Search

Objectives Stress and emotions alter eating behavior in several ways: While experiencing negative or positive emotions typically leads to increased food intake, stress may result in either over- or undereating. Several participant characteristics, like gender, BMI and restrained, emotional, or external eating styles seem to influence these relationships. Thus far, most research relied on experimental laboratory studies, thereby reducing the complexity of real-life eating episodes. The aim of the present study was to delineate the effects of stress, negative and positive emotions on two key facets of eating behavior, namely taste- and hunger-based eating, in daily life using ecological momentary assessment (EMA). Furthermore, the already mentioned individual differences as well as time pressure during eating, an important but unstudied construct in EMA studies, were examined. Methods Fifty-nine participants completed 10 days of signal-contingent sampling and data were analyzed using multilevel modeling. Results Results revealed that higher stress led to decreased taste-eating which is in line with physiological stress-models. Time pressure during eating resulted in less taste- and more hunger-eating. In line with previous research, stronger positive emotions went along with increased taste-eating. Emotional eating style moderated the relationship between negative emotions and taste-eating as well as hunger-eating. BMI moderated the relationship between negative as well as positive emotions and hunger-eating. Conclusions These findings emphasize the importance of individual differences for understanding eating behavior in daily life. Experienced time pressure may be an important aspect for future EMA eating studies.

Background: Imprecise carbohydrate counting as a measure to guide the treatment of diabetes may be a source of errors resulting in problems in glycemic control. Exact measurements can be tedious, leading most patients to estimate their carbohydrate intake. In the presented pilot study a smartphone application (BEAR), that guides the estimation of the amounts of carbohydrates, was used by a group of diabetic patients. Methods: Eight adult patients with diabetes mellitus type 1 were recruited for the study. At the beginning of the study patients were introduced to BEAR in sessions lasting 45 minutes per patient. Patients redraw the real food in 3D on the smartphone screen. Based on a selected food type and the 3D form created using BEAR an estimation of carbohydrate content is calculated. Patients were supplied with the application on their personal smartphone or a loaner device and were instructed to use the application in real-world context during the study period. For evaluation purpose a test measuring carbohydrate estimation quality was designed and performed at the beginning and the end of the study. Results: In 44% of the estimations performed at the end of the study the error reduced by at least 6 grams of carbohydrate. This improvement occurred albeit several problems with the usage of BEAR were reported. Conclusions: Despite user interaction problems in this group of patients the provided intervention resulted in a reduction in the absolute error of carbohydrate estimation. Intervention with smartphone applications to assist carbohydrate counting apparently results in more accurate estimations.

Patients with Frozen Shoulder suffer from a decreased mobility and pain. Exercise-based physiotherapy is a common treatment and patients mostly perform the exercises at home. Correct exercise performance and compliance are the main issues in home-based therapy of Frozen Shoulder patients. To support patients diagnosed with Frozen Shoulder, a multimodal 3D smartphone app was designed, developed and evaluated. Additional to ten potential users, one physician, five physiotherapists, three computer scientists, two 3D artists and one HCI specialist were involved in the co-creation process. The app was evaluated by five patients during a three-week pilot study, which showed the feasibility of our approach. Exercise correctness, usage of multimodal instructions and user satisfaction were analyzed. Exercise correctness was nearly perfect and the interactive 3D animation was used for exercise instructions. Satisfaction using the app was rated very high according to SUS score. The results confirm that the co-creation process led to an effective, highly satisfactory and actually used system.

The accurate assessment of nutrition information is a challenging task, but crucial for people with certain diseases, such as diabetes. An important part of the assessment of nutrition information is portion estimation, i.e. volume estimation. Given the volume and the food type, the nutrition information can be computed on the basis of the food type specific nutrition density. Recently mobile devices with depth sensors have been made available for the public (Google's project tango platform). In this work, an app for mobile devices with a depth sensor is presented which assists users in portion estimation. Furthermore, we present the design of a user study for the app and preliminary results.

