Measuring the response of human head and neck squamous cell carcinoma to irradiation in a microfluidic model allowing customized therapy

Radiotherapy is the standard treatment for head and neck squamous cell carcinoma (HNSCC), however, radioresistance remains a major clinical problem despite significant improvements in treatment protocols. Therapeutic outcome could potentially be improved if a patient's tumour response to irradiation could be predicted ex vivo before clinical application. The present study employed a bespoke microfluidic device to maintain HNSCC tissue whilst subjecting it to external beam irradiation and measured the responses using a panel of cell death and proliferation markers. HNSCC biopsies from five newly-presenting patients [2 lymph node (LN); 3 primary tumour (PT)] were divided into parallel microfluidic devices and replicates of each tumour were subjected to single-dose irradiation (0, 5, 10, 15 and 20 Gy). Lactate dehydrogenase (LDH) release was measured and tissue sections were stained for cytokeratin (CK), cleaved-CK18 (cCK18), phosphorylated-H2AX (λH2AX) and Ki.67 by immunohistochemistry. In addition, fragmented DNA was detected using terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL). Compared with non.irradiated controls, higher irradiation doses resulted in elevated CK18-labelling index in two lymph nodes [15 Gy; 34.8% on LN1 and 31.7% on LN2 (p=0.006)] and a single laryngeal primary tumour (20 Gy; 31.5%; p=0.014). Significantly higher levels of DNA fragmentation were also detected in both lymph node samples and one primary tumour but at varying doses of irradiation, i.e., LN1 (20 Gy; 27.6%; p=0.047), LN2 (15 Gy; 15.3%; p=0.038) and PT3 (10 Gy; 35.2%; p=0.01). The λH2AX expression was raised but not significantly in the majority of samples. The percentage of Ki.67 positive nuclei reduced dose-dependently following irradiation. In contrast no significant difference in LDH release was observed between irradiated groups and controls. There is clear interand intra-patient variability in response to irradiation when measuring a variety of parameters, which offers the potential for the approach to provide clinically valuable information

Major incident triage: Derivation and comparative analysis of the Modified Physiological Triage Tool (MPTT).

BACKGROUND: Triage is a key principle in the effective management at a major incident. There are at least three different triage systems in use worldwide and previous attempts to validate them, have revealed limited sensitivity. Within a civilian adult population, there has been no work to develop an improved system. METHODS: A retrospective database review of the UK Joint Theatre Trauma Registry was performed for all adult patients (>18years) presenting to a deployed Military Treatment Facility between 2006 and 2013. Patients were defined as Priority One if they had received one or more life-saving interventions from a previously defined list. Using first recorded hospital physiological data (HR/RR/GCS), binary logistic regression models were used to derive optimum physiological ranges to predict need for life-saving intervention. This allowed for the derivation of the Modified Physiological Triage Tool-MPTT (GCS≥14, HR≥100, 12<RR≥22). A comparison of the MPTT and existing triage tools was then performed using sensitivities and specificities with 95% confidence intervals. Differences in performance were assessed for statistical significance using a McNemar test with Bonferroni correction. RESULTS: Of 6095 patients, 3654 (60.0%) had complete data and were included in the study, with 1738 (47.6%) identified as priority one. Existing triage tools had a maximum sensitivity of 50.9% (Modified Military Sieve) and specificity of 98.4% (Careflight). The MPTT (sensitivity 69.9%, 95% CI 0.677-0.720, specificity 65.3%, 95% CI 0.632-0.675) showed an absolute increase in sensitivity over existing tools ranging from 19.0% (Modified Military Sieve) to 45.1% (Triage Sieve). There was a statistically significant difference between the performance (p<0.001) between the MPTT and the Modified Military Sieve. DISCUSSION & CONCLUSION: The performance characteristics of the MPTT exceed existing major incident triage systems, whilst maintaining an appropriate rate of over-triage and minimising under-triage within the context of predicting the need for a life-saving intervention in a military setting. Further work is required to both prospectively validate this system and to identify its performance within a civilian environment, prior to recommending its use in the major incident setting

A ‘smarter’ way of diagnosing the at risk foot: Development of a novel tool based on vibratory measurements in subjects with diabetes

Aim: To identify optimal vibration perception thresholds (VPT) to help design a ‘smart’ risk assessment tool in subjects with diabetes. Methods: We used our clinical database (Diabeta3) to identify baseline VPT in subjects in whom there is at least a 10 Volt (V) rise in VPT (hallux pulp) using a Neurothesiometer over time. The gradient chosen is based on previous work. The data helped us model the vibratory frequencies of a plate device (Vibrascan), which produces a more objective risk assessment than VPT. We used a longitudinal multilevel model to analyse the data. Results: In 929 subjects with diabetes showing a 10 V deterioration and who had a total of 8874 measurements, VPT increased from 13.8±8.4 V at first visit to 22.8±13.2 V (p<0.001) at final visit. In subjects (N=3920, 29995 measurements) who showed a smaller deterioration (<10 V), VPT increased from 13.7±10.7V to 14.6±11.3 V (p<0.01). Duration of diabetes, microalbuminuria and LDL cholesterol are positive significant correlates with increasing VPT. Conclusion: Based on these data we used the Neurothesiometer equivalent of 10V increments to help us develop Vibrascan as a modern and easy to use foot screening tool. The positive cardiovascular correlates strengthen the role of developing a vibratory screening tool utilising these data. The details of the device itself and its novelty in screening of subjects will be discussed in detail

Predicting diabetic neuropathy risk level using artificial neural network and clinical parameters of subjects with diabetes.

