This study aimed to determine whether the life cycle stages, or phenophases, of some plants in the urban environment of Central Park, New York, differ from the typical phenophases of the same plant species. The authors hypothesized that the phenophases of the thirteen plants we studied would differ from their typical phenophases due to the urban heat island effect. Although the phenophases of five plants matched up with typical trends, there were distinct changes in the phenophases of the other eight, possibly resulting from the urban heat island effect.

Previously established data indicate that cemeteries have contributed to groundwater and soil pollution, as embalming fluids can impact the microbiomes that exist in decomposing remains. In this study, Caputo et al hypothesized that microbial variation would be high between cemeteries from different eras due to dissimilarities between embalming techniques employed, and furthermore, that specific microbes would act as an indication for certain contaminants. Overall, they found that there is a variation in the microbiomes of the different eras’ cemeteries according to the concentrations of the phyla and their more specific taxa.

Cardiac autonomic and structural changes may occur in temporal lobe epilepsy patients and contribute to the risk of sudden unexpected death in epilepsy patients. Choi and colleagues reviewed clinical charts to obtain patients’ lifetime seizure count, antiepileptic drug use, and history of heart disease, followed by transthoracic echocardiogram to calculate left ventricle dimensions, ejection fraction, and left ventricle mass. By comparing epilepsy patients to control subjects, they found that epilepsy patients had thinner left ventricle walls and smaller ejection fraction, but with no significant difference in left ventricle mass.

In this study, the authors investigate the anti-cancer effects of Annona Reticulata (Ramphal or custard apple) by testing whether its extract could inhibit HeLa cell viability.

Palermo et al. examined the effect of group size on drinking habits of college and high school students. The authors found that both high school and college students tended to consume the most alcohol in group sizes of 4 or more, independent of how frequently they drink. They also found that the proportion of college students that drink is nearly twice the proportion of high school students that drink. This study supports previous findings that underage drinking happens in large groups and suggests that effective intervention in underage drinking would be at the group level.

Minerals such as iron are essential for life, but too much of a good thing can be poisonous. Here the authors investigate the effect of iron concentrations on the growth of an aquatic plant and find that supplementing small amounts of iron can help, but adding too much can be bad for the plant. These results should help inform decisions on allowable iron concentrations in the environment, aquatic farming, and even home aquariums.

A common form of Acne is caused by a species of bacterium called Cutibacterium acnes. By using a predictive algorithm and structural analysis, the authors identified 5 small molecules with high affinity to growth factors in Catibacterium acnes. This has potential implications for supplemental skincare products.

Agenesis of the Corpus Callosum (ACC) is a birth defect where an infant’s corpus callosum, the structure linking the brain’s two hemispheres to allow interhemispheric communication, fails to develop in a typical manner during pregnancy. Existing research on the connection between ACC and epilepsy leaves significant gaps, due to the lack of focused investigation. One important gap is the degree to which ACC may impact the course of epilepsy treatment and outcomes. The present study was conducted to test the hypotheses that epilepsy is highly prevalent among individuals with ACC, and that those with both ACC and epilepsy have a lower response rate to anticonvulsant drugs than other patients treated with anticonvulsant drugs. A weighted average of epilepsy rates was calculated from a review of existing literature, which supported the hypothesis that epilepsy was more common among individuals with ACC (25.11%) than in the general population (1.2%). An empirical survey administered to 57 subjects or parents of subjects showed that rate of intractable epilepsy among study subjects with both ACC and epilepsy was substantially higher than the rate found in the general population, indicating that individuals with both conditions had a lower response rate to the anticonvulsant drugs. This study contributes novel results regarding the potential for concurrence of ACC and epilepsy to interfere with anticonvulsant drug treatment. We also discuss implications for how medical professionals may use the findings of this study to add depth to their treatment decisions.

According to the World Health Organization, cancer is a leading cause of death globally. The disease’s prevalence is rapidly increasing in association with factors including the increased use of pesticides and herbicides, such as glyphosate, which is one of the most widely used herbicide ingredients. Natural antioxidants and phytochemicals are being tested as anti-cancer agents due to their antiproliferative, antioxidative, and pro-apoptotic properties. Thus, we aimed to investigate the potential role of S. amara extract as a therapeutic agent against glyphosate-induced toxicity and tumor-like morphologies in regenerating and homeostatic planaria (Dugesia dorotocephala).

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.