Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective:To construct a machine learning classification prediction model using planning-omics (planomics) features to predict the γ pass rate of intensity-modulated radiotherapy (IMRT) plan dose verification in fixed-field thoracic tumors, and evaluate the application of planomics in radiotherapy quality assurance.Methods:The fixed-field IMRT plans of 240 patients with chest tumors admitted to Department of Radiotherapy, Henan Cancer Hospital from August 2022 to March 2023 were retrospectively analyzed. All plans underwent dose verification using the electronic portal imaging system detector on the Varian accelerator to collect field dose data. The dose verification results were analyzed through Portal Dosimetry in the treatment planning system of Eclipse. The γ pass rate standard was set at 2%/2 mm with a 10% dose threshold. From the planning documents, 48 conventional planning features, 2476 planomics features, and the combination of the previous two feature sets were extracted. Subsequently, an auto-encoder classification model was constructed. To evaluate the classification efficacy of various feature sets, 20 random train-test divisions were conducted by calculating the area under the receiver operating characteristic curve (AUC) values along with the accuracy rates.Results:After the feature selection, 2 conventional features and 16 planomics features were finally selected. In the testing set, the AUC values for the model using combined features, planomics features, and conventional planned features were 0.802±0.030, 0.740±0.069, and 0.673±0.083, respectively. In contrast, in the training set, these AUC values were 0.844±0.074, 0.816±0.047, and 0.687±0.036, respectively. The accuracy rates were 0.752±0.083, 0.703±0.110, and 0.648±0.081 in the testing set, and 0.753±0.098, 0.751±0.075, and 0.624±0.054 in the training set for the combined, planomics, and conventional planning feature sets, respectively.Conclusions:For thoracic fixed-field adjusted radiotherapy planning, the machine learning method based on planomics features can be utilized to build a classification model for predicting the γ pass rate. Combining planomics features with conventional planned features can enhance the predictive performance of the classification models.

Objective:To compare the consistency and efficacy of ultrasound and CT in the preoperative diagnosis of cervical lymph node metastasis in patients with thyroid cancer, and to explore the clinical value of the combined application of multimodal imaging.Methods:The 119 thyroid cancer patients underwent surgical treatment from January to September 2023 in Zhongshan Hospital Affiliated to Dalian University were retrospectively analyzed. All patients underwent ultrasound and CT examinations before operation. The results of postoperative histopathology examination were taken as the gold standard, the efficacy of ultrasound and CT in preoperative diagnosis of cervical lymph node metastasis was compared.Results:A total of 1 721 cervical lymph nodes were detected in 119 patients with thyroid cancer, among which 1 378 lymph nodes were benign, and 343 lymph nodes were malignant, the rate of malignant lymph nodes was 19.93% (343/1 721). Among them, the proportion of malignant lymph nodes in area Ⅵ was the highest, 22.58% (245/1 085), followed by area Ⅲ, 21.26% (37/174). The sensitivity of CT in diagnosing cervical lymph node metastasis in patients with thyroid cancer was significantly higher than that of ultrasound diagnosis: 58.46% (38/65) vs. 38.46% (25/65), the specificity was significantly lower than that of ultrasound diagnosis: 85.19% (46/54) vs. 96.30% (52/54), and there were statistical differences ( P<0.01 and <0.05); there was no statistical difference in accuracy between CT and ultrasound ( P>0.05). Conclusions:In the preoperative diagnosis of cervical lymph node metastasis in patients with thyroid cancer by ultrasound and CT, ultrasound examination has no radiation risk, while CT examination has a higher diagnostic efficiency.

