Autonomic Nerve Activity and Blood Pressure in Ambulatory Dogs

Background The relationship between cardiac autonomic nerve activity and blood pressure (BP) changes in ambulatory dogs is unclear. Objective To test the hypotheses that simultaneous termination of stellate ganglion nerve activity (SGNA) and vagal nerve activity (VNA) predisposes to spontaneous orthostatic hypotension and that specific β2 adrenoceptor blockade prevents the hypotensive episodes. Methods We used a radiotransmitter to record SGNA, VNA and blood pressure (BP) in 8 ambulatory dogs. Video imaging was used to document postural changes. Results Out of these 8 dogs, 5 showed simultaneous sympathovagal discharges in which the minute by minute integrated SGNA correlated with integrated VNA in a linear pattern (“Group 1”). In these dogs abrupt termination of simultaneous SGNA-VNA at the time of postural changes (as documented by video imaging) was followed by abrupt (>20 mmHg over 4 beats) drops in BP. Dogs without simultaneous on/off firing (“Group 2”) did not have drastic drops in pressure. ICI 118,551 (ICI, a specific β2-blocker) infused at 3.1 µg/kg/hr for 7 days significantly increased BP from 126 (95% confidence interval, CI: 118 to 133) mmHg to 133 (95% CI 125 to141) mmHg (p=0.0001). The duration of hypotension (mean systolic BP < 100 mmHg) during baseline accounted for 7.1% of the recording. The percentage was reduced by ICI to 1.3% (p = 0.01). Conclusions Abrupt simultaneous termination of SGNA-VNA was observed at the time of orthostatic hypotension in ambulatory dogs. Selective β2 adrenoceptor blockade increased BP and reduced the duration of hypotension in this model

An automated machine learning approach to predict brain age from cortical anatomical measures

The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to predict the target variable? What are the hyperparameters for such a model? Given the plethora of possible answers to these questions, in the last years, automated ML (autoML) has been gaining attention. Here, we apply an autoML library called Tree-based Pipeline Optimisation Tool (TPOT) which uses a tree-based representation of ML pipelines and conducts a genetic programming-based approach to find the model and its hyperparameters that more closely predicts the subject's true age. To explore autoML and evaluate its efficacy within neuroimaging data sets, we chose a problem that has been the focus of previous extensive study: brain age prediction. Without any prior knowledge, TPOT was able to scan through the model space and create pipelines that outperformed the state-of-the-art accuracy for Freesurfer-based models using only thickness and volume information for anatomical structure. In particular, we compared the performance of TPOT (mean absolute error [MAE]: 4.612 ± .124 years) and a relevance vector regression (MAE 5.474 ± .140 years). TPOT also suggested interesting combinations of models that do not match the current most used models for brain prediction but generalise well to unseen data. AutoML showed promising results as a data-driven approach to find optimal models for neuroimaging applications

Genomic clustering analysis identifies molecular subtypes of thymic epithelial tumors independent of World Health Organization histologic type

Further characterization of thymic epithelial tumors (TETs) is needed. Genomic information from 102 evaluable TETs from The Cancer Genome Atlas (TCGA) dataset and from the IU-TAB-1 cell line (type AB thymoma) underwent clustering analysis to identify molecular subtypes of TETs. Six novel molecular subtypes (TH1-TH6) of TETs from the TCGA were identified, and there was no association with WHO histologic subtype. The IU-TAB-1 cell line clustered into the TH4 molecular subtype and in vitro testing of candidate therapeutics was performed. The IU-TAB-1 cell line was noted to be resistant to everolimus (mTORC1 inhibitor) and sensitive to nelfinavir (AKT1 inhibitor) across the endpoints measured. Sensitivity to nelfinavir was due to the IU-TAB-1 cell line’s gain-of function (GOF) mutation in PIK3CA and amplification of genes observed from array comparative genomic hybridization (aCGH), including AURKA, ERBB2, KIT, PDGFRA and PDGFB, that are known upregulate AKT, while resistance to everolimus was primarily driven by upregulation of downstream signaling of KIT, PDGFRA and PDGFB in the presence of mTORC1 inhibition. We present a novel molecular classification of TETs independent of WHO histologic subtype, which may be used for preclinical validation studies of potential candidate therapeutics of interest for this rare disease

Cervical vagal nerve stimulation activates the stellate ganglion in ambulatory dogs

