PRESENTERS

Department of Biological, Human, and Life Sciences

The in-silico and in-vitro characterization of epigenetic drugs (BET Pathway Targets) on a colorectal cancer cell line

Members of the bromodomain and extra-terminal domain (BET) family can lead to the overexpression of oncogenes (Shorstova et al., 2021). These include BRD2, BRD3, BRD4, and BRDT, with BRD4 being the most prominent protein (Shorstova et al., 2021). BET inhibitors (BETi), moderately reduce colorectal cancer cell (CRC) proliferation and MYC expression when used in monotherapy (Ma et al., 2016). This study aims to determine potential BETi in colorectal cancer (in silico) and to identify the effects of these drugs on CRC (in vitro). While prior studies have studied BETi in other cancer types, few studies focus on colorectal cancer, the third-most common cause of cancer deaths in the United States (The American Cancer Society medical and editorial content team, 2022). Therefore, using BETi as a therapeutic option for colorectal cancer could reduce mortality rates. JQ1, an extra terminal BET protein inhibitor that suppresses tumor progression, will be the control for the research to test computational programs and experimental molecules (Wen et al., 2020). The molecules found on PubChem will be converted into a numerical format, chemical fingerprints, and used with unsupervised learning algorithms (Sydow et al., 2019) to assess the molecules’ similarity to each other and JQ1. Once the molecules have been clustered, a few will be chosen and run through the respective programs, Autodock Vina (Trott et al., 2010) and Rxdock (Ruiz-Carmona et al., 2014). The drugs found to have the greatest binding affinity to BRD4 will then be computationally tested on colon cancer cells using DeepCDR (Liu et al, 2020). The proteins affected by JQ1, such as BRD4, will be used as a positive control/comparison to test untested drugs in the context of colorectal cancer. The proteins will be knockdown using siRNA. These drugs will then be ordered or synthesized and tested on colorectal cancer cells in different concentrations to measure their effects through procedures including MTT (Freimoser et al, 1999) and qPCR (Mullis, 1985) to measure cell viability and gene expression levels.

RESEARCHERS: Aanya B., Presentation High School '25; Michelle G., American High School '26; Shivali P., California High School '24

ADVISOR: Cunha, Cancer Research and Biological Sciences

KEYWORDS: Tissue Culture | Cancer | Molecular Biology | Pre-Clinical | Epigenetic

Department of Computer Science & Engineering

Using Autonomous Drones for Terrain Mapping and Route Creation and Optimization to Enhance Search and Rescue Operations

The proliferation of drones has revolutionized operations like photography, surveillance, and notably, search and rescue missions. As drone reliance surges, especially in challenging wilderness environments, the integration of autonomous drones emerges as a viable solution. In search and rescue, real-time terrain mapping becomes crucial due to changing landscapes after disasters. Furthermore, modernizing search techniques through real-time data and machine learning accelerates victim localization, significantly improving overall efficiency. Thus creating fast and reliable route creation, hugely important as it provides rescuers different ways based on sets of parameters to reach the victim.Here, we will explore how drones overcome challenges in conventional methods, highlighting their role in addressing diverse operational needs, as well as our current progress and how we are aiming to enhance search and rescue missions. 

RESEARCHERS: Aarsh M., The Quarry Lane School '25; Aarya A., Foothill High School '24; Tarun M., '24; Aryav D., Mission San Jose High School '25

ADVISOR: McMahan, Quantum Computing & Computer Science 

KEYWORDS: Terrain Mapping | YOLO | CNN | LiDAR | SLAM | A* | Dijkstra

Department of Biological, Human, and Life Sciences

PersonalityGPT: Bridging Communication Gaps Across Diverse Personalities Using AI

In the realm of AI-driven communication, PersonalityGPT is a groundbreaking solution that leveraging the influential Big Five personality traits to bridge communication gaps across diverse personality types. This innovative model integrates with users' emotional states, aided by sentient AI components, enhancing empathy and understanding. By seamlessly adapting its responses to different personality types, the model provides more authentic and meaningful conversations. Furthermore, the integration of sentient AI components amplifies its empathetic capabilities, enabling it to gauge and respond to nuanced emotional states, thereby fostering a deeper understanding of users' mental health, a field that is becoming evermore important.

