Serine hydrolases play important roles in signaling and human metabolism, yet little is known about their functions in gut commensal bacteria. Using bioinformatics and chemoproteomics, we identify serine hydrolases in the gut commensal Bacteroides thetaiotaomicron that are specific to the Bacteroidetes phylum. Two are predicted homologs of the human protease dipeptidyl peptidase 4 (hDPP4), a key enzyme that regulates insulin signaling. Functional studies reveal that BT4193 is a true homolog of hDPP4 that can be inhibited by FDA-approved type 2 diabetes medications targeting hDPP4, while the other is a misannotated proline-specific triaminopeptidase. We demonstrate that BT4193 is important for envelope integrity and that loss of BT4193 reduces B. thetaiotaomicron fitness during in vitro growth within a diverse community. However, neither function is dependent on BT4193 proteolytic activity, suggesting a scaffolding or signaling function for this bacterial protease.

The event page announcing a screening of Marlon Riggs' film, Tongues United, on its 30th anniversary.

We propose 3KG v2, a new self-supervised learning method for universal representation learning of electrocardiograms. This method builds upon its predecessor by featuring a new contrastive objective and transformation space. We assess the quality of representations generated by this algorithm by transferring pre- trained models from a large public dataset to various downstream tasks, including some with- out prior clinical association with ECGs. Performance evaluation is conducted in both few- shot and full data settings to account for limited and complete training data availability, respectively. For each task, we perform a linear evaluation to assess the effectiveness of the pretrained representations. For tasks in the full- data setting, we additionally perform a full-fine tuning to determine the performance ceiling of each method in a practical deployment scenario. Our results demonstrate that 3KG v2 consistently outperforms a randomly initialized model trained solely on the target task across all downstream tasks and settings. Specifically, we achieve state-of-the-art performance in few- shot diagnosis of right ventricular function and aortic valve stenosis, two conditions that typically require large amounts of labeled ECGs for effective model training. Moreover, we find that fine-tuning 3KG v2 on our source task’s labels can lead to exceptional transfer capability across a variety of tasks. Notably, our model demonstrates a high level of accuracy in predicting left atrial volume index, achieving a 0.720 C-index even in a few-shot setting. This achievement appears to be unprecedented, as we are not aware of any other ECG model that performs well on this task. While 3KG v2 out- performs our baselines and shows promising results on the majority of phenotype discovery tasks, there is still room for improvement in the absolute performance of any ECG model on many of these complex tasks. Further research is warranted to continue developing and improving such methods for phenotype discovery tasks on ECGs.

When I was a young child, my grandfather created a conference called "For All My Relations." Thousands of Native American people, traveling from over 200 reservations, flooded the conference hall in pursuit of learning how to best fight for tribal sovereignty, human rights, and land back. It was at this time I understood the importance of identifying as Indian, in addition to my own tribal designation. One tribe alone could not accomplish the work that must be done to better the lives of Native American people. Indian, as a generalized identity, allowed us to rally behind a shared cause, purpose, and value system, in turn giving us the strength to turn American imperialism and capitalism on its head. Despite the value in this generalized identity, it has come to my attention that as the Indian identity is taken in absence of ones' tribal community, ancestral land claims, diverse voices, and tribal visbility by designation are being silenced. This magazine seeks to interrogate this issue, as well as find answers as to how we can assume Indian identity while managing to maintain our own specific tribal identities, cultures, governments, and pursuits for land back. Identity forms and exists in its relationship with others. Before European contact, Native American's identities were formed through tribal and cultural differences. The Indian identity began to form as colonizers raped and pillaged both our people and land. This identity is the key to resisting institutional racism and is necessary for the unity of our people. Though we must assume this secondary identity in order to successfully organize our people, we must not forget that there are over 574 tribal nations in the United States and their individual cultures and identities. This magazine is written about California Indians and their relationship with pan-Indianism, but this body of work is to be read by all as this long fight we embark on is one that includes ALL MY RELATIONS.

An image-rich remembrance of the singer Jenny Lind, including a view of her celebrity as imagined experience in Gold Rush San Francisco. Presented at the 2023 Congress of the International Association of Music Libraries, Archives, and Documentation Centres (Cambridge, UK).

