ObjectiveTo analyze the trend of incidence, mortality rate and related life loss of colorectal cancer in Haishu District, Ningbo from 2017 to 2022, so as to provide a scientific basis for the prevention and treatment of colorectal cancer. MethodsThe incidence and death data of colorectal cancer among residents in Haishu District during 2017‒2022 were collected from the Ningbo Municipal Digital Disease Prevention and Control Platform. The incidence and mortality rate, the age-specific incidence and mortality rate, potential years of life lost (PYLL), potential years of life lost rate (PYLLR), and average years of life lost (AYLL) were calculated. The standardized rate was calculated based on the standardized population from the Sixth National Census in 2010, and the annual percentage change (APC) was calculated by Joinpoint Regression Program. ResultsA total of 2 595 cases of colorectal cancer were reported in Haishu District from 2017 to 2022, with a crude incidence rate of 68.23/100 000 and a standardized incidence rate of 39.72/100 000. There were no statistical differences in crude and standardized incidence rates(APC=2.288%, -0.160%,both P>0.05). In addition, a total of 898 colorectal cancer deaths were reported, with a crude mortality rate of 23.61/100 000 and a standardized mortality rate of 12.18/100 000, of which the crude mortality rate and standardized mortality rate of males showed an upward trend (APC=10.855%, 7.895%, both P<0.05). Furthermore, the crude incidence and mortality rate of colorectal cancer in males were higher than those in females (both P<0.05). The crude incidence and mortality rate of colorectal cancer in Haishu District showed an increasing trend by age (both P<0.05). PYLL caused by colorectal cancer was 7 818.52 person-years, and AYLL was 8.71 years, with a PYLLR of 2.06‰. ConclusionThe incidence and mortality rate of colorectal cancer in Haishu District are still at a high level. Colorectal cancer screening should be continued, relevant health knowledge should be facilitated and disseminated, awareness of early screening and diagnosis of colorectal cancer should be promoted, and ultimately improving the survival rate of the patients.

Fundus neovascularization is a significant cause of ocular diseases, mainly including retinal neovascularization and choroidal neovascularization. Anti-vascular endothelial growth factor therapy, though effective, has limitations such as a short half-life, non-responsiveness, and drug resistance. 6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a key regulator of glycolysis, affects the generation of pathological blood vessels by modulating the metabolism of vascular endothelial cells. Small molecule inhibitors targeting PFKFB3 protein have been confirmed in animal and cell models to significantly inhibit pathological angiogenesis, showing good therapeutic potential. However, most of them are still in the preclinical research stage. In the future, it is necessary to further investigate the mechanism of PFKFB3 gene, optimize the specificity and safety of the inhibitors, and explore the effects of combining them with existing therapies, so as to provide new strategies for the treatment of fundus neovascular diseases.

Objective To investigate the CT and MRI findings of rhabdomyosarcoma(RMS).Methods A retrospective analysis was conducted on CT and/or MRI data of 19 cases of pathologically confirmed RMS.The growth location,morphology,density/sig-nal intensity,enhancement pattern,and infiltration scope of the lesions were analyzed.Results Among the 19 patients,12 lesions were located in the head and neck regions(sinuses,nasal cavity,masseter muscle,infratemporal fossa,nasopharynx,and gum),2 in the lower extremities,1 in the left heart,1 in the mediastinum,1 in the prostate,1 in the testicle,and 1 in the pelvis.On CT scans,the lesions appeared as homogeneously iso-or hypodensity compared to the muscle,with homogeneous or inhomogeneous enhancement on contrast-enhanced scans.On MRI,the lesions exhibited iso-or hypointense signals on T1WI and inhomogeneous hyperintense signals on T2WI,with inhomogeneous enhancement on contrast-enhanced scans.All lesions had irregular morphologies but clear boundaries,and no calcification or hemorrhage was observed within the lesions.Lesions in the sinuses often invaded adjacent sinus cavities or the nasal cavity and orbit,and some lesions could involve the intracranial cavity through the cranial base foramina.Bone destruction could occurred.Regional lymph node enlargement in the drainage area was observed in some cases.One case exhibited multiple osseous metastases.Conclusion RMS can occur in various parts of the body,with the head and neck being the most common site.Most cases lack specificity,but CT and MRI is helpful to understand the location of the disease,its invasion of surrounding tissues,and the presence of metastasis,thereby assisting in treatment and prognosis evaluation.

