified random sampling method, 205 physicians from 54 clinical specialties in the hospital were selected to quantitatively evaluate the rationality, homogeneity, and clarity of the grouping results. The Likert 5-level scoring method was wsed to assign scores.Results:The network-structured clinical pathway grouping rule and nomenclature was established. A total of 341 main pathways and 35 sub-pathways covering 169 adjacent diagnosis related groups were formed. The quantitative assessment scores for rationality, homogeneity, and clarity were 4.90, 4.87 and 4.87 points, respectively.Conclusions:The network-structured clinical pathway grouping rule based on CHS-DRG had good, feasibility and standardization, and could meet the practical needs of clinical applications.

AIM To study the chemical constituents from the stems and barks of Maytenus variabilis(Hemsl.)C.Y.Cheng.METHODS The 95％ethanol extract from the stems and barks of M.variabilis was isolated and purified by silica gel,Sephadex LH-20 and semi preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Twenty-three compounds were isolated and identified as β-amyrin(1),3β-acetoxyolean-12-en-11-one(2),ursa-12-ene-11-one-3-ol octocosate(3),friedelin(4),canophyllol(5),pinoresinol(6),medioresinol(7),isolariciresinol(8),dihydrodehydrodiconiferyl alcohol(9),vanillic acid(10),7R,8S-5-methoxydihydrodehydroconiferyl alcohol(11),β-hydroxypropiovanillone(12),triptregeline B(13),triptregeline E(14),(+)-evofolin B(15),2,5-dimethoxybenzoquinone(16),olean-12-ene-3,11-dione(17),β-sitosterol(18),(-)-(7R,7'R,7"S,8S,8'S,8"S)-4',4"-dihydroxy-3,3',3",5-tetramethoxy-7,9',7',9-diepoxy-4,8"-oxy-8,8'-sesquineolignan-7",9"-diol(19),phyllostadimer B(20),rayalinol(21),lyoniresinol(22),dihydrobuddlenol B(23).CONCLUSION Compounds 3,9-11,13-14,16,19-21,23 are isolated from genus Maytenus for the first time,and compounds 2,4-5,7-8,12,15,17,22 are first found from this plant.

AIM To study the chemical constituents of Anaphalis margaritacea(L.)Benth.& Hook.f.and their antioxidant activities.METHODS Separation and purification were performed using silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH method and ABTS method.RESULTS Twenty-three compounds were isolated and identified as trans-tilidroside(1),4'-hydroxydehydrokawain(2),apigenin(3),3-O-kaempferol-3-O-acetyl-6-O-(p-coumamoyl)-α-D-glucopyranoside(4),kaempferol(5),quercetin-3-O-β-D-(6-O-Z-p-coumamoyl)-glucopyranoside(6),tiliroside(7),kaempferol-3-O-β-D-glucoside(8),3,5-dihydroxy-7,8-dimethoxyflavone(9),bis(2-ethylhexyl)adipate(10),3,5-dihydroxy-6,7,8-trimethoxyflavone(11),stigmasterol(12),myriophylloside B(13),1-hexadecanol(14),chlorogenic acid(15),4-hydroxy-N-{ 4-[3-(4-hydroxyphenyl)-E-acryloylamino]-butyl}-benzamide(16),3,6-dimethylpiperazine-2,5-dione(17),β-adenosine(18),5,6-dehydrokawain(19),kaempferol-3-O-(2",6"-di-O-E-p-coumaroyl)-β-D-glucopyranoside(20),kaempferol-3-O-(3"-O-E-p-coumaroyl)-(6"-O-E-feruloyl)-β-D-glucopyranoside(21),4,5-di-caffeoylquinic acid butyl ester(22),3,4-di-caffeoylquinic acid butyl ester(23).The IC50 values of compounds 1,7,22-23 against DPPH free radicals were(24.67±1.63)-(53.41±1.61)μmol/L,and the IC50 values of compounds 8,21-23 against ABTS+free radicals were(15.22±0.89)-(41.66±6.29)μmol/L.CONCLUSION Compounds 9,19-23 are isolated from genus Anaphalis for the first time,and 2,10,13,14,16,17,19-23 are first isolated from this plant.Compounds 1,7-8,21-23 have strong antioxidant activity.