Neuropeptide S (NPS) is a highly conserved peptide found in all tetrapods that functions in the brain to promote heightened arousal; however, the subpopulations mediating these phenomena remain unknown. We generated mice expressing Cre recombinase from the Nps gene locus (NpsCre) and examined populations of NPS+ neurons in the lateral parabrachial area (LPBA), the peri-locus coeruleus (peri-LC) region of the pons, and the dorsomedial thalamus (DMT). We performed brain-wide mapping of input and output regions of NPS+ clusters and characterized expression patterns of the NPS receptor (NPSR1). While the activity of all three NPS+ subpopulations tracked with vigilance state, only NPS+ neurons of the LPBA exhibited both increased activity prior to wakefulness and decreased activity during REM sleep, similar to the behavioral phenotype observed upon NPSR1 activation. Accordingly, we found that activation of LPBA, but not peri-LC NPS+ neurons increased wake and reduced REM sleep. Furthermore, given the extended role of the LPBA in respiration, and the link between behavioral arousal and breathing rate, we demonstrated that LPBA-, but not peri-LC-NPS+ neuronal activation increased respiratory rate. Together, our data suggests that NPS+ neurons of the LPBA represent an unexplored subpopulation regulating breathing and they are sufficient to recapitulate the sleep/wake phenotypes observed with broad NPS system activation.

Potassium K-edge XANES spectra used in 'A Combined Spectroscopic and Theoretical Analysis of Organic Potassium Compounds' by Richardson et al.

For her capstone project, Sarah Lee explored the growing intersection between digital privacy and U.S. reproductive rights in a post-Roe, data-driven world. Her research paper seeks to assess what legal factors and technological systems have enabled the formation of the existing abortion surveillance state, along with what duties are held by the federal government and tech companies to protect abortion-seekers' digital rights. In this paper, she lays out the prevailing impacts, risks and concerns surrounding abortion surveillance tactics in the digital era, as bred by the growing system of surveillance capitalism. She concludes with brief policy recommendations on the need for comprehensive data privacy legislation and greater data responsibility and transparency from tech companies. Student project deposited by department for archival purposes. Original work unavailable for public download due to permission restriction preferences of the author.

The perception of a “rising China” and “declining US” among Western academic and policymaking circles has sparked fears of an emboldened China that views military conflict as beneficial to their interests. This research aims to provide clarity on this issue by analyzing how Chinese state media portrays strategic competition with the US. Drawing from online Chinese-language news articles from media institutions that reflect the Chinese Communist Party’s official party line (People’s Daily, PLA Daily, Global Times, and Xinhua), I examine how these outlets depict economic, technological, military, political, and international competition with the US. This research analyzes these depictions against the backdrop of pivotal moments in 21st century US-China relations: the 2008 Great Recession, the 2012 Power Transition, the 2018 US-China Trade War, and 2020 COVID-19 Pandemic. Taking a random sample of articles from each time period, I assign each article a score ranging from “-1” to “1” to measure tone and calculate the percentage of positive, negative, and neutral stories within each time period and category of strategic competition. Second, I conduct a qualitative analysis of the articles within each random sample to identify general themes and messaging. This research identified a drastic rise in negative coverage of the US across the four time periods and five categories. This research also determined that Chinese state media has propagated a “peak-US” theory. According to this theory, the overall decline of the US has made it a more hostile power that aims to suppress China’s development and resurrect a “New Cold War.” Despite these views of a hostile US, state media narratives urged the US to return to cooperation and avoid war due to a recognition that China benefits more from overall cooperation with the US, especially in terms of economic and technological development.

For his human rights capstone project, Eddie Dilworth created a guide to national environmental justice screening tools from the Center for Diseases Control (CDC), Environmental Protection Agency (EPA), and White House Council on Environmental Quality (CEQ). These tools are meant to screen for communities that may face disproportionate burdens from climate change and environmental issues, and generally combine data on both environmental burdens, and socioeconomic factors to highlight these communities, including for additional research attention or government resources. However, it is challenging to read each of their 35+ page technical documentation reports and make an informed decision on which screening tool to use and what its limitations may be. This project thus aims to summarize the technical documentations of the tools, provide demonstrations of how to use them, and outline their main differences, in ArcGIS StoryMaps. Student project deposited by department for archival purposes. Original work unavailable for public download due to permission restriction preferences of the author.

