Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To study the survival time and its risk factors of patients with occupational pneumoconiosis. Methods: A total of 11 011 newly diagnosed occupational pneumoconiosis patients in Guangdong Province from 1980 to 2019 were selected as study subjects. The life table method was used for survival analysis. The influencing factors of survival time of occupational pneumoconiosis patients were analyzed using the WilCoxon (Gehan) test and Cox proportional hazards regression model. Results: The median survival time of pneumoconiosis patients was 26.0 years. The median survival period of stage Ⅰpatients was 3.5 years longer than that of stage Ⅱ patients and 10.1 years longer than that of stage Ⅲ patients. The median survival time of patients with an initial diagnosis age under 40.0 years old was 34.8 years longer than that of patients with an initial diagnosis age over 60.0 years old. The median survival time of patients with dust exposure duration under 25.0 years old was 13.6 years longer than patients with dust exposure duration age over 45.0 years old. The results of the Cox proportional hazards regression model showed that the initial diagnosis stage, initial diagnosis age, dust exposure duration, and medical insurance were risk factors of the survival time of occupational pneumoconiosis patients (all P<0.01). The risk of reduced survival time for patients with stage Ⅱ and stage Ⅲ as the initial diagnosis stage was 1.15 and 2.04 times higher, respectively, compared with stage Ⅰ patients (both P<0.01). The risk of reduced survival time for patients without medical insurance was 60.22 times higher than those with medical insurance (P<0.01). Conclusion: The risk factors of the survival time of occupational pneumoconiosis patients in Guangdong Province are initial diagnosis stage, initial diagnosis age, the dust exposure age, and medical insurance. Earlier detection, earlier diagnosis, and improvement of medical insurance coverage for patients can effectively improve the survival time of occupational pneumoconiosis patients.

Objective: To verify the accuracy of the autoregressive integrated moving average (ARIMA) in predicting the incidence of occupational pneumoconiosis (hereinafter referred as pneumoconiosis) and to predict the incidence of pneumoconiosis in Guangdong Province in the next five years. Methods: A follow-up survey was performed to collect data on pneumoconiosis patients reported in Guangdong Province from 1956 to 2021. Collected data from 1956 to 2016 were used as the training set to build an ARIMA model. Collected data from 2017 to 2021 were used as the prediction set to evaluate the predicting result of the ARIMA model. The ARIMA model was used to predict the incidence of pneumoconiosis in Guangdong Province in next five years. Results: The ARIMA (1,1,2) model was set up after model identification and order estimation. The model was used to predict the prediction set, and its result was good. The ARIMA result and actual values in 2021 were 213 and 210 cases, respectively, with a difference of only three cases. The number of pneumoconiosis cases predicted using the ARIMA model in Guangdong Province from 2022 to 2026 was 214, 204, 202, 194, and 191 cases, respectively, showing a trend of low-level prevalence. Conclusion: The ARIMA model demonstrates high accuracy in predicting pneumoconiosis incidence over a long period of time and with large sample sizes. The forecast results of the ARIMA(1,1,2) model indicate that the incidence of pneumoconiosis in Guangdong Province will be around 200 cases in the next five years, indicating a low-level prevalence.

Objective To understand the characteristics of long-working hours exposure of medical staff,and analyze the impact of long-working hours exposure on mental health problems such as occupational stress,depression,fatigue accumulation,and insomnia.Methods The cluster random sampling method was used to select the medical staff of 12 tertiary general hospitals in Guangdong Province as the research subjects,and the"Core Scale of Occupational Stress Measurement"and other scales were used to evaluate their occupational mental health.Results The average working hours of medical staff per day were(8.99±2.18)h;2,094 people were exposed during long working hours,accounting for 78.96%.The results of binary logistics regression analysis showed that after excluding the influence of sociodemographic factors such as age,long working hours(weekly working hours greater than 40 h)were the risk factors for occupational stress,depressive symptoms and fatigue accumulation of medical staff(P<0.01),and the longer the working week,the higher the risk of occupational stress,depressive symptoms and fatigue accumulation.Weekly working hours greater than 48 hours are risk factors for insomnia(P<0.01).Conclusion Long working hours are common among delivery workers on food delivery platforms,and long working hours are a risk factor for occupational tension and fatigue.

Objective - To investigate the effect of lung flora dysbiosis on the process of pulmonary fibrosis and lung epithelial （ ） Methods - mesenchymal transition EMT in mice with silicosis. Male C57BL/6 mice of specific pathogen free grade were ， ， ， （ ） randomly divided into the blank control group silicosis model group solvent control group vancomycin VM + ampicillin （ ） ， （ ） （ ） ， AMP group metronidazole MNZ + neomycin NEO group and mixed treatment group 12 mice in each group. Except for ， ， the blank control group which was given 20.0 µL of 0.9% NaCl solution the other five groups of mice were dosed with 20.0 µL of silica dust suspension at a mass concentration of 250.0 g/L using a single tracheal drip to establish the silicosis mouse model. ： The intranasal drip method was used to treat silicosis mice in each group as following mice in the solvent control group were - ； ； given double distilled water mice in the VM+AMP group were given VM at a mass concentration of 0.5 g/L and AMP at 1.0 g/L ； mice in the MNZ+NEO group were given MNZ at a mass concentration of 1.0 g/L and NEO at 1.0 g/L mice in the mixed ， treatment group were given the same doses of the four antibiotics mentioned above all in a drip volume of 50.0 µL. Silicosis ， ， mice were treated seven days and half an hour before silica dusting and 7 14 and 21 days after silica dusting. Mouse lungtissue was collected aseptically 28 days after silica dusting. Hematoxylin eosin and Masson trichrome staining methods were - used to observe the pathological changes. Western blotting was used to detect the relative protein expression of α smooth muscle （ - ）， - （ - ） （ ） actin α SMA E cadherin E CAD and vimentin VIM . Immunohistochemistry was used to detect the relative expression of - - E CAD and VIM. Real time fluorescence quantitative polymerase chain reaction was used to detect the expression levels of （Col1a2） Results collagen type Ⅰ alpha 2 mRNA in lung tissues. The histopathological results showed that the alveoli of the ， blank control group were thin and structurally intact with few surrounding infiltrating inflammatory cells and no abnormal ， distribution of collagen fibers. The alveoli of the silicosis model group were structurally disorganized with a large number of ， ， infiltrating inflammatory cells thickened alveolar walls and cellular fibrous nodules with abundant blue collagen deposit. In the ， ， VM+AMP group MNZ+NEO group and the mixed treatment group the inflammation and fibrosis were reduced with diferent degrees in the lung tissues compared to the silicosis model group and the solvent control group. The relative expression levels of - ， Col1a2 α SMA VIM protein and mRNA in lung tissues of mice in the silicosis model group were higher than those in the blank （ P ）， -CAD control group all <0.05 and the relative expression levels of E protein were lower than those in the blank control （P ） - ， Col1a2 group <0.05 . The relative expression levels of α SMA VIM protein and mRNA in lung tissues of mice in the MNZ+ （ P ）， -CAD NEO group and the mixed treatment group were lower all <0.05 and the relative expression levels of E protein were （P ）， Conclusion higher <0.05 when compared with the silicosis model group and the solvent control group. Pulmonary fibrosis ， - was reduced in silicosis mice with interventions in lung flora where anaerobic and gram negative bacteria affected pulmonary fibrosis and dysbiosis of the lung flora affected pulmonary EMT.

Circadian Rhythm/genetics* ; Gene Expression ; Humans ; Hydrocortisone ; Ischemic Stroke ; Melatonin