Citations

Background: Asymptomatic recurrences of atrial fibrillation (AF) are common after ablation of AF. Objective: We aimed to analyze the performance of the mobile ECG device using artificial intelligence (AI) algorithm in detection of AF after ablation. Method: A randomized controlled trial of AF screening using a handheld single-lead ECG monitor (BigThumb®) or a traditional follow-up strategy was conducted in patients with non-valvular AF after catheter ablation. Consecutive patients were randomized to either BigThumb Group (BT Group) or Traditional Follow-up Group (TF Group). Monitoring data was collected and analyzed. The ECGs collected by BigThumb were compared using the automated AF detection algorithm, AI algorithm and cardiologists’ manual review. Subsequent changes in adherence on oral anticoagulation of patients were also recorded. Result: We studied 218 patients (109 in BT Group, 109 in TF Group). After a follow-up of 345.4±60.2 days, AF-free survival rate was 64.2% in BT Group and 78.9% in TF Group (P=0.0163), with more adherence on oral anticoagulation in BT Group (P=0.0052). The participants in the BT Group recorded 26133 ECGs during the follow-up, among which 3299 (12.6%) were diagnosed as AF by cardiologists’ manual review. The sensitivity and specificity of the AI algorithm were 94.4% and 98.5% respectively, which are significantly higher than the automated AF detection algorithm (90.7% and 96.2%). Conclusion: We found that follow-up after AF ablation using BigThumb leads to a more frequent detection of AF recurrence and more adherence on oral anticoagulation. Artificial intelligence algorithm improves the accuracy of ECG diagnosis.

Abstract C-type natriuretic peptide (CNP) is an endothelium-drived vasorelaxing factor which is present in human plasma, urine and renal epithelial cells. Endothelin (ET) is a potent renal and systemic vasoconstrictor and sodium regulating peptide. To date, the localization of C-type natriuretic peptide and endothelin gene expression in human kidney remains poorly defined. We determined the co-localization of C-type natriuretic peptide and endothelin mRNA in normal human kidney using in situ hybridization (ISH) with synthesized human C-type natriuretic peptide or human endothelin oligonucleotide probes together with immunohistochemical staining (IHCS) with human CNP-22 and ET-1 antibodies with no crossreactivity. The sections treated with nonimmune rabbit serum (NRS) demonstrated no immunoperoxidase activity. Human renal tissue (n=7) was obtained from biopsy of normal cadaveric donor kidneys and normal autopsy specimens. In situ hybridization (Figure 1) demonstrated that C-type natriuretic peptide and endothelin mRNA presence in human kidney which was localized to proximal and distal tubes with similar intensities.

Introduction: The right ventricle (RV) strain measured by speckle tracking (RVS) is a novel method of assessing RV function. We compared RVS to RV fractional area change (FAC%), tricuspid annular peak systolic excursion (TAPSE) and Doppler tissue imaging-derived peak systolic velocity (S’) in the assessment of right ventricular (RV) systolic function measured using cardiac magnetic resonance imaging (MRI). Methods: We enrolled consecutive patients who underwent cardiac MRI between Jan 2012- Dec 2017 and a transthoracic echocardiogram (TTE) within 1 month of the MRI with no interval event. Baseline clinical characteristics and MRI parameters were extracted from chart review. Echocardiographic parameters were measured prospectively. TTE parameters including RVS, TAPSE, S’ and FAC% were tested for accuracy to identify impaired RV EF (EF <45% & <30%) using receiver operator curves. Results: The study cohort included 500 patients with mean age 55 yr ± 18 and right ventricular systolic pressure 33.7 ± 13.6 mmHg. The area under ROC for RVS was 0.69 (95% CI 0.63 – 0.75) and 0.78 (95% CI 0.70 – 0.88) to predict RVEF <45% & RVEF <30% respectively. The RV FAC % had second highest accuracy of predicting RVEF among all the TTE parameters tested in study. Conclusion: Right ventricular strain is the most accurate echocardiographic method to detect impaired right ventricular systolic function when using MRI as the gold standard.

Abstract Objective Chondrocyte apoptosis plays a vital role in osteoarthritis (OA) progression. Angelica sinensis polysaccharide (ASP), a traditional Chinese medicine, possesses anti-inflammatory and anti-apoptotic properties in chondrocytes. This study aimed to determine the protective role of ASP on sodium nitroprusside (SNP)-induced chondrocyte apoptosis, and explore the underlying mechanism. Method Human primary chondrocytes isolated from articular cartilage of OA patients were treated with SNP alone or in combination with different dose of ASP. Cell viability and apoptosis were assessed, and apoptosis-related proteins including Bcl-2 and Bax were detected. Autophagy levels were evaluated by light chain 3 (LC3)-II immunofluorescence staining, mRFP-GFP-LC3 fluorescence localisation and western blot (LC3II, p62, Beclin-1, Atg5). Meanwhile,activation of ERK 1/2 pathway was determined by western blot. The autophagy inhibitors 3-Methyladenine (3-MA), chloroquine (CQ) and a specific inhibitor of ERK1/2, SCH772984, were used respectively to confirm the autophagic effect of ASP. Results The results showed that SNP-induced chondrocyte apoptosis was significantly rescued by ASP, whereas ASP alone promoted chondrocytes proliferation. The anti-apoptotic effect of ASP was related to the enhanced autophagy and depended on the activation of ERK1/2 pathway.Conclusion ASP markedly rescued SNP-induced chondrocyte apoptosis by activating ERK1/2-dependent autophagy in chondrocytes, and it made ASP a potential therapeutic supplementation for OA treatment.

