In this work, the authors investigate the accuracy with which two different population growth models can predict population growth over time. They apply the Malthusian law or Logistic law to US population from 1951 until 2019. To assess how closely the growth model fits actual population data, a least-squared curve fit was applied and revealed that the Logistic law of population growth resulted in smaller sum of squared residuals. These findings are important for ensuring optimal population growth models are implemented to data as population forecasting affects a country's economic and social structure.
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Varying Growth Hormone Levels in Chondrocytes Increases Proliferation Rate and Collagen Production by a Direct Pathway
Bennett and Joykutty test whether growth hormone directly or indirectly affected the rate at which cartilage renewed itself. Growth hormone could exert a direct effect on cartilage or chondrocytes by modifying the expression of different genes, whereas an indirect effect would come from growth hormone stimulating insulin-like growth factor. The results from this research support the hypothesis that growth hormone increases proliferation rate using the direct pathway. This research can be used in the medical sciences for people who suffer from joint damage and other cartilage-related diseases, since the results demonstrated conditions that lead to increased proliferation of chondrocytes. These combined results could be applied in a clinical setting with the goal of allowing patient cartilage to renew itself at a faster pace, therefore keeping those patients out of pain from these chondrocyte-related diseases.
Read More...The Effects of Altered Microbiome on Caenorhabditis elegans Egg Laying Behavior
Since the discovery that thousands of different bacteria colonize our gut, many of which are important for human wellbeing, understanding the significance of balancing the different species on the human body has been intensely researched. Untangling the complexity of the gut microbiome and establishing the effect of the various strains on human health is a challenge in many circumstances, and the need for simpler systems to improve our basic understanding of microbe-host interactions seems necessary. C. elegans are a well-established laboratory animal that feed on bacteria and can thus serve as a less complex system for studying microbe-host interactions. Here the authors investigate how the choice of bacterial diet affects worm fertility. The same approach could be applied to many different outcomes, and facilitate our understanding of how the microbes colonizing our guts affect various bodily functions.
Read More...Reduce the harm of acid rain to plants by producing nitrogen fertilizer through neutralization
The phenomenon of dying trees and plants in areas affected by acid rain has become increasingly problematic in recent times. Is there any method to efficiently utilize the rainwater and reduce the harmfulness of acid rain or make it beneficial to plants? This study aimed to investigate the potential of neutralizing acid rainwater infiltrating the soil to increase soil pH, produce beneficial salts for plants, and support better plant growth. To test this hypothesis, precipitation samples were collected from six states in the U.S. in 2022, and the pH of the acid rain was measured to obtain a representative pH value for the country. Experiments were then conducted to simulate the neutralization of acid rain and the subsequent change in soil pH levels. To evaluate the effectiveness and feasibility of this method, cat grass was planted in pots of soil soaked with solutions mimicking acid rain, with control and experimental groups receiving neutralizing agents (ammonium hydroxide) or not. Plant growth was measured by analyzing the height of the plants. Results demonstrated that neutralizing agents were effective in improving soil pH levels and that the resulting salts produced were beneficial to the growth of the grass. The findings suggest that this method could be applied on a larger agricultural scale to reduce the harmful effects of acid rain and increase agricultural efficiency.
Read More...A novel approach to determine which organism best displays Gijswijt's Sequence in its genome
The sequence of nitrogenous bases that make up the DNA of organisms can contain hidden mathematical sequences. Here the authors used BioPython, a programming tool, to find an organism that displays Gijswijt’s Sequence in its genome. In this manner they found that the common carp best displays Gijswijt’s Sequence in its genome.
Read More...Unveiling bias in ChatGPT-3.5: Analyzing constitutional AI principles for politically biased responses
Various methods exist to mitigate bias in AI models, including "Constitutional AI," a technique which guides the AI to behave according to a list of rules and principles. Lo, Poosarla, Singhal, Li, Fu, and Mui investigate whether constitutional AI can reduce bias in AI outputs on political topics.
Read More...Using text embedding models as text classifiers with medical data
Assessing the possibility of using entomopathogenic fungi for mosquito control in Hawaii
Fungi that attack and kill insects have promise for targeting mosquitoes without the harmful environmental impacts of chemicals like DDT. To find out whether fungi might be effective in controlling mosquitoes in Hawaii, Jiang and Chan test the effects of Hawaiian fungal isolates on mosquito larvae.
Read More...Model selection and optimization for poverty prediction on household data from Cambodia
Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.
Read More...Machine learning for retinopathy prediction: Unveiling the importance of age and HbA1c with XGBoost
The purpose of our study was to examine the correlation of glycosylated hemoglobin (HbA1c), blood pressure (BP) readings, and lipid levels with retinopathy. Our main hypothesis was that poor glycemic control, as evident by high HbA1c levels, high blood pressure, and abnormal lipid levels, causes an increased risk of retinopathy. We identified the top two features that were most important to the model as age and HbA1c. This indicates that older patients with poor glycemic control are more likely to show presence of retinopathy.
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