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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).

Tertiary lymphoid structures (TLS) are lymph node-like structures that form at sites of inflammation, and their presence in cancer patients is predictive of a better clinical outcome. One significant obstacle to TLS formation is reduced immune cell infiltration into the tumor microenvironment (TME). Recent studies have shown that vasculature normalizing (VN) agents may override this defect to improve tissue perfusion and increased immune cell entry into the TME. However, their effects on immune cell and tumor cell phenotype remain understudied. Here the authors investigate whether treating tumor cells with VN would reduce their immunosuppressive phenotype and promote production of chemokine that recruit immune cells and foster TLS formation.

The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.

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.

AI analysis of brain scans offers promise for helping doctors diagnose brain tumors. Haider and Drosis explore this field by developing machine learning models that classify brain scans as "cancer" or "non-cancer" diagnoses.

The authors looked at ways that seizures in patients with glioblastoma could be treated using C. elegans as a model system.

With herbal plants providing an address to the adverse effects of oxidative stress found within the body, the authors of this article develop and assess a novel compound (“MAT20”) that blends three herbal plants for optimal oxidative stress relief.

In this study, the authors tested different approaches for removing arsenic from rice. Due to higher arsenic levels in water, some areas grow rice with higher levels as well. This is a health hazard and so developing methods to remove arsenic from the rice will be helpful to many. Using a rapid arsenic kit, the authors found that activated charcoal was the most effective at removing arsenic from rice.

Here the authors investigated the effectiveness of algal pretreatment in reducing nitrate toxicity and extending the survival of fish in contaminated river water. Their findings demonstrate that treating nitrate-polluted water with algae extended fish survival by up to 50%, suggesting that algae could serve as a valuable tool for mitigating the destructive impacts of agricultural and industrial runoff on aquatic ecosystems.

Here the authors investigate the relationship between environmental pollutants and cancer incidence rates across various geographical clusters in the United States from 2018 to 2020. By calculating Pearson correlation coefficients and t-statistics on CDC and EPA data, they demonstrated a strong correlation between specific pollutants and various cancers, offering insights that could help explain regional disparities in cancer rates and aid in preventing premature deaths.