Background: Patients with frozen shoulder show limited shoulder mobility often accompanied by pain. Common treatment methods include physiotherapy, pain medication, administration of corticosteroids, and surgical capsulotomy. Frozen shoulder often lasts from months to years and mostly affects persons in the age group of 40 to 70 years. It severely reduces the quality of life and the ability to work. Objective: The objective of this study was to evaluate the feasibility of a mobile health (mHealth) intervention that supports patients affected by “stage two” frozen shoulder. Patients were supported with app-based exercise instructions and tools to monitor their training compliance and progress. These training compliance and progress data supplement the patients’ oral reports to the physiotherapists and physicians and can assist them in therapy adjustment. Methods: In order to assess the feasibility of the mHealth intervention, a pilot study of a newly developed app for frozen shoulder patients was conducted with 5 patients for 3 weeks. The main function of the app was the instruction for exercising at home. Standardized questionnaires on usability such as System Usability Scale (SUS) and USE (Usefulness, Satisfaction, and Ease of use), and Technology Acceptance Model-2 (TAM-2) were completed by the study participants at the end of the study. Additionally, a nonstandardized questionnaire was completed by all patients. The correctness of the exercises as conducted by the patients was assessed by a physiotherapist at the end of the study. The mobility of the shoulder and pain in shoulder movement was assessed by a physiotherapist at the start and the end of the study. Results: The pilot study was successfully conducted, and the app was evaluated by the patients after 3 weeks. The results of the standardized questionnaires showed high acceptance (TAM-2) and high usability (SUS) of the developed app. The overall usability of the system as assessed by the SUS questionnaire was very good (an average score of 88 out of 100). The average score of the TAM-2 questionnaire on the intention to further use the app was 4.2 out of 5, which indicated that most patients would use the app if further available. The results of the USE questionnaires highlighted that the patients learned how to use the app easily (an average score of 4.2 out of 5) and were satisfied with the app (an average score of 4.7 out of 5). The frequency of app usage and training was very high based on patient reports and verified by analysis of the usage data. The patients conducted the exercises almost flawlessly. Conclusions: Our results indicate the feasibility of the mHealth intervention, as the app was easy to use and frequently used by the patients. The app supported the patients’ physiotherapy by providing clear exercising instructions. [JMIR Rehabil Assist Technol 2017;4(2):e6]

Summary Recurring groups of atoms in molecules are surrounded by specific canonical distributions of electrons. Deviations from these distributions reveal unrealistic molecular geometries. Here, we show how canonical electron densities can be combined with classical electron densities derived from X-ray diffraction experiments to drive the real space refinement of crystal structures. The refinement process generally yields superior molecular models with reduced excess electron densities and improved stereochemistry without compromising the agreement between molecular models and experimental data., Highlights ► Recurring groups of atoms in proteins are surrounded by canonical electron densities ► Deviations from canonical densities reveal unrealistic molecular geometries ► Canonical density refinement removes electron excess and improves stereochemistry

The construction of a consistent protein chemical shift database is an important step toward making more extensive use of this data in structural studies. Unfortunately, progress in this direction has been hampered by the quality of the available data, particularly with respect to chemical shift referencing, which is often either inaccurate or inconsistently annotated. Preprocessing of the data is therefore required to detect and correct referencing errors. In an earlier study we developed CheckShift, a program for performing this task automatically. Now we spent substantial effort in improving the running time of the CheckShift algorithm, which resulted in an running time decrease of 90%, thereby achieving equivalent quality to the former version of CheckShift. The reason for the running time decrease is twofold. Firstly we improved the search for the optimal re-referencing offset considerably. Secondly, as CheckShift is based on a secondary structure prediction from the amino acid sequence (formally PsiPred was used), we evaluated a wide range of available secondary structure prediction programs focusing on the special needs of the CheckShift algorithm. The results of this evaluation prove empirically that we can use faster secondary structure prediction programs than PsiPred without sacrificing CheckShift's accuracy. Very recently Wang and Markley (2009) gave a small list of extreme outliers of the former version of the CheckShift web-server. Those were due to the empirical reduction of the search space implemented in the old version. The new version of CheckShift now gives very similar results to RefDB and LACS for all outliers mentioned in Table 1 of Wang and Markley (2009).

