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This study investigated whether thiamine (vitamin B1) could mitigate the harmful effects of lead contamination on plant growth. Using garden cress (Lepidium sativum), we found that lead exposure reduced plant growth and biomass, while thiamine treatment partially alleviated these effects, improving shoot length and overall plant length. These findings highlight the potential of thiamine as a simple strategy to improve plant resilience to heavy metal stress, with implications for agricultural productivity and food security.

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.

Seeking to investigate eco-friendly biological methods to control weeds and enhance food crop yields, here the authors considered the effects of three essential oils on seed germination and radicle length of both a weed and a common crop. They found that treatment with turmeric oil had phytotoxic potential, leading to a reduction in both seed germination and radicle length of the weed. In contrast, ginger oil possessed allelopathic properties towards both. The authors suggest that essential oils could be used as eco-friendly bio-herbicides.

Using machine learning to predict the risk of algae bloom

The authors set out to develop an electrochemical device that would have efficient and sustained carbon dioxide capture.

This study investigates how bending radius, wavelength, and number of turns affect signal attenuation in single-mode optical fibers.

This study shows the efficacy of leveraging transfer learning, specifically from residual networks, to detect CVDs and possible signs of CVDs. The findings indicate that leveraging transfer learning from residual networks alongside medical professionals is a highly promising approach for CVD detection and diagnosis, warranting further investigation.

The authors looked at the immunogenicity of a newly developed pneumococcal conjugate vaccine compared to a previously developed one. They found the newly developed vaccine did elicit an immune response.

Here, seeking to explore new antimicrobial therapies, the authors investigated the antimicrobial activity of Maitake mushroom extract against Staphylococcus epidermidis, a common cause of antibiotic resistant hospital-acquired infections. They found that Maitake extract showed potent antimicrobial activity, with higher concentrations showing inhibition comparable to tetracycline.