Segmentation and Recognition of Multi-Food Meal Images for Carbohydrate Counting

In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

Biomass and Stored Carbohydrate Compensation after Above-Ground Biomass Removal in a Perennial Herb: Does Environmental Productivity Play a Role?

Many plant species are able to tolerate severe disturbance leading to removal of a substantial portion of the body by resprouting from intact or fragmented organs. Resprouting enables plants to compensate for biomass loss and complete their life cycles. The degree of disturbance tolerance, and hence the ecological advantage of damage tolerance (in contrast to alternative strategies), has been reported to be affected by environmental productivity. In our study, we examined the influence of soil nutrients (as an indicator of environmental productivity) on biomass and stored carbohydrate compensation after removal of aboveground parts in the perennial resprouter Plantago lanceolata. Specifically, we tested and compared the effects of nutrient availability on biomass and carbon storage in damaged and undamaged individuals. Damaged plants of P. lanceolata compensated neither in terms of biomass nor overall carbon storage. However, whereas in the nutrient-poor environment, root total non-structural carbohydrate concentrations (TNC) were similar for damaged and undamaged plants, in the nutrient-rich environment, damaged plants had remarkably higher TNC than undamaged plants. Based on TNC allocation patterns, we conclude that tolerance to disturbance is promoted in more productive environments, where higher photosynthetic efficiency allows for successful replenishment of carbohydrates. Although plants under nutrient-rich conditions did not compensate in terms of biomass or seed production, they entered winter with higher content of carbohydrates, which might result in better performance in the next growing season. This otherwise overlooked compensation mechanism might be responsible for inconsistent results reported from other studies.

Determination of carbohydrate-deficient transferrin in human serum by capillary zone electrophoresis: evaluation of assay performance and quality assurance over a 10-year period in the routine arena.

The performance of high-resolution CZE for determination of carbohydrate-deficient transferrin (CDT) in human serum based on internal and external quality data gathered over a 10-year period is reported. The assay comprises mixing of serum with a Fe(III) ion-containing solution prior to analysis of the iron saturated mixture in a dynamically double-coated capillary using a commercial buffer at alkaline pH. CDT values obtained with a human serum of a healthy individual and commercial quality control sera are shown to vary less than 10%. Values of a control from a specific lot were found to slowly decrease as function of time (less than 10% per year). Furthermore, due to unknown reasons, gradual changes in the monitored pattern around pentasialo-transferrin were detected, which limit the use of commercial control sera of the same lot to less than 2 years. Analysis of external quality control sera revealed correct classification of the samples over the entire 10-year period. Data obtained compare well with those of HPLC and CZE assays of other laboratories. The data gathered over a 10-year period demonstrate the robustness of the high-resolution CZE assay. This is the first account of a CZE-based CDT assay with complete internal and external quality assessment over an extended time period.

Transferrin immunoextraction for determination of carbohydrate-deficient transferrin in human serum by capillary zone electrophoresis

CZE-based assays for carbohydrate-deficient transferrin (CDT) in which serum is mixed with an Fe(III) ion-containing solution prior to analysis are effective approaches for the determination of CDT in patient samples. Sera of patients with progressed diseases, however, are prone to interferences comigrating with transferrin (Tf) that prevent the proper determination of CDT by CZE in these samples. The need of a simple and economic approach to immunoextract Tf from human serum prompted us to investigate the use of a laboratory-made anti-Tf spin column containing polyclonal rabbit anti-human Tf antibodies linked to Sepharose 4 Fast Flow beads. This article reports extraction column manufacturing and column characterization with sera having normal and elevated CDT levels. The developed procedure was applied to a number of relevant hepatology and dialysis patient samples and could thereby be shown to represent an effective method for extraction and concentration of all Tf isoforms. Furthermore, lipemic sera were delipidated using a mixture of diisopropyl ether and butanol prior to immunoextraction. CDT could unambiguously be determined in all pretreated samples.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

The human IgG anti-carbohydrate repertoire exhibits a universal architecture and contains specificity for microbial attachment sites.

Despite the paradigm that carbohydrates are T cell-independent antigens, isotype-switched glycan-specific immunoglobulin G (IgG) antibodies and polysaccharide-specific T cells are found in humans. We used a systems-level approach combined with glycan array technology to decipher the repertoire of carbohydrate-specific IgG antibodies in intravenous and subcutaneous immunoglobulin preparations. A strikingly universal architecture of this repertoire with modular organization among different donor populations revealed an association between immunogenicity or tolerance and particular structural features of glycans. Antibodies were identified with specificity not only for microbial antigens but also for a broad spectrum of host glycans that serve as attachment sites for viral and bacterial pathogens and/or exotoxins. Tumor-associated carbohydrate antigens were differentially detected by IgG antibodies, whereas non-IgG2 reactivity was predominantly absent. Our study highlights the power of systems biology approaches to analyze immune responses and reveals potential glycan antigen determinants that are relevant to vaccine design, diagnostic assays, and antibody-based therapies.

Are carbohydrate storage strategies of trees traceable by early–latewood carbon isotope differences?

Investigations of stable isotopes in early and latewood cellulose offer interesting insights to climate-driven adaptations of trees’ carbon storage strategy during different phenological phases.

Life-long growth of Quercus ilex L. at natural CO2 springs acclimates sulphur, nitrogen and carbohydrate metabolism of the progeny to elevated pCO2

The aim of the present study was to analyse whether offspring of mature Quercus ilex trees grown under life-long elevated pCO2 show alterations in the physiological response to elevated pCO2 in comparison with those originating from mature trees grown at current ambient pCO2. To investigate changes in C- (for changes in photosynthesis, biomass and lignin see Polle, McKee & Blaschke Plant, Cell and Environment 24, 1075–1083, 2001), N-, and S-metabolism soluble sugar, soluble non-proteinogenic nitrogen compounds (TSNN), nitrate reductase (NR), thiols, adenosine 5′-phosphosulphate (APS) reductase, and anions were analysed. For this purpose Q. ilex seedlings were grown from acorns of mother tree stands at a natural spring site (elevated pCO2) and a control site (ambient pCO2) of the Laiatico spring, Central Italy. Short-term elevated pCO2 exposure of the offspring of control oaks lead to higher sugar contents in stem tissues, to a reduced TSNN content in leaves, and basipetal stem tissues, to diminished thiol contents in all tissues analysed, and to reduced APS reductase activity in both, leaves and roots. Most of the components of C-, N- and S-metabolism including APS reductase activity which were reduced due to short-term elevated pCO2 exposure were recovered by life-long growth under elevated pCO2 in the offspring of spring oaks. Still TSNN contents in phloem exudates increased, nitrate contents in lateral roots and glutathione in leaves and phloem exudates remained reduced in these plants. The present results demonstrated that metabolic adaptations of Q. ilex mother trees to elevated pCO2 can be passed to the next generation. Short- and long-term effects on source-to-sink relation and physiological and genetic acclimation to elevated pCO2 are discussed.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.