Beam Angle Optimization for Automated Coplanar IMRT Lung Plans

Purpose: To investigate the effect of incorporating a beam spreading parameter in a beam angle optimization algorithm and to evaluate its efficacy for creating coplanar IMRT lung plans in conjunction with machine learning generated dose objectives.

Methods: Fifteen anonymized patient cases were each re-planned with ten values over the range of the beam spreading parameter, k, and analyzed with a Wilcoxon signed-rank test to determine whether any particular value resulted in significant improvement over the initially treated plan created by a trained dosimetrist. Dose constraints were generated by a machine learning algorithm and kept constant for each case across all k values. Parameters investigated for potential improvement included mean lung dose, V20 lung, V40 heart, 80% conformity index, and 90% conformity index.

Results: With a confidence level of 5%, treatment plans created with this method resulted in significantly better conformity indices. Dose coverage to the PTV was improved by an average of 12% over the initial plans. At the same time, these treatment plans showed no significant difference in mean lung dose, V20 lung, or V40 heart when compared to the initial plans; however, it should be noted that these results could be influenced by the small sample size of patient cases.

Conclusions: The beam angle optimization algorithm, with the inclusion of the beam spreading parameter k, increases the dose conformity of the automatically generated treatment plans over that of the initial plans without adversely affecting the dose to organs at risk. This parameter can be varied according to physician preference in order to control the tradeoff between dose conformity and OAR sparing without compromising the integrity of the plan.

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.

Comparison of nitrogen isotopic values from different preparation methods

We are writing to comment on the work of Tamburini et al. (2003, doi:10.1029/2000PA000616). During the course of subsequent discussions between the authors and ourselves, it has become clear that the published sedimentary nitrogen isotopic values for Ocean Drilling Program (ODP) Site 724 are in error. Our reanalysis of sediment samples from the same intervals has revealed a significant offset from the original d15N data, requiring a revised assessment of their initial interpretation. The purposes of this comment are to (1) address the origin of these errors; (2) outline a protocol for future validation of nitrogen isotopic analyses; and (3) provide revised interpretations of the sedimentary d15N data in terms of the regional relative contributions of denitrification and nitrogen fixation and mean state of the southwest monsoon. (2) Nitrogen isotopic values measured on late Quaternary sediments at Arabian Sea ODP Site 724 by Tamburini et al. (2003, doi:10.1029/2000PA000616) are inexplicably different from a number of published records of d15N from very nearby on the Oman margin (Altabet et al., 1995, doi:10.1038/373506a0; 1999, doi:10.1029/1999PA900035; 2002, doi:10.1038/415159a; Higginson et al., 2004, doi:10.1016/j.gca.2004.03.015) and elsewhere in the Arabian Sea (Reichart et al., 1998, doi:10.1029/98PA02203). These data were generated using similar instrumentation (elemental analyzer coupled with an isotope ratio mass spectrometer) and analytical methodology to those already published. Concerned by this clear discrepancy, we analyzed aliquots of sediment from the same depth intervals for nitrogen abundance and bulk sedimentary nitrogen isotopes. We have been unable to duplicate the values published by Tamburini et al. (2003, doi:10.1029/2000PA000616 ), even after analysis of multiple replicates and due consideration of natural sediment heterogeneities and postrecovery sample storage.

(Figure 4) Stable carbon isotopic values and relative contents of biphytanes and sugars from sediment sample from the Peru margin and from the Pakistan margin

