Prevalence and characteristics of somatic symptom disorder in the elderly in a community-based population: a large-scale cross-sectional study in China.

INTRODUCTION AND OBJECTIVES: The aging population is expected to reach 2 billion by 2050, but the impact of somatic symptom disorder (SSD) on the elderly has been insufficiently addressed. We aimed to clarify the prevalence of SSD in China and to identify physical and psychological differences between the elderly and non-elderly. METHODS: In this prospective multi-center study, 9020 participants aged (2206 non-elderly adults and 6814 elderly adults) from 105 communities of Shanghai were included (Assessment of Somatic Symptom in Chinese Community-Dwelling People, clinical trial number NCT04815863, registered on 06/12/2020). The Somatic Symptom Scale-China (SSS-CN) questionnaire was used to measure SSD. Depressive and anxiety disorders were assessed by the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), respectively. RESULTS: The prevalence of SSD in the elderly was higher than that in the non-elderly (63.2% vs. 45.3%). The elderly suffered more severe SSD (20.4% moderate and severe in elderly vs. 12.0% in non-elderly) and are 1.560 times more likely to have the disorder (95%CI: 1.399-1.739; p < .001) than the non-elderly. Comorbidity of depressive or anxiety disorders was 3.7 times higher than would be expected in the general population. Additionally, the results of adjusted multivariate analyses identified older age, female sex, and comorbid physical diseases as predictive risk factors of SSD in the elderly group. CONCLUSIONS: With higher prevalence of common physical problems (including hypertension, diabetes mellitus and cardio/cerebrovascular disease), the elderly in Shanghai are more vulnerable to have SSD and are more likely to suffer from comorbid depressive and anxiety disorders. SSD screening should be given more attention in the elderly, especially among older females with several comorbid physical diseases.

Radiomics-Based Quality Control System for Automatic Cardiac Segmentation: A Feasibility Study.

PURPOSE: In the past decade, there has been a rapid increase in the development of automatic cardiac segmentation methods. However, the automatic quality control (QC) of these segmentation methods has received less attention. This study aims to address this gap by developing an automatic pipeline that incorporates DL-based cardiac segmentation and radiomics-based quality control. METHODS: In the DL-based localization and segmentation part, the entire heart was first located and cropped. Then, the cropped images were further utilized for the segmentation of the right ventricle cavity (RVC), myocardium (MYO), and left ventricle cavity (LVC). As for the radiomics-based QC part, a training radiomics dataset was created with segmentation tasks of various quality. This dataset was used for feature extraction, selection, and QC model development. The model performance was then evaluated using both internal and external testing datasets. RESULTS: In the internal testing dataset, the segmentation model demonstrated a great performance with a dice similarity coefficient (DSC) of 0.954 for whole heart segmentations. Images were then appropriately cropped to 160 × 160 pixels. The models also performed well for cardiac substructure segmentations. The DSC values were 0.863, 0.872, and 0.940 for RVC, MYO, and LVC for 2D masks and 0.928, 0.886, and 0.962 for RVC, MYO, and LVC for 3D masks with an attention-UNet. After feature selection with the radiomics dataset, we developed a series of models to predict the automatic segmentation quality and its DSC value for the RVC, MYO, and LVC structures. The mean absolute values for our best prediction models were 0.060, 0.032, and 0.021 for 2D segmentations and 0.027, 0.017, and 0.011 for 3D segmentations, respectively. Additionally, the radiomics-based classification models demonstrated a high negative detection rate of >0.85 in all 2D groups. In the external dataset, models showed similar results. CONCLUSIONS: We developed a pipeline including cardiac substructure segmentation and QC at both the slice (2D) and subject (3D) levels. Our results demonstrate that the radiomics method possesses great potential for the automatic QC of cardiac segmentation.

Papillary-Muscle-Derived Radiomic Features for Hypertrophic Cardiomyopathy versus Hypertensive Heart Disease Classification.

