By: Lucas Song, Palo Alto High School

Low carbohydrate diets (LCD) have gained support for their monumental benefits, but their role in managing type 2 diabetes (T2D) is undetermined. This study uses a systematic review and meta-analysis to outline and assess the impact of low carbohydrate diets on diabetes remission, measured through HbA1c (hemoglobin A1C), and to determine if the maximum carbohydrate intake threshold impacts the efficacy of the diet.

By: Vansh Agrawal, Ardsley High School

Leukemia is a blood cancer that disrupts white blood cell production and can increase risks of infection, anemia, clotting, and stroke. However, there is limited large-scale research on how stroke treatment and outcomes differ in patients with leukemia. We analyzed National Inpatient Sample data from 2015–2022, including 3.8 million adult hospitalizations for acute ischemic stroke (AIS), of which 14,770 involved leukemia. After statistical weighting to balance demographics, we compared vascular risk factors, use of intravenous thrombolysis (IVT) and endovascular thrombectomy (EVT), complications, and discharge outcomes. Compared with other AIS patients, those with leukemia were less likely to have traditional stroke risk factors such as hypertension, diabetes, or smoking history. They were also less likely to receive IVT or EVT, likely due to concerns about bleeding risk. Despite differences in risk profiles and lower use of reperfusion therapies, leukemia patients had similar in-hospital survival and were more often discharged home rather than to a nursing facility. These findings suggest leukemia-associated stroke requires individualized risk–benefit assessment and may benefit from tailored treatment strategies.

By: Srishanth Ravi, Thomas Jefferson High School for Science and Technology

Ischemic stroke causes irreversible brain injury within minutes due to rapid metabolic failure and excitotoxic damage, yet current hypothermia-based neuroprotection methods are invasive, slow, or impractical in prehospital settings. This study investigated whether a portable, noninvasive thermoelectric neck patch could rapidly and safely induce targeted carotid artery cooling sufficient for neuroprotective hypothermia. A Peltier-based cooling patch was engineered and tested on a biomimetic phantom simulating skin, subcutaneous fat, muscle, and a perfused carotid artery at physiological flow, with temperature sensors embedded at multiple depths to quantify cooling dynamics. Patch application reduced arterial temperature to 31.9 °C within 15 minutes (0.334 °C/min), demonstrating effective cooling at clinically relevant depths. A fluorescence-based stroke simulation using the pH- and temperature-sensitive dye fluorescein validated hypothermic protection: at 32 °C, fluorescence decay was significantly slower than at 37 °C, indicating reduced biochemical degradation. Three-dimensional heat transfer modeling using Pennes’ bioheat equation with layered tissue properties closely matched experimental data, and cerebral metabolic rate modeling predicted a 33.1% reduction in oxygen demand. Together, these findings demonstrate rapid, selective carotid cooling and support a low-cost, noninvasive strategy for accelerated prehospital stroke intervention.

By: Aiden Chiu, Stuyvesant High School

Breast fine needle aspiration (FNA) is a minimally invasive, cost-effective method for evaluating breast lesions, but slide interpretation is subjective, leading to variable diagnoses. This study assessed inter-observer agreement in 116 de-identified breast FNA slides reviewed independently by three board-certified pathologists blinded to clinical and radiographic information. Slides were classified as nondiagnostic, negative, atypical, suspicious, or positive for carcinoma. Agreement was measured using Cohen’s kappa (κ), and key cytologic features—architectural disarray, nuclear membrane irregularity, single atypical cells, and myoepithelial cells—were analyzed for their effect on consistency. Results showed good agreement for positive carcinoma (κ≈0.60), fair agreement for negative cases (κ≈0.30), and low agreement for atypical or suspicious slides (κ≈0.11–0.20). Architectural disarray and nuclear membrane irregularity improved concordance, while single atypical cells and myoepithelial cells increased variability. These findings highlight the reproducibility of definitive diagnoses and the challenges of indeterminate cases, suggesting that combining cytology with clinical context and informatics-driven analysis can enhance diagnostic reliability and patient care.

By: Michelle Zhang, Walnut High School

Recurrent pregnancy loss (RPL) is a health condition that threatens the well-being of women. It is a condition where a woman experiences two or more consecutive pregnancy losses, often attributed to chromosomal aberrations. This study focused on assessing chromosomal abnormalities using a retrospective cohort approach. The sample size was 500 couples, consisting of 300 with a documented history of RPL and 200 with age-matched controls. Next-generation sequencing and karyotyping were used to assess the abnormalities in the collected blood and tissue samples. Basic descriptive analyses were performed to describe participants and their clinical profiles. The relationship between RPL risks and other specific chromosomal anomalies was conducted using chi-square tests and logistic regression. The findings indicated that 40% of cases in the test group had chromosomal abnormalities compared to 5% of the control group. Significant RPL risk was reported to be linked more with translocations and inversions.

By: Nidhi Veerendra, Downingtown STEM Academy

This research paper is related to health data analytics in predicting the prevalence of diabetes using machine learning models. Through publicly-available health datasets, it is clear that trends in demographics, lifestyle factors, and medical history play a significant role in influencing diabetes risk. This paper also explores an original interactive dashboard visualizing health data trends and forecasted future diabetes prevalence to inform healthcare providers and policymakers in the efficient use of their resources. Through the work, it is seen that machine learning could be integrated with public health data to improve disease prevention and management strategies.

**This paper ranked among the top 20 papers out of 300 participants in Camp BioMedizone 2024

By: Allison Yee, Mount Hebron High School

The underlying cause of hospital patients being at risk for dangers is the lack of sleep medical workers receive daily. The research goes deep into the science of the cause, following the numbers go up, suggesting that the lack of sleep on the workers' end is dangerous for both the patients and themselves as it leads to poor cognitive function, and can lead to accidents in the workplace. The reason that it is essential to address sleep deprivation specifically in hospitals is because many health risks are being exposed there where patients are already vulnerable, and this issue can be dealt with, not adding it onto the pile.

By: Carys Doyle, Penncrest High School

For my study, I examined the effects of external academic pressures on the mental health of high school students in the United States. I analyzed three common pressure groups: teachers, parents, and peers. To do this, I released a questionnaire to students at a 9-12 United States high school and then analyzed the correlations between their levels of perceived pressure and their mental health status. At the conclusion of my study, although not statistically significant, I found that as external academic pressure increases, the mental health of high school students decreases.

By: Kavi Seidman, Venice Senior High School

This study investigates the impact of light pollution on personality traits such as humility, groundedness, and ego among individuals who grew up in different lighting environments in California specifically. Using a survey-based approach, data were collected from individuals who spent their formative years in either the highly light-polluted environment of Los Angeles or the relatively low-light environment of the Greater Palm Springs area. The results indicate that individuals from areas with high light pollution demonstrate higher levels of egoistic traits and lower levels of humility and groundedness. On the opposite, those from areas with low light pollution tend to display higher levels of humility and groundedness. These findings suggest that environmental factors, such as light pollution, could play a very significant role in shaping personality development, highlighting the need for urban planning that considers psychological as well as ecological impacts.