Glycolipids are prominent constituents in the membranes of cells from all domains of life. For example, diglycosyl-glycerol dibiphytanyl glycerol tetraethers (2Gly-GDGTs) are associated with methanotrophic ANME-1 archaea and heterotrophic benthic archaea, two archaeal groups of global biogeochemical importance. The hydrophobic biphytane moieties of 2Gly-GDGTs from these two uncultivated archaeal groups exhibit distinct carbon isotopic compositions. To explore whether the isotopic compositions of the sugar headgroups provide additional information on the metabolism of their producers, we developed a procedure to analyze the d13C values of glycosidic headgroups. Successful determination was achieved by (1) monitoring the contamination from free sugars during lipid extraction and preparation, (2) optimizing the hydrolytic conditions for glycolipids, and (3) derivatizing the resulting sugars into aldononitrile acetate derivatives, which are stable enough to withstand a subsequent column purification step. First results of d13C values of sugars cleaved from 2Gly-GDGTs in two marine sediment samples, one containing predominantly ANME-1 archaea and the other benthic archaea, were obtained and compared with the d13C values of the corresponding biphytanes. In both samples the dominant sugar headgroups were enriched in 13C relative to the corresponding major biphytane. This 13C enrichment was significantly larger in the putative major glycolipids from ANME-1 archaea (~15 per mil) than in those from benthic archaea (<7 per mil). This method opens a new analytical window for the examination of carbon isotopic relationships between sugars and lipids in uncultivated organisms.

Jigsaw Java: Intelligent, Automated Marking

The popularity of Computing degrees in the UK has been increasing significantly over the past number of years. In Northern Ireland, from 2007 to 2015, there has been a 40% increase in acceptances to Computer Science degrees with England seeing a 60% increase over the same period (UCAS, 2016). However, this is tainted as Computer Science degrees also continue to maintain the highest dropout rates.
In Queen’s University Belfast we currently have a Level 1 intake of over 400 students across a number of computing pathways. Our drive as staff is to empower and motivate the students to fully engage with the course content. All students take a Java programming module the aim of which is to provide an understanding of the basic principles of object-oriented design. In order to assess these skills, we have developed Jigsaw Java as an innovative assessment tool offering intelligent, semi-supervised automated marking of code.
Jigsaw Java allows students to answer programming questions using a drag-and-drop interface to place code fragments into position. Their answer is compared to the sample solution and if it matches, marks are allocated accordingly. However, if a match is not found then the corresponding code is executed using sample data to determine if its logic is acceptable. If it is, the solution is flagged to be checked by staff and if satisfactory is saved as an alternative solution. This means that appropriate marks can be allocated and should another student have submitted the same placement of code fragments this does not need to be executed or checked again. Rather the system now knows how to assess it.
Jigsaw Java is also able to consider partial marks dependent on code placement and will “learn” over time. Given the number of students, Jigsaw Java will improve the consistency and timeliness of marking.

Errors in preparation and medication management in nursing professionals

The preparation and administration of medications is one of the most common and relevant functions of nurses, demanding great responsibility. Incorrect administration of medication, currently constitutes a serious problem in health services, and is considered one of the main adverse effects suffered by hospitalized patients. Objectives: Identify the major errors in the preparation and administration of medication by nurses in hospitals and know what factors lead to the error occurred in the preparation and administration of medication. Methods: A systematic review of the literature. Deined as inclusion criteria: original scientiic papers, complete, published in the period 2011 to May 2016, the SciELO and LILACS databases, performed in a hospital environment, addressing errors in preparation and administration of medication by nurses and in Portuguese language. After application of the inclusion criteria obtained a sample of 7 articles. Results: The main errors identiied in the pr eparation and administration of medication were wrong dose 71.4%, wrong time 71.4%, 57.2% dilution inadequate, incorrect selection of the patient 42.8% and 42.8% via inadequate. The factors that were most commonly reported by the nursing staff, as the cause of the error was the lack of human appeal 57.2%, inappropriate locations for the preparation of medication 57.2%, the presence of noise and low brightness in preparation location 57, 2%, professionals untrained 42.8%, fatigue and stress 42.8% and inattention 42.8%. Conclusions: The literature shows a high error rate in the preparation and administration of medication for various reasons, making it important that preventive measures of this occurrence are implemented.