We present SimShiftDB, a new program to extract conformational data from protein chemical shifts using structural alignments. The alignments are obtained in searches of a large database containing 13,000 structures and corresponding back-calculated chemical shifts. SimShiftDB makes use of chemical shift data to provide accurate results even in the case of low sequence similarity, and with even coverage of the conformational search space. We compare SimShiftDB to HHSearch, a state-of-the-art sequence-based search tool, and to TALOS, the current standard tool for the task. We show that for a significant fraction of the predicted similarities, SimShiftDB outperforms the other two methods. Particularly, the high coverage afforded by the larger database often allows predictions to be made for residues not involved in canonical secondary structure, where TALOS predictions are both less frequent and more error prone. Thus SimShiftDB can be seen as a complement to currently available methods.

A large number of microorganisms, both starter microorganisms and non-starter lactic acid bacteria originating from the base milk, or from various contamination sources during cheese manufacture, is associated with cheese ripening and the formation of flavour, texture and aroma. Under controlled conditions, Emmental and Bergkäse, a Gruyère-type cheese variety, were produced from pasteurised milk with standard starters and defined strains of facultatively heterofermentative lactobacilli (FHL), and partly with addition of a defined mixture of enterococci. Lactobacillus casei subsp. casei and L. rhamnosus (two strains each) were selected with respect to their potential for the utilisation of citric acid and ribose as sole energy source. The FHL developed up to 10(8) cfu/g within the first weeks of ripening, and viable counts in mature cheeses were 10(7) cfu/g, independent of the cheese variety. Bergkäse made with addition of L. rhamnosus strains showed a more pronounced proteolysis, resulting in reduced firmness and elasticity values of the cheese body, and FHL strains able to utilise citric acid improved the appearance of the cheeses by increasing the number of small eyes to the desired level. In Emmental cheese, the citric acid (+) strains reduced the intensity of propionic acid formation as the FHL apparently competed with the propionibacteria, and enterococci disappeared completely during maturation. Although further work is needed the study shows that, depending on the cheese variety, particular properties of FHL adjunct starters significantly affect important quality attributes of the resulting cheeses.

Smartphone usage has tremendously increased and most users keep their smartphones close throughout the day. Smartphones have a broad variety of sensors, that could automatically map and track the user’s life and behaviour. In this work we investigate whether automatically collected smartphone usage and sensor data can be employed to predict the experienced stress levels of a user using a customized brief version of the Perceived Stress Scale (PSS). To that end we have conducted a user study in which smartphone data and stress (as measured by the PSS seven times a day) were recorded for two weeks. We found significant correlations between stress scores and smartphone usage as well as sensor data, pointing to innovative ways for automatic stress measurements via smartphone technology. Stress is a prevalent risk factor for multiple diseases. Thus accurate and efficient prediction of stress levels could provide means for targeted prevention and intervention.

Experimental Camembert cheeses were made to investigate the effects on browning of the following factors: inoculation with Yarrowia lipolytica, the use of Penicillium candidum strains with different proteolytic activity, the addition of tyrosine, and the addition of Mn2+, thus leading to 16 different variants of cheese. Two physical colour parameters were used to describe browning, depending on the location in the cheeses: a whiteness index for the outside browning (mould mycelium), and a brownness index for the inside browning (surface of the cheese body). Mn2+ promoted a significant increase of browning at both locations, whereas Yar. lipolytica had the opposite effect. Outside browning was significantly more intense when using the Pen. candidum strain with higher proteolytic activity. A significant interaction was found between Yar. lipolytica and Pen. candidum. The yeast had no effect in combination with a low proteolytic strain of Pen. candidum, but significantly reduced proteolysis and browning in combination with a high proteolytic strain of Pen. candidum. We further confirmed that both strains of Pen. candidum were able to produce brown pigments from tyrosine, and thus both are presumably responsible for the browning activity in this type of cheese.

