AI Article Synopsis

  • Researchers explored how different diets influence weight gain in CD-1 mice as models for human obesity.
  • The study found that high-fat diets (60% and 45% fat) led to significantly greater increases in body and fat mass compared to lower fat diets.
  • Combining a high-fat diet with a standard stock diet resulted in even more weight gain, suggesting that this method could reduce the number of mice needed for experiments by about 40%.

Article Abstract

Mouse experimental models of diet-induced weight gain are commonly used as analogs to human obesity; however, a wide variety of feeding methods have been used and the most effective way to maximize weight gain is not known. Maximizing weight gain may allow for a reduction in the number of animals required for a given experiment. The purpose of this study was how to cause the greatest amount of weight gain in CD-1 mice by modifying the composition and source of their diet. To accomplish this goal, we completed two experiments: (1) Effect of dietary macronutrient fat intake (60% (HF60), 45% (HF45), 30% (HF30), or 13.5% (CON) fat diet for 18 weeks); and (2) Effect of 1:1 mixed HF60 and CON diets. Outcome measures included food intake, body mass, and body composition, which were measured bi-weekly and statistically analyzed using a repeated measures analysis of variance (RM-ANOVA). In Experiment 1, the greatest increase in body and fat mass was observed in HF60 (36%) and HF45 (29%) compared with HF30 and CON (P < 0.05). In Experiment 2, HF + stock diet (SK) gained 25% more body mass and 70% more fat mass than HF (P < 0.05). Collectively, these findings suggest that using a high-fat based diet (>45% calories from fat), mixed with a stock diet, results in substantially more weight gain over a similar period, of time, which would allow an investigator to use ~40% fewer animals in their experimental model.

Download full-text PDF

Source
http://dx.doi.org/10.1177/0023677213501658DOI Listing

Publication Analysis

Top Keywords

weight gain
24
fat mass
12
gain mouse
8
diet-induced weight
8
body mass
8
stock diet
8
gain
7
fat
6
weight
6
mass
5

Similar Publications

Background: The ring-augmented Roux-en-Y gastric bypass (raRYGB) has been reported to result in higher long-term weight loss compared to regular Roux-en-Y gastric bypass (RYGB). However, the type of ring used varied within studies, leading to heterogeneity in reported results. Therefore, this study compares the 5-year results of RYGB with and without ring augmentation using a specific prefabricated gastric ring.

View Article and Find Full Text PDF

Prediction of dry matter intake in growing Black Bengal goats using artificial neural networks.

Trop Anim Health Prod

January 2025

Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh, 243 122, India.

Dry matter intake (DMI) determination is essential for effective management of meat goats, especially in optimizing feed utilization and production efficiency. Unfortunately, farmers often face challenges in accurately predicting DMI which leads to wastage of feed and an increase in the cost of production. This investigation aimed to predict DMI in Black Bengal goats by using body weight (BW), body condition score (BCS), average daily gain (ADG), and metabolic body weight (MBW) by applying an artificial neural network (ANN) model.

View Article and Find Full Text PDF

Medications That May be Contributing to Your Patient's Weight Gain.

South Med J

February 2025

From the Department of Pharmacy Education and Practice, College of Pharmacy, University of Florida, Gainesville.

Nearly 42% of adults in the United States are considered obese. Although there are a number of contributing factors to obesity, one sometimes overlooked contributor to weight gain is medications. Within many classes of medications that may affect weight, the degree of weight gain varies.

View Article and Find Full Text PDF

Introduction And Hypothesis: This study aims to develop a postpartum stress urinary incontinence (PPSUI) risk prediction model based on an updated definition of PPSUI, using machine learning algorithms. The goal is to identify the best model for early clinical screening to improve screening accuracy and optimize clinical management strategies.

Methods: This prospective study collected data from 1208 postpartum women, with the dataset randomly divided into training and testing sets (8:2).

View Article and Find Full Text PDF

Introduction: Diarrhea is a prevalent disease among calves, which significantly hinders their growth and development, thereby impacting farm productivity and revenue. This study aimed to investigate the impact of diarrhea on calf growth.

Methods: Holstein male calves with similar birth weight (39.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!