Preparation of an Immunosorbent and its use in the Solid Phase Extraction of Benzodiazepines

The use of capillary electrophoresis (CE) has been restricted to applications having high sample concentrations because of its low sensitivity caused by small injection volumes and, when ultraviolet (UV) detection is used, the short optical path length. Sensitivity in CE can be improved by using more sensitive detection systems, or by preconcentration techniques which are based on chromatographic and/or electrophoretic principles. One of the promising strategies to improve sensitivity is solid phase extraction (SPE). Solid Phase Extraction utilizes high sample volumes and a variety of complex matrixes to facilitate trace detection. To increase the specificity of the SPE a selective solid phase must be chosen. Immunosorbents, which are a combination of an antibody and a solid support, have proven to be an excellent option because of high selectivity of the antibody. This thesis is an exploratory study of the application of immunosorbent-SPE combined with CE for trace concentration of benzodiazepines. This research describes the immobilization and performance evaluation of an immunosorbent prepared by immobilizing a benzodiazepine-specific antibody on aminopropyl silica. The binding capacity of the immunosorbent, measured as µg of benzodiazepine/ gram of immunosorbent, was 39 ± 10. The long term stability of the prepared immunosorbent has been improved by capping the remaining aminopropyl groups by reaction with acetic anhydride. The capped immunosorbent retained its binding capacity after several uses.

Electrochemical Immunosensing of Cortisol in an Automated Microfluidic System Towards Point-of-Care Applications

This dissertation describes the development of a label-free, electrochemical immunosensing platform integrated into a low-cost microfluidic system for the sensitive, selective and accurate detection of cortisol, a steroid hormone co-related with many physiological disorders. Abnormal levels of cortisol is indicative of conditions such as Cushing’s syndrome, Addison’s disease, adrenal insufficiencies and more recently post-traumatic stress disorder (PTSD). Electrochemical detection of immuno-complex formation is utilized for the sensitive detection of Cortisol using Anti-Cortisol antibodies immobilized on sensing electrodes. Electrochemical detection techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) have been utilized for the characterization and sensing of the label-free detection of Cortisol. The utilization of nanomaterial’s as the immobilizing matrix for Anti-cortisol antibodies that leads to improved sensor response has been explored. A hybrid nano-composite of Polyanaline-Ag/AgO film has been fabricated onto Au substrate using electrophoretic deposition for the preparation of electrochemical immunosening of cortisol. Using a conventional 3-electrode electrochemical cell, a linear sensing range of 1pM to 1µM at a sensitivity of 66µA/M and detection limit of 0.64pg/mL has been demonstrated for detection of cortisol. Alternately, a self-assembled monolayer (SAM) of dithiobis(succinimidylpropionte) (DTSP) has been fabricated for the modification of sensing electrode to immobilize with Anti-Cortisol antibodies. To increase the sensitivity at lower detection limit and to develop a point-of-care sensing platform, the DTSP-SAM has been fabricated on micromachined interdigitated microelectrodes (µIDE). Detection of cortisol is demonstrated at a sensitivity of 20.7µA/M and detection limit of 10pg/mL for a linear sensing range of 10pM to 200nM using the µIDE’s. A simple, low-cost microfluidic system is designed using low-temperature co-fired ceramics (LTCC) technology for the integration of the electrochemical cortisol immunosensor and automation of the immunoassay. For the first time, the non-specific adsorption of analyte on LTCC has been characterized for microfluidic applications. The design, fabrication technique and fluidic characterization of the immunoassay are presented. The DTSP-SAM based electrochemical immunosensor on µIDE is integrated into the LTCC microfluidic system and cortisol detection is achieved in the microfluidic system in a fully automated assay. The fully automated microfluidic immunosensor hold great promise for accurate, sensitive detection of cortisol in point-of-care applications.