Accurate assessment of nutrition information is an important part in the prevention and treatment of a multitude of diseases, but remains a challenging task. We present a novel mobile augmented reality application, which assists users in the nutrition assessment of their meals. Using the realtime camera image as a guide, the user overlays a 3D form of the food. Additionally the user selects the food type. The corresponding nutrition information is automatically computed. Thus accurate volume estimation is required for accurate nutrition information assessment. This work presents an evaluation of our mobile augmented reality approaches for portion estimation and offers a comparison to conventional portion estimation approaches. The comparison is performed on the basis of a user study (n=28). The quality of nutrition assessment is measured based on the error in energy units. In the results of the evaluation one of our mobile augmented reality approaches significantly outperforms all other methods. Additionally we present results on the efficiency and effectiveness of the approaches.

Treatment of diabetic patients strongly relies on the continuous logging of parameters relevant to glycemic control. Keeping diabetes diaries can be tedious which can affect the data quality and completeness. Mobile technologies could provide means to overcome these limitations. However, studies analyzing the direct effect on the treatment of patients are rare. In the presented study diabetic patients were supplied with a smartphone application to record various parameters relevant for glycemic control. Questions regarding the completeness of diabetes diaries were answered by the patients before and after the study. The attending diabetologist analyzed the data obtained from the smartphone-based diaries to determine whether these provided solutions for problems in glycemic control. The analysis of the available smartphone data provided the basis for therapeutic recommendations that can improve the daily glycemic control for almost all participants. Importantly, especially the newly developed implicit-activity logging, registering the participants' movements, provided important means to generate these recommendations.

Modified feeding of dairy cattle has been described frequently as an appropriate tool to improve rheological properties of fat based dairy products, especially butter, made in the winter feeding period. Controlled feeding experiments with subsequent small-scale cheese-making trials were performed to determine potential effects of oilseed feeding on chemical and physical properties of hard cheeses. Replacement of 1 kg grain by 1 kg shredded rapeseed in the daily cattle diet resulted in a significant increase of the amount of unsaturated fatty acids in the milk fat. The diet did not affect the fat, protein or lactose content of the milk, the cheeses’ gross composition or proteolysis. However, cheeses (approx. 60% dry matter, 50% fat in dry matter) made from milk of the experimental group were signficantly lower in firmness as expressed by the modulus and fracture stress measured by uniaxial compression than cheeses made from milk of the control group. The differences were also evident in sensory experiments. In accordance with results from a subsequent large-scale feeding experiment, oilseed feeding might be considered as an appropriate tool to reduce firmness differences between cheeses of summer and winter feeding periods.

Parallel productions of Austrian Bergkâse from raw or pasteurised milk were perfonned to monitor the effect of heat treatment on physical and sensory properties of the mature cheeses and, in sorne parameters, during ripening. Apart from sorne seasonal variations, analyses of variance showed that neither mechanical properties nor cheese body col our were influenced by the pasteuri- sation of the milk. However, sensory characterisation of smell and aroma as weil as of the basic taste categories of the mature Bergkâse samples showed that pasteurisation leads to reduced intensities of the typical Bergkâse flavour but increases bitterness scores significantly. In line with results from preceding papers, it may be concluded that it is essential to use raw milk for the production of Bergkâse with satisfactory product properties. © Inra/Elsevier, Paris. Bergkâse / raw milk flora / pasteurisation / physical property / sensory property

The effects of the indigenous raw milk flora on the chemical composition of Austrian Bergkâse was evaluated by means of repeated cheesemaking experiments from raw or pasteurised milk. GeneraIly, changes caused by the pasteurisation of raw milk did not significantly affect the gross com- ( position of the resulting cheeses but, as monitored by sampIing during maturation, systematically showed effects on proteolysis, Whereas degradation of ast-casein proved to be delayed in cheeses made from pasteurised milk due to effects caused by heat treatment and partial eIimination of the raw milk flora, an enhanced cIeavage of l3-casein was found in cheeses from pasteurised milk. These differences were also evident in the water-soluble fraction and, partly, in fractions containing smaller breakdown products and were presumably caused by heat-induced changes in the plasmin/plas- minogen complex. Additionally, effects of heat treatment and of indigenous raw milk flora on alka- line phosphatase and Iipolysis were observed. © InralElsevier, Paris. Bergkâse / raw milk flora / pasteurisation / composition / proteolysis

