healthcare

Multimodal computational models for early prediction of peritoneal recurrence in gastric cancer

ABSTRACT Gastric cancer represents a significant disease burden and is a leading cause of cancer-related deaths in the United States and globally. Approximately 80% of gastric cancer patients are diagnosed at an advanced stage, with the peritoneum being the most common site of relapse (peritoneal recurrence) after radical surgery. Nearly 50% of patients with advanced-stage gastric cancer develop peritoneal recurrence post-surgery, resulting in a median survival of only 3–6 months and a markedly reduced quality of life. Early peritoneal recurrence is primarily characterized by micro-metastasis, which traditional imaging techniques struggle to detect due to the small size of metastatic nodules. Predicting the likelihood and timing of peritoneal recurrence is crucial for identifying at- risk patients, enabling timely interventions that could improve survival rates and quality of life. Unfortunately, reliable predictive biomarkers and models for peritoneal recurrence in gastric cancer are lacking in clinical practice, highlighting an urgent need for innovative predictive tools. This proposal aims to develop and validate novel predictive models for early peritoneal recurrence in gastric cancer, leveraging advanced deep learning techniques and multimodal integration of clinical, radiological (CT), and histopathological (hematoxylin and eosin, H&E) data. In Aim 1, we will develop a rational approach for predicting peritoneal recurrence by creating a novel deep learning multimodal method guided by genomics knowledge. Additionally, we will integrate both deep learning-extracted features and traditional hand-crafted radiomics features with clinical data to improve prediction accuracy. Aim 2 focuses on developing a robust prediction model of peritoneal recurrence utilizing a pre-trained foundation model from large-scale H&E image data. Aim 3 will combine CT, H&E, and clinical data to further enhance predictive capabilities, employing an innovative cross-modal collaborative optimization approach for multimodal data integration. All models will be trained and internally validated using a retrospective cohort from Atrium Health Wake Forest Baptist Comprehensive Cancer Center and externally validated in two independent cohorts from additional institutions to ensure robustness across populations and imaging protocols. Additionally, we will compare our models with existing methods, including clinical staging and alternative fusion strategies. If successful, these models will enhance risk stratification and prediction of peritoneal recurrence in gastric cancer patients, significantly improving survival rates and quality of life by identifying those likely to develop peritoneal recurrence post-surgery and facilitating timely intervention. Furthermore, they can help avoid the risk of complications and extra medical costs associated with overtreatment. Since the information is derived from routinely examined CT, H&E and clinical data, they could be seamlessly integrated into current clinical workflows. The AI technology developed through this project has the potential to benefit underserved populations in low- resource settings and reduce healthcare disparities in the U.S.

Defining Microbial and Host Pathways Driving Asymptomatic C. difficile Colonization Associated with Aging and High-Sugar Diets

SUMMARY Clostridioides difficile infection (CDI) is a leading cause of healthcare-associated diarrhea, with rising incidence in community settings and a growing burden of asymptomatic colonization. Asymptomatic car- riers, particularly among the elderly and individuals consuming high-sugar diets, represent a critical but underexplored reservoir for transmission and disease progression. This proposal introduces novel, anti- biotic-independent mouse models demonstrating that both dietary sugar and aging independently pro- mote asymptomatic C. difficile colonization. We hypothesize that these factors disrupt colonization re- sistance (CR) through distinct but overlapping microbial, metabolic, and immune pathways. In Aim 1, we will define how traditional and emerging dietary sugars alter the gut environment to permit C. difficile colonization using in vitro bioreactors and in vivo models. Aim 2 will identify age-associated changes in microbiota and mucosal immunity that impair CR, using longitudinal studies and fecal micro- biota transfer. Aim 3 will functionally validate C. difficile genes upregulated during asymptomatic carriage using CRISPR-Cas9 mutants in both sugar- and age-induced models. This integrative, multi-omics approach will uncover the mechanisms enabling asymptomatic colonization and identify microbial and host targets for intervention. The findings will inform microbiome-based strat- egies to prevent CDI in vulnerable populations and shift current paradigms in CDI risk assessment and prevention.