RESEARCHERS: Ayush P., Irvington High School '26; Rishabh S., Mission San Jose High School '26; Ishan R., Monte Vista High School '24;  Rini Jain, Dublin High School '26,

ADVISOR: Jahanikia, Life Sciences, Neuroimaging, Psychology & Bioinformatics

KEYWORDS: Big 5 Personality Traits | LLMs | Sentient AI | Mental Health

Department of Computer Science & Engineering

Mapping Terrain with Autonomous Drones

RESEARCHERS: Andrew D., Leland High School '26; Aditya K., Skyline High School (WA) '25

ADVISOR: McMahan, Quantum Computing & Computer Science 

KEYWORDS: Autonomous Drones | Mapping | Cartography 

Department of Chemistry, Biochemistry, and Physics

Progress towards the total synthesis of Sporovexin A

RESEARCHERS: Allen K., Gunn High School '25

ADVISOR: Njoo, Organic Chemistry

KEYWORDS: Cancer Biology | Drug Research | Sporovexin A 

Department of Biological, Human, and Life Sciences

The Effects of Arbuscular Mycorrhizal Fungi on the Growth of Apium Graveolens

Arbuscular Mycorrhizal Fungi are obligate biotrophs, meaning they extract nutrients solely from living plant tissues and cannot grow apart from their hosts (Besemer, 2021). AMF also are symbionts; they are able to form a mutualistic relationship with plants (Tracey Besemer, 2021). To find the ideal amount of fungus that accelerated plant growth, research was conducted on Golden Self-Blanching Celery seeds, also known as ​​Apium graveolens. The hypothesis states that the celery plants with AMF would exhibit more growth than the control because AMF can aid in reducing fertilizer amounts that cause pollution and conserve water during droughts in the future. The experiment was conducted in bins with equal amounts of soil and differing quantities of AMF. The results showed that the control group without any AMF grew the best due to a multitude of reasons such as the altering amounts of water during the experiment and a lack of natural sunlight. One goal for future experiments is to control confounding factors that can inhibit or improve the growth of the Golden Self-Blanching Celery plant.  

RESEARCHERS: Krisa D., Mission San Jose High School '26; Maitreyee P., Las Lomas High School '25; Shrinidhi P., Foothill High School '24; Saachi S., BASIS Independent High School '24

ADVISOR: Kaur, Microbiology & Environmental Genetics

KEYWORDS: AMF | Arbuscular Mycorrhizal Fungi | Apium Graveolens | Golden Self-Blanching Celery | Mutualistic Relationships

Department of Computer Science & Engineering

Comparing Time Complexities of Quantum - Adapted Classical Sorting Algorithms in a Memory-Bound Scenario

The rich diversity of lignin small molecules derived from podophyllotoxin, a non-covalent tubulin inhibitor isolated from the podophyllum family, has led to the discovery and clinical development of several anticancer agents including etoposide and teniposide, FDA approved DNA topoisomerase inhibitors, that are structurally altered at the C-4 hydroxyl and subsequently exhibit independent biological activities and/or mechanisms of actions. Given the immense pharmacological importance of this feature, we sought to establish a structure-activity relationship regarding modification at C-4 on the potency, specificity, and chemical properties of podophyllotoxin. We synthesized and evaluated a systematic library of close-in diversified esters at the C-4 position of podophyllotoxin to explore prodrugging capability and evaluate the effect of bulk on potency. The installation of bulky esters attenuates the compounds’ potency against human cancer cell lines, and we plan to further investigate the biological activity of these analogs through tubulin polymerization assays, cell cycle analysis, and live cell imaging. 

RESEARCHERS: Raj P., Fremont High School '26; Eashan M., Dublin High School '25

ADVISOR: McMahan, Quantum Computing & Computer Science 

KEYWORDS: Quantum Computing | Quantum Algorithms | Sorting | Quantum Optimization | Time Complexity | Space-Bound Case

Department of Biological, Human, and Life Sciences

Assessing the Efficacy of Podophyllotoxin Derivatives Against Colorectal Carcinoma Cells

The antimitotic drug podophyllotoxin (PDOX) and its derivatives have previously shown antimetastatic properties with a limited range of applications approved for clinical use due to factors such as systemic toxicity, low bioavailability, and development of drug resistance. PDOX, derived from the podophyllum peltatum plant, causes cell cycle arrest through inhibiting microtubule formation; many of its derivatives follow a different mechanism of action. Unsubstituted PDOX prodrug (unsub), dimethoxy PDOX prodrug, and PDOX prodrug with alkyne were assessed for their cytotoxicity against HCT-116 colorectal carcinoma cells and MCF-7 breast adenocarcinoma 1 through MTT assays.

