Dartmouth Institute for Health Policy and Clinical Practice
Dartmouth Digital Commons (Dartmouth College)Not a member yet
8214 research outputs found
Sort by
ADVANCING MOBILE SENSING IN DYNAMIC ENVIRONMENTS
Get PDFThis thesis presents a comprehensive exploration of enhancing mobile sensing capabilities to address various aspects of human behavior, mental health, personality, social functioning and beyond. We redesign the StudentLife app to improve its sensing efficiency and dependability, enabling support for multi-year-long studies. By adopting new app design, this study addresses the technical challenges of continuous sensing and enhances system robustness. The work is organized into several key studies that collectively aim to expand the scope of mobile sensing in diverse and complex environments.
The first study broadens the scope of mobile sensing to assess personality traits, exploring the potential of within-person variability in behavior to predict personality traits. By analyzing data from 646 college students, this study demonstrates significant correlations between sensed behaviors and self-reported personality traits, offering a novel approach for passive personality assessment.
The second study utilizes mobile sensing data to provide insights into the social functioning of individuals with mental health disorders, specifically schizophrenia. This study identifies behavioral patterns correlated with various aspects of social functioning, highlighting the potential for mobile sensing to inform new assessment and intervention strategies.
The third study investigates the integration voice diaries to enhance the prediction of auditory verbal hallucination (AVH) severity. This approach leverages deep learning models to analyze speech and mobility data, showcasing the feasibility of using mobile sensing for in-the-wild psychiatric symptom assessment.
The fourth study predicts the mental well-being of college students with a special emphasis on first-generation students, using longitudinal mobile sensing data to identify risk factors and behavioral patterns associated with mental health.
Finally, the thesis investigates the challenge of domain drift and model degradation over time, exploring adaptation technologies to maintain the effectiveness of mobile sensing frameworks for depression detection. By analyzing passive sensing data and self-reported surveys from undergraduate students over several years, this work demonstrates the efficacy of domain adaptation strategies in ensuring robust depression detection.
Together, these studies contribute to the development of power-efficient, scalable, and adaptable mobile sensing systems, pushing the boundaries of mobile sensing technologies, and offering new perspectives on assessing mental health and beyond
Hierarchal single-cell lineage tracing reveals differential fate commitment of CD8 T-cell clones in response to acute infection.
Get PDFGenerating balanced populations of CD8 effector and memory T cells is necessary for immediate and durable immunity to infections and cancer. Yet, a definitive understanding of CD8 differentiation remains unclear. Here we used CARLIN, a processive lineage recording mouse model with single-cell RNA-seq and TCR-seq to track endogenous antigen-specific CD8 T cells during acute viral infection.
Transcriptional profiling of antigen-specific T cells at the peak of the effector response to Vesicular stomatitis virus uncovered a diverse repertoire of expanded antigen-specific T-cell clones represented by seven transcriptional states. TCR enrichment analysis identified TCR clones with differential memory- or effector-fate biases during the peak of the effector phase. Shared Vb segments and amino acid motifs were found within TCR biased categories despite high overall TCR diversity. Using single-cell CARLIN barcode-seq we tracked multi-generational TCR clones and found that unlike unbiased or memory-biased TCR clones, which stably retain their fate profiles, effector-biased TCR clones could adopt memory- or effector-bias within subclones. Using TCR retrogenic mice we validated the fate commitment of one effector biased TCR clone and two memory biased TCR clones. These biased clones also maintained their lineage preference under different inflammatory cues that had previously been reported to alter T cell fate. We also demonstrate that TCRs identified in the effector phase to be memory biased were able to promote antigen-driven CD8 T cell differentiation into multiple long-lived memory subsets in response to an acute viral infection.
