Objective:To investigate the clinical effect of composite surgery in the treatment of chronic common carotid artery occlusion(CCAO).Methods:A retrospective descriptive study was conducted. The clinical data of 7 patients with CCAO admitted to Xuanwu Hospital, Capital Medical University from October 2020 to December 2023 were collected retrospectively. There were 6 males and 1 female. The age was (66.7±10.9) years, ranging from 52 to 83 years. Outpatient or telephone follow-up were conducted after surgery, carotid artery ultrasound or computed tomography angiography were performed at 3 months, 6 months, and 1 year postoperatively to determine vascular patency. The selection of surgical methods and clinical effect were analyzed. Normally distributed measurement data were expressed as mean±standard deviation ( ± s). The measurement data of skewed distribution were expressed by M ( Q1, Q3). Count data were expressed as frequency. Results:All 7 patients were diagnosed with chronic CCAO before operation, 6 on the left and 1 on the right. 3 cases affected the middle and distal segments of the common carotid artery, 1 case affected the proximal segment, and 1 case each affected the middle and distal segments, the remaining case involves the entire common carotid artery. All the procedures were successfully performed, among which 4 cases underwent carotid endarterectomy combined with stent placement, and 3 cases did not receive stent placement after carotid endarterectomy. 1 patient developed neck hematoma after surgery and the remaining patients recovered well after surgery without any complications or deaths. The follow-up time was 13.5(4.0, 20.5) months; 1 patient was lost to follow-up, and 6 patients received effective follow-up. the common carotid artery remained unobstructed in all 6 patients, and there were no transient ischemic attacks or strokes during the follow-up period.Conclusion:Composite surgery is a safe and feasible method that can be used to treat chronic CCAO lesions, and has satisfactory short-term results.

AIM:To investigate the role of phosphoenolpyruvate carboxykinase 1(PCK1)in the proliferation and migration of mouse vascular smooth muscle cells(VSMCs)and the underlying mechanism.METHODS:The prolif-eration and migration of mouse VSMCs were induced by platelet-derived growth factor(PDGF)-BB.The cells were divided into a vehicle group and a PDGF-BB group.The expression of PCK1 was detected by Western blot and immunofluores-cence staining.The mouse Pck1 siRNA(si Pck1)were transfected into mouse VSMCs to silence PCK1.The cells were di-vided into the vehicle,si Pck1+vehicle,PDGF-BB and si Pck1+PDGF-BB groups.The protein level of PCK1 was detected by Western blot.The proliferation was explored by Ki-67 immunofluorescence staining and the viability was detected by CCK-8 assay.The migration was determined by a scratch test.Mitochondrial dynamics were observed via transmission electron microscopy.A lentivirus carrying dynamin-related protein 1(Drp1)gene(lenti-Drp1)was transfected into VSMCs to induce them to overexpress DRP1.The cells were divided into the PDGF-BB,si Pck1+PDGF-BB,lenti-Drp1+PDGF-BB and lenti-Drp1+si Pck1+PDGF-BB groups.Proliferation,migration and mitochondrial dynamics were measured as described above.RESULTS:PDGF-BB increased the protein expression of PCK1 and DRP1,cell viability,the per-centage of Ki-67-positive cells,the wound healing rate and mitochondrial division in VSMCs.These effects were sup-pressed when PCK1 protein expression was silenced.After DRP1 was overexpressed,the inhibitory effects of PCK1 silenc-ing on cell viability,the percentage of Ki-67-positive cells,the wound healing rate and mitochondrial division were signifi-cantly reversed.CONCLUSION:PCK1 promotes the mitochondrial division,proliferation and migration of VSMCs in mice by upregulating the expression of DRP1.

Diabetic foot ulcer is a serious and destructive complication of diabetes， with the rates of disability and mortality increasing year by year， which poses a serious threat to human physical and mental health. In the treatment of diabetic foot ulcer with traditional Chinese medicine （TCM）， the combination of syndrome differentiation and overall concept can not only alleviate TCM syndrome but also accelerate wound healing， reduce wound recurrence， delay the further deterioration of diabetic foot ulcer， and decrease the rates of disability and mortality. Modern studies have demonstrated that the difficult healing of diabetic foot ulcer is closely associated with the abnormal distribution of cytokines such as inflammatory cytokines， growth factors， and chemokines. With the deepening of modern medical research on TCM， the treatment of diabetic foot ulcer via regulation of cytokines by Chinese medicinal monomers and prescriptions has become a research focus. This paper summarizes the current research status at home and abroad and draws the following conclusions. ① Sesamol， geniposide， Danggui Buxuetang， and Zizhu ointment can regulate tumor necrosis factor-α （TNF-α）， interleukin （IL）-1， IL-6， IL-10 and other inflammatory cytokines to inhibit wound inflammation. ② Angelicae Dahuricae Radix， salvianolic acid B， Sixiao powder， Badu Shengji ointment （Zhuang medicine）， etc.， regulate vascular endothelial growth factor （VEGF）， platelet-derived growth factor （PDGF）， transforming growth factor （TGF）， epidermal growth factor （EGF） and other growth factors to promote collagen deposition and angiogenesis on wound surface. ③ Paeoniflorin， cryptanshinone， bee venom， and Huiyang Shengji decoction regulate CXC chemokine ligand （CXCL） 1， CXCL2， C-C chemokine ligand （CCL） 2， CCL3， stromal cell-derived factor-1α （SDF-1α）， monocyte chemoattract protein-1 （MCP-1） and other chemokines to reduce inflammatory response and promote neovascularization and wound granulation tissue formation. ④ In the treatment of diabetic foot ulcer， Chinese medicinal monomers and prescriptions have different and complicated mechanisms. The multi-target treatment manner determines that Chinese medicines can act on a variety of cytokines to participate in various stages of wound healing and thus play a therapeutic role. The conclusion above aims to provide ideas for the experimental research and clinical treatment of diabetic foot ulcer with TCM in the future.