After coming to power in the wake of the infamous Hungarian Revolution of 1956, János Kádár built his regime upon a delicate balance between upholding socialist ideals and appeasing a disgruntled, scarred nation. The slogan that became Kádár’s central doctrine perfectly represented this balance: “those who are not against us, are with us.” Existing literature on Kádárist Hungary portrays the period’s stability as a product of the leader’s compromising personality and political cunning. While accurate, these accounts largely neglect the role of Kádár’s political police as a primary organ of two-way interaction between the party and populace. Internal informational documents from the Ministry of the Interior III. reveal that the mass informant network served as the spearhead of interaction between the party and population in the realm of national security, which was viewed as essential to the building of socialism. The informant network’s transformation alongside the political police from a crude, coercive, and inherently dishonest body into a more focused, sophisticated, and interactive machine reveal much about the implementation of János Kádár’s vision for socialist Hungary. Described as a “living, controllable device,” the political police’s informant network provided Hungarian citizens with an accessible and personally beneficial means of cooperation with the state. The network allowed Hungarians to prove themselves “not against” Kádár’s Party.

Cryogenic Electron Microscopy (Cryo-EM) is an established method of imaging biomolecules with an electron microscope. The current process of preparing samples for Cryo-EM involves loading the grid into a plunge-freezer and plunging it into liquid ethane to freeze the grid. As the grid falls into the liquid ethane, two samples are mixed and deposited on the grid using a microfluidic spraying device. In order to improve the practicality and repeatability of the plunge-freezer, a mechatronic device was built to simplify the process of replacing the microfluidic spraying device.

Our coastal marine station, along with many others, holds a valuable collection of student research reports spanning several decades. These reports contain historical observations that could play a crucial role in identifying changes in biodiversity and revealing the impacts of climate change. However, a major obstacle in utilizing these observations of marine plants and animals is that they are essentially buried within vast amounts of text, making manual analysis impractical. In recent years, a dedicated team of Stanford Libraries staff has been experimenting with various text-mining approaches on our collection of student reports from Hopkins Marine Station. Our objective has been to identify species occurrences (species + place + date) and verify the accuracy of these observations. While we have achieved some small successes along the way, progress has been hindered by limited staff resources to develop a trained language model and a user interface to efficiently process over 700 papers. Nonetheless, our hopes were reignited by recent advancements in pre-trained large language models (LLMs) such as GPT-4 and LLaMA. In this presentation, I will share our journey of exploring the potential of applying an LLM approach on our corpus. I will delve into the development of prompts to extract taxonomic names, places, habitats, and dates from the corpus, and provide an overview of the workflow that spans from compiling collection metadata to the extraction of species occurrences.

We present an ice-penetrating radar dataset acquired over the Greenland ice sheet by aircraft during the years 1971, 1972, 1974, 1978, and 1979. The dataset comprises over 177,000 km of flight lines and contains a wealth of information on the state of the Greenland ice sheet including information on ice thickness and englacial properties. During data collection in the 1970s, the data were recorded on optical film rolls and in this manuscript, we document the digitization of these film 5 rolls and their associated geographical information. Our digitization of the data enables interaction with and analysis of the data and facilitates comparison with modern-day radar observations. The complete dataset in full resolution with associated scanned notes is available here.

Introduction: Intimate partner violence (IPV) survivors’ help-seeking is influenced by a complex interplay of barriers and facilitators. This includes both internal and external factors that affect a survivor’s decision to seek and ability to obtain resources. While understanding these factors is crucial to ensuring appropriate care, there is currently no agreed upon, comprehensive framework for capturing IPV survivors’ help-seeking. Objectives: We seek to answer the question: How can the Three Delays Model (3DM) and the Behavioral Model of Health Services Use (BMHSU), as well as proposed adaptations of these models, provide a framework for understanding barriers and facilitators of IPV survivors’ help-seeking? Methods: This secondary qualitative analysis was performed on transcripts from nine focus groups obtained as part of a larger study on IPV survivors’ help-seeking as influenced by the COVID-19 pandemic. Qualitative codes representing the theoretical constructs of each model and its adaptation were identified and set a priori, and to maintain a deductive coding approach, no new codes were added throughout data analysis. Manual coding of the transcripts was done by the first author. Once all transcripts were coded, code frequency and code co-occurrence analyses were performed to determine how well the different models mapped onto IPV survivors’ experiences. Results: Codes from the BMHSU adaptation were applied most often, and codes from the 3DM adaptation were applied least often. The 3DM captured IPV survivors’ barriers to initially accessing care; however, it did not allow for a nuanced understanding of how the care system affected help-seeking. The BMHSU adaptation provided the richest understanding of IPV survivors’ barriers and facilitators to help-seeking with its expanded inclusion of psychosocial factors. Conclusion: These findings highlight the strengths and limitations of two theoretical models and their adaptations, allowing for a better framework for understanding barriers and facilitators of IPV survivors’ help-seeking. Future research is needed to integrate these models into one comprehensive model for capturing factors contributing to IPV survivors’ help-seeking.

