Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective:To investigate the current status of endoscopic treatment for gastroesophageal varices in portal hypertension in China, and to provide supporting data and reference for the development of endoscopic treatment.Methods:In this study, initiated by the Liver Health Consortium in China (CHESS), a questionnaire was designed and distributed online to investigate the basic condition of endoscopic treatment for gastroesophageal varices in portal hypertension in 2022 in China. Questions included annual number and indication of endoscopic procedures, adherence to guideline for preventing esophagogastric variceal bleeding (EGVB), management and timing of emergent EGVB, management of gastric and isolated varices, and improvement of endoscopic treatment. Proportions of hospitals concerning therapeutic choices to all participant hospitals were calculated. Guideline adherence between secondary and tertiary hospitals were compared by using Chi-square test.Results:A total of 836 hospitals from 31 provinces (anotomous regions and municipalities) participated in the survey. According to the survey, the control of acute EGVB (49.3%, 412/836) and the prevention of recurrent bleeding (38.3%, 320/836) were major indications of endoscopic treatment. For primary [non-selective β-blocker (NSBB) or endoscopic therapies] and secondary prophylaxis (NSBB and endoscopic therapies) of EGVB, adherence to domestic guideline was 72.5% (606/836) and 39.2% (328/836), respectively. There were significant differences in the adherence between secondary and tertiary hospitals in primary prophylaxis of EGVB [71.0% (495/697) VS 79.9% (111/139), χ2=4.11, P=0.033] and secondary prophylaxis of EGVB [41.6% (290/697) VS 27.3% (38/139), χ2=9.31, P=0.002]. A total of 78.2% (654/836) hospitals preferred endoscopic therapies treating acute EGVB, and endoscopic therapy was more likely to be the first choice for treating acute EGVB in tertiary hospitals (82.6%, 576/697) than secondary hospitals [56.1% (78/139), χ2=46.33, P<0.001]. The optimal timing was usually within 12 hours (48.5%, 317/654) and 12-24 hours (36.9%, 241/654) after the bleeding. Regarding the management of gastroesophageal varices type 2 and isolated gastric varices type 1, most hospitals used cyanoacrylate injection in combination with sclerotherapy [48.2% (403/836) and 29.9% (250/836), respectively], but substantial proportions of hospitals preferred clip-assisted therapies [12.4% (104/836) and 26.4% (221/836), respectively]. Improving the skills of endoscopic doctors (84.2%, 704/836), and enhancing the precision of pre-procedure evaluation and quality of multidisciplinary team (78.9%, 660/836) were considered urgent needs in the development of endoscopic treatment. Conclusion:A variety of endoscopic treatments for gastroesophageal varices in portal hypertension are implemented nationwide. Participant hospitals are active to perform emergent endoscopy for acute EGVB, but are inadequate in following recommendations regarding primary and secondary prophylaxis of EGVB. Moreover, the selection of endoscopic procedures for gastric varices differs greatly among hospitals.

Animals ; Macaca mulatta ; Optic Disk ; Glaucoma ; Craniocerebral Trauma ; Intraocular Pressure ; Low Tension Glaucoma

Objective To explore the effectiveness of FOCUS-PDCA(find,organise,clarify,understand,select,plan,do,check and act)mode in prevention and treatment of incontinence-associated dermatitis(IAD)in emergency intensive care unit(EICU),and to reduce the incidence of IAD.Methods A pre-post control study design was employed in this study.Inpatients admitted to the EICU of the hospital between 1st January and 31st December 2022 were enrolled as study subjects.A total of 169 patients in EICU between January and June 2022 were assigned as a control group,while 197 patients in EICU between July and December 2022 as an trial group.Patients in the control group received conventional quality management,while those in the trial group were treated with the FOCUS-PDCA mode.The two groups were compared in terms of incidence of IAD,the knowledge,trust and behaviour scores of the nurses,and satisfaction from the communications with nurses before and after implementation of the FOCUS-PDCA mode.Results All patients in the two groups had completed the study.Following the implementation of FOCUS-PDCA mode,patients in the trial group exhibited a significantly decrease in incidence of IAD from 10.06%(trial group)to 1.52%(control group),significant increase of scores on the IAD knowledge,behaviour and satisfaction from communications with the nurses,from(36.07±3.98),(16.56±2.15)and(25.15±5.21),to(38.59±3.72),(18.07±1.66),and(30.67±5.84),respectively(all P<0.05).Conclusion FOCUS-PDCA mode can effectively decrease the incidence of IAD,enhance the IAD knowledge and behaviour of nurses and gain satisfactions from communication with nursing staff and clinical quality,thereby improving therapeutic outcomes.

