Objective:To construct a prior based on the inherent properties of PET to accurately segment the lesion areas.Methods:A network framework for PET tumor segmentation driven by geodesic priors was proposed (geodesic network for short). Specifically, partial differential equations were constructed to characterize the geodesic distances between different regions in PET images. Tumor marker points identified by CT labeling were used as the initial conditions for the equations. To enhance the contrast between areas of lung or breast tumors and normal tissues, a smooth Heaviside function was utilized to map the geodesic distances. The network framework adopted a dual-branch architecture, using geodesic priors to assist in PET image segmentation.Results:The proposed method achieved a Dice coefficient of 94.92% in lung cancer segmentation and 90.12% in breast cancer segmentation. With the addition of geodesic priors in the Unet, the Dice coefficient for breast cancer increased by 32.37% (from 42.50% to 74.87%).Conclusion:Geodesic priors can significantly improve segmentation outcomes and enhance the generalization capability of the network.

Branch atheromatous disease(BAD)is a type of ischemic stroke that is prone to early neurological deterioration(END),which profoundly impacts patient prognosis and remains a focus of clinical research and practice.This article reviews the diagnosis,risk factors,risk prediction,along with imaging and prevention strategies of END in BAD patients,aiming to provide a theoretical basis for the early clinical identification and intervention of END to improve the prognosis of patients with BAD.

Background Exposure to ozone (O₃) is closely associated with an increased risk of mortality in the population, but this association exhibits regional heterogeneity, and relevant research in northern and central-western China is limited. Hohhot, as a typical city in the northern and western region, has seen a significant upward trend in O₃ concentrations (an increase of 17.9 μg·m⁻³ in 2020 compared to 2016). Studies targeting this region can fill the regional research gap. Objective To evaluate the health effects of ground-level O₃ exposure on resident mortality in Hohhot from 2018 to 2023. Methods Air quality, meteorological, and mortality data in Hohhot from 2018 to 2023 were collected. A time-series analysis based on Quasi-Poisson generalized additive model (GAM) was employed, controlling for meteorological factors, day-of-week effects, and holiday effects, to assess the impact of O₃ on non-accidental mortality, mortality from circulatory system diseases (CSD), and mortality from respiratory system diseases (RSD). Results From 2018 to 2023, the non-accidental, CSD, and RSD mortalities in Hohhot amounted to 89721, 47394, and 11378 cases, respectively. The daily maximum 8-hour average O₃ concentration (O₃-8 h) was 90.00 μg·m⁻³. According to the Class I limit (100 μg·m⁻³) of GB 3095—2012 Ambient Air Quality Standard, the annual average number of days exceeding the standard was 144 d. For single-day lag effects, O₃ had the strongest health impact on non-accidental mortality and CSD mortality on the current day (lag0), with effect sizes of 0.78% (95%CI: 0.33%, 1.24%) and 1.10% (95%CI: 0.50%, 1.71%), respectively. The strongest impact on RSD mortality occurred on the second day (lag2), with an effect size of 1.61% (95%CI: 0.61%, 2.62%). The subgroup analyses showed that for every 10 μg·m⁻³ increase in O₃-8 h concentration, the risk of non-accidental mortality in females increased by 0.70% (95%CI: 0.01%, 1.41%); for CSD mortality, the risk in males and individuals aged ≥65 years increased by 0.73% (95%CI: 0.01%, 1.47%) and 0.76% (95%CI: 0.13%, 1.39%), respectively. During the warm season, statistically significant risks were observed for non-accidental, CSD, and RSD mortalities, with increases of 1.07% (95%CI: 0.54%, 1.60%), 1.31% (95%CI: 0.59%, 2.04%), and 2.27% (95%CI: 1.07%, 3.49%), respectively. In the two-pollutant models incorporating sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), particulate matter with an aerodynamic diameter of 10 micrometers or less (PM₁₀), and fine particulate matter (PM_2.5), the effect estimates (excess risk) of O₃ remained stable and statistically significant (P<0.05), indicating model robustness. Conclusion Ground-level O₃ exposure in Hohhot increases mortalities due to non-accidental causes, CSD, and RSD, with more pronounced effects during the warm season. Females and individuals aged ≥65 years may be susceptible populations. Therefore, relevant authorities should prioritize the potential health risks of O₃ exposure, particularly to vulnerable groups, and promote targeted prevention and control strategies.

