Obesity is the most common clinical disorder and is associated with various medical conditions in dogs. Appropriate dietary management potentially provides weight loss in a safe, healthy, and efficacious manner. In order to elucidate whether dietary fiber, carnitine, diacylglycerol (DAG), and low glycemic index (LGI) act on such dietary components, a series of studies was conducted: 1) the combination of dietary fiber/carnitine effect on short term (3 and 7 h) satiety and long term (6 weeks) canine weight loss, 2) the combination of dietary LGI/high glycemic index (HGI) starches and DAG/triacylglycerol (TAG) effect during a 9 week canine weight loss period, and 3) the DAG effect on triglyceride rich lipoprotein (TRL) metabolism isolated from canine plasma 3-4 h postprandially. The combination of dietary fiber/carnitine supplementation decreased both food and energy intake at 3 h post-feeding, suggesting that this combination diet provided 3 h post-meal satiety. This combination supplement also increased postprandial plasma B- hydroxybutyrate (BHB) at d 42 and body fat and weight loss at d 42 from baseline. This combination supplement did not alter plasma vitamin A distributions or concentrations although it contained high vitamin A as B-carotene. In the second study, the LGI diets resulted in a more pronounced body weight loss than the HGI diets due to lower diet digestibilities. These data are consistent with LGI diets decreasing metabolizable energy and consequently consuming less energy compared to the HGI diets. The DAG diets lowered postprandial plasma TAG at weeks 1 and 8 in and increased plasma BHB at week 8, suggesting an increase in fat oxidation. The combination of DAG/LGI decreased postprandial total cholesterol at week 8. Lipoprotein concentrations were not altered by diet types. Fasting lipoprotein lipase (LPL) and hepatic lipase (HL) activities were not affected by diets. In the final study, DAG ingestion decreased TRL and plasma TAG concentrations vs. TAG ingestion. The DAG enriched meal increased non-esterified fatty acid, monoacylglycerol, and 1,3-DAG and decreased TAG in TRLs which may be attributed to larger TRL particle size compared to the TAG meal. Consequently, the DAG derived TRLs showed increased affinity of core TAG for LPL and HL in vitro. Moreover, the intravenous injection of the DAG derived canine TRLs into mice underwent more rapid blood clearance associated with the greater hepatic uptake compared to the TAG derived TRL injection. In conclusion, the combination of dietary fiber/carnitine and DAG/LGI preferably reduced body weight and stimulated fat oxidation, which promotes overall weight loss. The postprandial plasma TAG lowering effect of DAG is the result, at least partially, from the efficient clearance of TRLs from blood circulation and their ability to act as a more efficient substrate for plasma lipolytic enzymes.

Ziel der Arbeit war eine Steigerung der Wasseraufnahme und Harndilution durch Supplementierung von Natriumchlorid (NaCl) oder pH-Wert-Senkung durch Zugabe von Ammoniumchlorid (NH4Cl) zur Reduktion des Harnsteinbildungspotenzials. Durch die NaCl-Zulage wurde die Harnmenge signifikant gesteigert und das spezifische Gewicht des Harns gesenkt. Eine NaCl-Gabe stellt somit einen möglichen ergänzenden therapeutischen Ansatz für eine vermehrte Ausscheidung von Kristallen dar. Eine Ansäuerung des Harns durch Zulage von NH4Cl ließ sich nicht erreichen.