Background: A risk assessment tool has been developed for automated estimation of level of neuropathy based on the clinical characteristics of patients. The smart tool is based on risk factors for diabetic neuropathy which utilises vibration perception threshold (VPT) and a set of clinical variables as potential predictors. Methods: Significant risk factors included: age, height, weight, urine albumin to creatinine ratio (ACR), HbA1c, total cholesterol and duration of diabetes. The continuous scale VPT was recorded using a Neurothesiometer and classified into three categories based on the clinical thresholds in volts (V): low risk (0 to 20.99 V), medium risk (21 to 30.99 V) and high risk (≥ 31 V). Results: The initial study had shown that by just using patient data (n=5088) an accuracy of 54% was achievable. Having established the effectiveness of the “classical” method a special Neural Network based Proportional Odds Model (NNPOM) was developed which provided the highest level of prediction accuracy (>70%) using the simulated patient data (n=4158). Conclusion: In the absence of any assessment devices or trained personnel it is possible to establish with reasonable accuracy a diagnosis of diabetic neuropathy by means of the clinical parameters of the patient alone

Plate versus bulk trolley food service in a hospital: comparison of patients’ satisfaction

Objective The aim of this research was to compare plate with bulk trolley food service in hospitals in terms of patient satisfaction. Key factors distinguishing satisfaction with each system would also be identified. Methods A consumer opinion card (n = 180), concentrating on the quality indicators of core foods, was used to measure patient satisfaction and compare two systems of delivery, plate and trolley. Binary logistic regression analysis was used to build a model that would predict food service style on the basis of the food attributes measured. Further investigation used multinomial logistic regression to predict opinion for the assessment of each food attribute within food service style. Results Results showed that the bulk trolley method of food distribution enables all foods to have a more acceptable texture, and for some foods (potato, P = 0.007; poached fish, P = 0.001; and minced beef, P ≤ 0.0005) temperature, and for other foods (broccoli, P ≤ 0.0005; carrots, P ≤ 0.0005; and poached fish, P = 0.001) flavor, than the plate system of delivery, where flavor is associated with bad opinion or dissatisfaction. A model was built indicating patient satisfaction with the two service systems. Conclusion This research confirms that patient satisfaction is enhanced by choice at the point of consumption (trolley system); however, portion size was not the controlling dimension. Temperature and texture were the most important attributes that measure patient satisfaction with food, thus defining the focus for hospital food service managers. To date, a model predicting patient satisfaction with the quality of food as served has not been proposed, and as such this work adds to the body of knowledge in this field. This report brings new information about the service style of dishes for improving the quality of food and thus enhancing patient satisfaction

Dynamic Programming for Resource Allocation in Multi-Allelic Trait Introgression

Trait introgression is a complex process that plant breeders use to introduce desirable alleles from one variety or species to another. Two of the major types of decisions that must be made during this sophisticated and uncertain workflow are: parental selection and resource allocation. We formulated the trait introgression problem as an engineering process and proposed a Markov Decision Processes (MDP) model to optimize the resource allocation procedure. The efficiency of the MDP model was compared with static resource allocation strategies and their trade-offs among budget, deadline, and probability of success are demonstrated. Simulation results suggest that dynamic resource allocation strategies from the MDP model significantly improve the efficiency of the trait introgression by allocating the right amount of resources according to the genetic outcome of previous generations

Confirmation of Sentinel Lymph Node Identity by Analysis of Fine-Needle Biopsy Samples Using Inductively Coupled Plasma–Mass Spectrometry

Background: The sentinel lymph node (SLN) biopsy technique is a reliable means of determining the tumor-harboring status of regional lymph nodes in melanoma patients. When technetium 99 m-labeled antimony trisulfide colloid (99 mTc-Sb2S3) particles are used to perform preoperative lymphoscintigraphy for SLN identification, they are retained in the SLN but are absent or present in only tiny amounts in non-SLNs. The present study investigated the potential for a novel means of assessing the accuracy of surgical identification of SLNs. This involved the use of inductively coupled plasma-mass spectrometry (ICP-MS) to analyze antimony concentrations in fine-needle biopsy (FNB) samples from surgically procured lymph nodes. Methods: A total of 47 FNB samples from surgically excised lymph nodes (32 SLNs and 15 non-SLNs) were collected. The SLNs were localized by preoperative lymphoscintigraphy that used 99 mTc-Sb2S3, blue dye, and gamma probe techniques. The concentrations of antimony were measured in the FNB samples by ICP-MS. Results: The mean and median antimony concentrations (in parts per billion) were .898 and .451 in the SLNs, and .015 and .068 in the non-SLNs, the differences being highly statistically significant (P < .00005). Conclusions: Our results show that ICP-MS analysis of antimony concentrations in FNB specimens from lymph nodes can accurately confirm the identity of SLNs. Used in conjunction with techniques such as proton magnetic resonance spectroscopy for the nonsurgical evaluation of SLNs, ICP-MS analysis of antimony concentrations in FNB samples could potentially serve as a minimally invasive alternative to surgery and histopathologic evaluation to objectively classify a given node as sentinel or nonsentinel and determine its tumor-harboring status. © 2007 The Author(s)

Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis

Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. We generated over 100 000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10 000–20 000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible

Systematic design for trait introgression projects

We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing TI projects that require dynamic decision making. The CTP framework also revealed that previously identified ‘best’ strategies can be improved to be at least twice as effective without increasing time or expenses