Browse Articles

Unveiling the wound healing potential of umbilical cord derived conditioned medium: an in vitro study

Vasal et al. | Jun 17, 2024

Unveiling the wound healing potential of umbilical cord derived conditioned medium: an <em>in vitro</em> study

Chronic wounds pose a serious threat to an individual’s health and quality of life. However, due to the severity and morbidity of such wounds, many pre-existing treatments are inefficient or costly. While the use of skin grafts and other such biological constructs in chronic wound healing has already been characterized, the use of umbilical cord tissue has only recently garnered interest, despite the cytokine-rich composition of Wharton’s jelly (cord component). Our current study aimed to characterize the use of an umbilical cord derived conditioned medium (UC-CM) to treat chronic wounds.

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Comparative analysis of CO2 emissions of electric ride-hailing vehicles over conventional gasoline personal vehicles

Raman et al. | Jan 12, 2024

Comparative analysis of CO<sub>2</sub> emissions of electric ride-hailing vehicles over conventional gasoline personal vehicles
Image credit: Paul Hanaoka

While some believe that ride-hailing services offer reduced CO2 emissions compared to individual driving, studies have found that driving without passengers on ride-hailing trips or "deadheading" prevents this. Here, with a mathematical model, the authors investigated if the use of electric vehicles as ride-hailing vehicles could offer reduced CO2 emissions. They found that the improved vehicle efficiency and cleaner generation could in fact lower emissions compared to the use of personal gas vehicles.

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Predicting baseball pitcher efficacy using physical pitch characteristics

Oberoi et al. | Jan 11, 2024

Predicting baseball pitcher efficacy using physical pitch characteristics
Image credit: Antoine Schibler

Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.

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Blue light blocking glasses: do they do what they promise?

Lee et al. | Dec 13, 2023

Blue light blocking glasses: do they do what they promise?
Image credit: nacer eddine

With increased screen time and exposure to blue light, an increasing number of people have sleep deprivation. Blue light suppresses the release of melatonin and hinders sleep at night. We hypothesized that people could get a greater amount of sleep by controlling the blue light exposure from screen time before bedtime. BBG’s effect on reducing time to fall asleep was significant within the teenage group, but not significant in the adult group. This indicated that BBG could improve the time taken to sleep for young teenagers post screen time in the evening.

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Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation in situ

Bhat et al. | Jul 18, 2023

Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation <i>in situ</i>
Image credit: Karolina Grabowska

The Environmental Protection Agency (EPA) reports a significant number of heavy metal-contaminated sites across the United States. To address this public health concern, rhizoremediation using microbes has emerged as a promising solution. Here, a combination of soil microbes were inoculated in the rhizosphere in soil contaminated with 500 parts per million (ppm) of lead. Results showed rhizoremediation is an effective bioremediation strategy and may increase crop productivity by converting nonarable lands into arable lands.

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The velocity of white dwarf stars relates to their magnitude

Glazer et al. | Jun 30, 2023

The velocity of white dwarf stars relates to their magnitude
Image credit: Jacub Gomez

Using the European Space Agency’s Gaia dataset, the authors analyzed the relationship between white dwarfs’ magnitudes and proper motions. They hypothesized that older white dwarf stars may have different velocities than younger ones, possibly that stars slow down as they age. They found that the white dwarfs in the dataset were substantially redder and higher magnitude (traits traditionally associated with older stars) as compared to their non-fast counterparts.

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Associations between substance misuse, social factors, depression, and anxiety among college students

Kouser et al. | Jun 12, 2023

Associations between substance misuse, social factors, depression, and anxiety among college students
Image credit: Jordan Encarnacao

Here, the authors considered the effects of relationship status and substance use on the mental health of colleges students, where they specifically examined their correlation with depression, anxiety, and the fear of missing out (FoMO). Through a survey of college students they found that those with higher substance misuse had higher levels of anxiety, depression, and FoMO, while those involved in longer-term relationships had lower levels of FoMo and alcohol use.

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Modeling and optimization of epidemiological control policies through reinforcement learning

Rao et al. | May 23, 2023

Modeling and optimization of epidemiological control policies through reinforcement learning

Pandemics involve the high transmission of a disease that impacts global and local health and economic patterns. Epidemiological models help propose pandemic control strategies based on non-pharmaceutical interventions such as social distancing, curfews, and lockdowns, reducing the economic impact of these restrictions. In this research, we utilized an epidemiological Susceptible, Exposed, Infected, Recovered, Deceased (SEIRD) model – a compartmental model for virtually simulating a pandemic day by day.

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Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning

Chong et al. | May 01, 2023

Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
Image credit: Pixabay

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.

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