Moreover, the observed TCR bias in cell fate commitment was not limited to the effector response as our transcriptional and TCR enrichment analysis of antigen-specific CD8 T cells at a memory timepoint also revealed long-lived effector (LLEC) biased, effector memory (TEM) biased and tissue resident memory (TRM) biased TCR clones. Shared Vb segments were found in the LLEC and TEM biased TCRs while TRM biased clones preferred a unique set of Vb segments. Collectively, our study demonstrates that a heterogenous T-cell repertoire specific for a shared antigen is composed of clones with distinct TCR-intrinsic fate biases
LEVERAGING PASSIVELY-COLLECTED WEARABLE ACCELEROMETRY DATA COUPLED WITH MACHINE LEARNING TO LONGITUDINALLY DETECT AND PREDICT MAJOR DEPRESSIVE DISORDER
Get PDFMajor depressive disorder (MDD) is a debilitating and heterogenous mental health disorder that is characterized by symptoms including low mood, issues with sleep, psychomotor difficulties, and fatigue. MDD affects one in twenty adults worldwide and has shown increased prevalence in the United States over the past twenty years. As such, efforts to effectively screen, diagnose, and treat MDD are paramount. However, to address these concerns, an increased understanding of an individual’s daily behavior is required, which is not adequately captured by infrequent clinical visits. One such method for consistent, longitudinal observation, passively-collected accelerometry, serves as an observational method for unobtrusively capturing movement, sedentary and sleep behaviors in real-time. Therefore, the primary effort of this thesis work is to investigate the utility of leveraging longitudinal, passively-collected accelerometer information in detecting and predicting outcomes related to MDD. The primary data source for this work comes from the nationally representative 2011-2014 National Health And Nutrition Examination Survey and two separate clinical samples. A combination of unsupervised machine learning, supervised machine learning, and deep learning techniques were used to characterize movement, sedentary and sleep behaviors for individuals with MDD, as well as investigate depression presence, individual depressive symptoms, long-term depression variability, and acute depression variability. Taken together, this work highlights the utility of using solely passively-collected accelerometry to investigate outcomes related to MDD and seeks to provide insight into the utility of implementing such approaches in real-world clinical settings to both improve our understanding of, and opportunities for, clinical engagement for individuals with MDD
Energy and Empowerment in the High Arctic
Get PDFNational governments continue to depend on fossil fuels for electricity and heat generation in Arctic communities. This dependence threatens the economic, environmental, and cultural sustainability of Arctic communities and subjects them to future volatility and uncertainty. In Greenland, the centralized government structure creates additional challenges for northern communities by limiting the inclusion of local knowledge and priorities in favor of national, standardized solutions. This research identifies pathways towards fossil fuel reduction in northern Greenlandic communities via 1.) analyzing the potential for renewable energy inclusion in grid-scale or residential energy generation and 2.) analysis of the potential for energy reduction in housing. Furthermore, this research provides insights into the policy tools that make energy generation and conservation strategies financially and technically accessible to residents of northern Greenland. A model of Qaanaaq’s energy grid is developed and determines that under various economic circumstances, hybrid energy systems, including solar PV, battery energy storage, and diesel, are cost-optimal and technically feasible for Qaanaaq, both from a utility and community perspective. Financial tools that aim to reduce upfront costs could significantly lower barriers to entry for both community-owned renewable energy and residential self-supply. Energy audits of a sample of homes in Qaanaaq reveal significant potential for energy efficiency improvements that can best be met via new, open-sourced designs in the Greenlandic standard housing program. Designs that have been co-created with community members and a local carpenter are presented, ensuring that the new designs overcome specific housing barriers and meet lifestyle, economic, and practical considerations. Open-sourced designs lower the cost of entry into the program and make energy-efficient designs more broadly accessible to those seeking new housing. This research provides pathways toward an affordable future in northern Greenlandic communities via solutions for lowering energy generation costs and energy burdens and increasing access to energy-efficient, affordable housing
Gastroenterology Environmental Impact Assessment: LCA in Endoscopy
No full textWith this project we aimed to understand the current state of endoscopy carbon impact and ideate several possible solution sets to help our sponsor, gastroenterologist Dr. Heiko Pohl, know where to focus future engineering design and research. In the first term of research, we reviewed LCA frameworks and observed endoscopy procedures to understand where there were opportunities to improve on the carbon footprint of the procedure. Once identified, these improvement areas were the focus of our second term of work:
1. Hypothetical packaging, shipping, and material changes
2. Designing a reusable handle for polyp removal procedures
3. Designing a mechanism to keep bioloads out of the endoscope during procedures like a bile duct explorationhttps://digitalcommons.dartmouth.edu/wetterhahn_2024/1000/thumbnail.jp
Host-Microbe Interactions and the Developing Gut Microbiome in Infants with Cystic Fibrosis
Get PDFCystic Fibrosis (CF) is a progressive genetic disease that leads to dysfunction of ion transport across epithelial cell membranes. A major hallmark in CF is chronic inflammation in the intestine, though the mechanisms by which this occurs are still unknown. Here, we describe the developing microbiome in CF infants. We first performed metagenomic sequencing on a longitudinal cohort of CF infants and compared the microbial dynamics of these samples to multiple non-CF cohorts. Through various computational approaches, we reveal a delay in the maturation of the microbiome in CF compared to non-CF, characterized by shifts in abundance and prevalence of species identified as biomarkers of age progression. These results motivate future mechanistic studies to determine whether this delay can be corrected using our age model species.