Objective To compare the predictive effectiveness of the Glasgow coma scale(GCS),GCS-pupils scale(GCS-P),Glasgow-Pittsburgh coma scale(GPCS),full outline of unresponsiveness scale(FOUR),and coma recovery scale-revised(CRS-R)in forecasting the prognosis of severe stroke patients.Methods A prospective,consecutive cohort of severe stroke patients admitted to the Department of Neurology,First Medical Center of Chinese PLA General Hospital from September 2021 to April 2024 was enrolled.Demographic and clinical data were collected,including age,sex,length of hospital stay,diagnosis(severe ischemic stroke,severe cerebral hemorrhage,aneurysmal subarachnoid hemorrhage),medical history(hypertension,diabetes,coronary artery disease),smoking and drinking habits,vital signs upon admission(temperature,pulse,respiration,blood pressure),neurological examination findings(including speech and brainstem reflexes)at admission,head imaging results(CT,MRI)within 24 h of admission to assess the presence of brain herniation,and whether intubation occurred within 24 h of admission.Patients underwent GCS,GCS-P,GPCS,FOUR,and CRS-R scoring within 8h of admission.Telephone follow-up was conducted at 6 months post-stroke to assess outcomes using the modified Rankin scale(mRS),with mRS scores of 0-2 classified as the good prognosis group and 3-6 as the poor prognosis group.The receiver operating characteristic(ROC)curve was used to assess the prognostic prediction value of the five scales for poor outcomes at 6 months.The area under the ROC curve(AUC)was calculated,and pairwise comparisons of AUC were performed using the Delong test.Results A total of 179 severe stroke patients were enrolled,including 116 males and 63 females.The group consisted of 132 patients with severe ischemic stroke,30 with severe intracerebral hemorrhage,and 17 with aneurysmal subarachnoid hemorrhage.At 6months,126patients had a poor prognosis and 53 had a good prognosis.(1)There were statistically significant differences in age,temperature,pulse,history of coronary artery disease,smoking and drinking habits,presence of speech impairment,abnormal brainstem reflexes,brain herniation,intubation within 24 h of admission,and GCS,GCS-P,GPCS,FOUR,and CRS-R scores between the poor and good prognosis groups(all P＜0.05).(2)ROC analysis revealed that the AUC(95％CI)for predicting poor outcomes at 6 months in severe stroke patients for GCS,GCS-P,GPCS,FOUR,and CRS-R were 0.808(0.742-0.863),0.815(0.750-0.869),0.828(0.765-0.880),0.841(0.780-0.892),and 0.831(0.768-0.883),respectively.Sensitivities were 76.98％,78.57％,82.54％,84.13％,and 82.54％,and specificities were 73.58％,73.58％,67.92％,71.70％,and 73.58％,respectively.The FOUR had the highest AUC,with an optimal cutoff value of 13.(3)Pairwise comparisons of AUC showed a statistically significant difference between the FOUR and GCS(the difference value of AUC is 0.034,95％CI 0.004-0.064,Z=2.194,P=0.028),but no significant differences were observed between other scales(all P＞0.05).Conclusion Compared to GCS,GCS-P,GPCS,and CRS-R,FOUR may provide more valuable prognostic information for severe stroke patients.

Branch atheromatous disease(BAD)is a type of ischemic stroke that is prone to early neurological deterioration(END),which profoundly impacts patient prognosis and remains a focus of clinical research and practice.This article reviews the diagnosis,risk factors,risk prediction,along with imaging and prevention strategies of END in BAD patients,aiming to provide a theoretical basis for the early clinical identification and intervention of END to improve the prognosis of patients with BAD.