Objective To explore the chain mediating effects of family care and psychosocial adaptation between stigma and social alienation in patients with psoriasis.Methods A convenience sample of 465 psoriasis patients treated from January 2022 to March 2024 was enrolled in this study.Data were collected using a general information questionnaire,Social Impact Scale(SIS),Family Care Index Questionnaire(FCIQ),Ostomy Psychosocial Adaptation Scale(OPAS),and General Alienation Scale(GAS).A pilot study with 30 participants was conducted to assess the feasibility of the questionnaires.Dual data entry and logical checks were performed by trained investigators.Results Demographic analysis showed significant differences in stigma scores among patients with different disease durations(F=4.32,P=0.013)and severity levels(F=6.87,P=0.001).The total scores for stigma,family care,psychosocial adaptation,and social alienation were 65.12±12.34,5.25±2.48,33.21±12.14,and 37.36±7.19,respectively.Stigma was positively correlated with social alienation(r=0.612)and negatively corre-lated with family care(r=-0.411)and psychosocial adaptation(r=-0.536)(all P<0.05).Family care and psychosocial adaptation had a chain mediating effect between stigma and social alienation,with a mediating effect value of 0.327,accounting for 45.21％ of the total effect.Conclusion Stigma directly impacts social alienation in psoriasis patients and indirectly affects it through family care and psychosocial adaptation.Healthcare professionals can reduce social alienation by enhancing family care and psychosocial adaptation through intervention support networks.

Objective:To investigate the prevalence of scoliosis among middle school students through school-based screening, and to analyze the correlations between axial trunk rotation (ATR) angle and Cobb angle among those with scoliosis considering gender, age, body mass index (BMI) and curve type, so as to provide references for early prevention and treatment.Methods:Random cluster sampling was used to enroll 9501 middle school students from 11 schools in the Hanyang District of Wuhan. They underwent a six-step scoliosis screening with a forward bending test, scoliometer measurements, and confirmatory X-ray examinations. The students exhibiting scoliosis were stratified by gender, age, BMI, and curve type. The correlation between ATR angle and Cobb angle was subsequently analyzed within each subgroup.Results:Scoliosis was observed in 358 of the students (150 boys and 208 girls), a positive screening rate of 3.8%. Moreover, the positive screening rate was significantly higher among the girls (4.8%) than among the boys (2.9%). There was a moderate Spearman correlation ( r=0.69) between the ATR and Cobb angles in 358 of the students with scoliosis, both the boys ( r=0.69) and the girls ( r=0.70). When it came to age, there was a positive correlation between the ATR and Cobb angles for students aged 13 to 16 irrespective of their BMI classification, except that there was no significant correlation between the two angles for those classified as obese. In terms of Peking Union Medical College (PUMC) classification, there was a positive correlation for those in types Ia, Ib, Ic, IIa, IIb, IIc and IId, but there was no significant correlation between the two angles for those in type III. Conclusions:Scoliosis is prevalent among the group of adolescents studied. Society, schools and parents need to prioritize prevention, heightened awareness, timely diagnosis and early treatment, particularly for girls. The ATR angle may serve as a practical surrogate for estimating Cobb angle severity in scoliosis screening for single-curve or double-curve cases. However, ATR measurements may yield false-negative results among those with triple-curve deformities or the obese, underscoring the need for supplementary diagnostic methods among such populations.