We then expanded upon this work to explore a specific metabolic pathway in CF. Indole is a beneficial derivative of the tryptophan metabolism pathway that is known to modulate intestinal inflammation. Metabolomics was performed on nine indole pathway metabolites and showed no differences between CF and non-CF samples in the first year. Machine learning was used to determine whether metabolite and metagenomic data are predictive of age and disease state. Metagenomic data was more predictive of both conditions, and non-CF machine learning models are more predictive than CF models. Reiterating the developmental delay in the CF microbiome, we emphasize the importance of correcting dysbiosis in future work.
Finally, we look at B. fragilis, which is altered in CF and investigate the effects of an associated zinc-metalloprotease toxin, B. fragilis toxin (BFT) on non-CF primary colonoids. Our preliminary results contradict the existing body of BFT literature; thus, further exploration is required prior to making any definitive conclusions on the impact of BFT in human colonoids, and before expanding into CF samples.
Together, we took a comprehensive computational approach to exploring the developing intestinal microbiome in infants with CF and reveal several novel findings that have created opportunities for future experiments with the goal of motivating novel therapeutic development to improve the quality of life of these patients
Interstellar helium voyages: Modeling and comparing theoretical and observed data
No full textThe heliosphere is the volume of space occupied by the solar plasma, surrounded by the local interstellar medium flowing around it. Interstellar neutral atoms, such as helium, can travel from the interstellar medium into the heliosphere unimpeded, affected only by gravity. Therefore, detection of these atoms provides information about the state of the local interstellar medium. This poster details the creation of programs to model the theoretical detection of interstellar neutral helium atoms, 1 AU away from the sun. The final produced plots show the flux of interstellar neutral helium on a mollweide all sky map. These plots were designed to be comparable to data from NASA\u27s IBEX satellite. Analysis of these theoretical plots and IBEX data provides insight into what atoms IBEX is likely missing in its detection.https://digitalcommons.dartmouth.edu/wetterhahn_2024/1013/thumbnail.jp
Investigating the neural circuitry of motivation in both food and social rewards
No full textEnvironmental cues that predict rewards can become attractive. Sign-tracking is a conditioned response where animals interact with reward-predicting cues due to incentive salience, or motivational value attribution. However, this behavior can become maladaptive if it remains inflexible to context or cue changes. Previous research indicates that cholinergic (ACh) neurons in the nucleus accumbens (NAc) enable behavioral flexibility in sign-tracking responses. This study aims to investigate the role of ACh transmission in the development and adaptation of sign-tracking in rodents when environmental cues change.https://digitalcommons.dartmouth.edu/wetterhahn_2024/1009/thumbnail.jp
Singular bound states in the 1D pseudoharmonic oscillator
No full textThis project aims to analyze the bound-state solutions of the one-dimensional pseudoharmonic oscillator potential. Past literature has suggested that bound-state solutions exist only when the coupling constant is greater than or equal to negative one quarter. However, previous research using matrix mechanics and a transcendental Kummer function has discovered bound-state solutions in the region less than negative one quarter. The wave functions of these solutions will be extensively studied by analyzing the limiting form of their probability distribution to understand the origins of these singular energies. Additionally, the expectation values of these wave functions will be analyzed, considering that the singular bound-state wave functions are not peaked at the origin. This analysis will also extend to a modified version of the hydrogen atom to investigate if it exhibits similar behavior. These analyses will offer insights into the essential mathematical properties of singular potentials in one dimension and explore the existence of a universal probability distribution for such states in singular one-dimensional potentials.https://digitalcommons.dartmouth.edu/wetterhahn_2024/1008/thumbnail.jp