RESEARCHERS: Aretha L., Mission San Jose High School '24; Srikar P., Amador Valley High School '24

ADVISOR: Zhang, Biology & Cancer Research

KEYWORDS: Cancer Biology | Drug Research | Tubulin Polymerization | Podophyllum 

Department of Biological, Human, and Life Sciences

Efficacy of novel KRAS inhibitors against G12C positive cell lines

Oncogenic mutations in the GTPase protein KRAS are implicated in approximately 25% of human cancers - specifically, the most common mutation - G12C - is found in 13% of lung cancers. This single residue substitution causes irreversible binding to the GTP substrate, thereby forcing the protein into a permanent, activated state. While KRAS has been previously considered an undruggable chemotherapeutic target, the discovery of acrylate-based covalent inhibitors of G12C KRAS has led to the development of two FDA-approved chemotherapeutic agents: Sotorasib (AMG-510) and Adagrasib (MRTX849). Inspired by the pharmacophore model of these compounds, the Njoo Group developed a series of twelve isoxazole-based covalent inhibitors of G12C KRAS, synthesized via a scalable and diversifiable three step synthesis. Compounds were evaluated for cytotoxicity against G12C positive mutant cell lines (MCF7) and G12C negative mutant cell lines (HCT-116). Dosage and time dependent viability graphs were generated for MTT assays performed on A1P1 and A3P1. 

RESEARCHERS: Samuel H., BASIS Independent Fremont Upper School '24; Samahith T., BASIS Independent Fremont Upper School '26

ADVISOR: Zhang, Biology & Cancer Research

KEYWORDS: Medicinal Chemistry | Cancer Biology | KRAS | Carcinoma | mcf7 | Isoxazole

Department of Chemistry, Biochemistry, and Physics

Design, Synthesis and Biological Evaluation of C-4 Close-in Analogs of Podophyllotoxin

The rich diversity of lignin small molecules derived from podophyllotoxin, a non-covalent tubulin inhibitor isolated from the podophyllum family, has led to the discovery and clinical development of several anticancer agents including etoposide and teniposide, FDA approved DNA topoisomerase inhibitors, that are structurally altered at the C-4 hydroxyl and subsequently exhibit independent biological activities and/or mechanisms of actions. Given the immense pharmacological importance of this feature, we sought to establish a structure-activity relationship regarding modification at C-4 on the potency, specificity, and chemical properties of podophyllotoxin. We synthesized and evaluated a systematic library of close-in diversified esters at the C-4 position of podophyllotoxin to explore prodrugging capability and evaluate the effect of bulk on potency. The installation of bulky esters attenuates the compounds’ potency against human cancer cell lines, and we plan to further investigate the biological activity of these analogs through tubulin polymerization assays, cell cycle analysis, and live cell imaging. 

RESEARCHERS: Breanna L., Leland High School '24; Harriet C., Las Lomas High School '24

ADVISOR: Njoo, Organic Chemistry

KEYWORDS: Natural Products | Organic Synthesis | Prodrugs | Chemical Biology 

Department of Biological, Human, and Life Sciences

AI-based Classroom Assisted Tool for Helping ADHD Students, Teacher & Parents

RESEARCHERS: Adhvaith R., Washington High School '25, Aayush R., Arizona College Prep High School '25, Bhadra R., The Bishop's School '25; Harsh S. John F Kennedy High School '24

ADVISOR: Jahanikia, Life Sciences, Neuroimaging, Psychology & Bioinformatics

KEYWORDS: 

Department of Biological, Human, and Life Sciences

In vitro characterization of human epigenetic inhibitors (DNA Methyltransferase inhibitors and HDACs) on HCT-116 Colorectal cancer cells

Colorectal cancer (CRC) starts in the colon or the rectum, and is the third most common cancer, the second most common cancer leading to death (American Cancer Society, 2019). We used the cell line known as epithelial human colorectal carcinoma 116 (HCT-116) cell line, which was derived from an adult male (Imanis Life Sciences, n.d.). The project’s main goal is to compare various DNMT inhibitors that reactivate tumor suppressor genes by demethylating them (Brueckner et al., 2005). We chose decitabine as the control variable due to its potency as a nucleoside inhibitor (Rondelet et al., 2017). Through this use of decitabine, we plan on comparing its efficacy to various DNMT and later HDAC inhibitors (Xu et al. 2007). We will also be using MTT assays, qPCR, and Western Blots for further research.