A novel approach based on multi-scale adaptive residual network(MSAR)is proposed to address the issues of single input data and inadequate feature extraction in current epilepsy detection approaches.The first 5 orders intrinsic mode functions for electroencephalography signal is obtained using empirical mode decomposition,and the decomposed the first 5 orders intrinsic mode functions are input into MSAR which incorporates CBAM-Residual and multi-scale adaptive convolutional network to extract multi-scale time-frequency information as well as fine-grained features of the signal.Subsequently,the signal features extracted by MSAR are fused and input into the fully connected layer to realize classification.The proposed approach obtains a classification accuracy of 98.94%on the CHB-MIT dataset,which is a notable improvement above the existing methods.

Purpose To explore the differences of clinical and CT features between peripheral lung sarcomatoid carcinoma(PLSC),solitary pulmonary lesion(SPL),and common non-small cell lung cancer(CNSCLC),and to improve the diagnostic accuracy of PLSC.Materials and Methods Thirty patients with pathologically confirmed PLSC(sarcomatoid carcinoma group)were enrolled,and 68 cases of SPL(pneumonia group)and 73 cases of CNSCLC(lung cancer group)were selected as the control group,the clinical and CT features of PLSC were compared with SPL and NSCLC,respectively.A binary Logistic regression model was constructed based on the above statistically different parameters,and the area under the curve was used to evaluate the diagnostic efficiency of the regression model.Results Compared with clinical features,the proportion of smokers in sarcomatoid carcinoma group was significantly higher than that in pneumonia group and lung cancer group.The proportion of patients with a family history of first-degree relative malignancy in the sarcomatoid carcinoma group was significantly higher than that in the pneumonia group.The incidence of respiratory symptoms in sarcomatoid carcinoma group was significantly higher than that in lung cancer group(x2=5.800-16.611,all P＜0.025).Compared with CT features,the incidence of extensive necrosis and circular enhancement in PLSC group were significantly higher than those in SPL and CNSCLC group,while ΔCT value of both arterial and venous phase in PLSC group were significantly lower than those in the other two groups.The incidence of lobulation and air bronchogram of PLSC group were significantly higher than those of SPL group,but the incidence of pleural attachment and linear enhancement around the necrotic area of PLSC group were significantly lower than that of SPL group.The longest diameter of lesion in PLSC group was significantly larger than that in lung CNSCLC group,and the incidence of necrosis was significantly higher than that CNSCLC cancer group(x2/Z=-5.784-31.877,all P＜0.025).Compared with SPL,family history of malignancy,presence of air bronchogram and circular enhancement,absence of pleural attachment,and lower ΔCT value of venous phase were independent predictors of PLSC.The area under the curve of this model was 0.975.Compared with CNSCLC,the presence of respiratory symptoms,larger lesion,and circular enhancement were independent predictors of PLSC,and the area under the curve of this model was 0.870.Conclusion The clinical and CT features of PLSC are significantly different from those of SPL and CNSCLC.Identifying these differences correctly can help improve the preoperative diagnostic accuracy and the prognosis of patients.

Objective:To evaluate the effectiveness of virtual case teaching integrating standardized patients (SP) and objective structured clinical examination (OSCE) in enhancing students' clinical thinking and practical skills in experimental exercise therapy course.Methods:In April 2023, 52 students from the 2021 cohort and 54 students from the 2022 cohort of the Rehabilitation Therapy undergraduate program at Xinjiang Medical University were selected and divided into the experimental group and control group according to their classes. In the shoulder joint mobilization experimental class of the exercise therapy course, virtual SP teaching was performed in the experimental group of both cohorts. For the control group, student-led SP teaching was performed in the 2021 cohort, while the traditional "lecture + demonstration" method was used in the 2022 cohort. Upon completion of teaching, theoretical exams, case analysis, practical exams, and a teaching satisfaction survey were conducted on the students. Data were analyzed using the t-test and chi-square test in SPSS 25.0. Results:In both cohorts, the experimental group had similar theoretical exam scores ( P=0.207 and P=0.097, respectively) to the control group, but had higher practical exam scores ( P=0.013 and P=0.002, respectively) than the control group. In the case analysis exam, the experimental group scored higher than the control group in the 2022 cohort ( t=2.84, P=0.006) but similarly to the control group in the 2021 cohort ( t=1.53, P=0.132). All students believed that virtual SP teaching was most engaging. In terms of understanding complex concepts, increasing active participation, and fostering clinical thinking, the 2022 cohort was more satisfied with virtual SP teaching, whereas the 2021 cohort experienced no significant difference between virtual SP teaching and student-led SP teaching. In addition, the 2021 cohort found that student-led SP teaching was more helpful for improving doctor-patient communication skills. Conclusions:The application of virtual SP teaching in the experimental exercise therapy course effectively enhances students' practical skills and case analysis capabilities, contributing greatly to their overall clinical management thinking.