Music theory is often considered to be irrelevant to our experience of music. This course will demonstrate that the opposite is true—understanding the laws governing the art of sound enhances our ability to appreciate, enjoy, and even remember music. Reversing the traditional academic practice of moving from concepts to real music, we will start with concrete musical examples and seek to extract their theoretical premises.

The goal of this paper is to understand Latino voting behavior during the 2016 and 2020 presidential elections using precinct-level analysis. The 2016 and 2020 presidential elections were cases of elections where Latinos were demonstrated to have voted for Republican candidates in surprising numbers. Analysis of data from precincts with high proportions of Latino citizen voting age population was utilized to provide a comprehensive description of the Latino electorate and address the ecological inference problem that emerges when attempting to infer voting behavior of electorate subgroups like Latinos using aggregate data. Using precinct-level Latino demographic data created for this analysis, Latinos were found to have voted more Republican in 2020 than in 2016. Additionally, in 2020, Latinos were found to lean more Republican than non-Latinos in precincts with high proportions of Latino citizen voting age population.

The ability to predict which protein sequences can act as transcriptional activators or repressors is important for understanding the function of human and viral transcription factors (TFs) inside human cells and for building synthetic biology tools for gene control. Here, I integrate multiple high-throughput data sets acquired using a recently developed method (HT-Recruit) that tests hundreds of thousands of protein sequences for their effect on reporter genes in live human cells. I first created a data processing pipeline using ground truth validations to regularize results from multiple HT-Recruit screens, allowing cross-screen comparisons as well as proper model training. After processing these datasets, I built and trained convolutional neural network machine learning models that predict both activation and repression for protein sequences across the human transcription factors. These are the first models to be trained on human TF data, as well as the first to predict repressors. Some protein sequences are bifunctional in that they both activate and repress, so it is important to be able to predict both.

For much of recent history, the thought of machines being in any semblance within reach of human cognition has been one of imagination. But now, technology has speedily caught up to these aspirations, and society faces the daunting task of accepting, learning, and utilizing such tools. Specifically in the lens of design and architecture, what needs to be done at this point is to (1) reflect on how technology currently plays a role within it, and (2) determine how technology should continue to impact it. In this thesis, I will survey artificial intelligence applications dedicated to image generation and explore how they serve the purposes of architectural design. In particular, I will utilize recently popular text-to-image applications, such as Midjourney alongside existing GANs. Given these current various outputs available from machine learning tools, there is yet no current framework or methodology defined for architects to utilize these tools to manifest a 3D structure out of them. I will propose a framework for how architects can use various generative architectural outputs, namely massing and programming, to realize an actual 3D structure that serves as inspiration in the early design stages. However, besides being a guideline for individuals who wish to use these tools, ultimately this framework could also be referenced as a preliminary model for those working on the continuous improvement of 3D machine learning algorithms. After all, as the design process inevitably becomes more digitized, it is important to maintain a humanistic and an authentically architectural approach within the algorithms that oversee our design outputs.

Alternative splicing enables the differential expression of multiple mRNA transcripts and multiple functionally unique protein isoforms derived from the same gene. Interestingly, genes encoding synaptic regulators are both alternatively spliced and implicated in the development of several neuropsychiatric disorders including autism spectrum disorders, schizophrenia, and Tourette’s syndrome. Mechanisms by which synapses are formed and dynamically regulated remain unclear, but the alternative splicing of trans-synaptic regulators is thought to play a decisive role in mediating neuronal communication. To deduce a representative model for neuronal alternative splicing in the making and shaping of synapses (as reflected in changes to synaptic RNA and protein levels), Khdrbs (Sam68, Slm1, Slm2) and Nova splice factors (Nova1, Nova2) were virally overexpressed in primary neurons cultured from neonatal mice. In-vitro validation of RNA-seq-reported changes in synaptic splicing demonstrated that Khdrbs factors exclusively regulate the alternative splicing of multiple Neurexin (Nrxn) homologs, cell-adhesion molecules crucial for the development of functional synapses. Additionally, immunoblot analysis revealed a strikingly consistent loss of key synaptic proteins, coupled with decreased expression of astrocytic markers, in Slm1-overexpressed cultures, suggesting a splice factor-specific role in maintaining tripartite synapses by which glial contributions are likely paramount. In short, the experiments performed here capture the discrete effects of neuronal alternative splicing in the regulation of core synaptic components and offer insight into the molecular bases underpinning a broad range of animal behaviors.