Maintenance of head and neck tumor on-chip: gateway to personalized treatment?

Aim: Head and neck squamous cell carcinomas (HNSCC) are solid tumors with low overall survival (40–60%). In a move toward personalized medicine, maintenance of tumor biopsies in microfluidic tissue culture devices is being developed. Methodology/ results: HNSCC (n = 15) was dissected (5–10 mg) and either analyzed immediately or cultured in a microfluidic device (37°C) for 48 h. No difference was observed in morphology between pre- and postculture specimens. Dissociated samples were analyzed using trypan blue exclusion (viability), propidium iodide flow cytometry (death) and MTS assay (proliferation) with no significant difference observed highlighting tissue maintenance. Computational fluid dynamics showed laminar flow within the system. Conclusion: The microfluidic culture system successfully maintained HNSCC for 48 h, the culture system will allow testing of different treatment modalities with response monitoring. Lay abstract: Head and neck cancers often have a poor treatment outcome. In order to study the response of the tissue, a miniaturized culture system has been developed to keep a small piece of tumor alive. In the current study, we show that small pieces of cancer tissue can be maintained in the system, using tissue structure and viability of single cells as a guide. In future work, patient equivalent treatments can be applied to these microculture systems to investigate individual patient tumor responses, which could help to guide treatment selection

Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE). By allowing the diffusion and reaction terms to be multilayer perceptrons (MLPs), the nonlinear forms of these terms can be learned while simultaneously converging to the solution of the governing PDE. Further, the trained MLPs are used to guide the selection of biologically interpretable mechanistic forms of the PDE terms which provides new insights into the biological and physical mechanisms that govern the dynamics of the observed system. The method is evaluated on sparse real-world data from wound healing assays with varying initial cell densities [2]

Learning differential equation models from stochastic agent-based model simulations

Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology, and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common approaches to the analysis of agent-based models include extensive Monte Carlo simulation of the model or the derivation of coarse-grained differential equation models to predict the expected or averaged output from the agent-based model. Both of these approaches have limitations, however, as extensive computation of complex agent-based models may be infeasible, and coarse-grained differential equation models can fail to accurately describe model dynamics in certain parameter regimes. We propose that methods from the equation learning field provide a promising, novel, and unifying approach for agent-based model analysis. Equation learning is a recent field of research from data science that aims to infer differential equation models directly from data. We use this tutorial to review how methods from equation learning can be used to learn differential equation models from agent-based model simulations. We demonstrate that this framework is easy to use, requires few model simulations, and accurately predicts model dynamics in parameter regions where coarse-grained differential equation models fail to do so. We highlight these advantages through several case studies involving two agent-based models that are broadly applicable to biological phenomena: a birth-death-migration model commonly used to explore cell biology experiments and a susceptible-infected-recovered model of infectious disease spread

Transfer of arbitrary quantum emitter states to near-field photon superpositions in nanocavities

We present a method to analyze the suitability of particular photonic cavity designs for information exchange between arbitrary superposition states of a quantum emitter and the near-field photonic cavity mode. As an illustrative example, we consider whether quantum dot emitters embedded in "L3" and "H1" photonic crystal cavities are able to transfer a spin superposition state to a confined photonic superposition state for use in quantum information transfer. Using an established dyadic Green's function (DGF) analysis, we describe methods to calculate coupling to arbitrary quantum emitter positions and orientations using the modified local density of states (LDOS) calculated using numerical finite-difference time-domain (FDTD) simulations. We find that while superposition states are not supported in L3 cavities, the double degeneracy of the H1 cavities supports superposition states of the two orthogonal modes that may be described as states on a Poincar\'{e}-like sphere. Methods are developed to comprehensively analyze the confined superposition state generated from an arbitrary emitter position and emitter dipole orientation.Comment: 22 pages, 9 figure

Evaluation of Content and Accessibility of Orthopaedic Trauma Fellowship Websites

Background: Residents frequently use the internet to find material on fellowship programs. The Orthopaedic Trauma Association (OTA) website serves as a central hub for information on an orthopaedic trauma fellowship (OTF). This study aims to evaluate the accessibility, content, and perceived importance of OTF websites. Methods: We reviewed the 49 OTFs accredited by the OTA fellowship database as of January 2014. We searched for corresponding OTF websites by using the provided OTA hyperlinks and conducting a separate Google search of program location and institution. Links to websites of general orthopaedic programs were not counted. Content of OTF websites was analyzed by noting the presence or absence of specific items in fellow education (11 items) and recruitment (5 items). Results: Of 49 OTFs, a total of 39 (80%) websites specific to the fellowship were identified by searching the OTA database and Google browser. Seven (14%) programs listed on the OTA database provided links directly to fellowship programs. Most programs (28; 57%) did not provide links to specific OTFs or provided non-functional links on the OTA website. Of the 39 accessible OTF websites, a total of 24 (61%) had complete information regarding recruitment and 14 (36%) provided complete details on education. Conclusions: Most accredited OTFs do not adequately use the internet to provide easily accessible and complete information. Further details (especially regarding the role, education, and schedule) would help prospective candidates in thoroughly evaluating programs. The discrepancy in content and accessibility can hinder prospective fellows from appropriately investigating fellowship programs

Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients.