Objective To develop a Nomogram clinical prediction model for the pathological occurrence of extraprostatic extension(EPE)after radical prostatectomy in prostate cancer patients,using simplified site-specific magnetic resonance imaging(MRI)indicators and other clinical parameters.Methods A total of 181 prostate cancer patients[mean age(69.0±7.3)years]who underwent radical prostatectomy were included.These patients had received 3-Tesla multi-parametric magnetic resonance imaging(3-T mpMRI)within 6 months prior to surgery.Based on mpMRI measurements[capsular contact length(CCL)>15 mm,capsular bulging/irregularities,diameter of index lesion(dIL),and evident extraprostatic extension(eEPE)],the dIL?sEPE grading system was derived.The optimal cut-off value of dIL(denoted as dIL)was determined using the Youden J index,and categorized it into a binary variable.A Logistic regression model was established based on the dIL?sEPE grading and clinical scores.The predictive performance of clinical indicators,MRI indicators,and combined clinical and MRI indicators were compared.Finally,a clinical prediction model integrating both clinical and MRI data was developed.Results Pathological EPE was found in 46 out of 181 cases(25.4% ).A Nomogram prediction model for EPE was established with a combination of the dIL?sEPE grading and clinical indicators.Conclusion The combination of dIL?sEPE grading with clinical indicators accurately predicts extracapsular extension in prostate cancer.The Nomogram model that established,based on MRI imaging characteristics and clinical indicators has good performance and is easy to use.It is beneficial to stratifying management for prostate cancer patients,and it provides valuable guidance for patients suitable for nerve-sparing surgery.

[Purpose]To analyze the trends of cancer incidence and mortality from 1991 to 2020 in Jiashan County of Zhejiang Province,and to predict trends from 2021 to 2035.[Methods]Cancer cases and deaths from 1991 to 2020 in Jiashan County were collected.The crude inci-dence rate and mortality rate,age-standardized rate(ASR)were calculated.The annual percentage change(APC)and average annual percentage change(AAPC)were calculated by Joinpoint model to analyze the trend of cancer incidence and mortality.The age-period-cohort model was used to predict the trends of cancer incidence and mortality from 2021 to 2035 and the estimated annual percentage change(EAPC)was calculated.[Results]The age-standardized incidence rates by Chinese standard population(ASIRC)in Jiashan were 159.06/105,187.25/105,and 254.37/105 during 1991-2000,2001-2010,and 2011-2020,respectively.The trends in young and middle-aged women and people above 65 years old were more predominant.Lung,stomach,colorectal,liver and female breast cancers were major incident cancers for the period from 1991 to 2020.The cancer incidence showed an increasing trend from 1991 to 2020(AAPC=2.17％,P＜0.05)and is expect-ed to continue to increase over 2021 to 2035(EAPC=3.03％,P＜0.05).The age-standardized mor-tality rates by Chinese standard population(ASMRC)in Jiashan were 119.74/105,117.79/105,and 100.11/105 during 1991-2000,2001-2010,and 2011-2020,respectively.Lung,liver,stomach,colorectal,esophageal,and pancreatic cancers were leading causes of cancer deaths from 1991 to 2020.The cancer mortality showed a decreasing trend from 1991 to 2020(AAPC=-1.00％,P＜0.05)and is expected to continue to decline over 2021 to 2035(EAPC=-1.67％,P＜0.05).[Conclusion]The mortality rate from cancers has been gradually declined in Jiashan County,while the incidence rate has increased significantly and will continue to increase in the next 15 years.High incidence of lung cancer,liver cancer,gastric cancer and colorectal cancer makes it crucial to pay close attention to key groups and strengthen the control of risk factors of high inci-dence cancer.