Objective To compare the predictive effectiveness of the Glasgow coma scale(GCS),GCS-pupils scale(GCS-P),Glasgow-Pittsburgh coma scale(GPCS),full outline of unresponsiveness scale(FOUR),and coma recovery scale-revised(CRS-R)in forecasting the prognosis of severe stroke patients.Methods A prospective,consecutive cohort of severe stroke patients admitted to the Department of Neurology,First Medical Center of Chinese PLA General Hospital from September 2021 to April 2024 was enrolled.Demographic and clinical data were collected,including age,sex,length of hospital stay,diagnosis(severe ischemic stroke,severe cerebral hemorrhage,aneurysmal subarachnoid hemorrhage),medical history(hypertension,diabetes,coronary artery disease),smoking and drinking habits,vital signs upon admission(temperature,pulse,respiration,blood pressure),neurological examination findings(including speech and brainstem reflexes)at admission,head imaging results(CT,MRI)within 24 h of admission to assess the presence of brain herniation,and whether intubation occurred within 24 h of admission.Patients underwent GCS,GCS-P,GPCS,FOUR,and CRS-R scoring within 8h of admission.Telephone follow-up was conducted at 6 months post-stroke to assess outcomes using the modified Rankin scale(mRS),with mRS scores of 0-2 classified as the good prognosis group and 3-6 as the poor prognosis group.The receiver operating characteristic(ROC)curve was used to assess the prognostic prediction value of the five scales for poor outcomes at 6 months.The area under the ROC curve(AUC)was calculated,and pairwise comparisons of AUC were performed using the Delong test.Results A total of 179 severe stroke patients were enrolled,including 116 males and 63 females.The group consisted of 132 patients with severe ischemic stroke,30 with severe intracerebral hemorrhage,and 17 with aneurysmal subarachnoid hemorrhage.At 6months,126patients had a poor prognosis and 53 had a good prognosis.(1)There were statistically significant differences in age,temperature,pulse,history of coronary artery disease,smoking and drinking habits,presence of speech impairment,abnormal brainstem reflexes,brain herniation,intubation within 24 h of admission,and GCS,GCS-P,GPCS,FOUR,and CRS-R scores between the poor and good prognosis groups(all P＜0.05).(2)ROC analysis revealed that the AUC(95％CI)for predicting poor outcomes at 6 months in severe stroke patients for GCS,GCS-P,GPCS,FOUR,and CRS-R were 0.808(0.742-0.863),0.815(0.750-0.869),0.828(0.765-0.880),0.841(0.780-0.892),and 0.831(0.768-0.883),respectively.Sensitivities were 76.98％,78.57％,82.54％,84.13％,and 82.54％,and specificities were 73.58％,73.58％,67.92％,71.70％,and 73.58％,respectively.The FOUR had the highest AUC,with an optimal cutoff value of 13.(3)Pairwise comparisons of AUC showed a statistically significant difference between the FOUR and GCS(the difference value of AUC is 0.034,95％CI 0.004-0.064,Z=2.194,P=0.028),but no significant differences were observed between other scales(all P＞0.05).Conclusion Compared to GCS,GCS-P,GPCS,and CRS-R,FOUR may provide more valuable prognostic information for severe stroke patients.

Objective:To construct a prior based on the inherent properties of PET to accurately segment the lesion areas.Methods:A network framework for PET tumor segmentation driven by geodesic priors was proposed (geodesic network for short). Specifically, partial differential equations were constructed to characterize the geodesic distances between different regions in PET images. Tumor marker points identified by CT labeling were used as the initial conditions for the equations. To enhance the contrast between areas of lung or breast tumors and normal tissues, a smooth Heaviside function was utilized to map the geodesic distances. The network framework adopted a dual-branch architecture, using geodesic priors to assist in PET image segmentation.Results:The proposed method achieved a Dice coefficient of 94.92% in lung cancer segmentation and 90.12% in breast cancer segmentation. With the addition of geodesic priors in the Unet, the Dice coefficient for breast cancer increased by 32.37% (from 42.50% to 74.87%).Conclusion:Geodesic priors can significantly improve segmentation outcomes and enhance the generalization capability of the network.

Skin modeling of transdermal drug delivery system refers to experimental models that mimic the structure and function of human skin to explore and evaluate absorption,penetration,and efficacy of medicines in transdermal drug delivery.It provides an alternative to traditional human skin experiments and reduces the use of human skin in medical research,which is convenient,controllable,and cost effective.For skin models of transdermal drug delivery systems,this article introduces commonly used animal skin models,artificial skin models,and recombinant human skin models from the perspective of the transdermal absorption pathway of medicines,and analyzes their advantages,disadvantages,and applications so provide references the research and development of transdermal formulations and topical therapies.