CT image based organ segmentation is essential for radiotherapy treatment planning, and it is laborious and time consuming to outline the endangered organs and target areas before making radiation treatment plans. This study proposes a fully automated segmentation method based on fusion convolutional neural network to improve the efficiency of physicians in outlining the endangered organs and target areas. The CT images of 170 postoperative cervical cancer stage IB and IIA patients were selected for network training and automatic outlining of bladder, rectum, femoral head and CTV, and the neural network was used to localize easily distinguishable vessels around the target area to achieve more accurate outlining of CTV.
Female ; Humans ; Image Processing, Computer-Assisted ; Neural Networks, Computer ; Organs at Risk ; Pelvis ; Tomography, X-Ray Computed ; Uterine Cervical Neoplasms/surgery*

Drug-induced hyperglycemia/diabetes is a global issue. Some drugs induce hyperglycemia by activating the pregnane X receptor (PXR), but the mechanism is unclear. Here, we report that PXR activation induces hyperglycemia by impairing hepatic glucose metabolism due to inhibition of the hepatocyte nuclear factor 4-alpha (HNF4α)‒glucose transporter 2 (GLUT2) pathway. The PXR agonists atorvastatin and rifampicin significantly downregulated GLUT2 and HNF4α expression, and impaired glucose uptake and utilization in HepG2 cells. Overexpression of PXR downregulated GLUT2 and HNF4α expression, while silencing PXR upregulated HNF4α and GLUT2 expression. Silencing HNF4α decreased GLUT2 expression, while overexpressing HNF4α increased GLUT2 expression and glucose uptake. Silencing PXR or overexpressing HNF4α reversed the atorvastatin-induced decrease in GLUT2 expression and glucose uptake. In human primary hepatocytes, atorvastatin downregulated GLUT2 and HNF4α mRNA expression, which could be attenuated by silencing PXR. Silencing HNF4α downregulated GLUT2 mRNA expression. These findings were reproduced with mouse primary hepatocytes. Hnf4α plasmid increased Slc2a2 promoter activity. Hnf4α silencing or pregnenolone-16α-carbonitrile (PCN) suppressed the Slc2a2 promoter activity by decreasing HNF4α recruitment to the Slc2a2 promoter. Liver-specific Hnf4α deletion and PCN impaired glucose tolerance and hepatic glucose uptake, and decreased the expression of hepatic HNF4α and GLUT2. In conclusion, PXR activation impaired hepatic glucose metabolism partly by inhibiting the HNF4α‒GLUT2 pathway. These results highlight the molecular mechanisms by which PXR activators induce hyperglycemia/diabetes.

Objective:To resolve the issue of poor automatic segmentation of the bowel in women with pelvic tumors, a Dense V-Network model was established, trained and evaluated to accurately and automatically delineate the bowel of female patients with pelvic tumors.Methods:Dense Net and V-Net network models were combined to develop a Dense V-Network algorithm for automatic segmentation of 3D CT images. CT data were collected from 160 patients with cervical cancer, 130 of which were randomly selected as the training set to adjust the model parameters, and the remaining 30 were used as test set to evaluate the effect of automatic segmentation.Results:Eight parameters including Dice similarity coefficient (DSC) were utilized to quantitatively evaluate the segmentation effect. The DSC value, JD, ΔV, SI, IncI, HD (cm), MDA (mm), and DC (mm) of the small intestine were 0.86±0.03, 0.25±0.04, 0.10±0.07, 0.88±0.05, 0.85±0.05, 2.98±0.61, 2.40±0.45 and 4.13±1.74, which were better than those of any other single algorithm.Conclusion:Dense V-Network algorithm proposed in this paper can deliver accurate segmentation of the bowel organs. It can be applied in clinical practice after slight revision by physicians.