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite presenting with symptomatic overlap. Currently, there is a need of inexpensive DLB biomarkers which can be fulfilled by electroencephalography (EEG). In this regard, an established electrophysiological difference in DLB is a decrease of dominant frequency (DF)-the frequency with the highest signal power between 4 and 15 Hz. Here, we investigated network connectivity in EEG signals acquired from DLB patients, and whether these networks were able to differentiate DLB from healthy controls (HCs) and associated dementias. We analysed EEG recordings from old adults: HCs, AD, DLB and Parkinson's disease dementia (PDD) patients. Brain networks were assessed with the minimum spanning tree (MST) within six EEG bands: delta, theta, high-theta, alpha, beta and DF. Patients showed lower alpha band connectivity and lower DF than HCs. DLB and PDD showed a randomised MST compared with HCs and AD in high-theta and alpha but not in DF. The MST randomisation in DLB and PDD reflects decreased brain efficiency as well as impaired neural synchronisation. However, the lack of network topology differences at the DF between all dementia groups and HCs may indicate a compensatory response of the brain to the neuropathology.The research was funded by The Newcastle upon Tyne Hospitals NHS Charity, and supported by the Northumberland Tyne & Wear National Health Service (NHS) Foundation Trust and the National Institute of Health Research (NIHR) Biomedical Research Centre (BRC) at Newcastle University. S.G. was supported by the NIHR MedTech In vitro diagnostic Co-operatives scheme (ref MIC-2016-014). The study —participant recruitment and data collection— was funded by an intermediate clinical Wellcome Trust Fellowship (WT088441MA) to J-P.T

Total Sitting Time and Sitting Pattern in Postmenopausal Women Differ by Hispanic Ethnicity and are Associated With Cardiometabolic Risk Biomarkers.

Background Sedentary behavior is pervasive, especially in older adults, and is associated with cardiometabolic disease and mortality. Relationships between cardiometabolic biomarkers and sitting time are unexplored in older women, as are possible ethnic differences. Methods and Results Ethnic differences in sitting behavior and associations with cardiometabolic risk were explored in overweight/obese postmenopausal women (n=518; mean±SD age 63±6 years; mean body mass index 31.4±4.8 kg/m2). Accelerometer data were processed using validated machine-learned algorithms to measure total daily sitting time and mean sitting bout duration (an indicator of sitting behavior pattern). Multivariable linear regression was used to compare sitting among Hispanic women (n=102) and non-Hispanic women (n=416) and tested associations with cardiometabolic risk biomarkers. Hispanic women sat, on average, 50.3 minutes less/day than non-Hispanic women (P<0.001) and had shorter (3.6 minutes less, P=0.02) mean sitting bout duration. Among all women, longer total sitting time was deleteriously associated with fasting insulin and triglyceride concentrations, insulin resistance, body mass index and waist circumference; longer mean sitting bout duration was deleteriously associated with fasting glucose and insulin concentrations, insulin resistance, body mass index and waist circumference. Exploratory interaction analysis showed that the association between mean sitting bout duration and fasting glucose concentration was significantly stronger among Hispanic women than non-Hispanic women (P-interaction=0.03). Conclusions Ethnic differences in 2 objectively measured parameters of sitting behavior, as well as detrimental associations between parameters and cardiometabolic biomarkers were observed in overweight/obese older women. The detrimental association between mean sitting bout duration and fasting glucose may be greater in Hispanic women than in non-Hispanic women. Corroboration in larger studies is warranted

Bostonia: The Boston University Alumni Magazine. Volume 11

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs

Antibiotic Prophylaxis with Trimethoprim-Sulfamethoxazole versus No Treatment after Mid-to-Distal Hypospadias Repair: A Prospective, Randomized Study

Purpose. To evaluate the impact of prophylactic antibiotics after distal hypospadias repair on postoperative bacteriuria, symptomatic urinary tract infection, and postoperative complications in a prospective, randomized trial. Materials and Methods. Consecutive patients aged 6 months to 2 years were enrolled at our institution between June 2013 and May 2017. Consenting patients were randomized to antibiotic prophylaxis with trimethoprim-sulfamethoxazole versus no antibiotic. Patients had catheterized urine samples obtained at surgery and 6–10 days postoperatively. The primary outcome was bacteriuria and pyuria at postoperative urine collection. Secondary outcomes included symptomatic urinary tract infection and postoperative complications. Results. 70 patients consented to the study, of which 35 were randomized to receive antibiotics compared to 32 who did not. Demographics, severity of hypospadias, and type of repair were similar between the groups. Patients in the treatment group had significantly less pyuria (18%) and bacteriuria (11%) present at stent removal compared to the nontreatment group (55% and 63%; p=0.01 and p<0.001, resp.). No patient had a symptomatic urinary tract infection. There were 11 postoperative complications. Conclusions. Routine antibiotic prophylaxis appears to significantly decrease bacteriuria and pyuria in the immediate postoperative period; however, no difference was observed in symptomatic urinary tract infection or postoperative complications. Clinical Trial Registration Number NCT02593903