Theoretical Model for a Highly Sensitive Near Infrared Biosensor Based on Bloch Surface Wave with Dirac Semimetal

Synergistic antibacterial attributes of copper-doped polydopamine nanoparticles: an insight into photothermal enhanced antibacterial efficacy

Antibiotic-resistant bacteria and associated infectious diseases pose a grave threat to human health. The antibacterial activity of metal nanoparticles has been extensively utilized in several biomedical applications, showing that they can effectively inhibit the growth of various bacteria. In this research, copper-doped polydopamine nanoparticles (Cu@PDA NPs) were synthesized through an economical process employing deionized water and ethanol as a solvent. By harnessing the high photothermal conversion efficiency of polydopamine nanoparticles (PDA NPs) and the inherent antibacterial attributes of copper ions, we engineered nanoparticles with enhanced antibacterial characteristics. Cu@PDA NPs exhibited a rougher surface and a higher zeta potential in comparison to PDA NPs, and both demonstrated remarkable photothermal conversion efficiency. Comprehensive antibacterial evaluations substantiated the superior efficacy of Cu@PDA NPs attributable to their copper content. These readily prepared nano-antibacterial materials exhibit substantial potential in infection prevention and treatment, owing to their synergistic combination of photothermal and spectral antibacterial features.

Subdividing Stress Groups into Eustress and Distress Groups Using Laterality Index Calculated from Brain Hemodynamic Response

A stress group should be subdivided into eustress (low-stress) and distress (high-stress) groups to better evaluate personal cognitive abilities and mental/physical health. However, it is challenging because of the inconsistent pattern in brain activation. We aimed to ascertain the necessity of subdividing the stress groups. The stress group was screened by salivary alpha-amylase (sAA) and then, the brain’s hemodynamic reactions were measured by functional near-infrared spectroscopy (fNIRS) based on the near-infrared biosensor. We compared the two stress subgroups categorized by sAA using a newly designed emotional stimulus-response paradigm with an international affective picture system (IAPS) to enhance hemodynamic signals induced by the target effect. We calculated the laterality index for stress (LIS) from the measured signals to identify the dominantly activated cortex in both the subgroups. Both the stress groups exhibited brain activity in the right frontal cortex. Specifically, the eustress group exhibited the largest brain activity, whereas the distress group exhibited recessive brain activity, regardless of positive or negative stimuli. LIS values were larger in the order of the eustress, control, and distress groups; this indicates that the stress group can be divided into eustress and distress groups. We built a foundation for subdividing stress groups into eustress and distress groups using fNIRS.