When applying deep learning to the automatic segmentation of organs at risk in medical images, we combine two network models of Dense Net and V-Net to develop a Dense V-network for automatic segmentation of three-dimensional computed tomography (CT) images, in order to solve the problems of degradation and gradient disappearance of three-dimensional convolutional neural networks optimization as training samples are insufficient. This algorithm is applied to the delineation of pelvic endangered organs and we take three representative evaluation parameters to quantitatively evaluate the segmentation effect. The clinical result showed that the Dice similarity coefficient values of the bladder, small intestine, rectum, femoral head and spinal cord were all above 0.87 (average was 0.9); Jaccard distance of these were within 2.3 (average was 0.18). Except for the small intestine, the Hausdorff distance of other organs were less than 0.9 cm (average was 0.62 cm). The Dense V-Network has been proven to achieve the accurate segmentation of pelvic endangered organs.
Algorithms ; Humans ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; Neural Networks, Computer ; Organs at Risk ; Pelvis ; Tomography, X-Ray Computed

We use a dense and fully connected convolutional network with good feature learning in small samples, to automatically pre-deline CTV of cervical cancer patients based on CT images and evaluate the effect. The CT data of stage IB and IIA postoperative cervical cancer with similar delineation scope were selected to be used to evaluate the pre-sketching accuracy from three aspects:sketching similarity, sketching offset and sketching volume difference. It has been proved that the 8 most representative parameters are superior to those with single network and reported internationally before. Dense V-Net can accurately predict CTV pre-delineation of cervical cancer patients, which can be used clinically after simple modification by doctors.
Automation ; Female ; Humans ; Machine Learning ; Patients ; Tomography, X-Ray Computed ; Uterine Cervical Neoplasms/diagnostic imaging*

Objective To evaluate the accuracy and validate the feasibility of auto-segmentation based on self-registration and Atlas in adaptive radiotherapy for cervical cancer using MIM-Maestro software.Methods The CT scan images and delineation results of 60 cervical cancer patients were obtained to establish the Atlas template database.The planning CT (pCT) and replanning CT (rCT) images were randomly selected from 15 patients for the contouring of clinical target volume (CTV) and organs at risk (OAR) by an experienced radiation oncologist.The rCT images of 15 patients were auto-contoured using Atlas-based auto-segmentation (Atlas group),and mapping contours from the pCT to the rCT images was performed by rigid and deformable image registration (rigid group and deformable group).The time for the three methods of auto-segmentation was also recorded.The similarity of the auto-contours and reference contours was assessed using dice similarity coefficient (DSC),overlap index (OI),the average hausdorff distance (AHD) and the deviation of centroid (DC),and the results were statistically compared among three groups by using one-way analysis of variance.Results The mean time was 89.2 s,22.4 s and 42.6 s in the Atlas,rigid and deformable groups respectively.The DSC,OI and AHD for the CTV and rectum in the rigid and deformable groups significantly differed from those in the Atlas group (all P＜0.001).In the rigid and deformable groups,the OI for the intestine significantly differed from that in the Atlas group.The mean DSC for CTV was 0.89 in the rigid and deformable groups,and 0.76 in the Atlas group.The optimal delineation of the bladder,pelvis and femoral heads was obtained in the deformable group.Conclusions AIl three methods of auto-segmentation can automatically and rapidly contour the CTV and OARs.The performance in the deformable group is better than that in the rigid and Atlas groups.

Objective To discuss and evaluate the dosimetric characteristics of different plans implementing stereotactic radiotherapy(SRT)for intracranial tumors using Fixed and Iris collimators of CyberKnife VSI.Methods Twenty patients with intracranial tumors were selected and divided into group A with a small target volume(≤30 cm3)and group B with a large target volume(≥30 cm3). There were 10 patients in each group,and the prescribed dose to the target was 21 Gy in 3 fractions. For each patient, two treatment plans were designed using Fixed and Iris collimators. By analyzing the dosimetric parameters such as conformity index(CI),homogeneity index(HI), gradient index(GI), gradient score index(GSI), and organs at risk (OAR),the quality and efficiency of the plans were evaluated in order to discuss the beam characteristics for two sets of collimators. The difference was analyzed with the paired t-test. Results The mean time of Iris plan for delivering was significantly less than that of Fixed plan(group A:P=0.001;group B:P=0.000). In group B,the peripheral dose(20% and 10% of the prescribed dose)volumes of Fixed plan were significantly less than those of Iris plan(P=0.001 and 0.009). For OAR,D minof the visual pathway and D meanor D minof the eyeball in group B were significantly different between Fixed and Iris plans(all P<0.05), while in group A, only D minof the optic chiasm was significantly different between the two plans(P=0.043). For the other parameters of targets,there were no significant differences between Fixed and Iris plans in both groups(all P>0.05). Conclusions Apart from less treatment time in the Iris plan, there are no significant dosimetric differences between the two collimator plans of CyberKnife VSI in treating small intracranial tumor. For the large and complex tumor,although Iris plan meets the requirement for OAR dose constraints,its low-dose volumes are larger than those of Fixed plan. Further studies of the dosimetric characteristics in CyberKnife should be done.