Regulation of neutrophil endoplasmic reticulum stress response by IRE1a

Project Summary/Abstract: The lungs are exposed to pathogens and environmental toxins that trigger stress and cause numerous respiratory diseases. Effective host defenses against lung infection by bacterial pathogens, including methicillin- resistant Staphylococcus aureus (MRSA), rely on innate immune cells including neutrophils, prominent early responders to sites of infection. If host defenses are ineffective, MRSA causes serious lung infection, resulting in severe morbidity and a significant economic burden on healthcare facilities, where it is endemic. MRSA infections have a mortality rate of up to 14% and an estimated $500 million in healthcare costs in the US alone. Increasing resistance to vancomycin, the last resort antibiotic for MRSA infections, underscore the urgent need for innovative treatment approaches. Although directly targeting pathogens with antibiotics has been a successful approach for treating infections, many pathogens, including MRSA, eventually will become resistant to these drugs. As an alternative, immunomodulatory strategies to enhance host defenses, such as those shown to be effective against cancer cells, have the potential for treating drug-resistant pathogen infections. Recently, we showed that the inositol-requiring enzyme 1-α (IRE1α), an endoplasmic reticulum (ER) stress sensor, is required for clearance of MRSA in a murine skin abscess model, where neutrophils are robustly recruited to the site of infection. Further, IRE1α coordinates signaling events upstream of calcium (Ca2+) mobilization, histone citrullination, and production of mitochondrial reactive oxygen species (mitoROS), all of which are important for neutrophil inflammatory responses including the formation of antimicrobial neutrophil extracellular traps (NETs). Because excessive neutrophil activation and NET release can be detrimental to vital organs, it is not clear whether neutrophil IRE1α-mediated stress responses aid or impede the resolution of infection in the lungs. While IRE1α activation has been linked to the development of lung fibrosis through the regulation of alveolar epithelial- to-mesenchymal transition in the context of chronic inflammatory diseases, its role in pulmonary neutrophil defenses is unknown. Thus, there is a gap in our knowledge of how cellular stress responses modulate pulmonary neutrophil defenses and infection outcomes in the lungs. The overarching goal of this proposal is to elucidate the mechanisms by which neutrophil IRE1α signaling influences production of mitoROS and Ca2+ mobilization to drive NET release, injure lungs, and regulate pulmonary host defense against MRSA. We will accomplish the following Aims: (1) Define the molecular mechanisms underlying IRE1α-mediated mitoROS hyperactivation of human and mouse primary neutrophils and excessive NET release, and (2) Elucidate the role of neutrophil IRE1α signaling in excessive NET release, lung injury, and immunity in vivo using a MRSA pneumonia infection mouse model. These studies will yield mechanistic insight into how IRE1α-driven ER stress responses impact pulmonary neutrophil defenses and lung injury revealing potential targets for anti-microbial immunotherapies.

Eosinophils promote persistence and transmission during Bordetella spp. infections

ABSTRACT Despite widespread vaccination, Bordetella spp., the causative agents of whooping cough, continue to circulate globally. Resurgent outbreaks contribute to significant healthcare burdens and costs estimated up to $79 million annually. This persistence and reemergence highlight a critical need for new therapies and prevention methods. Our laboratory investigates bacterial and host drivers that enable Bordetella success, defined as enhanced persistence, reinfection, and transmission. We have identified the Bordetella sigma factor BtrS as a regulator of immunosuppressive pathways that modulate eosinophil function. Leveraging genetically tractable Bordetella strains, advanced murine models, and immunological tools, we are uniquely positioned to dissect how eosinophils contribute to respiratory bacterial infections. Our preliminary data reveal that eosinophils promote Bordetella persistence. Our results also show that the anti-inflammatory cytokine IL1 receptor antagonist (IL1Ra) also contribute to persistence. However, the contribution of eosinophil-derived immunosuppressors remains unclear and will be investigated in Specific Aim 1. Moreover, we have evidence that eosinophils are required for nasal shedding, through mucus enhancement, and paroxysmal coughing, via exacerbation of bronchoconstriction, during Bordetella spp. infection, two key metrics of transmission. The eosinophil-effectors that promote shedding, coughing, and transmission, will be investigated in Specific Aim 2. Based on our data, we hypothesize that eosinophils contribute to Bordetella pathogenesis by (1) promoting persistent infection and (2) enhancing transmission through mucus-driven shedding and cough reflex induction. This proposal will test this hypothesis through two specific aims: Aim 1: Delineate the immunosuppressive role of eosinophils in modulating host responses and enabling Bordetella persistence. Aim 2: Define the mechanisms by which eosinophils facilitate Bordetella spp. transmission. By reframing eosinophils as active modulators of bacterial pathogenesis, this research challenges traditional views of eosinophils as terminal effector cells and positions them as novel targets for therapeutic intervention, that might be applicable to other mucosal pathogens. The outcomes will contribute to our understanding of eosinophil biology in infection and may lead to innovative strategies to halt bacterial persistence and transmission.