Objective:To compare the consistency and efficacy of ultrasound and CT in the preoperative diagnosis of cervical lymph node metastasis in patients with thyroid cancer, and to explore the clinical value of the combined application of multimodal imaging.Methods:The 119 thyroid cancer patients underwent surgical treatment from January to September 2023 in Zhongshan Hospital Affiliated to Dalian University were retrospectively analyzed. All patients underwent ultrasound and CT examinations before operation. The results of postoperative histopathology examination were taken as the gold standard, the efficacy of ultrasound and CT in preoperative diagnosis of cervical lymph node metastasis was compared.Results:A total of 1 721 cervical lymph nodes were detected in 119 patients with thyroid cancer, among which 1 378 lymph nodes were benign, and 343 lymph nodes were malignant, the rate of malignant lymph nodes was 19.93% (343/1 721). Among them, the proportion of malignant lymph nodes in area Ⅵ was the highest, 22.58% (245/1 085), followed by area Ⅲ, 21.26% (37/174). The sensitivity of CT in diagnosing cervical lymph node metastasis in patients with thyroid cancer was significantly higher than that of ultrasound diagnosis: 58.46% (38/65) vs. 38.46% (25/65), the specificity was significantly lower than that of ultrasound diagnosis: 85.19% (46/54) vs. 96.30% (52/54), and there were statistical differences ( P<0.01 and <0.05); there was no statistical difference in accuracy between CT and ultrasound ( P>0.05). Conclusions:In the preoperative diagnosis of cervical lymph node metastasis in patients with thyroid cancer by ultrasound and CT, ultrasound examination has no radiation risk, while CT examination has a higher diagnostic efficiency.

Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective:To construct a machine learning classification prediction model using planning-omics (planomics) features to predict the γ pass rate of intensity-modulated radiotherapy (IMRT) plan dose verification in fixed-field thoracic tumors, and evaluate the application of planomics in radiotherapy quality assurance.Methods:The fixed-field IMRT plans of 240 patients with chest tumors admitted to Department of Radiotherapy, Henan Cancer Hospital from August 2022 to March 2023 were retrospectively analyzed. All plans underwent dose verification using the electronic portal imaging system detector on the Varian accelerator to collect field dose data. The dose verification results were analyzed through Portal Dosimetry in the treatment planning system of Eclipse. The γ pass rate standard was set at 2%/2 mm with a 10% dose threshold. From the planning documents, 48 conventional planning features, 2476 planomics features, and the combination of the previous two feature sets were extracted. Subsequently, an auto-encoder classification model was constructed. To evaluate the classification efficacy of various feature sets, 20 random train-test divisions were conducted by calculating the area under the receiver operating characteristic curve (AUC) values along with the accuracy rates.Results:After the feature selection, 2 conventional features and 16 planomics features were finally selected. In the testing set, the AUC values for the model using combined features, planomics features, and conventional planned features were 0.802±0.030, 0.740±0.069, and 0.673±0.083, respectively. In contrast, in the training set, these AUC values were 0.844±0.074, 0.816±0.047, and 0.687±0.036, respectively. The accuracy rates were 0.752±0.083, 0.703±0.110, and 0.648±0.081 in the testing set, and 0.753±0.098, 0.751±0.075, and 0.624±0.054 in the training set for the combined, planomics, and conventional planning feature sets, respectively.Conclusions:For thoracic fixed-field adjusted radiotherapy planning, the machine learning method based on planomics features can be utilized to build a classification model for predicting the γ pass rate. Combining planomics features with conventional planned features can enhance the predictive performance of the classification models.

Background::Ductal carcinoma in situ with microinvasion (DCIS-MI) is defined as ductal carcinoma in situ (DCIS) with a microscopic invasive focus ≤1 mm in the longest diameter. The current literature is controversial concerning the clinical prognostic features and management of DCIS-MI. This narrative review described recently reported literature regarding the characteristics, treatment, and prognosis of it.Methods::Searching PubMed for relevant articles covering the period of 1982 to 2021 using the following terms by MeSH and free-word: breast cancer, microinvasion, DCIS, DCIS-MI, and invasive ductal carcinoma (IDC).Results::DCIS-MI tends to express more aggressive pathological features such as necrosis, HER2+, ER- or PR-, and high nuclear grade. The overall prognosis of DCIS-MI is typically good, however, some indicators such as young age, HR-, HER2+ and multimicroinvasive lesions, were associated with worse prognoses. And there are also conflicting results on the differences between the prognoses of DCIS-MI and DCIS or T1a-IDC. Postoperative chemotherapy and anti-HER2 therapy still have uncertain benefits and are more likely to be used to treat high-risk patients who are HR- orHER2+ to improve the prognosis.Conclusion::DCIS-MI has more aggressive pathological features, which may suggest its biological behavior is worse than that of DCIS and similar to early IDC. Although the overall prognosis of DCIS-MI is good, when making decisions about adjuvant therapy clinicians need to give priority to the hormone receptor status, HER2 expression and axillary lymph node status of patients, because these may affect the prognosis and treatment response.

