Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation

A lean neck mass clinic model: Adding value to care

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115945/1/lary25535.pd

Integrated Molecular Profiling as an Approach to Identify PI3K Inhibitor Resistance Mechanisms

The identification of drug resistance pathways and approaches to target these pathways remains a significant and important challenge in cancer biology. Here, we address this challenge in the context of ongoing efforts to advance phosphatidylinositol 3-kinase (PI3K) inhibitors for the treatment of PI3K-aberrant cancers. While PI3K inhibitors have had tremendous success in some diseases, such as breast cancer, early clinical trials in other malignancies, such as head and neck squamous cell carcinoma (HNSCC), have not had the same level of success. Since HNSCC and other cancers display relatively high PI3K pathway alteration rates (>45%), these underwhelming results suggest that additional or unexpected factors may contribute to the lower response rates. Here, we highlight some of the emerging functional genomic and sequencing approaches being used to identify predictive biomarkers of PI3K inhibitor response using both cancer cell lines and clinical trial specimens. Importantly, these approaches have uncovered both innate genetic and adaptive mechanisms driving PI3K inhibitor resistance. In this chapter, we describe recent technological advances that have revolutionized our understanding of PI3K inhibitor resistance pathways in HNSCC and highlight how these and other approaches lay the groundwork to make significant strides in our understanding of molecular pharmacology in the cancer field

- My Research Is Their Business, but I’m Not Their Business- : Patient and Clinician Perspectives on Commercialization of Precision Oncology Data

BackgroundGenetic sequencing and precision oncology have supported clinical breakthroughs but depend upon access to vast arrays of research specimens and data. One way for academic medical centers to fund such infrastructure and research is - commercialization- of access to specimens and data to industry. Here we explore patient and clinician perspectives regarding cancer specimen and data commercialization with the goal of improving such processes in the future.Materials and MethodsThis qualitative analysis was embedded within a prospective precision oncology sequencing study of adults with head and neck cancer. Via semistructured dyadic interviews with patients with cancer and their doctors, we assessed understanding and concerns regarding potential commercialization, opinions regarding investment of profits, and perspectives regarding the return of information directly to participants from industry.ResultsSeveral patient- and clinician- participants did not understand that the consent form already permitted commercialization of patient genetic data and expressed concerns regarding who would profit from the data, how profits would be used, and privacy and access. Patients were generally more comfortable with commercialization than clinicians. Many patients and clinicians were comfortable with investing profits back into research, but clinicians were more interested in investment in head and neck cancer research specifically. Patients generally supported potential return- of- results from a private entity, but their clinicians were more skeptical.ConclusionOur results illustrate the limitations of mandatory disclosures in the informed consent process. The voices of both patients and their doctors are critical to mitigate violations of privacy and a degradation of trust as stakeholders negotiate the terms of academic and commercial engagement.Implications for PracticeFurther education is needed regarding how and why specimens and data in precision oncology research may be commercialized for both patients and providers alike. This process will require increased transparency, comprehension, and engagement of involved stakeholders.To better understand perspectives on cancer specimen and data commercialization, interviews of patients participating in a prospective precision medicine cancer sequencing study were conducted, along with corresponding interviews with the patients’ referring doctors. This article reports the results and aims to improve the consent process for biospecimen and health data sharing and commercialization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156136/2/onco13272.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156136/1/onco13272_am.pd

The molecular landscape of the University of Michigan laryngeal squamous cell carcinoma cell line panel

BackgroundLaryngeal squamous cell carcinomas (LSCCs) have a high risk of recurrence and poor prognosis. Patient‐derived cancer cell lines remain important preclinical models for advancement of new therapeutic strategies, and comprehensive characterization of these models is vital in the precision medicine era.MethodsWe performed exome and transcriptome sequencing as well as copy number analysis of a panel of LSCC‐derived cell lines that were established at the University of Michigan and are used in laboratories worldwide.ResultsWe observed a complex array of alterations consistent with those reported in The Cancer Genome Atlas head and neck squamous cell carcinoma project, including aberrations in PIK3CA, EGFR, CDKN2A, TP53, and NOTCH family and FAT1 genes. A detailed analysis of FAT family genes and associated pathways showed disruptions to these genes in most cell lines.ConclusionsThe molecular profiles we have generated indicate that as a whole, this panel recapitulates the molecular diversity observed in patients and will serve as useful guides in selecting cell lines for preclinical modeling.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151290/1/hed25803.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151290/2/hed25803_am.pd

Predictors of survival after total laryngectomy for recurrent/persistent laryngeal squamous cell carcinoma