Improving Disease-Modifying Therapy Uptake among Patients with Multiple Sclerosis

Project Summary/Abstract Recent advances in the epidemiology of multiple sclerosis (MS) indicate that its prevalence is similar among White (238 per 100,000) and Black (226 per 100,000) populations. These data challenge historic assumptions about individuals with northern European heritage having higher risk and prevalence of MS. Evidence also suggests that MS incidence may be higher than previously recognized in the United States and increasing over time with more individuals identified and diagnosed year over year. MS continues to impose significant and growing burden on patients, healthcare systems and society. These health differences in the diagnosis, treatment and symptom management of MS in light of the increasing prevalence of MS in the US are an important public health issue that requires broader urgent research and policy attention to reduce the overall disease burden. In this study, we will use real-world data derived from the electronic health records (EHR) from four large academic medical centers (University of Kentucky, University of Virginia, Virginia Commonwealth University, and University of Southern California). Extracted EHR data from these four medical centers will be deidentified, combined, and harmonized. We will use this combined data set to examine (1) whether there are any differences in the timely treatment of disease modifying therapy (DMT) among different MS populations, (2) any disparities in the management of symptoms and comorbidities, (3) how non-medical factors of health such as income, education, and health insurance status (patientlevel), linguistically appropriate care provision (provider-level), and neighborhood factors (system-level) affect these outcomes and influence disparities across populations, and (4) assess whether disparities exist in the risks of cardiovascular disease CVD and mortality in MS subgroups and examine if these disparities can be reduced with improved treatment of MS and vascular comorbidities. In pursuing these objectives, we will identify clinical solutions (e.g., optimal DMT sequences) and non-medical factors such as neighborhood factors such as poverty, educational achievement, crime rates, civic participation, and housing quality, access to care factors, and cultural and linguistic match between providers and patients that substantially contribute to health disparities. For actionable solutions, we will rank-order these factors by their relative importance in addressing disparities, which will guide decision-making at the policy, system, and provider level. Our long-term objective is to develop public health strategies and scalable solutions to reduce overall burden in the management of MS. This project is expected to help policy makers and health system administrators in prioritizing interventions and to have implications for clinical practice in improving care of all patients with MS in neurology clinics, at the healthcare system level, and for national health policy.

Intrinsic and extrinsic mechanisms underlying trigeminal nerve deficits in familial dysautonomia

PROJECT SUMMARY Rare diseases impose a significant burden on the US healthcare system, accounting for nearly half of all expenditures for their treatment. This statistic alone supports the need to invest in research to develop therapeutic interventions for rare diseases since the economic benefit outweighs the continued expense of financial resources. Familial dysautonomia (FD) is a rare, hereditary disease that arises from a splice site mutation in Elongator acetyltransferase complex subunit 1 (ELP1) and impacts the nervous system. To date, FD patients continue to face life-threatening complications involving basic involuntary functions like swallowing and somatosensation because there is no cure for this ultimately fatal neuropathy. FD patients exhibit symptoms due to defects in their somatosensory trigeminal nerves, whose cell bodies reside in the trigeminal ganglion (TG) and are derived from neural crest and placode cells. Recent studies from our lab using an FD mouse model (Elp1 deleted from neural crest cells) revealed TG axon outgrowth and target tissue innervation deficits, recapitulating phenotypes observed in FD patients. However, the mechanisms by which Elp1 mediates normal TG development, and how this goes awry in FD, remain largely elusive. To gain insight into Elp1 function, we performed mass spectrometry to evaluate the TG proteome of normal and FD mouse embryos. Our results uncovered statistically significant increases in extracellular matrix (ECM) and ECM binding proteins, pointing to altered TG biomechanical properties and, more broadly, changes in mechanotransduction, the process by which cells translate extrinsic cues into intrinsic signaling pathways that modulate gene expression. Importantly, proper axon outgrowth relies upon mechanotransduction as growth cones on axons sense and respond to their environment. In the head, this environment consists of ECM and cranial mesenchyme cells, but the impact of Elp1 loss from the latter is not known, including the potential for altered tissue biomechanics that could influence TG axon outgrowth. We hypothesize that loss of Elp1 induces changes in the biomechanical properties of both the TG/nerves and ECM/cranial mesenchyme, modifying mechanotransduction and leading to TG defects in FD, which we will interrogate in the following Specific Aims: 1) define the biomechanical properties of the TG/nerves and ECM/cranial mesenchyme and 2) determine the role of cranial mesenchyme Elp1 in mediating proper TG axon outgrowth. Our innovative research proposal takes a systems-level, multidisciplinary approach involving embryology, biomechanics, and high-resolution microscopy, with the goal of integrating molecular, cellular, and tissue data. These results will significantly advance our knowledge of the molecular mechanisms underscoring TG development and, collectively, inform treatment strategies for birth defects or disorders like FD with TG dysfunction, as well as nerve repair and/or regeneration after injury or disease.