BACKGROUND AND OBJECTIVES: Recent studies showed that, in addition to parasympathetic nerves, cervical vagal nerves contained significant sympathetic nerves. We hypothesized that cervical vagal nerve stimulation (VNS) may capture the sympathetic nerves within the vagal nerve and activate the stellate ganglion. MATERIALS AND METHODS: We recorded left stellate ganglion nerve activity (SGNA), left thoracic vagal nerve activity (VNA), and subcutaneous electrocardiogram in seven dogs during left cervical VNS with 30 seconds on-time and 30 seconds off time. We then compared the SGNA between VNS on and off times. RESULTS: Cervical VNS at moderate (0.75 mA) output induced large SGNA, elevated heart rate (HR), and reduced HR variability, suggesting sympathetic activation. Further increase of the VNS output to >1.5 mA increased SGNA but did not significantly increase the HR, suggesting simultaneous sympathetic and parasympathetic activation. The differences of integrated SGNA and integrated VNA between VNS on and off times (ΔSGNA) increased progressively from 5.2 mV-s {95% confidence interval (CI): 1.25-9.06, p=0.018, n=7} at 1.0 mA to 13.7 mV-s (CI: 5.97-21.43, p=0.005, n=7) at 1.5 mA. The difference in HR (ΔHR, bpm) between on and off times was 5.8 bpm (CI: 0.28-11.29, p=0.042, n=7) at 1.0 mA and 5.3 bpm (CI 1.92 to 12.61, p=0.122, n=7) at 1.5 mA. CONCLUSION: Intermittent cervical VNS may selectively capture the sympathetic components of the vagal nerve and excite the stellate ganglion at moderate output. Increasing the output may result in simultaneously sympathetic and parasympathetic capture

Role of KEAP1/NFE2L2 Mutations in the Chemotherapeutic Response of Patients with Non-Small Cell Lung Cancer.

Purpose: Activation of NFE2L2 has been linked to chemoresistance in cell line models. Recently, somatic mutations that activate NFE2L2, including mutations in NFE2L2, KEAP1, or CUL3, have been found to be associated with poor outcomes in patients with non–small cell lung cancer (NSCLC). However, the impact of these mutations on chemoresistance remains incompletely explored. Experimental Design: We investigated the effect of Keap1 deletion on chemoresistance in cell lines from Trp53-based mouse models of lung squamous cell carcinoma (LSCC) and lung adenocarcinoma (LUAD). Separately, we identified 51 patients with stage IV NSCLC with KEAP1, NFE2L2, or CUL3 mutations and a matched cohort of 52 wild-type patients. Time to treatment failure after first-line platinum doublet chemotherapy and overall survival was compared between the two groups. Results: Deletion of Keap1 in Trp53-null murine LUAD and LSCC resulted in increased clonogenic survival upon treatment with diverse cytotoxic chemotherapies. In patients with NSCLC, median time to treatment failure (TTF) after first-line chemotherapy for the KEAP1/NFE2L2/CUL3-mutant cohort was 2.8 months compared with 8.3 months in the control group (P &lt; 0.0001). Median overall survival (OS) was 11.2 months in the KEAP1/NFE2L2/CUL3-mutant group and 36.8 months in the control group (P ¼ 0.006). Conclusions: Keap1 deletion confers chemoresistance in murine lung cancer cells. Patients with metastatic NSCLC with mutations in KEAP1, NFE2L2, or CUL3 have shorter TTF and OS after first-line platinum doublet chemotherapy compared with matched controls. Novel approaches for improving outcomes in this subset of patients with NSCLC are therefore needed. ©2019 American Association for Cancer Research.1

Genetic Determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo.

In lung adenocarcinoma, oncogenic EGFR mutations co-occur with many tumor suppressor gene alterations; however, the extent to which these contribute to tumor growth and response to therapy in vivo remains largely unknown. By quantifying the effects of inactivating 10 putative tumor suppressor genes in a mouse model of EGFR-driven Trp53-deficient lung adenocarcinoma, we found that Apc, Rb1, or Rbm10 inactivation strongly promoted tumor growth. Unexpectedly, inactivation of Lkb1 or Setd2-the strongest drivers of growth in a KRAS-driven model-reduced EGFR-driven tumor growth. These results are consistent with mutational frequencies in human EGFR- and KRAS-driven lung adenocarcinomas. Furthermore, KEAP1 inactivation reduced the sensitivity of EGFR-driven tumors to the EGFR inhibitor osimertinib, and mutations in genes in the KEAP1 pathway were associated with decreased time on tyrosine kinase inhibitor treatment in patients. Our study highlights how the impact of genetic alterations differs across oncogenic contexts and that the fitness landscape shifts upon treatment. SIGNIFICANCE: By modeling complex genotypes in vivo, this study reveals key tumor suppressors that constrain the growth of EGFR-mutant tumors. Furthermore, we uncovered that KEAP1 inactivation reduces the sensitivity of these tumors to tyrosine kinase inhibitors. Thus, our approach identifies genotypes of biological and therapeutic importance in this disease.This article is highlighted in the In This Issue feature, p. 1601