The effects of composite milk protein phenotypes on the composition and cheesemaking properties of milk were studied. Pooled milks from 12 selected groups of Brown cattle with particular phenotype combinations of β-casein (A2A2, A2B), κ-casein (AA, AB, BB) and β-lactoglobulin (AA, BB) were investigated. αs1-Cn BB was common to all animals. Milk collection and cheesemaking trials on a pilot scale were repeated four times during winter 1993. The interaction between all three gene loci (β-Cn, κ-Cn, β-Lg) was found to be highly significant (P < 0.001) for the contents of total protein, casein, whey protein and fat. The casein number was 0–4% (absolute) higher for β-Lg BB milk than for β-Lg AA milk. The relative amount of κ-casein consistently increased from κ-Cn AA to κ-Cn BB. The losses of fat and curd fines in the whey and moisture-adjusted cheese yield were also affected by the genotype combinations. Recovery of milk solids was 3% higher for β-Cn A2B milk than for β-Cn A2A2 milk (P = 0.010).

Dans un grand nombre d'experimentations faites a grande echelle, des emmentals ont ete fabriques a partir de lait cru, avec addition de 0, 10 et 20 % d'eau au melange caille/lactoserum apres decoupage du caille. Pendant l'affinage de 16 semaines dans des conditions standards, des echantillons appropries ont ete preleves dans les meules de fromages et soumis a des analyses. Les resultats montrent que les parametres de composition, c'est-a-dire les teneurs en matiere grasse, matiere seche et calcium, etaient en partie influences par l'affinage, mais restaient totalement inaffectes par le pourcentage d'eau ajoutee. Toutefois, la dilution du lactoserum reduisait la quantite de lactose fermentescible des fromages non affines et entrainait des differences dans le pH et la teneur en acide lactique. Du fait de l'acceleration du developpement des bacteries propioniques induite par le pH, la degradation des lactates a ete trouvee plus prononcee dans les emmentals fabriques avec une addition de 20 % d'eau. En consequence, les taux eleves d'acide propionique et l'acceleration de la formation de l'ouverture etaient evidents dans de tels fromages. D'un autre cote, la quantite croissante d'eau additionnee au melange caille/lactoserum entrainait une reduction de la degradation de la caseine α s1 et une baisse des parametres de proteolyse secondaire. De plus, la contrainte et la deformation a la fracture apparente etaient tres affectees par l'addition d'eau. Les emmentals fabriques avec 20 % d'eau montrent un taux significativement plus eleve de contrainte a la fracture, qui peut etre percu comme une mesure instrumentale de la fermete sensorielle. Comme de plus grands taux de deformation a la fracture impliquent generalement une elasticite sensorielle croissante du fromage, la technologie de l'addition d'eau semble etre un outil approprie pour minimiser les defectuosites sensorielles (fromage a « pâte courte » de consistance), ameliorer la capacite de stockage et diminuer le risque d'une fermentation tardive.

Summary - Randomly-selected Austrian bacterial surface-ripened cheeses were examined for changes in the microbiological composition of the smear. The bacterial counts of the Tilsit cheeses from 14 cheese plants and of 3 types of soft cheeses selected varied fram 1()4 ta 109 cfu/cm2 smear 3 d after manufacture and fram 108 ta 109 cfu/cm2 smear after a ripening period of 3 weeks. The flora tolerated a NaCI content of at least 80 g/kg in the plate count agar. A total of 386 isolates of coryneform bacteria were identified. The bacterial flora proved ta be of mixed population. However, Brevibacterium linens accounted for a large share of the flora, comprising 30% of the total bacterial count, Besides Brevibacterium linens, the other main types found ta be present in the heterogeneous flora were creamcoloured and yellow-pigmented coryneforms, which were predominantly identified as Arthrobacter globiformis and Brevibacterium ammoniagenes. The coryneforms isolated fram the cheeses 3 d after manufacture were more prateoly1ic than those isolated at later stages of ripening.

