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Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Sirohi et al. | Sep 25, 2022

Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

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Using explainable artificial intelligence to identify patient-specific breast cancer subtypes

Suresh et al. | Jan 12, 2024

Using explainable artificial intelligence to identify patient-specific breast cancer subtypes

Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.

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The Effect of Anubias barteri Plant Species on Limiting Freshwater Acidification

Ramanathan et al. | Jul 06, 2021

The Effect of <i>Anubias barteri</i> Plant Species on Limiting Freshwater Acidification

Research relating to freshwater acidification is minimal, so the impact of aquatic plants, Anubias barteri var. congensis and Anubias barteri var. nana, on minimizing changes in pH was explored in an ecosystem in Northern California. Creek water samples, with and without the aquatic plants, were exposed to dry ice to simulate carbon emissions and the pH was monitored over an eight-hour period. There was a 25% difference in the observed pH based on molar hydrogen ion concentration between the water samples with plants and those without plants, suggesting that aquatic plants have the potential to limit acidification to some extent. These findings can guide future research to explore the viable partial solution of aquatic plants in combating freshwater acidification.

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Effect of hypervitaminosis A in regenerating planaria: A potential model for teratogenicity testing

Bennet et al. | Dec 12, 2022

Effect of hypervitaminosis A in regenerating planaria: A potential model for teratogenicity testing

This unique research study evaluated the potential use of the flatworm, brown planaria (Dugesia tigrine), as an alternative model for teratogenicity testing. In this study, we exposed amputated planaria to varying concentrations of a known teratogen, vitamin A (retinol), for approximately 2 weeks, and evaluated multiple parameters including the formation of blastema and eyes. The results from this study demonstrated that high concentrations of retinol caused defects in head and eye formation in regenerating planaria, with similarities to vitamin A related teratogenicity findings in mammals. Based on these results, regenerating brown planaria are a promising alternative model for teratogenicity testing, which can potentially be paradigm shifting as it can reduce cost, time, and pregnant animal use in research.

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Modulation of VEGF and TGF beta in 5-FU induced inflammation in MCF-7 using an herbal formulation

Vinay Nair et al. | Jun 03, 2022

Modulation of VEGF and TGF beta in 5-FU induced inflammation in MCF-7 using an herbal formulation

Acquired drug resistance is an increasing challenge in treating cancer with chemotherapy. One mechanism
behind this resistance is the increased inflammation that supports the progression and development of
cancer that arises because of the drug’s presence. Integrative oncology is the field that focuses on including natural products alongside traditional therapy to create a treatment that focuses on holistic patient well-being.
In this study, the authors demonstrate that the use of an herbal formulation, consisting of turmeric and green tea, alongside a traditional chemotherapeutic drug, 5-fluorouracil (FU) significantly decreases the level of cytokines produced in breast cancer cells when compared to the levels produced when exposed solely to the chemo drug. The authors conclude that this combination of treatment, based on the principle of integrative oncology, shows potential for reducing the resistance against treatment conferred through increased inflammation. Consequently, this suggests a prospective way forward in improving the efficacy of cancer treatment.

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Attitudes towards mental health in Indians who practice yoga regularly and those who do not

Komar et al. | Jul 13, 2022

Attitudes towards mental health in Indians who practice yoga regularly and those who do not

Whether it is through implicit association or intentional practice, yoga has been known to help individuals maintain good mental health. However, many communities, such as South Asian communities, often project the stereotype that embodies neglecting topics such as mental health and considering them taboo. In this online survey-based study, the authors focused on examining whether yoga would alter individuals’ attitudes toward mental health. They hypothesized that 1) participants who regularly practiced yoga would be more familiar with the term mental health, 2) participants who practiced yoga would value their mental health more, and 3) participants who practiced yoga regularly would be more open about their mental health and be more likely to reach out for professional help if needed. They did not find a statistical significance for any of our hypotheses which suggests that yoga may not have an effect on perceptions of mental health in yoga-practicing Indian adults.

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Analyzing honey’s ability to inhibit the growth of Rhizopus stolonifer

Johnecheck et al. | Jun 06, 2023

Analyzing honey’s ability to inhibit the growth of <i>Rhizopus stolonifer</i>
Image credit: Johnecheck et al. 2023

Rhizopus stolonifer is a mold commonly found growing on bread that can cause many negative health effects when consumed. Preservatives are the well-known answer to this problem; however, many preservatives are not naturally found in food, and some have negative health effects of their own. We focused on honey as a possible solution because of its natural origin and self-preservation ability. We hypothesized that honey would decrease the growth rate of R. stolonifer . We evaluated the honey with a zone of inhibition (ZOI) test on agar plates. Sabouraud dextrose agar was mixed with differing volumes of honey to generate concentrations between 10.0% and 30.0%. These plates were then inoculated with a solution of spores collected from the mold. The ZOI was measured to determine antifungal effectiveness. A statistically significant difference was found between the means of all concentrations except for 20.0% and 22.5%. Our findings support the hypothesis as we showed a positive correlation between the honey concentration and growth rate of mold. By using this data, progress could be made on an all-natural, honey-based preservative.

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