Purpose: This study aimed to assess the value of radiomic features derived from the myocardium (MYO) and papillary muscle (PM) for left ventricular hypertrophy (LVH) detection and hypertrophic cardiomyopathy (HCM) versus hypertensive heart disease (HHD) differentiation. Methods: There were 345 subjects who underwent cardiovascular magnetic resonance (CMR) examinations that were analyzed. After quality control and manual segmentation, the 3D radiomic features were extracted from the MYO and PM. The data were randomly split into training (70%) and testing (30%) datasets. Feature selection was performed on the training dataset. Five machine learning models were evaluated using the MYO, PM, and MYO+PM features in the detection and differentiation tasks. The optimal differentiation model was further evaluated using CMR parameters and combined features. Results: Six features were selected for the MYO, PM, and MYO+PM groups. The support vector machine models performed best in both the detection and differentiation tasks. For LVH detection, the highest area under the curve (AUC) was 0.966 in the MYO group. For HCM vs. HHD differentiation, the best AUC was 0.935 in the MYO+PM group. Comparing the radiomics models to the CMR parameter models for the differentiation tasks, the radiomics models achieved significantly improved the performance (p = 0.002). Conclusions: The radiomics model with the MYO+PM features showed similar performance to the models developed from the MYO features in the detection task, but outperformed the models developed from the MYO or PM features in the differentiation task. In addition, the radiomic models performed better than the CMR parameters' models.

Protocol for pyrotinib cardiac safety in patients with HER2-positive early or locally advanced breast cancer-The EARLY-MYO-BC study.

Background and aim: Cardiotoxicity has become the most common cause of non-cancer death among breast cancer patients. Pyrotinib, a tyrosine kinase inhibitor targeting HER2, has been successfully used to treat breast cancer patients but has also resulted in less well-understood cardiotoxicity. This prospective, controlled, open-label, observational trial was designed to characterize pyrotinib's cardiac impacts in the neoadjuvant setting for patients with HER2-positive early or locally advanced breast cancer. Patients and methods: The EARLY-MYO-BC study will prospectively enroll HER2-positive breast cancer patients who are scheduled to receive four cycles of neoadjuvant therapy with pyrotinib or pertuzumab added to trastuzumab before radical breast cancer surgery. Patients will undergo comprehensive cardiac assessment before and after neoadjuvant therapy, including laboratory measures, electrocardiography, transthoracic echocardiography, cardiopulmonary exercise testing (CPET), and cardiac magnetic resonance (CMR). To test the non-inferiority of pyrotinib plus trastuzumab therapy to pertuzumab plus trastuzumab therapy in terms of cardiac safety, the primary endpoint will be assessed by the relative change in global longitudinal strain from baseline to completion of neoadjuvant therapy by echocardiography. The secondary endpoints include myocardial diffuse fibrosis (by T1-derived extracellular volume), myocardial edema (by T2 mapping), cardiac volumetric assessment by CMR, diastolic function (by left ventricular volume, left atrial volume, E/A, and E/E') by echocardiography, and exercise capacity by CPET. Discussion: This study will comprehensively assess the impacts of pyrotinib on myocardial structural, function, and tissue characteristics, and, furthermore, will determine whether pyrotinib plus trastuzumab is a reasonable dual HER2 blockade regimen with regard to cardiac safety. Results may provide information in selecting an appropriate anti-HER2 treatment for HER2-positive breast cancer. Clinical trial registration: https://clinicaltrials.gov/, identifier NCT04510532.

Biochemical and biophysical properties of an unreported T96R mutation causing transthyretin cardiac amyloidosis.

OBJECTIVES: We presented an unreported T96R mutation induced transthyretin cardiac amyloidosis (ATTR). The biochemical and biophysical properties were explored to support its pathogenicity. BACKGROUND: Understanding the biochemical and biophysical nature of genetically mutated transthyretin (TTR) proteins is key to provide precise medical cares for ATTR patients. RESULTS: Genetic testing showed heterozygosity for the T96R pathogenic variant c.347C > G (ATTR p.T116R) after myocardial biopsy confirmed amyloid deposition. Biochemical characterizations revealed slight perturbation of its thermodynamic stability (Cm=3.7 M for T96R, 3.4 M for WT and 2.3 M for L55P (commonly studied TTR mutant)) and kinetic stability (t1/2=39.8 h for T96R, 42 h for WT and 4.4 h in L55P). Crosslinking experiment demonstrated heterozygous subunit exchange between wild-type and TTR T96R protein destabilized the tetramer. Inhibitory effect of tafamidis and diflunisal on TTR T96R fibril formation was slightly less effective compared to WT and L55P. CONCLUSIONS: A novel T96R mutation was identified for TTR protein. Biochemical and biophysical analyses revealed slightly destabilized kinetic stability. T96R mutation destabilized heterozygous protein but not proteolytic degradation, explaining its pathogenicity. Inhibitory effect of small molecule drugs on T96R mutation was different, suggesting personalized treatment may be required.