RESEARCHERS: Shree R., Amador Valley High School '26; Aditya S., American High School '24

ADVISOR: Cunha, Biology & Cancer Research

KEYWORDS: DNMT | Decitabine | HDAC | HCT116 | Colorectal Cancer | Tumor | Biology | Demethylating | Inhibitor

Department of Biological, Human, and Life Sciences

Investigating the neural process behind different style of meditation & yoga: An EEG Study

The research on the effects of meditation on the brain using electroencephalography (EEG) has garnered considerable attention in recent years, building upon decades of prior investigation. Despite this extensive body of work, the precise influence of meditation on neural processes within the body remains elusive. In this study, our objective was to gain a comprehensive understanding of how individuals respond to different meditation practices, specifically focusing on mantra repetition meditation and open awareness thinking. To analyze the collected data, we employed well-established software tools such as MatLab and EEGLab. Sleep data, an integral component of our study, is categorized into distinct stages. Our analysis specifically focused on deciphering the sleep non-REM pattern associated with open awareness thinking. To discern and delineate the sleep stages present within the meditation data, we employed the SSAVE (Sleep Cycle and Spectrogram Analysis and Visualization for Electroencephalography) python algorithm. Throughout our data processing and preliminary analysis, we made intriguing observations. As we advance our investigation, we aim to unravel the intricate relationship between meditation and neural processes, particularly within the context of sleep. By shedding light on the interplay between meditation, brain activity, and sleep patterns, we aspire to deepen our understanding of the direct effects of meditation, while exploring its potential benefits for cognitive functioning, stress reduction, and overall physical well-being.

RESEARCHERS: Saanvi G., Dublin High School '26; Urvi A., Leigh High School '26

ADVISOR: Jahanikia, Life Sciences, Neuroimaging, Psychology & Bioinformatics

KEYWORDS: EEG | Meditation | Sleep | Attention | Technology

Department of Biological, Human, and Life Sciences

Analyzing Trends in California Snowpack

RESEARCHERS: Krish B., Thomas Jefferson High School for Science and Technology '26

ADVISOR: Adams, Marine Biology & Water Sciences

KEYWORDS: 

Department of Biological, Human, and Life Sciences

Comparative Genomic Analysis of Colorectal Cancer Microbiome Bacteria to Discover Novel Relationships

Colorectal cancer (CRC) is uncontrolled tumor growth that originally starts in either the rectum or colon. Our research is focused on the microbiome in the gut. The end goal is to target signaling pathways in order to decrease the metastasis and malignity of gut tumors by increasing or decreasing the expression of certain bacteria genes in CRC. The probiotic bacteria’s byproducts may play a role in this process. The usage of the R programming language allowed us to first narrow our target proteins down into a few that were common between known probiotic bacteria. We then utilized NCBI Blast to align the genomes of the probiotic bacteria in order to find structural similarities and differences that may play a role in how probiotic bacteria inhibit CRC. Currently, we are analyzing bacteria present from a recent cancer microbiome review paper to reveal novel phenotypic and genotypic differences at the protein and signaling/pathway levels. We hope to perform Protein Annotation and KEGG Pathway analysis to reveal undiscovered relationships. Eventually, we hope our research will help narrow down specific proteins/pathways in bacteria that microbiology, wet-lab, researchers can manipulate in order to find cheaper and novel ways to reduce colorectal cancer. 

RESEARCHERS: Harshita K., Amador Valley High School '25; Shriya V., Shepton High School '26

ADVISOR: Cunha, Biology & Cancer Research

Keywords: Colorectal Cancer | Comparative Analysis | Microbiome Bacteria | Bioinformatics

Department of Computer Science & Engineering

Using Quantum Neural Networks (QNNs) and the Mathematical Morphological Reconstruction Algorithm for early stage brain tumor detection

Mathematical Morphological Reconstruction (MMR), Quantum Neural Networks (QNNs), and Convolutional Neural Networks (CNN) are algorithms that quantum physicists and neuroscientists have analyzed for early-stage brain tumor detection as present detection methods face false detection. Investigating external factors of brain tumors for early detection objectives does pose challenges. Still, this result could augment accuracy and open opportunities for other elusive early cancers. The project's main focus is comparing the efficiency, detection rate, and speed of the MMR and QNN algorithm with that of the CNN algorithm. Mass data collection of MRI brain scans overall, dilation, erosion, skull stripping methods for the MMR algorithm, mapping the encoding and convolutional and pooling layers of the QNN and CNN algorithm have been performed through OpenCV2's morphology functions, skull stripping methods, and Qiskit. 

