Model organisms like Homo sapiens, Drosophila, and E. coli, while useful to various fields of study, present a problem to the scientific community: many other organisms’ proteins, metabolic processes, and biochemical mechanisms are not as well understood by comparison. Pocillopora damicornis (Pdam), like many other coral organisms, faces environmental stresses and threats to its survival in ocean ecosystems with limited understanding of its biochemical mechanisms, making it difficult to help preserve. However, upon analyzing the symbiotic relationship of Pdam and photosynthetic algae, it was reasoned that the coral organism is capable of detecting light. Following up with results of prior bioinformatics analysis courtesy of Kumar, L., Klein-Seetharaman, J., Et. Al, it was proposed that light sensitive proteins in corals are the following four candidates: 2270, 12246, 629, 19775. If chromophores form and their opsin shifts can be visualized in the case in any of the coral candidate opsin genes, it supports the hypothesis that the proteins are indeed a light sensitive opsin protein. If a light sensitive opsin protein is identified, it provides a direction by which efforts can be directed towards to understand corals at the biochemical level for their preservation in the face of unprecedented threats to sustainability.
Alzheimer’s disease (AD) is a common neurodegenerative disorder affecting approximately 10% of people aged 65 and up and 30-50% over 85. In pathological AD representations, a way to recognize early onset AD is the increased levels of pro-NGF in BFCNs that come from the downregulation of NGF with age. Pro-NGF has a higher affinity for p75NTR, which binds and participates in the pro-NGF-p75NTR-sortilin complex sequentially cleaved by α- and γ-secretase. Pro-NGF triggers apoptosis through the cleavage of the intracellular membrane by γ-secretase. Since γ-secretase physically cleaves off the intramembrane portion that promotes TNF- and Fas-dependent apoptotic signaling pathways, it has a crucial role in AD and must be better understood. This research aims to understand better and visualize γ-secretase and its actions, specifically with its interactions with the substrate p75NTR in the RIP process. To analyze γ-secretase function, the proteins must be produced and analyzed through the protein expression protocol. During protein production, DNA, cell concentrations, and optical density measurements were difficult to produce due to the incompetency of e. coli cells (DH5α), contamination of the Sf9 insect cell culture, and decreased viability of aged insect cells. We identified the problems and improved the conditions for future project development.
Ketone levels give an insight into the bodies metabolism. People with epilepsy or people dieting may want to keep their levels high, whereas type one diabetics or those recovering from eating disorders may want to keep their levels low. Current ketone detection methods involve blood samples or urinalysis. A ketone (acetone) biosensor was fabricated to detect levels in human breath, providing a noninvasive way to quickly and accurately detect ketone levels in the body.
The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
Energy Expenditure (EE) (kcal/day) is a key parameter used to guide obesity treatment, and it is often measured from CO2 production, VCO2 (mL/min), and/or O2 consumption, VO2 (mL/min) through the principles of indirect calorimetry. Current EE measurement technologies are limited due to the requirement of wearable facial accessories, which can introduce errors as measurements are not taken under free-living conditions. A novel contactless system, the SmartPad, which measures EE via VCO2 from a room’s ambient CO2 concentration transients was evaluated. First, SmartPad accuracy was validated by comparing the SmartPad’s EE and VCO2 measurements with the measurements of a reference instrument, the MGC Ultima CPXTM, in a cross-sectional study consisting of 20 subjects. A high correlation between the SmartPad’s EE and VCO2 measurements and the MGC Ultima CPX’s EE and VCO2 measurements was found, and the Bland-Altman plots contained a low mean bias for EE and VCO2 measurements. Thus, the SmartPad was validated as being accurate for VCO2 and EE measurements. Next, resting EE (REE) and exercise VCO2 measurements were recorded using the SmartPad and the MGC Ultima CPXTM at different operating CO2 threshold ranges to investigate the influence of measurement duration on system accuracy in an effort to optimize the SmartPad system. The SmartPad displayed 90% accuracy (±1 SD) for 14–19 min of REE measurement and for 4.8–7.0 min of exercise, using a known room’s air exchange rate. Additionally, the SmartPad was validated by accurately measuring subjects’ REE across a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m^2) with REEs ranging from ~1200 to ~3000 kcal/day. Lastly, the SmartPad has been used to assess the physical fitness of subjects via the “Contactless Thermodynamic Efficiency Test” (CTET).
First, a simple detection paradigm based on reflectance interferometry is developed. This method is simple, low cost and can be easily applied for protein array detection.
Second, a label-free charge sensitive optical detection (CSOD) technique is developed for detecting of both large and small molecules. The technique is based on that most molecules relevant to biomedical research and applications are charged or partially charged. An optical fiber is dipped into the well of a microplate. It detects the surface charge of the fiber, which does not decrease with the size (mass) of the molecule, making it particularly attractive for studying small molecules.
Third, a method for mechanically amplification detection of molecular interactions (MADMI) is developed. It provides quantitative analysis of small molecules interaction with membrane proteins in intact cells. The interactions are monitored by detecting a mechanical deformation in the membrane induced by the molecular interactions. With this novel method small molecules and membrane proteins interaction in the intact cells can be detected. This new paradigm provides mechanical amplification of small interaction signals, allowing us to measure the binding kinetics of both large and small molecules with membrane proteins, and to analyze heterogeneous nature of the binding kinetics between different cells, and different regions of a single cell.
Last, by tracking the cell membrane edge deformation, binding caused downstream event – granule secretory has been measured. This method focuses on the plasma membrane change when granules fuse with the cell. The fusion of granules increases the plasma membrane area and thus the cell edge expands. The expansion is localized at the vesicle release location. Granule size was calculated based on measured edge expansion. The membrane deformation due to the granule release is real-time monitored by this method.
