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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.

Supplemental Table 1.-Oligonucleotide sequences.

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 GSK3β, and consequently confer cells resistance to apoptosis. Pharmacologic inhibition or knockdown of MCL1 blocked this PI3K–GSK3β–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.

Supplemental Figure 1. Kaplan-Meier survival curves of glioma patients with positive or negative MCL1 expression (P-value by log-rank test). Supplemental Figure 2. Layout of apoptotic antibody array and results analysis. Supplemental Figure 3. Evaluation of the anti�GBM effect of the combined treatment of UMI�77 and temozolomide (U+T). Supplemental Figure 4. Combination treatment of temozolomide and UMI-77 in established GBM cell lines.

We presented an unreported T96R mutation induced transthyretin cardiac amyloidosis (ATTR). The biochemical and biophysical properties were explored to support its pathogenicity.Understanding the biochemical and biophysical nature of genetically mutated transthyretin (TTR) proteins is key to provide precise medical cares for ATTR patients.Genetic testing showed heterozygosity for the T96R pathogenic variant c.347C G (ATTRA 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.

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 GSK3β, and consequently confer cells resistance to apoptosis. Pharmacologic inhibition or knockdown of MCL1 blocked this PI3K–GSK3β–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.

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 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.