BackgroundTotal laryngectomy remains the treatment of choice for recurrent/persistent laryngeal squamous cell carcinoma (SCC) after radiotherapy (RT) or chemoradiotherapy (CRT). However, despite attempts at aggressive surgical salvage, survival in this cohort remains suboptimal.MethodsA prospectively maintained single‐institution database was queried for patients undergoing total laryngectomy for recurrent/persistent laryngeal SCC after initial RT/CRT between 1998 and 2015(n = 244). Demographic, clinical, and survival data were abstracted. The Kaplan‐Meier survival curves and hazard ratios (HRs) were calculated.ResultsFive‐year overall survival (OS) was 49%. Five‐year disease‐free survival (DFS) was 58%. Independent predictors of OS included severe comorbidity (Adult Comorbidity Evaluation‐27 [ACE‐27] scale; HR 3.76; 95% confidence interval [CI] 1.56‐9.06), and positive recurrent clinical nodes (HR 2.91; 95% CI 1.74‐4.88).ConclusionSevere comorbidity status is the strongest predictor of OS, suggesting that increased attention to mitigating competing risks to health is critical. These data may inform a risk prediction model to allow for focused shared decision making, preoperative health optimization, and patient selection for adjuvant therapies.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139972/1/hed24918.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139972/2/hed24918_am.pd

The immune cell landscape in kidneys of patients with lupus nephritis.

Lupus nephritis is a potentially fatal autoimmune disease for which the current treatment is ineffective and often toxic. To develop mechanistic hypotheses of disease, we analyzed kidney samples from patients with lupus nephritis and from healthy control subjects using single-cell RNA sequencing. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid cells, T cells, natural killer cells and B cells that demonstrated both pro-inflammatory responses and inflammation-resolving responses. We found evidence of local activation of B cells correlated with an age-associated B-cell signature and evidence of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, implying a potentially central role in cell trafficking. Gene expression of immune cells in urine and kidney was highly correlated, which would suggest that urine might serve as a surrogate for kidney biopsies

Mutational profiles of persistent/recurrent laryngeal squamous cell carcinoma

BackgroundWe sought to describe targeted DNA sequencing data of persistent/recurrent laryngeal squamous cell carcinoma (LSCC) and to compare gene‐specific alteration frequencies with that of primary, untreated LSCC specimens from The Cancer Genome Atlas (TCGA).MethodsThe tumors of 21 patients with persistent/recurrent LSCC were subjected to targeted DNA sequencing using the Ion AmpliSeq Comprehensive Cancer Panel. Gene‐specific alteration frequencies were compared (Chi‐Square test) to primary, untreated LSCC sequencing data from TCGA using the cBioPortal platform.ResultsPersistent/recurrent LSCC was characterized by a high rate of inactivating alterations in TP53 (38.1%) and CDKN2A (33%), amplification events of CCND1 (19.1%), and ERBB2 (14.3%), and NOTCH1 (19.1%) mutations. Comparison of primary vs persistent/recurrent LSCC revealed significant differences in alteration frequencies of eight critical genes: BAP1, CDKN2A, DCUN1D1, MSH2, MTOR, PIK3CA, TET2, and TP53.ConclusionsOur results provide preliminary support for a distinct mutational profile of persistent/recurrent LSCC that requires validation in larger cohorts.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147873/1/hed25444.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147873/2/hed25444_am.pd

The Nanostructure of Myoendothelial Junctions Contributes to Signal Rectification between Endothelial and Vascular Smooth Muscle Cells

Micro-anatomical structures in tissues have potential physiological effects. In arteries and arterioles smooth muscle cells and endothelial cells are separated by the internal elastic lamina, but the two cell layers often make contact through micro protrusions called myoendothelial junctions. Cross talk between the two cell layers is important in regulating blood pressure and flow. We have used a spatiotemporal mathematical model to investigate how the myoendothelial junctions affect the information flow between the two cell layers. The geometry of the model mimics the structure of the two cell types and the myoendothelial junction. The model is implemented as a 2D axi-symmetrical model and solved using the finite element method. We have simulated diffusion of Ca2+ and IP3 between the two cell types and we show that the micro-anatomical structure of the myoendothelial junction in itself may rectify a signal between the two cell layers. The rectification is caused by the asymmetrical structure of the myoendothelial junction. Because the head of the myoendothelial junction is separated from the cell it is attached to by a narrow neck region, a signal generated in the neighboring cell can easily drive a concentration change in the head of the myoendothelial protrusion. Subsequently the signal can be amplified in the head, and activate the entire cell. In contrast, a signal in the cell from which the myoendothelial junction originates will be attenuated and delayed in the neck region as it travels into the head of the myoendothelial junction and the neighboring cell