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 investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms

Objective To study the expression characteristics of osteoprotegerin(OPG)/receptor activator of nuclear factor-κB ligand(RANKL)/receptor activator of nuclear factor-κB(RANK)system and the relationship with fibrosis in myocardial tissues of rats with chronic heart failure.Methods SD rats were randomly divided into sham-operation group(12 rats)and model group.In sham-operation group,surgical thread was passed through the abdominal aorta without constricting it after laparotomy;in model group,establish the heart failure model by abdominal aorta coarctation.The successful model rats were randomly divided into model 1 week(12 rats),model 2 weeks(11 rats),model 4 weeks(11 rats),model 8 weeks(11 rats)and model 12 weeks groups(11 rats).The end point of the study is at week 12.The contents of hydroxyproline(HYP),total myocardial collagen and collagen volume fraction(CVF)were compaired in all proups.The expression levels of OPG,RANKL and RANK proteins in cardiomyocytes were determined by Western blot.Results The contents of HYP in sham-operation,model 1 week,model 2 weeks,model 4 weeks,model 8 weeks and model 12 weeks group were(0.25±0.04),(0.37±0.05),(0.45±0.04),(0.60±0.05),(0.82±0.10)and(1.03±0.07)μg·mg-1;the total myocardial collagen contents were(1.87±0.31),(2.73±0.38),(3.36±0.31),(4.47±0.37),(6.08±0.74)and(7.67±0.49)μg·mg-1;the CVF were(1.95±0.23)％,(2.40±0.25)％,(3.65±0.25)％,(5.43±0.29)％,(6.97±0.36)％and(9.38±0.49)％;the relative expression levels of OPG protein were 0.64±0.07,0.80±0.07,1.02±0.07,1.32±0.11,2.13±0.12 and 2.84±0.16;the relative expression levels of RANKL protein were 0.71±0.08,1.06±0.07,1.53±0.07,2.62±0.12,4.46±0.14 and 6.11±0.16;the relative expression levels of RANK protein were 0.30±0.05,0.45±0.05,0.63±0.06,0.98±0.07,1.43±0.10 and 1.63±0.10.With the extention of time,the above indexs of all model groups were significantly higher than those in the sham-operation group(all P＜0.05).There were positive linear correlation between the relative expression levels of OPG,RANKL,RANK protein and the levels of CVF and total contents in cardiomyocytes of rats with chronic heart failure(allP＜0.01).Conclusions In the process of chronic heart failure,the expression of OPG/RANKL/RANK axis is obviously enhanced,in which the up-regulation of RANKL level is most obvious.The expression level of OPG/RANKL/RANK is positively correlated with CVF and total myocardial collagen content.

The development status of the key technologies of first-aid robotics was introduced in autonomous system,embo-died intelligence,digital twins,large artificial intelligence model and autonomous unmanned medical treatment.The present situation in first-aid robotics equipment was reviewed for first-aid diagnosis,treatment,assistance and transportation.The development trends of the key technology and equipment of first-aid robotics were analyzed.It was pointed out the involve-ment of big model-based embodied intelligence technology and digital twins technology in first aid might provide new pers-pectives for the application and advancement of specialized first-aid robotics.[Chinese Medical Equipment Journal,2025,46(3):96-114]

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.