<p></p><p>Phenylketonuria (PKU) is an inherited metabolic disorder affecting 1 in every 10,000 to 15,000 newborns in the United States every year. Caused by a genetic mutation, PKU results in an excessive build up of the amino acid Phenylalanine (Phe) in the body leading to symptoms including but not limited to intellectual disability, hyperactivity, psychiatric disorders and seizures. Most PKU patients must follow a strict diet limited in Phe. The aim of this research study is to formulate, implement and compare techniques for Phe estimation in commercial foods using the information on the food label (Nutritional Fact Label and ordered ingredient list). Ideally, the techniques should be both accurate and amenable to a user friendly implementation as a Phe calculator that would aid PKU patients monitor their dietary Phe intake.</p> <p> The first approach to solve the above problem is a mathematical one that comprises three steps. The three steps were separately proposed as methods by Jieun Kim in her dissertation. It was assumed that the third method, which is more computationally expensive, was the most accurate one. However, by performing the three methods subsequently in three different steps and combining the results, we actually obtained better results than by merely using the third method.</p> <p> The first step makes use of the protein content in the foods and Phe:protein multipliers. The second step enumerates all the ingredients in the food and uses the minimum and maximum Phe:protein multipliers of the ingredients along with the protein content. The third step lists the ingredients in decreasing order of their weights, which gives rise to inequality constraints. These constraints hold assuming that there is no loss in the preparation process. The inequality constraints are optimized numerically in two phases. The first involves nutrient content estimation by approximating the ingredient amounts. The second phase is a refinement of the above estimates using the Simplex algorithm. The final Phe range is obtained by performing an interval intersection of the results of the three steps. We implemented all three steps as web applications. Our proposed three-step method yields a high accuracy of Phe estimation (error <= +/- 13.04mg Phe per serving for 90% of foods).</p> <p> The above mathematical procedure is contrasted against a machine learning approach that uses the data in an existing database as training data to infer the Phe in any given food. Specifically, we use the K-Nearest Neighbors (K-NN) classification method using a feature vector containing the (rounded) nutrient data. In other words, the Phe content of the test food is a weighted average of the Phe values of the neighbors closest to it using the nutrient values as attributes. A four-fold cross validation is carried out to determine the hyper-parameters and the training is performed using the United States Department of Agriculture (USDA) food nutrient database. Our tests indicate that this approach is not very accurate for general foods (error <= +/- 50mg Phe per 100g in about 38% of the foods tested). However, for low-protein foods which are typically consumed by PKU patients, the accuracy increases significantly (error <= +/- 50mg Phe per 100g in over 77% foods).</p> <p> The machine learning approach is more user-friendly than the mathematical approach. It is convenient, fast and easy to use as it takes into account just the nutrient information. In contrast, the mathematical method additionally takes as input a detailed ingredient list, which is cumbersome to be located in a food database and entered as input. However, the Mathematical method has the added advantage of providing error bounds for the Phe estimate. It is also more accurate than the ML method. This may be due to the fact that for the ML method, the nutrition facts alone are not sufficient to estimate Phe and that additional information like the ingredients list is required. </p><br><p></p>

Ziel der Arbeit war eine Steigerung der Wasseraufnahme und Harndilution durch Supplementierung von Natriumchlorid (NaCl) oder pH-Wert-Senkung durch Zugabe von Ammoniumchlorid (NH4Cl) zur Reduktion des Harnsteinbildungspotenzials. Durch die NaCl-Zulage wurde die Harnmenge signifikant gesteigert und das spezifische Gewicht des Harns gesenkt. Eine NaCl-Gabe stellt somit einen möglichen ergänzenden therapeutischen Ansatz für eine vermehrte Ausscheidung von Kristallen dar. Eine Ansäuerung des Harns durch Zulage von NH4Cl ließ sich nicht erreichen.

生活於手機相機普及的今日，人們逐漸依賴隨手可得的行動裝置記錄生活，影像記錄儼然成為今日人們記錄生活的方式之一。本研究致力於提供使用者個人化之飲食管理系統，讓使用者在利用影像記錄飲食之時，改變自身的多樣性飲食攝取行為，讓個體更為健康。透過健康控制與社會認知理論，我們以影像後設資料的運用，增加自我效能，提供使用者方便的飲食記錄方式、以及更能掌握自身的營養狀況，讓使用者在記錄飲食的同時，還能改變自身飲食攝取行為，更能作為未來回憶飲食狀況之線索。在實驗設計上，我們邀請6位受試者使用本研究所開發的飲食管理系統，利用兩週的時間真實模擬生活中的飲食記錄環境。我們分析使用者實驗前後的自我效能問卷，以及所記錄的飲食記錄作為評估依據。實驗結果顯示，我們的系統能夠提升個體自我效能外，還能夠改變個體的飲食攝取行為。因此本研究有效促進自我效能感協助使用者在記錄生活，讓個體飲食更加健康 / In these days, as the popularity of smart phone grows, people tend to rely on mobile devices to record their lives. Digital photograph has become one of the ways people recording their daily lives. This research is aimed at providing users with personalized dietary management system, allowing users not only use photos to record their life, but also change their behavior to keep users in good health. Based on health control and social cognitive theory, this application utilizes the metadata of the images to enhance self-efficacy, to provide users an easier way to record their dietary and take better control of their own health. Furthermore, the data of the application allows users to recall the dietary and thus improves users’ dietary habits. For the experimental design, 6 subjects were invited to use rthis dietary management application, to record their daily dietary in two weeks. The subjects were asked to use the system, and answer a questionnaire related to the self-efficiency of their adequate dietary after using the application. Experimental results shows that this system not only helps users enhance individual self-efficacy in dietary but also change their dietary habit to achieve the goal of balanced dietary and in good health.