Schedule of Events

Microplastic contamination is a global issue that is harmful to the environment, marine life and even humans. Our study focused on the potential microplastic pollution of fish in the area of Channel Islands Harbor in Ventura County. Our method was to dissect and analyze the tissues of several fishes, Scomber japonicus (Pacific mackerel) and Atherinopsis californiensis (Jacksmelt), using a dissecting microscope and Fourier transform infrared spectroscopy (FTIR) for quantification and identification of the micro- contaminants. The previously frozen fish had been caught in May of 2024 as future lobster bait four months prior to the start of this study. Our research identified a number of microplastics found deeply embedded in the tissue walls of the fish including the presence of polyacrylamides (PAMs) in the oviduct of a female Pacific mackerel and in the G.I tract of another Pacific mackerel. This study suggests that remediation of micropollutants in the marine environment is needed to protect marine species and the humans that consume them.

Microplastic contamination of the world’s ecosystem has been documented in many studies overthe past two decades. This study focused on the possibility that microplastics could make theirway into root vegetables that are constantly in contact with the soil. The presence ofmicroplastics in root vegetables was proven using Fourier transform infrared spectroscopy onsamples collected from three, organically grown, root vegetables from various sources. Thisstudy strongly suggests the prevalence of micro-contaminants in a common component of thehuman diet. The spectra were compared with a commercial library of standards from AgilentTechnologies. Peaks were assigned for functional group recognition. These spectra matchedmaterials such as alginic acid, polystyrene, fiberglass, and butadiene rubber. Anthropogeniccontamination of these food groups could signify a major cause of disease now and in the future.

Studying the structure and function of oxidized microplastics is vital to correctly identifying them in their oxidized form in the environment (beach, ocean, etc.). The current limitation of microplastic analysis is that FT IR Spectroscopy reference libraries only show the unoxidized form of these plastics, making it challenging to identify aged and weathered plastics. This study aimed to bridge that gap by creating a library of artificially oxidized polymers. We hypothesized that exposure to UV light would induce oxidative changes in the microplastics, leading to the addition of peaks in their FT IR spectra. First, we established a baseline of the three most commonly found plastics in nature–polypropylene (PP), polyethylene (PE), and polystyrene (PS)–and confirmed their spectra to current reference libraries. The samples were then subjected to three separate oxidation techniques: heat, UV, and an electrophoresis salt solution. We then took weekly scans of each sample and analyzed changes in their spectra. Our results indicate that oxidation introduced new spectra peaks and shifts, specifically adding a 1700 cm-1 carbonyl functional group. We then hypothesized an oxidation mechanism for the three plastic structures. The development of this FT IR reference library for oxidized microplastics will benefit the field-based identification research of microplastics. This has implications for our understanding of identifying which microplastics are in nature and their true origins. This study impacts further understanding of microplastic degradation pathways and improves analytical methods for environmental research.

The presence of microplastics in the environment has become an increasing concern, mainly in regions where coastal and agricultural activities contribute to contamination. This study investigates and compares the impact and extent of microplastic and microfiber pollution in two different locations.  We choose to compare the Channel Islands Harbor, a center for recreational and commercial maritime activity and the Santa Clara Riverbed, which passes through farmland right before draining into the Pacific Ocean near the Ventura Harbor.   Our goal in examining sand sediment from the two sites is to identify the quantities and type of the micro contaminants found.
    Sediment samples were collected at high tides at both sites using Rose Bengal stain to differentiate between synthetic and organic microfibers.  Samples were then vacuum filtered to isolate the contaminants and analyzed with a Nikon dissecting microscope and Fourier transform infrared spectroscopy.
    Initial results indicate that there is a greater concentration of microplastics in the Santa Clara Riverbed, suggesting that they are likely brought in by irrigation systems, textile waste, and agricultural runoff. In contrast, microfiber contamination was more prevalent in the Channel Islands Harbor, potentially due to boating activity, urban runoff and marine infrastructure. The findings draw attention to the different sources of pollution that impact inland river systems as opposed to coastal ones, highlighting the necessity of more studies to create efficient mitigation plans and legislative actions.

