Exploration of risk factors for weight loss in head and neck cancer patients

Introduction: Head and neck cancer patients receiving radiotherapy can experience a number of toxicities, including weight loss and malnutrition, which can impact upon the quality of treatment. The purpose of this retrospective cohort study is to evaluate weight loss and identify predictive factors for this patient group. Method and materials: 40 patients treated with radiotherapy since 2012 at the study centre were selected for analysis. Data was collected from patient records. The association between potential risk factors and weight loss was investigated. Results: Mean weight loss was 5 kg (6%). 24 patients lost >5% starting body weight. Age, Tstage,N-stage, chemotherapy and starting body weight were individually associated with significant differences in weight loss. On multiple linear regression analysis age and nodal status were predictive. Conclusion: Younger patients and those with nodal disease were most at risk of weight loss. Other studies have identified the same risk factors along with several other variables. The relative significance of each along with a number of other potential factors is yet to be fully understood. Further research is required to help identify patients most at risk of weight loss; and assess interventions aimed at preventing weight loss and malnutrition.</p

Sport Specificity and Training Influence Bone and Body Composition In Women Collegiate Athletes

Sport Specificity and Training Influence Bone and Body Composition In Women Collegiate Athletes Jennifer M. Markos†, Aaron F. Carbuhn†, Tara E. Fernandez‡, Amy F. Bragg‡, John S. Green‡, FACSM, and Stephen F. Crouse‡, FACSM. Department of Health and Kinesiology and Department of Athletics, Texas A&M University, College Station, TX 77843, (Sponsor: S.F. Crouse) This is a novel descriptive study to characterize off-season, pre-season, and post-season bone and body composition measures in women collegiate athletes. PURPOSE: To quantify changes in women collegiate athletes’ bone mineral content, bone mineral density (BMD), arm BMD, leg BMD, pelvis BMD, spine BMD, and body composition (i.e., total body mass, lean mass, fat mass, and percent body fat) within each sport through the seasonal periods, and among the sports at each seasonal period. METHODS: 67 women collegiate athletes from softball (n = 17), basketball (n = 10), volleyball (n = 7), swimming (n = 16), and track jumpers and sprinters (n = 17) were scanned using duel energy x-ray absorptiometry (DXA) at three seasonal periods: 1) before pre-season training defined as off-season (OFF), 2) at end of preseason training (PRE), and 3) after the competitive season (POST). Summary of RESULTS: Repeated measures ANOVA within-sport seasonal changes in table; PRE/POST = highest value measured at PRE or POST. α \u3c 0.05 for all tests of significance. Seasonal Period %Body fat BMD (g/cm2) Pelvis BMD (g/cm2) Spine BMD (g/cm2) Softball OFF 27.1±5.0* 1.254±0.081* 1.385±0.127 1.216±0.149 PRE/POST 25.7±5.0 1.261±0.082 1.405±0.141 1.268±0.154 Basketball OFF 25.5±5.5* 1.333±0.064* 1.469±0.123* 1.356±0.178 PRE/POST 22.7±5.6 1.349±0.055 1.494±0.119 1.391±0.146 Volleyball OFF 27.7±4.1 1.284±0.065* 1.366±0.139 1.254±0.102* PRE/POST 27.1±5.1 1.310±0.071 1.371±0.149 1.360±0.121 Swimming OFF 22.0±4.3 1.112±0.067 1.110±0.104* 1.063±0.127* PRE/POST 21.9±4.1 1.121±0.067 1.124±0.105 1.105±0.126 Track Jumpers and Sprinters OFF 15.4±4.6* 1.292±0.075* 1.432±0.124* 1.280±0.135* PRE/POST 14.3±3.9 1.307±0.080 1.470±0.128 1.337±0.140 Values are means ± standard deviations. *Significant difference between off-season and pre or post-season ANOVA for differences by sports at the PRE/POST period showed results for both pelvis BMD and spine BMD as follows: softball = basketball = volleyball = track \u3e swimmers. CONCLUSION: These data serve as sport-specific benchmarks for comparisons at in-season and off-season training periods among women collegiate athletes in various sports. They also serve to document changes in body composition and bone density with training, and may serve to guide coaches in the development of sport specific nutritional and strength and conditioning programs to optimize athletic performance. Research supported in part by the Sydney & J.L. Huffines Institute for Sports Medicine and Human Performanc

Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections

Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers. As scientific literature grows, this becomes increasingly challenging. Meanwhile, authors summarize prior research in papers' related work sections, though this is scoped to support a single paper. A formative study found that while reading multiple related work paragraphs helps overview a topic, it is hard to navigate overlapping and diverging references and research foci. In this work, we design a system, Relatedly, that scaffolds exploring and reading multiple related work paragraphs on a topic, with features including dynamic re-ranking and highlighting to spotlight unexplored dissimilar information, auto-generated descriptive paragraph headings, and low-lighting of redundant information. From a within-subjects user study (n=15), we found that scholars generate more coherent, insightful, and comprehensive topic outlines using Relatedly compared to a baseline paper list

CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context

When reading a scholarly article, inline citations help researchers contextualize the current article and discover relevant prior work. However, it can be challenging to prioritize and make sense of the hundreds of citations encountered during literature reviews. This paper introduces CiteSee, a paper reading tool that leverages a user's publishing, reading, and saving activities to provide personalized visual augmentations and context around citations. First, CiteSee connects the current paper to familiar contexts by surfacing known citations a user had cited or opened. Second, CiteSee helps users prioritize their exploration by highlighting relevant but unknown citations based on saving and reading history. We conducted a lab study that suggests CiteSee is significantly more effective for paper discovery than three baselines. A field deployment study shows CiteSee helps participants keep track of their explorations and leads to better situational awareness and increased paper discovery via inline citation when conducting real-world literature reviews

Validation of the Survey Simulator tool for the NEO Surveyor mission using NEOWISE data

The Near Earth Object Surveyor mission has a requirement to find two-thirds of the potentially hazardous asteroids larger than 140 meters in size. In order to determine the mission's expected progress toward this goal during design and testing, as well as the actual progress during the survey, a simulation tool has been developed to act as a consistent and quantifiable yardstick. We test that the survey simulation software is correctly predicting on-sky positions and thermal infrared fluxes by using it to reproduce the published measurements of asteroids from the NEOWISE mission. We then extended this work to find previously unreported detections of known near Earth asteroids in the NEOWISE data archive, a search that resulted in 21,661 recovery detections, including 1,166 objects that had no previously reported NEOWISE observations. These efforts demonstrate the reliability of the NEOS Survey Simulator tool, and the perennial value of searchable image and source catalog archives for extending our knowledge of the small bodies of the Solar System.Comment: 19 pages, 6 figures, accepted for publication in PS

UBVRI Light Curves of 44 Type Ia Supernovae

We present UBVRI photometry of 44 type-Ia supernovae (SN Ia) observed from 1997 to 2001 as part of a continuing monitoring campaign at the Fred Lawrence Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics. The data set comprises 2190 observations and is the largest homogeneously observed and reduced sample of SN Ia to date, nearly doubling the number of well-observed, nearby SN Ia with published multicolor CCD light curves. The large sample of U-band photometry is a unique addition, with important connections to SN Ia observed at high redshift. The decline rate of SN Ia U-band light curves correlates well with the decline rate in other bands, as does the U-B color at maximum light. However, the U-band peak magnitudes show an increased dispersion relative to other bands even after accounting for extinction and decline rate, amounting to an additional ~40% intrinsic scatter compared to B-band.Comment: 84 authors, 71 pages, 51 tables, 10 figures. Accepted for publication in the Astronomical Journal. Version with high-res figures and electronic data at http://astron.berkeley.edu/~saurabh/cfa2snIa

The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces

Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need for new technology to support the reading process grows. In contrast to the process of finding papers, which has been transformed by Internet technology, the experience of reading research papers has changed little in decades. The PDF format for sharing research papers is widely used due to its portability, but it has significant downsides including: static content, poor accessibility for low-vision readers, and difficulty reading on mobile devices. This paper explores the question "Can recent advances in AI and HCI power intelligent, interactive, and accessible reading interfaces -- even for legacy PDFs?" We describe the Semantic Reader Project, a collaborative effort across multiple institutions to explore automatic creation of dynamic reading interfaces for research papers. Through this project, we've developed ten research prototype interfaces and conducted usability studies with more than 300 participants and real-world users showing improved reading experiences for scholars. We've also released a production reading interface for research papers that will incorporate the best features as they mature. We structure this paper around challenges scholars and the public face when reading research papers -- Discovery, Efficiency, Comprehension, Synthesis, and Accessibility -- and present an overview of our progress and remaining open challenges