A new computer program, called SHIFTX2, is described which is capable of rapidly and accurately calculating diamagnetic 1H, 13C and 15N chemical shifts from protein coordinate data. Compared to its predecessor (SHIFTX) and to other existing protein chemical shift prediction programs, SHIFTX2 is substantially more accurate (up to 26% better by correlation coefficient with an RMS error that is up to 3.3× smaller) than the next best performing program. It also provides significantly more coverage (up to 10% more), is significantly faster (up to 8.5×) and capable of calculating a wider variety of backbone and side chain chemical shifts (up to 6×) than many other shift predictors. In particular, SHIFTX2 is able to attain correlation coefficients between experimentally observed and predicted backbone chemical shifts of 0.9800 (15N), 0.9959 (13Cα), 0.9992 (13Cβ), 0.9676 (13C′), 0.9714 (1HN), 0.9744 (1Hα) and RMS errors of 1.1169, 0.4412, 0.5163, 0.5330, 0.1711, and 0.1231 ppm, respectively. The correlation between SHIFTX2’s predicted and observed side chain chemical shifts is 0.9787 (13C) and 0.9482 (1H) with RMS errors of 0.9754 and 0.1723 ppm, respectively. SHIFTX2 is able to achieve such a high level of accuracy by using a large, high quality database of training proteins (>190), by utilizing advanced machine learning techniques, by incorporating many more features (χ2 and χ3 angles, solvent accessibility, H-bond geometry, pH, temperature), and by combining sequence-based with structure-based chemical shift prediction techniques. With this substantial improvement in accuracy we believe that SHIFTX2 will open the door to many long-anticipated applications of chemical shift prediction to protein structure determination, refinement and validation. SHIFTX2 is available both as a standalone program and as a web server (http://www.shiftx2.ca). Electronic supplementary material The online version of this article (doi:10.1007/s10858-011-9478-4) contains supplementary material, which is available to authorized users.

The construction of a consistent protein chemical shift database is an important step toward making more extensive use of this data in structural studies. Unfortunately, progress in this direction has been hampered by the quality of the available data, particularly with respect to chemical shift referencing, which is often either inaccurate or inconsistently annotated. Preprocessing of the data is therefore required to detect and correct referencing errors. We have developed a program for performing this task, based on the comparison of reported and expected chemical shift distributions. This program, named CheckShift, does not require additional data and is therefore applicable to data sets where structures are not available. Therefore CheckShift provides the possibility to re-reference chemical shifts prior to their use as structural constraints.

Experimental samples of Bergkâse, an Austrian regional hard cheese variety usually made from raw milk, were produced from raw or pasteurised milks in parallel to evaluate the influence of the indigenous microflora on microbiological composition and selected fermentation compounds. Fac- ultatively heterofermentative lactobacilli (FHL) dominated the non-starter flora in cheeses made from raw milk. Viable numbers increased from 1Q4-106 cfu-g-' at the age of 1 week to reach their final levelof 108 cfu-g! within the first month of ripening. In contrast, cheeses made from pasteurised milk exhibited FHL counts which were at least three orders of magnitude lower or even undetectable. In the raw milk cheeses, the development of organic acids during maturation differed from that in the pasteurised ones, and was dependent on the number and the metabolic activity of the microorganisms. Differences in the citrate metabolism and in propionic acid fermentation, which occurred in raw milk cheeses only, cau be attributed to the occurrence ofFHL and propionic acid bacteria, respectively. © InralElsevier, Paris.

Understanding the relationship between protein structure and biological function is a central theme in structural biology. Advances are severely hampered by errors in experimentally determined protein structures. Detection and correction of such errors is therefore of utmost importance. Electron densities in molecular structures obey certain rules which depend on the molecular environment. Here we present and discuss a new approach that relates electron densities computed from a structural model to densities expected from prior observations on identical or closely related molecular environments. Strong deviations of computed from expected densities reveal unrealistic molecular structures. Most importantly, structure analysis and error detection are independent of experimental data and hence may be applied to any structural model. The comparison to state-of-the-art methods reveals that our approach is able to identify errors that formerly remained undetected. The new technique, called RefDens, is accessible as a public web service at http://refdens.services.came.sbg.ac.at. Electronic Supplementary Material The online version of this article (doi: 10.1007/s10858-010-9408-x) contains supplementary material, which is available to authorized users.