Microplastic contamination is truly an escalating environmental concern, specifically in sedimentary environments where accumulation raises risks to marine ecosystems and human health. Traditional methods for extracting microplastics, as well as microfibers, from sand sediments include mixing the sand with artificial seawater at a salinity of 35 ppt (3.5% NaCl), and then by decanting the supernatant onto filter paper. The saltwater helps with buoyancy, allowing the microplastics to remain suspended after mixing. However, it is not very convenient and improving efficiency and scalability in microplastic extraction remains a challenge. This study aims to use sand sediment samples extracted from the estuary of the Santa Clara riverbed that empties into the Pacific Ocean. We plan to compare different extraction methods for retrieving microplastics from sand sediments optimizing the microfibers/microplastic extraction by testing three different solutions, deionized (DI) water, 3.5% NaCl, and a 2% sodium dodecyl sulfate (SDS) against two agitation techniques: mechanical stirring and vibrational energy. We hypothesize that SDS, because of its ability to interact with hydrophobic particles, will enhance microplastic recovery compared to NaCl and DI water. Also, we explore vibrational energy as an alternative to stirring by using a standard laboratory vortexer. If vibrational extraction demonstrates comparable or superior efficiency, scaling up sediment processing using vibrational energy is possible. Fourier Transform Infrared (FTIR) spectroscopy will be used for polymer identification after filtering. Our results aim to optimize microplastic recovery techniques, providing a finding for more effective sediment contamination assessments and potential large-scale investigations.

Immunity is plastic and varies with many internal and external factors, including sex. Immunity can be lower in males than females, potentially due to differences in circulating immunomodulatory hormones. However, sex-specific differences in immunity remain poorly understood in juvenile wild birds. Avian malaria has negatively affected many endemic Hawaiian songbirds, but the Hawaii Amakihi is one of the only native species with tolerance to the disease. Increased tolerance may be related to increased immunity because Amakihi populations with greater tolerance of avian malaria have higher levels of some measures of innate immunity.  Sex-specific differences in immunity could have important implications for individual susceptibility to infection. However, these relationships between immunity and sex remain wholly unexplored in juvenile Amakihi. The goal of our project was to determine whether immunity varies by sex in juvenile Amakihi. We hypothesized that females would have greater immunity than males due to differences in immunomodulatory hormones. To test this hypothesis, we collected blood samples from free-living juvenile Amakihi for molecular sexing and to measure innate immunity and circulating prolactin. In support of our hypothesis, the number of WBCs was significantly higher in females than males (p = 0.0375), while no sex-specific differences were observed for agglutination (p = 0.629). Prolactin levels tended to be higher in females than males (p = 0.206) and correlated positively with number of WBCs (p = 0.317), but these results were not statistically significant, suggesting that prolactin is unlikely to be the mechanism directly mediating differences in WBCs across sex.

Microplastics are pervasive environmental pollutants that often go unnoticed due to their small size. Traditional extraction methods from sand or soil sediment involve creating a slurry in a 3.5% salt solution, allowing sediments to settle while keeping microplastics suspended. The supernatant is then decanted onto a filter to collect contaminants for analysis.
This study presents a novel extraction method using electrolysis in a solution of sand, water, and 0.04% sodium dodecyl sulfate (SDS). SDS facilitates microplastic binding and migration through an electric field. Sand sediment samples were collected from the Santa Clara Riverbed. A slurry of sand, water and SDS solution was placed in the well associated with the negative electrode of an electrophoresis box. The box was then filled with buffer solution, and electrolysis was conducted at 100 volts for 30 minutes. Afterward, the aqueous solution near the positive electrode was removed and filtered.
Results were compared to the traditional decanting method using sand from the same location. The electrolysis method extracted significantly more microplastics than the conventional approach.
 

Reinforcement learning, specifically DQN models, have been created to play games from the 1970s and 1980s, such as Space Invaders (Mnih et al., 2013). This study attempts to create a DQN model to play the game of Tetris and reach a score of at least 1 million points. In this model, the Q-learning algorithm was used in tandem with a deep neural network to maximize the rewards, in this case points, obtained from interacting with the Tetris environment. Every time a new piece was chosen by a randomizer, the agent chose an action to take by ranking all possible moves based on the rewards gained from the resulting state observation. This was done by passing all state observations through a neural network with two hidden layers each with 42 artificial neurons and comparing the ranks from the single node output layer. Each state observation consists of five features which describe the maximum height reached on the board, the minimum height on the board, the number of holes between placed pieces, the number of filled rows, and the difference in adjacent column heights. After successive training sessions and iterative adjustments to gamma and to other learning constants, training stopped at a loss of 185 and a high score of 5.265 billion points, played in real time with the use of the hold move, where a secondary piece is evaluated alongside the main piece. Results suggest that the agent gained a fundamental understanding of the complexities of Tetris, mirroring other studies’ results.