Development of a passive and remote magnetic microsensor with thin-film giant magnetoimpedance element and surface acoustic wave transponder

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98710/1/JApplPhys_109_07E524.pd

Spectrum of immune checkpoint inhibitors-induced endocrinopathies in cancer patients: a scoping review of case reports

Abstract Background Since 2011 six immune checkpoint inhibitors (ICI) have been approved to treat patients with many advanced solid tumor and hematological malignancies to improve their prognosis. Case reports of their endocrine immune-related adverse events [irAEs]) are increasingly published as more real-world patients with these malignancies are treated with these drugs. They alert physicians of a drug’s AEs (which may change during a drug’s life cycle) and contribute to post-marketing safety surveillance. Using a modified framework of Arksey and O’Malley, we conducted a scoping review of the spectrum and characteristics of ICI-induced endocrinopathies case reports before and after ICIs are marketed. Methods In July 2017, we searched, without date and language restrictions, 4 citation databases for ICI-induced endocrinopathies. We also hand-searched articles’ references, contents of relevant journals, and ran supplemental searches to capture recent reports through January 2018. For this study, a case should have information on type of cancer, type of ICI, clinical presentation, biochemical tests, treatment plus temporal association of ICI initiation with endocrinopathies. Two endocrinologists independently extracted the data which were then summarized and categorized. Results One hundred seventy nine articles reported 451 cases of ICI-induced endocrinopathies - 222 hypopituitarism, 152 thyroid disorders, 66 diabetes mellitus, 6 primary adrenal insufficiencies, 1 ACTH-dependent Cushing’s syndrome, 1 hypoparathyroidism and 3 diabetes insipidus cases. Their clinical presentations reflect hormone excess or deficiency. Some were asymptomatic and others life-threatening. One or more endocrine glands could be affected. Polyglandular endocrinopathies could present simultaneously or in sequence. Many occur within 5 months of therapy initiation; a few occurred after ICI was stopped. Mostly irreversible, they required long-term hormone replacement. High dose steroids were used when non-endocrine AEs coexisted or as therapy in adrenal insufficiency. There was variability of information in the case reports but all met the study criteria to make a diagnosis. Conclusions The spectrum of ICI-induced endocrinopathies is wide (5 glands affected) and their presentation varied (12 endocrinopathies). Clinical reasoning integrating clinical, biochemical and treatment information is needed to properly diagnose and manage them. Physicians should be vigilant for their occurrence and be able to diagnose, investigate and manage them appropriately at onset and follow-up.https://deepblue.lib.umich.edu/bitstream/2027.42/147443/1/40842_2018_Article_73.pd

Evaluation of Hemoglobin A1c Criteria to Assess Preoperative Diabetes Risk in Cardiac Surgery Patients

Objective: Hemoglobin A1c (A1C) has recently been recommended for diagnosing diabetes mellitus and diabetes risk (prediabetes). Its performance compared with fasting plasma glucose (FPG) and 2-h post-glucose load (2HPG) is not well delineated. We compared the performance of A1C with that of FPG and 2HPG in preoperative cardiac surgery patients. Methods: Data from 92 patients without a history of diabetes were analyzed. Patients were classified with diabetes or prediabetes using established cutoffs for FPG, 2HPG, and A1C. Sensitivity and specificity of the new A1C criteria were evaluated. Results: All patients diagnosed with diabetes by A1C also had impaired fasting glucose, impaired glucose tolerance, or diabetes by other criteria. Using FPG as the reference, sensitivity and specificity of A1C for diagnosing diabetes were 50% and 96%, and using 2HPG as the reference they were 25% and 95%. Sensitivity and specificity for identifying prediabetes with FPG as the reference were 51% and 51%, respectively, and with 2HPG were 53% and 51%, respectively. One-third each of patients with prediabetes was identified using FPG, A1C, or both. When testing A1C and FPG concurrently, the sensitivity of diagnosing dysglycemia increased to 93% stipulating one or both tests are abnormal; specificity increased to 100% if both tests were required to be abnormal. Conclusions: In patients before cardiac surgery, A1C criteria identified the largest number of patients with diabetes and prediabetes. For diagnosing prediabetes, A1C and FPG were discordant and characterized different groups of patients, therefore altering the distribution of diabetes risk. Simultaneous measurement of FGP and A1C may be a more sensitive and specific tool for identifying high-risk individuals with diabetes and prediabetes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90436/1/dia-2E2011-2E0074.pd

Energy scavenging from insect flight

This paper reports the design, fabrication and testing of an energy scavenger that generates power from the wing motion of a Green June Beetle (C otinis nitida ) during its tethered flight. The generator utilizes non-resonant piezoelectric bimorphs operated in the d 31 bending mode to convert mechanical vibrations of a beetle into electrical output. The available deflection, force, and power output from oscillatory movements at different locations on a beetle are measured with a meso-scale piezoelectric beam. This way, the optimum location to scavenge energy is determined, and up to ~115 µW total power is generated from body movements. Two initial generator prototypes were fabricated, mounted on a beetle, and harvested 11.5 and 7.5 µW in device volumes of 11.0 and 5.6 mm 3 , respectively, from 85 to 100 Hz wing strokes during the beetle's tethered flight. A spiral generator was designed to maximize the power output by employing a compliant structure in a limited area. The necessary technology needed to fabricate this prototype was developed, including a process to machine high-aspect ratio devices from bulk piezoelectric substrates with minimum damage to the material using a femto-second laser. The fabricated lightweight spiral generators produced 18.5–22.5 µW on a bench-top test setup mimicking beetles' wing strokes. Placing two generators (one on each wing) can result in more than 45 µW of power per insect. A direct connection between the generator and the flight muscles of the insect is expected to increase the final power output by one order of magnitude.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90804/1/0960-1317_21_9_095016.pd

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods

Gradient Descent Optimization in Gene Regulatory Pathways

BACKGROUND: Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms. METHODOLOGY: In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings. CONCLUSIONS: We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological significance and applicability of the optimal pathways has also been discussed. Finally the usefulness of the present method on genetic engineering is depicted with an example