Squamosa promoter binding protein-like (SPL) family is a group of important transcription factors involved in the regulation of plant growth and development and the response to environmental stress, but there are few studies in perennial fruit trees such as citrus. In this study, Ziyang Xiangcheng (Citrus junos Sib.ex Tanaka), an important rootstock of Citrus, was used as the material for analysis. Based on plantTFDB transcription factor database and sweet orange genome database, 15 SPL family members were genome-widely identified and cloned from Ziyang Xiangcheng, and named CjSPL1-CjSPL15. Sequence analysis showed that the open reading frame (ORF) length of CjSPLs ranged from 393 bp to 2 865 bp, encoding 130-954 amino acids. Phylogenetic tree divided 15 CjSPLs into 9 subfamilies. Gene structure and conserved domain analysis predicted 20 different conserved motifs and SBP basic domains. Analysis of cis-acting promoter elements predicted 20 different promoter elements, including those related to plant growth and development, abiotic stress and secondary metabolites. The expression patterns of CjSPLs under drought, salt and low temperature stresses were analyzed by real-time fluorescence quantitative PCR (qRT-PCR), and many CjSPLs were significantly up-regulated after stress treatment. This study provides a reference for further study on the function of SPL family transcription factors in citrus and other fruit trees.
Phylogeny ; Transcription Factors/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Multigene Family ; Stress, Physiological

Objective: To elucidate clinical characteristics and build a prognostic nomogram for patients with vulvar cancer. Methods: The study population was drawn from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly assigned to training and validation sets. Cox proportional hazards model and competing risk model were used to identify the prognostic parameters of overall survival (OS) and cancer-specific survival (CSS) to construct a nomogram. The nomogram was assessed by concordance index (C-index), area under the curve (AUC), calibration plot, and decision curve analysis (DCA). Results: A total of 20,716 patients were included in epidemiological analysis, of whom 7,025 patients were selected in survival analysis, including 4,215 and 2,810 in training and validation sets, respectively. The multivariate Cox model showed that the predictors for OS were age, marital status, histopathology, differentiation and tumor node metastasis (TNM) stages, whether to undergo surgery and chemotherapy. However, the predictors for CSS were age, race, differentiation and TNM stages, whether to undergo surgery and radiation. The C-index for OS and CSS in the training set were 0.76 and 0.80. The AUC in the training set for 1-, 3- and 5-year OS and CSS were 0.84, 0.81, 0.80 and 0.88, 0.85, 0.83, respectively, which was similar in the validation set. The calibration curves showed good agreement between prediction and actual observations. DCA revealed that the nomogram had a better discrimination than TNM stages. Conclusions The nomogram showed accurate prognostic prediction in OS and CSS for vulvar cancer, which could provide guidance to clinical practice.

Objective:To summarize the clinical features of special portal hypertension-Abernethy malformation reported at home and abroad.Methods:The relevant literature on Abernethy malformation published at home and abroad from January 1989 to August 2021 was collected. Patients'clinical features, imaging and laboratory test results, diagnosis, treatment, and prognosis were analyzed.Results:A total of 380 cases were included from 60 and 202 domestic and foreign literatures. Among them, there were 200 cases of type I, with 86 males and 114 females, and the average age was (17.08±19.42) years, while there were 180 cases of type II, with 106 males and 74 females, and the average was (14.85±19.60) years. The most common reason for the first visit of an Abernethy malformation patient's was gastrointestinal system symptoms such as hematemesis and hematochezia caused by portal hypertension (70.56%). Multiple malformations were present in 45.00% of type Ⅰ and 37.80% of type Ⅱ patients. The most prevalent condition was congenital heart disease (62.22%, and 73.53%). Complications related to Abernethy malformation was occurred in 127 and 105 cases with type I and type II, respectively, with liver lesions in 74.02% (94/127) and 39.05% (42/105) and hepatopulmonary syndrome of 33.07% (42/127) and 39.05% (41/105), respectively. The imaging diagnosis of type I and type II Abernethy malformations were mainly based on abdominal computed tomography (59.00%, and 76.11%). Liver pathology was performed in 27.10% of patients. Blood ammonia increased by 89.06% and 87.50%, and AFP increased by 29.63% and 40.00% in laboratory findings. 9.76% (8/82) and 6.92% (9/130) died, while 84.15% (61/82) and 88.46% (115/130) had improved conditions after medical conservative, or surgical treatment.Conclusion:Abernethy malformation is a rare disease in which congenital portal vein development abnormalities lead to significant portal hypertension and portasystemtic shunt. Patients often seek medical treatment for gastrointestinal bleeding and abdominal pain. Type Ⅰ is more common in women, often associated with multiple malformations, and prone to secondary intrahepatic tumors. Liver transplantation is the main treatment method. Type Ⅱ is more prevalent in males, and shunt vessel occlusion is the first treatment choice. Overall, type Ⅱ has a better therapeutic impact than type Ⅰ.

According to the subject characteristics of radiation oncology, three teaching practices were carried out in the teaching of standardized residency training: teaching situation transformation under the guidance of constructivism theory, expanding teaching with points to areas, and organ system-centered medical classroom under the guidance of case analysis. At the same time, it combines the guidance of the residents' active exploration, integrated thinking and cooperative learning. Through the modulation of teaching and learning practices guided by constructivism, the residents' learning and understanding of radiation oncology knowledge and the integration and construction ability of "organ system-centered" medical knowledge are promoted, their active learning potential and innovative thinking ability are stimulated, and finally the teaching quality of this specialty is improved.