RESUMO
An increasing body of studies propose that structural abnormalities begin with focal brain regions then propagate to other regions following the architecture of healthy brain network in neuropsychiatric disorders. However, these findings are untested in obsessive-compulsive disorder (OCD), also showing widespread structural brain abnormalities. In this study, we aimed to investigate whether healthy functional brain network contributed to structural brain abnormalities in OCD. The gray matter morphological abnormalities were obtained in 98 patients with OCD in relative to matched healthy controls (n = 130, HCs). The network diffusion model (NDM) was conducted to identify putative seed regions and patterns of disease propagation from seed regions to other brain regions along the functional network in OCD. The NDM has been proved to succeeded in capturing the trans-neuronal propagation of pathology and even in predicting future longitudinal progression of pathology in neurodegenerative diseases. In this study, when seeding at the right anterior cingulate cortex, the NDM best recapitulated the patterns of gray matter morphological abnormalities, suggesting this region was the most likely seed region. Further analyses revealed that pathology preferentially propagated to higher order brain systems from seed region. For non-seed regions, the arrival time of pathology was negatively correlated with their shortest functional paths to the seed (r = -0.46, p < 0.001). These results suggest that gray matter morphological abnormalities are constrained by healthy brain network and reveal temporal sequencing of pathology progression in OCD.
Assuntos
Imageamento por Ressonância Magnética , Transtorno Obsessivo-Compulsivo , Humanos , Imageamento por Ressonância Magnética/métodos , Encéfalo , Substância Cinzenta/patologia , Córtex CerebralRESUMO
Purpose: Glycated hemoglobin (HbA1c) is widely used in diabetes management and now recommended for diagnosis and risk assessment. Our research focused on investigating the optimal cutoff points of HbA1c for diagnosis of diabetes and prediabetes in Chinese breast cancer women, aiming to enhance early detection and tailor treatment strategies. Patients and Methods: This study involved 309 breast cancer women without diabetes history in China. Patients were categorized into groups of newly diagnosed diabetes, prediabetes, and normal glucose tolerance using oral glucose tolerance test (OGTT) according to the 2010 ADA criteria. HbA1c data were collected from all patients. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the HbA1c screening. Results: Among the 309 breast cancer women without diabetes history, 96 (31.0%) were identified with diabetes and 130 (42.1%) had prediabetes according to OGTT, and the incidence of normal glucose tolerance was only 26.9% (83). ROC curve analysis, using OGTT as a reference, revealed that the area under the curve of 0.903 (P<0.001, 95% CI, 0.867-0.938) for HbA1c alone, indicating high accuracy. The optimal HbA1c cutoff for identifying diabetes was determined to be 6.0%, with a sensitivity of 78.1% and specificity of 86.4%. For prediabetes, the ROC curve for HbA1c alone showed that the area under the ROC curve of 0.703 (P<0.001, 95% CI, 0.632-0.774), with an optimal cutoff of 5.5% (sensitivity of 76.9% and specificity of 51.8%). Conclusion: The prevalence of undiagnosed diabetes is very high in breast cancer women without diabetes history in China. The optimal cutoff points of HbA1c for identifying diabetes and prediabetes are 6.0% and 5.5% in Chinese breast cancer women, respectively.
