The authors investigated prophages present in Streptococcus bacteria that may increase their survival in different environments.
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DNA-SEnet: A convolutional neural network for classifying DNA-asthma associations
In this study, the authors developed a model named DNA Sequence Embedding Network (DNA-SEnet) to classify DNA-asthma associations using their genomic patterns.
Read More...Mapping QTLs for Popping Ability in a Popcorn × Dent Maize Genetic Cross
Have you ever wondered what contributes to the popping ability of popcorn? In this study, the authors use Quantitative Trait Locus (QTL) mapping to identify genes that may contribute to specific popping characteristics including kernel size and popping expansion volume (PEV).
Read More...A Phylogenetic Study of Conifers Describes Their Evolutionary Relationships and Reveals Potential Explanations for Current Distribution Patterns
Many species of trees are distributed widely around the world, though not always in a way that makes immediate sense. The authors here use genetic information to help explain the geographic distribution of various conifer species throughout the world.
Read More...Lack of correlation between odor composition and neuron response in the olfactory cortex of mice
To address whether odor sensory circuits are organized topographically, the authors investigate whether the neuronal responses to similar odors amongst different mice mapped similarly in brain.
Read More...Testing Different Polymers and Boron Nitride Nanotube Properties in Fabrication of Ion-selective Membranes
One largely untapped source of clean energy is the use of osmotic gradients where freshwater and saltwater are mixed, for example at estuaries. To harness such energy, charge-selective membranes are needed to separate the anions and cations in saltwater, establishing an electric potential like a battery. The objective of this study was twofold: to investigate the creation of the polymer matrix and test the properties of boron nitride nanotubes, as both are essential in the creation of an ion-selective membrane. Out of three polymer samples tested in this study, the mixture known as Soltech 704 showed the best resistance to etching, as well as the highest UV cure rate.
Read More...Characterization of Drought Tolerance in Arabidopsis Mutant fry1-6
In a world where water shortage is becoming an increasing concern, and where population increase seems inevitable, food shortage is an overwhelming concern for many. In this paper, the authors aim to characterize a drought-resistant strain of A. thaliana, investigating the cause for its water resistance. These and similar studies help us learn how plants could be engineered to improve their ability to flourish in a changing climate.
Read More...Cathodal Galvanotaxis: The Effect of Voltage on the distribution of Tetrahymena pyriformis
The surface of the unicellular eukaryote, Tetrahymena pyriformis, is covered with thousands of hair-like cilia. These cilia are very similar to cilia of the human olfactory and respiratory tracts making them model organisms for studying cilia function and pathology. The authors of this study investigated the effect of voltage on T. pyriformis galvanotaxis, the movement towards an electrical stimulus. They observed galvanotaxis towards the cathode at voltages over 4V which plateau, indicating opening of voltage gated-ion channels to trigger movement.
Read More...Are Age and Sex Related to Emotion Recognition Ability in Children and Teenagers?
Humans have a natural ability to recognize emotional cues from the facial expressions of others, as a crucial evolutionary trait to navigate social interactions. This ability likely develops through normal development and social experience, but it is unclear how much influence age and sex have in emotional facial recognition (EFR). In this study, the authors investigate EFR in children and teenagers, and look at whether accurate emotional recognition does occur more in males or females.
Read More...Predicting baseball pitcher efficacy using physical pitch characteristics
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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