Objective:To develop a network-structured clinical pathway grouping rule based on the principles and methods of China healthcare security diagnosis related groups(CHS-DRG), for references for optimizing clinical pathway management.Methods:From August to November 2024, this study constructed a network-structured clinical pathway management framework, followed the grouping principles of CHS-DRG, and developed a network-structured clinical pathway grouping rule through literature analysis and expert discussions. 54 clinical specialists from the sample hospital were organized and grouped according to the rule for the normal magnification cases(139 218 cases) of DRG medical insurance settlement in the hospital in 2023. Using a stratified random sampling method, 205 physicians from 54 clinical specialties in the hospital were selected to quantitatively evaluate the rationality, homogeneity, and clarity of the grouping results. The Likert 5-level scoring method was wsed to assign scores.Results:The network-structured clinical pathway grouping rule and nomenclature was established. A total of 341 main pathways and 35 sub-pathways covering 169 adjacent diagnosis related groups were formed. The quantitative assessment scores for rationality, homogeneity, and clarity were 4.90, 4.87 and 4.87 points, respectively.Conclusions:The network-structured clinical pathway grouping rule based on CHS-DRG had good, feasibility and standardization, and could meet the practical needs of clinical applications.

AIM To study the chemical constituents from the stems and barks of Maytenus variabilis(Hemsl.)C.Y.Cheng.METHODS The 95％ethanol extract from the stems and barks of M.variabilis was isolated and purified by silica gel,Sephadex LH-20 and semi preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Twenty-three compounds were isolated and identified as β-amyrin(1),3β-acetoxyolean-12-en-11-one(2),ursa-12-ene-11-one-3-ol octocosate(3),friedelin(4),canophyllol(5),pinoresinol(6),medioresinol(7),isolariciresinol(8),dihydrodehydrodiconiferyl alcohol(9),vanillic acid(10),7R,8S-5-methoxydihydrodehydroconiferyl alcohol(11),β-hydroxypropiovanillone(12),triptregeline B(13),triptregeline E(14),(+)-evofolin B(15),2,5-dimethoxybenzoquinone(16),olean-12-ene-3,11-dione(17),β-sitosterol(18),(-)-(7R,7'R,7"S,8S,8'S,8"S)-4',4"-dihydroxy-3,3',3",5-tetramethoxy-7,9',7',9-diepoxy-4,8"-oxy-8,8'-sesquineolignan-7",9"-diol(19),phyllostadimer B(20),rayalinol(21),lyoniresinol(22),dihydrobuddlenol B(23).CONCLUSION Compounds 3,9-11,13-14,16,19-21,23 are isolated from genus Maytenus for the first time,and compounds 2,4-5,7-8,12,15,17,22 are first found from this plant.

Aim To explore the in vitro anti-human triple-negative breast cancer(TNBC)effect and mech-anism of Austocystin R.Methods MTT assay was used to evaluate the anti-tumor potential of Austocystin R for various human tumor cells and normal cells.Flow cytometry was employed to evaluate the influence on cell cycle progression.mRFP-GFP-LC3 adenovirus transfection was used to evaluate the autophagic flux process.Western blot assay was used to verify the effect of Austocystin R on the expression of related pro-teins.Results The results showed that Austocystin R significantly inhibited the proliferation of multiple tumor cells in a dose-dependent manner,especially for the MDA-MB-231 cells with an IC50 of 1.45μmol·L-1.In addition,Austocystin R increased the protein expression of PTEN,p53,p-p53,p27,p21,and down-regulated the expression of p-PI3K,p-AKT and p-mTOR.Austocystin R can significantly increase the proportion of S-phase MDA-MB-231 cells,inhibit the expression of Cyclin D1,CDK4,CDK6,Rb,Cyclin B1 and CDK1,and promote the expression of Cyclin E1 and CDK2.Austocystin R can promote the autophagic flux process of MDA-MB-231 cells,promote the expres-sion of LC3 Ⅰ/Ⅱ,p-Beclin-1,p-ULK1,HMGB-1 and Atg 14 proteins,and inhibit the expression of Beclin-1,ULK1,p62,ATG 3,ATG 4B,ATG 5,ATG 7,ATG 12,ATG 13 and ATG 16L1 proteins.Conclusion Austo-cystin R can exhibit its anti-TNBC activity by inhibi-ting the PI3K/AKT/mTOR signaling pathway,blocking the cell cycle at the S phase and inducing autophagic cell death.