Mars delivery service - development of the electro-mechanical systems of the Sample Fetch Rover for the Mars Sample Return Campaign

This thesis describes the development of the Sample Fetch Rover (SFR), studied for Mars Sample Return (MSR), an international campaign carried out in cooperation between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The focus of this document is the design of the electro-mechanical systems of the rover. After placing this work into the general context of robotic planetary exploration and summarising the state of the art for what concerns Mars rovers, the architecture of the Mars Sample Return Campaign is presented. A complete overview of the current SFR architecture is provided, touching upon all the main subsystems of the spacecraft. For each area, it is discussed what are the design drivers, the chosen solutions and whether they use heritage technology (in particular from the ExoMars Rover) or new developments. This research focuses on two topics of particular interest, due to their relevance for the mission and the novelty of their design: locomotion and sample acquisition, which are discussed in depth. The early SFR locomotion concepts are summarised, covering the initial trade-offs and discarded designs for higher traverse performance. Once a consolidated architecture was reached, the locomotion subsystem was developed further, defining the details of the suspension, actuators, deployment mechanisms and wheels. This technology is presented here in detail, including some key analysis and test results that support the design and demonstrate how it responds to the mission requirements. Another major electro-mechanical system developed as part of this work is the one dedicated to sample tube acquisition. The concept of operations of this machinery was defined to be robust against the unknown conditions that characterise the mission. The design process led to a highly automated robotic system which is described here in its main components: vision system, robotic arm and tube storage.

Newborn Hearing Screening And Early Diagnostic In The Nicu.

The aim was to describe the outcome of neonatal hearing screening (NHS) and audiological diagnosis in neonates in the NICU. The sample was divided into Group I: neonates who underwent NHS in one step and Group II: neonates who underwent a test and retest NHS. NHS procedure was automated auditory brainstem response. NHS was performed in 82.1% of surviving neonates. For GI, referral rate was 18.6% and false-positive was 62.2% (normal hearing in the diagnostic stage). In GII, with retest, referral rate dropped to 4.1% and false-positive to 12.5%. Sensorineural hearing loss was found in 13.2% of infants and conductive in 26.4% of cases. There was one case of auditory neuropathy spectrum (1.9%). Dropout rate in whole process was 21.7% for GI and 24.03% for GII. We concluded that it was not possible to perform universal NHS in the studied sample or, in many cases, to apply it within the first month of life. Retest reduced failure and false-positive rate and did not increase evasion, indicating that it is a recommendable step in NHS programs in the NICU. The incidence of hearing loss was 2.9%, considering sensorineural hearing loss (0.91%), conductive (1.83%) and auditory neuropathy spectrum (0.19%).

Macrophage Cell Activation With Acute Apical Abscess Contents Determined By Interleukin-1 Beta And Tumor Necrosis Factor Alpha Production.

This clinical study has investigated the antigenic activity of bacterial contents from exudates of acute apical abscesses (AAAs) and their paired root canal contents regarding the stimulation capacity by levels of interleukin (IL)-1 beta and tumor necrosis factor alpha (TNF-α) throughout the root canal treatment against macrophage cells. Paired samples of infected root canals and exudates of AAAs were collected from 10 subjects. Endodontic contents were sampled before (root canal sample [RCS] 1) and after chemomechanical preparation (RCS2) and after 30 days of intracanal medication with calcium hydroxide + chlorhexidine gel (Ca[OH]2 + CHX gel) (RCS3). Polymerase chain reaction (16S rDNA) was used for detection of the target bacteria, whereas limulus amebocyte lysate was used to measure endotoxin levels. Raw 264.7 macrophages were stimulated with AAA exudates from endodontic contents sampled in different moments of root canal treatment. Enzyme-linked immunosorbent assays were used to measure the levels of TNF-α and IL-1 beta. Parvimonas micra, Porphyromonas endodontalis, Dialister pneumosintes, and Prevotella nigrescens were the most frequently detected species. Higher levels of endotoxins were found in samples from periapical exudates at RCS1 (P < .005). In fact, samples collected from periapical exudates showed a higher stimulation capacity at RCS1 (P < .05). A positive correlation was found between endotoxins from exudates with IL-1 beta (r = 0.97) and TNF-α (r = 0.88) production (P < .01). The significant reduction of endotoxins and bacterial species achieved by chemomechanical procedures (RCS2) resulted in a lower capacity of root canal contents to stimulate the cells compared with that at RCS1 (P < .05). The use of Ca(OH)2 + CHX gel as an intracanal medication (RCS3) improved the removal of endotoxins and bacteria from infected root canals (P < .05) whose contents induced a lower stimulation capacity against macrophages cells at RCS1, RCS2, and RCS3 (P < .05). AAA exudates showed higher levels of endotoxins and showed a greater capacity of macrophage stimulation than the paired root canal samples. Moreover, the use of intracanal medication improved the removal of bacteria and endotoxins from infected root canals, which may have resulted in the reduction of the inflammatory potential of the root canal content.

