Developing a Heart-Rate Monitoring App to Help Families in Identifying Mood Changes for Children Diagnosed With Neurodivergence
This study dives into the benefits of a heart rate (HR) monitoring application to aid families in identifying mood changes in children diagnosed with neurodivergence. Children with neurodivergence often struggle with communicating their emotions, which often results in tantrums or emotional outbursts, and this study plans to address this by creating an app that detects users’ HR to calculate heart rate variability (HRV) and detect when the user’s heart rate variability (HRV) levels become higher than usual. Heart-rate variability is defined as a small variation of the interval between every heartbeat, it’s calculated with the formula of . By looking at the developments of these small variations, it will be 60/𝐵𝑃𝑀 × 1000 easier to notice then the interval for heartbeats are shorter, meaning the body is in need of more blood pumped quickly for support. The app is connected to a heart rate sensor that is worn by the user. The heart-rate sensor frequently uploads data to the app which the app processes and carefully observes while looking for any sudden, dramatic change. The sensor and app was tested and proved to meet the expected requirements of functionality. Four participants with neurodivergence were asked to equip the heart-rate sensor and results showed that different developments of heart-rate variability were able to be detected by the app, these participants varied in their type of neurodivergence as well as their age. As an example, the third participant showed the purpose of the app most visibly, having a resting heart-rate of 86 BPM (697.67 ms) turning into a high 107 BPM (561.68ms) after changing activities. When the user’s sensor detects a sudden spike in heart-rate variability, the app notified the parent account about this change in emotion. This study has supported the relevance of using heart-rate variability to observe changes in mood.
Eradicating Cystic Fibrosis Biofilms by a Novel Non-Toxic, Multi-Pathway Salicylate Therapy
1.1. Cystic Fibrosis Biofilms Biofilms are bacterial aggregates in a matrix of polysaccharides, proteins and nucleic acids (Donlan, 2002). They account for 80% of all chronic infections and cause over 500,000 deaths annually. Cystic fibrosis (CF) is a genetic disorder characterized by mucus accumulation in the respiratory tracts (Morrison et al., 2020). This impairs mucociliary clearance, allowing chronic colonization by bacterial biofilms, leading to fatal respiratory failure, lung scarring, and necrosis of pulmonary epithelial tissues (Martin et al., 2021). 1.2. Obstacles in Current Treatments Three major therapies are used against CF biofilms: (1) aminoglycoside antibiotics like tobramycin, (2)non-aminoglycoside antibiotics such as ciprofloxacin and vancomycin, and (3) non-antibiotic therapies including flushing, chlorination, and ultraviolet disinfection. These have two major flaws. First, they are cytotoxic; 30% of patients experience acute kidney injury after three days of intravenous aminoglycoside therapy (Joyce et al., 2017). Furthermore, non-aminoglycoside therapies can cause phospholipid buildup in lysosomes of proximal tubule epithelial cells, accounting for 10-20% of acute renal failure cases. Second, antibiotic resistance due to horizontal gene transfer and mutations has significantly reduced treatment effectiveness. Therefore, cystic fibrosis biofilms remain a critical threat with few effective treatments. 1.3. Salicylate Derivatives This project tackled this issue using an innovative non-antibiotic approach with salicylate derivatives. Salicylates, a class of benzoic acids—benzene-based carboxylic acids (Figure 1)—used in painkillers and blood thinners, were investigated for their antibiofilm potential through a 3-step process: 1. Literature review: Identified three key biofilm therapeutic targets: quorum sensing, bacterial adhesion, and cell motility. Disrupting these pathways would result in biofilm eradication. 2. Molecule Identification: Recognized key molecules in each pathway: LasR, adhesins, and flagellin. Inhibiting these molecules would disrupt the pathways. 3. Screening: Found that salicylates could inhibit the identified molecules, though they had never been tested against cystic fibrosis biofilms.