Background::Ductal carcinoma in situ with microinvasion (DCIS-MI) is defined as ductal carcinoma in situ (DCIS) with a microscopic invasive focus ≤1 mm in the longest diameter. The current literature is controversial concerning the clinical prognostic features and management of DCIS-MI. This narrative review described recently reported literature regarding the characteristics, treatment, and prognosis of it.Methods::Searching PubMed for relevant articles covering the period of 1982 to 2021 using the following terms by MeSH and free-word: breast cancer, microinvasion, DCIS, DCIS-MI, and invasive ductal carcinoma (IDC).Results::DCIS-MI tends to express more aggressive pathological features such as necrosis, HER2+, ER- or PR-, and high nuclear grade. The overall prognosis of DCIS-MI is typically good, however, some indicators such as young age, HR-, HER2+ and multimicroinvasive lesions, were associated with worse prognoses. And there are also conflicting results on the differences between the prognoses of DCIS-MI and DCIS or T1a-IDC. Postoperative chemotherapy and anti-HER2 therapy still have uncertain benefits and are more likely to be used to treat high-risk patients who are HR- orHER2+ to improve the prognosis.Conclusion::DCIS-MI has more aggressive pathological features, which may suggest its biological behavior is worse than that of DCIS and similar to early IDC. Although the overall prognosis of DCIS-MI is good, when making decisions about adjuvant therapy clinicians need to give priority to the hormone receptor status, HER2 expression and axillary lymph node status of patients, because these may affect the prognosis and treatment response.

Objective:To explore the efficacy of a flat ground exoskeleton robot in improving the walking ability of stroke survivors.Methods:Fifty-eight stroke survivors with mobility difficulties were randomly divided into a robot group ( n=29) and a control group ( n=29). In addition to routine rehabilitation, the control group received conventional walking training, while the robot group underwent exoskeleton robot-assisted gait training. The 30-minute training sessions were held twice a day, 5 days per week for 5 weeks. Before as well as after 2 and 4 weeks of treatment, everyone′s walking ability was tested using the 6-minute walk test (6MWT) and functional ambulation scale (FAC). General lower limb motor function was quantified using the Fugl-Meyer Lower Extremity assessment (FMA-LE). Moreover, gait analysis was conducted before and after 4 weeks of treatment. Results:After 2 and 4 weeks of treatment, the average 6MWT times of both groups were significantly better than before the treatment, with the improvement of the robot group significantly greater than that of the control group after 2 weeks. After 2 and 4 weeks the average FMA-LE and FAC scores of both groups had improved significantly compared with before treatment. After 4 weeks the stride frequency and gait cycle of both groups had improved significantly.Conclusions:Exoskeleton robot-assisted gait training can improve walking ability and lower limb motor function of stroke survivors about as well as conventional walking training.

In the wake of the COVID-19 pandemic, only through whole-hearted cooperation and joined efforts can medical institutions, governments, and social organizations cope with emergency, convert the crisis into opportunities, promote modern governance and accomplish high-quality development in the fight against the pandemic. Taking the First Affiliated Hospital of Xi’an Jiaotong University as an example, this paper analyzes the all-media communication matrix of "one network platform, 3W + N" that the hospital established during the pandemic by combining the authoritative official website with WeChat, Wesee, Weibo and that other publicity media. The study explores how to create a publicity brand that is mindful, poignant, compassionate and devoted and maintains its scientific and refined management, so as to achieve the professional goal of educating the public, shouldering the responsibility in the combat against the pandemic, and taking the lead in the research on the pandemic.