RESEARCHERS: Riddhi S., Evergreen Valley High School '26; Tiffany L., Quarry Lane High School '25

ADVISOR: McMahan, Computer Science & Quantum Computing

KEYWORDS: Mathematical Morphological Reconstruction (MMR) | Quantum Neural Networks (QNNs) | Convolutional Neural Networks (CNN) | Early-stage Brain Tumor Detection | Quantum Computing

Department of Chemistry, Biochemistry, and Physics

Design, Discovery, and Anti-Cancer Activity of Isoxazole-Based Covalent Inhibitors Targeting G12C Mutant K-Ras

Oncogenic mutations in the GTPase protein K-Ras are implicated in approximately 25% of human cancers - specifically, the most common mutation - G12C - is found in 13% of lung cancers. This single residue substitution causes irreversible binding to the GTP substrate by inhibiting GTP hydrolysis, and therefore forcing the protein into a permanent, activated state. While K-Ras has been previously considered an undruggable chemotherapeutic target, the discovery of acrylate based covalent inhibitors of G12C K-Ras has led to the development of two FDA approved chemotherapeutic agents: Sotorasib (AMG-510) and Adagrasib (MRTX849). Inspired by this pharmacophore model, we developed a series of isoxazole based covalent inhibitors of G12C K-Ras, and evaluated their in vitro potency against HCT116 and MCF7 human cancer cell lines. Furthermore, a GTPase assay was developed to measure the GTP enzyme activity of wild-type K-Ras and the G12C mutated protein. Moreover, we used molecular docking to rationalize the potency of these compounds. 

RESEARCHERS: Polina B., Los Altos High School '24

ADVISOR: Njoo

Keywords: Medicinal Chemistry | Organic Synthesis | GTPase | Inhibitors 

Department of Computer Science & Engineering

Particle Collision

Abstract: Information will be posted soon

RESEARCHERS: Vishnu S., Foothill High School '27; Krishna C., Mission San Jose High School '25; Lisa I., Foothill High School '24; Vedha V., Amador Valley High School '25; Tashvi B., Monta Vista High School '27

ADVISOR: McMahan

KEYWORDS: 

Department of Chemistry, Biochemistry, and Physics

In Vitro Activity and Structure-Activity Relationship of Dual-Purpose Small-Molecule Inhibitors Against Human Acid Ceramidase and the SARS-CoV-2 Main Protease

The emergence of global pandemics such as the novel coronavirus in COVID-19 has prompted many to seek therapeutic leads from existing small-molecular libraries through drug repurposing. From such a screen, carmofur, a 5-fluorouracil derivative initially developed as an antineoplastic agent to treat colorectal cancer, has also been identified as a potent covalent inhibitor of the main protease of SARS-CoV-2 (Mpro), making it a promising therapeutic agent against COVID-19. In this study, we develop an optimized protocol for producing carmofur and its analogs in a scalable and efficient fashion, enabling the structural exploration of a single chemical platform against two biochemical targets– human acid ceramidase and the SARS-CoV-2 main protease. Specifically, we present preliminary structure-activity relationship (SAR) data of our compounds with potent in vitro anticancer properties as well as potentially unique anti-SARS-CoV-2 properties. These biochemical results are rationalized through molecular docking simulations.

RESEARCHERS: Lexi X., Leland High School ‘25;  Amber L., Leland High School ‘25

ADVISOR: Njoo, Organic Chemsitry

Department of Computer Science & Engineering

Determining the Extent to Which Outside Influences have Changed the Greek Language over Time Using Slang Detection and Machine Learning

Throughout history, the Greek language has experienced outside influence and research that supersedes many other languages that continue to exist today. The barrier between their current language and ancient Greek has led to the efforts of researchers from all over the globe to attempt to decode various ancient texts. Our goal of analyzing various linguistic corpora and different texts will give insight into language evolution. We hypothesized that influences from Proto-Indo-European languages, such as their grammatical syntax, cognates, and regional similarities, correlate to the close relationships that these ancestral languages and their descending dialects hold with ancient Greek. Comprehensive data sets regarding the ancient language will be analyzed using techniques such as the K-Nearest Neighbors Algorithm to supplement our deep learning Artificial Intelligence to achieve the cross-linguistic goal. An understanding of how transforming slang influences how Greek has evolved provides a future basis for growth in the complex intersections of cultures in our current world.

RESEARCHERS: Brian S., Foothill High School ‘25; Ratul C., Foothill High School ‘25; Ayaan C., San Ramon Valley High School ‘25

ADVISOR: McMahan

KEYWORDS: Artificial Intelligence | K-Nearest Neighbors Algorithm | Linguistic Corpora | Proto-Indo-European languages | Language Evolution | Cross-Linguistics | Slang Detection | Globalization | Greek Language |