Food venue choice, consumer food environment, but not food venue availability within daily travel patterns are associated with dietary intake among adults, Lexington Kentucky 2011

Objective The retail food environment may be one important determinant of dietary intake. However, limited research focuses on individuals’ food shopping behavior and activity within the retail food environment. This study’s aims were to determine the association between six various dietary indicators and 1) food venue availability; 2) food venue choice and frequency; and 3) availability of healthy food within food venue. Methods In Fall, 2011, a cross-sectional survey was conducted among adults (n=121) age 18 years and over in Lexington, Kentucky. Participants wore a global position system (GPS) data logger for 3-days (2 weekdays and 1 weekend day) to track their daily activity space, which was used to assess food activity space. They completed a survey to assess demographics, food shopping behaviors, and dietary outcomes. Food store audits were conducted using the Nutrition Environment Measurement Survey-Store Rudd (NEMS-S) in stores where respondents reported purchasing food (n=22). Multivariate logistic regression was used to examine associations between six dietary variables with food venue availability within activity space; food venue choice; frequency of shopping; and availability of food within food venue. Results 1) Food venue availability within activity space – no significant associations. 2) Food Venue Choice – Shopping at farmers’ markets or specialty grocery stores reported higher odds of consuming fruits and vegetables (OR 1.60 95% CI [1.21, 2.79]). Frequency of shopping - Shopping at a farmers’ markets and specialty stores at least once a week reported higher odds of consumption of fruits and vegetables (OR 1.55 95% CI [1.08, 2.23]). Yet, shopping frequently at a super market had higher odds of consuming sugar-sweetened beverages (OR 1.39 95% CI [1.03, 1.86]). 3) Availability of food within store – those who shop in supermarkets with high availability of healthy food has lower odds of consuming sugar-sweetened beverages (OR 0.65 95% CI [0.14, 0.83]). Conclusion Interventions aimed at improving fruit and vegetable intake need to consider where individuals’ purchase food and the availability within stores as a behavioral and environmental strategy

Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study

OBJECTIVES: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading times. MATERIALS AND METHODS: A retrospective analysis of 438 prospectively collected WB-MRI scans from multicenter Streamline studies (February 2013-September 2016) was undertaken. Disease sites were manually labeled using Streamline reference standard. Whole-body MRI scans were randomly allocated to training and testing sets. A model for malignant lesion detection was developed based on convolutional neural networks and a 2-stage training strategy. The final algorithm generated lesion probability heat maps. Using a concurrent reader paradigm, 25 radiologists (18 experienced, 7 inexperienced in WB-/MRI) were randomly allocated WB-MRI scans with or without ML support to detect malignant lesions over 2 or 3 reading rounds. Reads were undertaken in the setting of a diagnostic radiology reading room between November 2019 and March 2020. Reading times were recorded by a scribe. Prespecified analysis included sensitivity, specificity, interobserver agreement, and reading time of radiology readers to detect metastases with or without ML support. Reader performance for detection of the primary tumor was also evaluated. RESULTS: Four hundred thirty-three evaluable WB-MRI scans were allocated to algorithm training (245) or radiology testing (50 patients with metastases, from primary 117 colon [n = 117] or lung [n = 71] cancer). Among a total 562 reads by experienced radiologists over 2 reading rounds, per-patient specificity was 86.2% (ML) and 87.7% (non-ML) (-1.5% difference; 95% confidence interval [CI], -6.4%, 3.5%; P = 0.39). Sensitivity was 66.0% (ML) and 70.0% (non-ML) (-4.0% difference; 95% CI, -13.5%, 5.5%; P = 0.344). Among 161 reads by inexperienced readers, per-patient specificity in both groups was 76.3% (0% difference; 95% CI, -15.0%, 15.0%; P = 0.613), with sensitivity of 73.3% (ML) and 60.0% (non-ML) (13.3% difference; 95% CI, -7.9%, 34.5%; P = 0.313). Per-site specificity was high (>90%) for all metastatic sites and experience levels. There was high sensitivity for the detection of primary tumors (lung cancer detection rate of 98.6% with and without ML [0.0% difference; 95% CI, -2.0%, 2.0%; P = 1.00], colon cancer detection rate of 89.0% with and 90.6% without ML [-1.7% difference; 95% CI, -5.6%, 2.2%; P = 0.65]). When combining all reads from rounds 1 and 2, reading times fell by 6.2% (95% CI, -22.8%, 10.0%) when using ML. Round 2 read-times fell by 32% (95% CI, 20.8%, 42.8%) compared with round 1. Within round 2, there was a significant decrease in read-time when using ML support, estimated as 286 seconds (or 11%) quicker (P = 0.0281), using regression analysis to account for reader experience, read round, and tumor type. Interobserver variance suggests moderate agreement, Cohen κ = 0.64; 95% CI, 0.47, 0.81 (with ML), and Cohen κ = 0.66; 95% CI, 0.47, 0.81 (without ML). CONCLUSIONS: There was no evidence of a significant difference in per-patient sensitivity and specificity for detecting metastases or the primary tumor using concurrent ML compared with standard WB-MRI. Radiology read-times with or without ML support fell for round 2 reads compared with round 1, suggesting that readers familiarized themselves with the study reading method. During the second reading round, there was a significant reduction in reading time when using ML support

Tropospheric water vapour above Switzerland over the last 12 years

Integrated Water vapour (IWV) has been measured since 1994 by the TROWARA microwave radiometer in Bern, Switzerland. Homogenization techniques were used to identify and correct step changes in IWV related to instrument problems. IWV from radiosonde, GPS and sun photometer (SPM) was used in the homogenisation process as well as partial IWV columns between valley and mountain weather stations. The average IWV of the homogenised TROWARA time series was 14.4 mm over the 1996–2007 period, with maximum and minimum monthly average values of 22.4 mm and 8 mm occurring in August and January, respectively. A weak diurnal cycle in TROWARA IWV was detected with an amplitude of 0.32 mm, a maximum at 21:00 UT and a minimum at 11:00 UT. For 1996–2007, TROWARA trends were compared with those calculated from the Payerne radiosonde and the closest ECMWF grid point to Bern. Using least squares analysis, the IWV time series of radiosondes at Payerne, ECMWF, and TROWARA showed consistent positive trends from 1996 to 2007. The radiosondes measured an IWV trend of 0.45±0.29%/y, the TROWARA radiometer observed a trend of 0.39±0.44%/y, and ECMWF operational analysis gave a trend of 0.25±0.34%/y. Since IWV has a strong and variable annual cycle, a seasonal trend analysis (Mann-Kendall analysis) was also performed. The seasonal trends are stronger by a factor 10 or so compared to the full year trends above. The positive IWV trends of the summer months are partly compensated by the negative trends of the winter months. The strong seasonal trends of IWV on regional scale underline the necessity of long-term monitoring of IWV for detection,understanding, and forecast of climate change effects in the Alpine region

Microwave remote sensing of water vapor in the atmosphere

Abstract. Water vapor in the atmosphere plays a crucial role in climate and in atmospheric processes. Due to its long chemical lifetime it can be used as a tracer for investigations of dynamical processes in the middle atmosphere. Microwave radiometry is one of the few remote sensing methods which is capable of inferring Information on the water vapor content of the troposphere to the mesosphere, however with a different altitude resolution. Different microwave radiometers that can be operated from the ground and from an airborne platform have been built at the Institute of Applied Physics, University of Berne. The paper presents the method of microwave remote sensing and gives an overview of recently achieved results with regard to water vapor distribution as a function of altitude and Iatitude. First results of an imaging radiometer for the two dimensional distribution of liquid water is presented. </jats:p