176 Background: Multiple tumour tissue studies have demonstrated the prognostic utility of CNVs in mCRPC. However, accurate assessment of CNVs in plasma cfDNA remains challenging, and prognostic significance has not been well characterized. Using a large customized panel, we correlated plasma CNVs with clinical outcomes in a contemporary cohort of mCRPC patients. Methods: Deep targeted sequencing was performed using a 180-gene cfDNA panel (Predicine) in 56 patients commencing AR pathway inhibitors (enzalutamide or abiraterone; n = 34) or taxane chemotherapy (n = 22) at two Australian institutions. Kaplan-Meier estimates and Cox proportional-hazards models were used to correlate CNVs with progression-free survival (PFS) and overall survival (OS). Significant results were validated in an independent cohort (Mayo Clinic, n = 144). Results: Median follow-up was 19.4 months (mo; IQR 11.3-31.9). The most common CNVs in the Australian cohort are shown (Table). OS was significantly decreased in patients with PI3KCA gain (median 21.7 mo vs 6.6 mo, p < 0.0001), PTEN loss (24.8 mo vs 11.7 mo, p = 0.0019) and AR gain (21.7 mo vs 12.0 mo, p = 0.0083). Furthermore, all three alterations independently predicted for poor survival in multivariable analyses (MVA; Table). Findings in the independent cohort showed similar OS results in MVA: PIK3CA gain (HR 2.0, p = 0.07), PTEN loss (HR 1.7, p = 0.08) and AR gain (HR 1.7, p = 0.03). Conclusions: Sequencing of plasma cfDNA revealed that PTEN loss, and PIK3CA and AR gain are associated with inferior clinical outcomes in patients commencing contemporary systemic treatment. These data support therapeutic strategies co-targeting the PI3K and AR pathways in mCRPC.[Table: see text]

We clarify that DNA damage triggers autophagy by CHK2-FOXK axis, and misregulation of this pathway leads to chemoresistance.

Oral squamous cell carcinoma (OSCC) is among the most commonly diagnosed malignancies in the world. Patients with OSCC often develop treatment resistance, resulting in a poor prognosis. Mounting evidence indicates that interactions between cancerous cells and other components of the tumor microenvironment (TME) determine their response to treatment. Herein, we examined the role of cancer stem cell-derived extracellular vesicles (CSC_EVs) generated from CAL27 and SCC-15 OSCC cells in the development of cisplatin (CDDP) resistance. We demonstrated that CSC_EVs enhance CDDP resistance, clonogenicity, and the tumorsphere formation potential of OSCC cells. Our bioinformatics analyses revealed that OSCC_EVs are enriched with microRNA (miR)-21-5p and are associated with increased metastasis, stemness, chemoresistance, and poor survival in patients with OSCC. Mechanistically, enhanced activity of CSC_EVs was positively correlated with upregulated β-catenin, phosphatidylinositol-3 kinase (PI3K), signal transducer and activator of transcription 3 (STAT3), mammalian target of rapamycin (mTOR), and transforming growth factor (TGF)-β1 messenger (m)RNA and protein expression levels. CSC_EVs also conferred a cancer-associated fibroblast (CAF) phenotype on normal gingival fibroblasts (NGFs), with the resultant CAFs enhancing the oncogenicity of OSCC cells. Interestingly, treatment with ovatodiolide (OV), the bioactive component of Anisomeles indica, suppressed OSCC tumorigenesis by reducing the cargo content of EVs derived from CSCs, suppressing self-renewal, and inhibiting the NGF-CAF transformation by disrupting EV-TME interactions. Moreover, by suppressing miR-21-5p, STAT3, and mTOR expressions in CSC_EVs, OV re-sensitized CSCs to CDDP and suppressed OSCC tumorigenesis. In vivo, treatment with OV alone or in combination with CDDP significantly reduced the tumor sphere-forming ability and decreased EV cargos containing mTOR, PI3K, STAT3, β-catenin, and miR-21-5p. In summary, our findings provide further strong evidence of OV’s therapeutic effect in OSCC.

Abstract There is a need for new approaches and endpoints in oncology drug development, particularly with the advent of immunotherapies and the multiple drug combinations under investigation. Tumor dynamics modeling, a key component to oncology “model-informed drug development,” has shown a growing number of applications and a broader adoption by drug developers and regulatory agencies in the past years to support drug development and approval in a variety of ways. Tumor dynamics modeling is also being investigated in personalized cancer therapy approaches. These models and applications are reviewed and discussed, as well as the limitations and issues open for further investigations. A close collaboration between stakeholders like clinical investigators, statisticians, and pharmacometricians is warranted to advance clinical cancer therapeutics.