The authors investigate how improper disposal of medication can be mitigated through community education efforts.

The independent effects of metastasis-promoting gene CD151 in the process of metastasis are not known. This study aimed to isolate CD151 to discover what its role in metastasis would be uninfluenced by potential interactions with other components and pathways in human cells. Results showed that CD151 significantly increased the adhesion of the cells and decreased their motility. Thus, it may be that CD151 is upregulated in cancer cells for the last step of metastasis, and it increases the chances of success of metastasis by aiding in implantation of the cancer cells. Targeting CD151 in chemotherapeutic modalities could therefore potentially slow or prevent metastasis.

Major depressive disorder (MDD) is a prevalent mood disorder. The direct causes and biological mechanisms of depression still elude understanding, though genetic factors have been implicated. This study looked to identify the mechanism behind the aberrant response to the dexamethasone suppression test (DST) displayed by MDD patients, in which they display a lack of cortisol suppression. Analysis revealed several pro-inflammatory genes that were significant and differentially expressed between affected and non-affected groups in response to the DST. Looking at ways to decrease the inflammatory response could have implications for treatment and may explain why some people treated for depression still display symptoms or may lead researchers to different classes of drugs for treatment.

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.

Uveal melanoma (UM) is a rare subtype of melanoma but the most frequent primary cancer of the eye in adults. The goal of this study was to research the genetic causes of UM through a comprehensive frequency analysis of base-pair mismatches in patient genomes. Results showed a total of 130 genetic mutations, including seven recurrent mutations, with most mutations occurring in chromosomes 3 and X. Recurrent mutations varied from 8.7% to 17.39% occurrence in the UM patient sample, with all mutations identified as missense. These findings suggest that UM is a recessive heterogeneous disease with selective homozygous mutations. Notably, this study has potential wider significance because the seven genes targeted by recurrent mutations are also involved in other cancers.

Here, the authors chose to investigate the efficacy of zinc oxide nanoparticles (ZnO NPs) and cisplatin or zinc ions in inducing cancer apoptosis. While both treatments were found to reduce the proliferation of lung cancer cells, the authors suggest that further studies to identify the mechanism are necessary.

Berberine is a natural quaternary alkaloid that has anti-microbial and anti-cancer effects. This compound can bind to Guanine Quadruplex (G4) DNA secondary complexes to help inhibit cancer cell proliferation. In this study, the authors investigate whether incorporating large aromatic rings helps to stabilize berberine-G4 interactions.

Treatments inhibiting Notch signaling pathways have been explored by researchers as a new approach for the treatment of glioblastoma tumors, which is a fast-growing and aggressive brain tumor. Recently, retinoic acid (RA) therapy, which inhibits Notch signaling, has shown a promising effect on inhibiting glioblastoma progression. RA, which is a metabolite of vitamin A, is very important in embryonic cellular development, which includes the regulation of multiple developmental processes, such as brain neurogenesis. However, high doses of RA treatment caused many side effects such as headaches, nausea, redness around the injection site, or allergic reactions. Therefore, we hypothesized that a combination treatment of RA and siRNA targeting NOTCH1 (siNOTCH1), the essential gene that activates Notch signaling, would effectively inhibit brain cancer cell proliferation. The aim of the study was to determine whether inhibiting NOTCH1 would inhibit the growth of brain cancer cells by cell viability assay. We found that the combination treatment of siNOTCH1 and RA in low concentration effectively decreased the NOTCH1 expression level compared to the individual treatments. However, the combination treatment condition significantly decreased the number of live brain cancer cells only at a low concentration of RA. We anticipate that this novel combination treatment can provide a solution to the side effects of chemotherapy.

Kadıoğlu and Oğuzalp study the synergistic effects of Metformin and Captopril, two commonly prescribed drugs for type 2 diabetes and hypertension, respectively. Using C. elegans nematodes as a model system, the authors find that the nematodes decreased in average body length when exposed to Metformin or Captopril individually, but grew 11% in body length when both drugs were used together. Because C. elegans body size is regulated in part by the TGF-β signaling pathway, the authors suggest that synergistic effects of these two drugs may be modulating TGF-β activity, a previously uncharacterized phenomenon.

Coral bleaching is a fatal process that reduces coral diversity, leads to habitat loss for marine organisms, and is a symptom of climate change. This process occurs when corals expel their symbiotic dinoflagellates, algae that photosynthesize within coral tissue providing corals with glucose. Restoration efforts have attempted to repair damaged reefs; however, there are over 360,000 square miles of coral reefs worldwide, making it challenging to target conservation efforts. Thus, predicting the likelihood of bleaching in a certain region would make it easier to allocate resources for conservation efforts. We developed a machine learning model to predict global locations at risk for coral bleaching. Data obtained from the Biological and Chemical Oceanography Data Management Office consisted of various coral bleaching events and the parameters under which the bleaching occurred. Sea surface temperature, sea surface temperature anomalies, longitude, latitude, and coral depth below the surface were the features found to be most correlated to coral bleaching. Thirty-nine machine learning models were tested to determine which one most accurately used the parameters of interest to predict the percentage of corals that would be bleached. A random forest regressor model with an R-squared value of 0.25 and a root mean squared error value of 7.91 was determined to be the best model for predicting coral bleaching. In the end, the random model had a 96% accuracy in predicting the percentage of corals that would be bleached. This prediction system can make it easier for researchers and conservationists to identify coral bleaching hotspots and properly allocate resources to prevent or mitigate bleaching events.