Myocardial Tissue-Level Characteristics of Adults With Metabolically Healthy Obesity.

BACKGROUND: It remains unclear whether adults with metabolically healthy obesity (MHO) have altered myocardial tissue-level characteristics. OBJECTIVES: This study aims to assess the subclinical myocardial tissue-level characteristics of adults with MHO. METHODS: The EARLY-MYO-OBESITY (EARLY Assessment of MYOcardial Tissue Characteristics in OBESITY; NCT05277779) registry was a prospective, 3-center, cardiac imaging study of obese nondiabetic individuals without cardiac symptoms who underwent cardiac magnetic resonance. Myocardial tissue-level characteristics, including extracellular volume fraction (ECV) and native T2 values, were measured as indicators of myocardial fibrosis and edema. Global longitudinal peak systolic strain and early diastolic longitudinal strain rate were assessed by tissue tracking analysis to detect subclinical systolic and diastolic dysfunction. RESULTS: A total of 120 participants were included: MHO (n = 32; mean age, 38 years; 41% men), metabolically healthy controls without obesity (n = 32; mean age: 37 years; 41% men), and metabolically unhealthy obesity (MUHO) (n = 56; mean age: 37 years; 55% men). The MHO group had higher ECV and native T2 values than healthy controls (both P < 0.001); furthermore, the ECV was higher in the MUHO group than in the MHO group (P = 0.002). The prevalence of myocardial fibrosis was 44% (14 of 32) in the MHO group and 71% (40 of 56) in the MUHO group. Although there was no intergroup difference in left ventricular ejection fraction, the MHO group had reduced global longitudinal peak systolic and early diastolic longitudinal strain rates, indicating subclinical systolic and diastolic dysfunction. Multivariate regression analysis identified increased body mass index to be an independent risk factor for myocardial fibrosis (OR: 6.28 [95% CI: 3.17-12.47]; P < 0.001). CONCLUSIONS: This study provides the first evidence of subclinical myocardial tissue-level remodeling in adults with obesity, regardless of metabolic health. Early identification of cardiac impairment may facilitate preventive strategies against heart failure in the MHO population. (EARLY Assessment of MYOcardial Tissue Characteristics in OBESITY [EARLY-MYO-OBESITY]; NCT05277779).

Targeting the Synthetic Vulnerability of PTEN-Deficient Glioblastoma Cells with MCL1 Inhibitors.

PTEN deletion or mutation occurs in 30% to 60% of patients with glioblastoma (GBM) and is associated with poor prognosis. Efficacious therapy for this subgroup of patients is currently lacking. To identify potential target(s) to selectively suppress PTEN-deficient GBM growth, we performed a three-step synthetic lethal screen on LN18 PTEN wild-type (WT) and knockout (KO) isogeneic GBM cell lines using a library containing 606 target-selective inhibitors. A MCL1 inhibitor UMI-77 identified in the screen exhibited excellent suppression on the proliferation, colony formation, 3D spheroid, and neurosphere formation of PTEN-deficient GBM cells. Mechanistically, loss of PTEN in GBM cells led to upregulation of MCL1 in posttranslational level via inhibition of GSK3ß, and consequently confer cells resistance to apoptosis. Pharmacologic inhibition or knockdown of MCL1 blocked this PI3K-GSK3ß-MCL1 axis and caused reduction of several antiapoptotic proteins, finally induced massive caspase-3 cleavage and apoptosis. In both subcutaneous and orthotopic GBM models, knockdown of MCL1 significantly impaired the in vivo growth of PTEN-deficient xenografts. Moreover, the combination of UMI-77 and temozolomide synergistically killed PTEN-deficient GBM cells. Collectively, our work identified MCL1 as a promising target for PTEN-deficient GBM. For future clinical investigations, priority should be given to the development of a selective MCL1 inhibitor with efficient brain delivery and minimal in vivo toxicity.