RESUMO
BACKGROUND: Association between breast cancer (BC) and thyroid nodules (TNs) is still unclear. This research was to estimate the prevalence and risk factors of TN in Chinese BC women at initial diagnosis. METHODS: 1731 Chinese early-stage BC women at initial diagnosis underwent thyroid ultrasound and 1:1 age-matched Chinese healthy women underwent health examination in corresponding period were enrolled for analysis. RESULTS: Prevalence of TN and TI-RADS ≥ 4 TN in BC patients (56.27% and 9.76%) were higher than healthy people (46.04% and 5.49%), respectively, P < 0.001. Among BC patients, prevalence of TN and TI-RADS ≥ 4 TN in hormone receptor (HR)-positive patients (59.57% and 11.81%) were higher than HR-negative patients (48.77% and 5.10%), respectively, P < 0.001, while without difference between HR-negative patients and healthy people. After adjusting for age and BMI, HR-positive patients had higher risk of TN (OR = 1.546, 95%CI 1.251-1.910, P < 0.001) and TI-RADS ≥ 4 TN (OR = 3.024, 95%CI 1.943-4.708, P < 0.001) than HR-negative patients. Furthermore, the risk of TI-RADS ≥ 4 TN was higher in patients with estrogen receptor (ER) positive (OR = 2.933, 95%CI 1.902-4.524), progesterone receptor (PR) positive (OR = 1.973, 95%CI 1.378-2.826), Ki-67 < 20% (OR = 1.797, 95%CI 1.280-2.522), and tumor size < 2 cm (OR = 1.804, 95%CI 1.276-2.552), respectively, P < 0.001. CONCLUSIONS: Prevalence of TN, especially TI-RADS ≥ 4 TN, in Chinese early-stage BC women was higher than healthy people. HR-positive patients had higher prevalence and risk of TN, while without difference between HR-negative patients and healthy people. The increased risk of TN was correlated with ER-positive, PR-positive, lower Ki-67 expression, and smaller tumor size.
Assuntos
Neoplasias da Mama , Nódulo da Glândula Tireoide , Humanos , Feminino , Nódulo da Glândula Tireoide/patologia , Nódulo da Glândula Tireoide/epidemiologia , Neoplasias da Mama/patologia , Neoplasias da Mama/epidemiologia , Pessoa de Meia-Idade , Estudos Transversais , Fatores de Risco , Prevalência , Adulto , Receptores de Estrogênio/metabolismo , China/epidemiologia , Idoso , Estudos de Casos e Controles , Receptores de Progesterona/metabolismo , UltrassonografiaRESUMO
BACKGROUND: The correlation between breast cancer and hepatitis B virus (HBV) remains inconclusive. This study aims to explore the serological status of HBV infection and past infection in different age groups of female breast cancer patients, patients with benign breast diseases, and individuals undergoing routine physical examinations. METHODS: Serum data on HBV serological markers were collected and analyzed from 6072 female breast cancer patients first diagnosed from September 2012 to July 2020 at the First Affiliated Hospital of Chongqing Medical University, along with 4019 women with benign breast diseases and 54,740 healthy females undergoing routine physical examinations in the same period. The data were stratified by age for comparison between groups. RESULTS: The prevalence of HBV infection and past infection in the breast cancer group (7.9%, 55.1%) was higher than that in the benign breast disease group (6.5%, 39.1%) and the healthy females group(5.0%, 17.6%);the rate of only HBV surface antibody positivity (HBsAb ( +)) in the breast cancer group (10.3%) was lower than that in the benign breast disease group (26.9%) and the healthy females group (49.2%), with significant differences between the three groups (p < 0.05). Stratified by age, the prevalence of HBV infection in the breast cancer group (8%, 8.9%) and benign breast disease group (7.75%, 8.1%)was higher than that in the healthy females group (4.5%, 6.3%) in the 30-39 and 40-49 age group, respectively. The past infection rate of HBV in the breast cancer group (24.8%, 45.0%) was higher than that in the benign breast disease group (16.1%, 35.4%) in the ≤ 29 and 30-39 age group, respectively.. The past infection rate of HBV in the breast cancer group was higher than that in the healthy females group in all age groups, while the rate of only HBsAb ( +) in the breast cancer group was lower than that in the benign breast disease group and the routine physical examination group in all age groups. CONCLUSIONS: Breast cancer women and women with benign breast diseases have higher rates of hepatitis B virus infection and previous infections, with more significant differences among middle-aged women. Breast cancer women and women with benign breast diseases have lower rates of only HBsAb ( +) for HBV.