Objective To investigate the influencing factors for chronic pancreatitis(CP)complicated by pancreatogenic portal hypertension(PPH),and to establish a predictive model.Methods A retrospective analysis was performed for the clinical data of 99 patients with CP complicated by PPH who were hospitalized in The First Affiliated Hospital of Kunming Medical University,Chuxiong Yi Autonomous Prefecture People's Hospital,Wenshan People's Hospital,and Puer People's Hospital from January 2017 to December 2022,and these patients were enrolled as PPH group.The incidence density sampling method was used to select 198 CP patients from databases as control group.The independent-samples t test was used for comparison of normally distributed continuous data between two groups,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups;the chi-square test or the Fisher's exact test was used for comparison of categorical data between two groups.The Least Absolute Shrinkage and Selection Operator(LASSO)regression model was used to identify the potential predictive factors for CP complicated by PPH,and the predictive factors obtained were included in the multivariate Logistic regression analysis to obtain independent risk factors,which were used to establish a nomogram prediction model.The receiver operating characteristic(ROC)curve,the calibration curve,and the Hosmer-Lemeshow goodness-of-fit test were used to perform internal validation of the model,and the clinical decision curve was used to assess the clinical practicability of the model.Results There were significant differences between the two groups in sex,history of recurrent acute pancreatitis attacks,acute exacerbation of CP,bile duct stones,peripancreatic fluid accumulation,pseudocysts,pulmonary infection,elevated C-reactive protein(CRP),elevated procalcitonin,fibrinogen(FIB),neutrophil-lymphocyte ratio(NLR),gamma-glutamyl transpeptidase,total bilirubin,direct bilirubin,low-density lipoprotein(LDL),serum amylase,D-dimer,and serum albumin(all P<0.05).The predictive variables obtained by the LASSO regression analysis included sex,recurrent acute pancreatitis attacks,bile duct stones,peripancreatic fluid accumulation,pulmonary infection,pseudocysts,CRP,NLR,FIB,and LDL.The multivariate Logistic regression analysis showed that sex(odds ratio[OR]=2.716,P<0.05),recurrent acute pancreatitis attacks(OR=2.138,P<0.05),peripancreatic fluid accumulation(OR=2.297,P<0.05),pseudocysts(OR=2.805,P<0.05),and FIB(OR=1.313,P<0.05)were independent risk factors for CP complicated by PPH.The above factors were fitted into the model,and the Bootstrap internal validation showed that the nomogram model had an area under the ROC curve of 0.787(95%confidence interval:0.730—0.844),and the calibration curve was close to the reference curve.The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good degree of fitting(χ2=7.469,P=0.487).The clinical decision curve analysis showed that the prediction model had good clinical practicability.Conclusion Male sex,recurrent acute pancreatitis attacks,peripancreatic fluid accumulation,pseudocysts,and FIB are independent risk factors for CP complicated by PPH,and the nomogram model established has good discriminatory ability,calibration,and clinical practicability.

Objective:To investigate the risk factors of moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP) complicated with pancreatogenic portal hypertension (PPH) and to establish a prediction model.Methods:From January 1, 2016 to December 31, 2022, a total of 1 095 patients diagnosed with MSAP or SAP at the First Affiliated Hospital of Kunming Medical University were enrolled and divided into PPH group (145 cases) and non-PPH group (950 cases) according to the presence or absence of concomitant PPH. The general data (gender, etiology of acute pancreatitis, days of hospitalization, etc.), complications (portal vein thrombosis, pancreatic pseudocyst, pancreatic encapsulated necrosis, etc.), laboratory indicators (albumin, D-dimer, etc.), and scores of modified computed tomography severity index (MCTSI) were collected in the two groups. The least absolute shrinkage and selection operator(LASSO) and multivariate logistic regression analysis were performed to analyze the independent risk factors of MSAP and SAP complicated with PPH, and the nomogram prediction model was established. The area under the curve of the receiver operating characteristic curve was calculated to evaluate the discrimination of the calibration curve and Hosmer-Lemeshow goodness of fit test were used to assess the predictive accuracy of the model, and clinical decision curve analysis (DCA) was used to evaluate the clinical practicability of the model.Results:The results of LASSO and multivariate logistic regression analysis showed that portal vein thrombosis, pancreatic pseudocyst, pancreatic encapsulated necrosis, days of hospitalization, MCTSI and decreased albumin were independent risk factors of MSAP and SAP complicated with PPH ( OR=7.013, 2.085, 1.846, 1.030, 1.235 and 0.955; 95% confidence interval 4.061 to 12.112, 1.255 to 3.463, 1.066 to 3.199, 1.013 to 1.047, 1.123 to 1.357 and 0.927 to 0.983; all P<0.05). The area under the curve of the model was 0.820 (95% confidence interval 0.780 to 0.859), the calibration curve was close to the reference curve, and the Hosmer-Lemeshow goodness-fit test showed that the model had a good fit ( χ2=9.82, P=0.278). The result of DCA indicated that the model had a high net benefit in a wide range of risk threshold (threshold probability 0.1 to 0.9), and had certain clinical practicability. Conclusions:Portal vein thrombosis, pancreatic pseudocyst, pancreatic encapsulated necrosis, days of hospitalization, MCTSI and decreased albumin are the independent risk factors of MSAP and SAP complicated with PPH. The established nomogram model has good differentiation, calibration and clinical practicability.