Arrhythmia is a common cardiovascular disease,and its diagnosis primarily relies on electrocardiograms(ECG).Leveraging computational techniques to achieve automatic arrhythmia classification can avoid human errors while improving diagnostic efficiency.An arrhythmia classification method based on a residual-structured deep convolutional generative adversarial network(ResDCGAN)and an improved ResNet34 is proposed to address the class imbalance in ECG data and the limitation of one-dimensional ECG processing.Specifically,the one-dimensional ECG signals are firstly denoised using variational mode decomposition.These denoised signals are then converted into two-dimensional Gramian angular summation field images.Subsequently,the proposed ResDCGAN is employed for data balancing,and finally,arrhythmia classification is carried out using a ResNet34 enhanced with coordinate attention.Experimental tests on the MIT-BIH arrhythmia database show that the proposed method achieves improvements of 0.22%,1.60%,1.89%,and 1.73%in accuracy,precision,recall rate,and F1-score,respectively,obtaining an accuracy of 99.66%.These results fully demonstrate the effectiveness of the proposed method,providing an effective solution for ECG data balancing and arrhythmia classification.

Objective To investigate the CT and MRI findings of rhabdomyosarcoma(RMS).Methods A retrospective analysis was conducted on CT and/or MRI data of 19 cases of pathologically confirmed RMS.The growth location,morphology,density/sig-nal intensity,enhancement pattern,and infiltration scope of the lesions were analyzed.Results Among the 19 patients,12 lesions were located in the head and neck regions(sinuses,nasal cavity,masseter muscle,infratemporal fossa,nasopharynx,and gum),2 in the lower extremities,1 in the left heart,1 in the mediastinum,1 in the prostate,1 in the testicle,and 1 in the pelvis.On CT scans,the lesions appeared as homogeneously iso-or hypodensity compared to the muscle,with homogeneous or inhomogeneous enhancement on contrast-enhanced scans.On MRI,the lesions exhibited iso-or hypointense signals on T1WI and inhomogeneous hyperintense signals on T2WI,with inhomogeneous enhancement on contrast-enhanced scans.All lesions had irregular morphologies but clear boundaries,and no calcification or hemorrhage was observed within the lesions.Lesions in the sinuses often invaded adjacent sinus cavities or the nasal cavity and orbit,and some lesions could involve the intracranial cavity through the cranial base foramina.Bone destruction could occurred.Regional lymph node enlargement in the drainage area was observed in some cases.One case exhibited multiple osseous metastases.Conclusion RMS can occur in various parts of the body,with the head and neck being the most common site.Most cases lack specificity,but CT and MRI is helpful to understand the location of the disease,its invasion of surrounding tissues,and the presence of metastasis,thereby assisting in treatment and prognosis evaluation.

Arrhythmia is a common cardiovascular disease,and its diagnosis primarily relies on electrocardiograms(ECG).Leveraging computational techniques to achieve automatic arrhythmia classification can avoid human errors while improving diagnostic efficiency.An arrhythmia classification method based on a residual-structured deep convolutional generative adversarial network(ResDCGAN)and an improved ResNet34 is proposed to address the class imbalance in ECG data and the limitation of one-dimensional ECG processing.Specifically,the one-dimensional ECG signals are firstly denoised using variational mode decomposition.These denoised signals are then converted into two-dimensional Gramian angular summation field images.Subsequently,the proposed ResDCGAN is employed for data balancing,and finally,arrhythmia classification is carried out using a ResNet34 enhanced with coordinate attention.Experimental tests on the MIT-BIH arrhythmia database show that the proposed method achieves improvements of 0.22%,1.60%,1.89%,and 1.73%in accuracy,precision,recall rate,and F1-score,respectively,obtaining an accuracy of 99.66%.These results fully demonstrate the effectiveness of the proposed method,providing an effective solution for ECG data balancing and arrhythmia classification.