Preparation Of An Agar-silver Nanoparticles (a-agnp) Film For Increasing The Shelf-life Of Fruits.

Preparation of protective coating possessing antimicrobial properties is present day need as they increase the shelf life of fruits and vegetables. In the present study, preparation of agar-silver nanoparticle film for increasing the shelf life of fruits is reported. Silver nanoparticles (Ag-NPs) biosynthesised using an extract of Ocimum sanctum leaves, were mixed with agar-agar to prepare an agar-silver nanoparticles (A-AgNp) film. This film was surface-coated over the fruits, Citrus aurantifolium (Thornless lime) and Pyrus malus (Apple), and evaluated for the determination of antimicrobial activity of A-AgNp films using disc diffusion method, weight loss and shelf life of fruits. This study demonstrates that these A-AgNp films possess antimicrobial activity and also increase the shelf life of fruits.

Comparison Between Automated And Microscopic Analysis In Body Fluids Cytology.

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Preparation, Characterization And In Vitro Digestibility Of Gellan And Chitosan-gellan Microgels.

Gellan microgels with potential application in delivery systems were obtained by physically cross-linked gellan gum. The microgels were produced by atomization followed by ionotropic gelation using CaCl2 (gellan/Ca) or KCl (gellan/K) as hardening agent and part of them were coated with chitosan in order to improve their resistance to gastric digestion. Size distribution, morphology and zeta potential of microgels were evaluated before and after in vitro digestion process. The long term stability was also evaluated. Spherical microparticles were obtained at gellan concentration above 0.6% w/w, showing average size among 70-120 μm. Most of the coated and uncoated microgels showed stability in aqueous media, except the uncoated gellan/K microgel. The in vitro digestion evaluation showed that all particles maintained their size and shape after the gastric digestion step. However, the enteric digestion caused disintegration of microgels indicating their potential application for enteric delivery systems. The chitosan-coated microgels showed lower degree of fragmentation when compared to the uncoated microgels, indicating that the coating process enable a better control of microgels releasing properties during the enteric digestion.

Reference Values For High-density Lipoprotein Particle Size And Volume By Dynamic Light Scattering In A Brazilian Population Sample And Their Relationships With Metabolic Parameters.

Current data indicate that the size of high-density lipoprotein (HDL) may be considered an important marker for cardiovascular disease risk. We established reference values of mean HDL size and volume in an asymptomatic representative Brazilian population sample (n=590) and their associations with metabolic parameters by gender. Size and volume were determined in HDL isolated from plasma by polyethyleneglycol precipitation of apoB-containing lipoproteins and measured using the dynamic light scattering (DLS) technique. Although the gender and age distributions agreed with other studies, the mean HDL size reference value was slightly lower than in some other populations. Both HDL size and volume were influenced by gender and varied according to age. HDL size was associated with age and HDL-C (total population); non- white ethnicity and CETP inversely (females); HDL-C and PLTP mass (males). On the other hand, HDL volume was determined only by HDL-C (total population and in both genders) and by PLTP mass (males). The reference values for mean HDL size and volume using the DLS technique were established in an asymptomatic and representative Brazilian population sample, as well as their related metabolic factors. HDL-C was a major determinant of HDL size and volume, which were differently modulated in females and in males.