Engineering inducible morphotype switching control in Mycobacterium abscessus for investigating infection outcomes and discovering pathophysiological-targeted treatments

PROJECT SUMMARY Antibiotic-resistant nontuberculous mycobacteria (NTM) infections are rising at a rate of 8% each year and account for ~$1.7 billion in annual U.S. healthcare costs. Mycobacterium abscessus (Mabs), the most common rapidly growing NTM infection, is notoriously nicknamed the “antibiotic nightmare” for its extensive intrinsic and inducible broad-range multidrug resistance to antibiotic countermeasures. As part of its natural infection cycle, Mabs undergoes a morphotypical conversion from smooth to rough, characterized by irreversible genetic changes resulting in the loss of cell envelope glycopeptidolipids (GPLs). This morphotypic conversion is intimately associated with disease progression, ultimately leading to debilitating, refractory Mabs pulmonary disease. Specific stimuli triggering Mabs morphotypical conversion are unknown, thus preventing directed investigations into morphotype-specific immunological responses and the discovery of morphotype-specific therapeutic targets. This project leverages cutting-edge molecular genetic tools, including CRISPR (clustered regularly interspersed short palindromic repeats) interference (CRISPRi) and inducible knockdown control of CRISPRi via the anhydrotetracycline-inducible TetR-regulated promoter-operator system, to create six unique, reversible Mabs smooth to conditional rough morphotype strains. These molecular morphoswitchable strains allow precise investigator-mediated on-off control of Mabs surface GPLs, enabling investigations into Mabs morphological plasticity, unique pathophysiology traits associated with each morphotype, and the complex interplay between Mabs and morphotype-specific immunological responses. In Aim 1, we implement CRISPRi inducible knockdown tunable control of Mabs morphotype switching by targeting six, independent genetic targets directly involved in GPL biosynthesis (mps1, mps2) or transport (mmpS4, mmpL4a, mmpL4b, gap) and validate in vitro morphoswitching. In Aim 2, we establish and confirm Mabs morphoswitching and intracellular growth in infected THP-1 macrophages. Subsequently, we evaluate differential and distinct innate cellular immune responses elicited by Mabs smooth and Mabs conditional rough morphotypes during intracellular infection in human primary monocyte-derived macrophages. Collectively, these studies create a suite of characterized and reversible Mabs smooth and conditional rough morphoswitchable strains with controlled, regulated, and on- demand expression of Mabs surface GPLs. By enabling precisely timed and controlled induction of the Mabs conditional rough morphotype during intracellular growth, we can molecularly dissect and investigate fundamental Mabs host-pathogen interactions and immunological responses that so substantially influence negative clinical outcomes.

The Insights and Outcomes of the Wellcome-funded Waiting Times Project

Waiting is one of healthcare’s core experiences. It is there in the time it takes to access services; through the days, weeks, months or years needed for diagnoses; in the time that treatment takes; and in the elongated time-frames of recovery, relapse, remission and dying.Funded by the Wellcome Trust, our project opens up what it means to wait in and for healthcare by examining lived experiences, representations and histories of delayed and impeded time.In an era in which time is lived at increasingly different and complex tempos, Waiting Times looks to understand both the difficulties and vital significance of waiting for practices of care, offering a fundamental re-conceptualisation of the relation between time and care in contemporary thinking about health, illness, and wellbeing.

AI for Multi-centre Epilepsy Lesion Detection on MRI

Epilepsy surgery is a safe but underutilised treatment for drug-resistant focal epilepsy. One challenge in the presurgical evaluation of patients with drug-resistant epilepsy are patients considered “MRI negative”, i.e. where a structural brain abnormality has not been identified on MRI. A major pathology in “MRI negative” patients is focal cortical dysplasia (FCD), where lesions are often small or subtle and easily missed by visual inspection. In recent years, there has been an explosion in artificial intelligence (AI) research in the field of healthcare. Automated FCD detection is an area where the application of AI may translate into significant improvements in the presurgical evaluation of patients with focal epilepsy. I will provide an overview of our automated FCD detection work, the Multicentre Epilepsy Lesion Detection (MELD) project and how AI algorithms are beginning to be integrated into epilepsy presurgical planning at Great Ormond Street Hospital and elsewhere around the world. Finally, I will discuss the challenges and future work required to bring AI to the forefront of care for patients with epilepsy.

Children-Agent Interaction For Assessment and Rehabilitation: From Linguistic Skills To Mental Well-being

Socially Assistive Robots (SARs) have shown great potential to help children in therapeutic and healthcare contexts. SARs have been used for companionship, learning enhancement, social and communication skills rehabilitation for children with special needs (e.g., autism), and mood improvement. Robots can be used as novel tools to assess and rehabilitate children’s communication skills and mental well-being by providing affordable and accessible therapeutic and mental health services. In this talk, I will present the various studies I have conducted during my PhD and at the Cambridge Affective Intelligence and Robotics Lab to explore how robots can help assess and rehabilitate children’s communication skills and mental well-being. More specifically, I will provide both quantitative and qualitative results and findings from (i) an exploratory study with children with autism and global developmental disorders to investigate the use of intelligent personal assistants in therapy; (ii) an empirical study involving children with and without language disorders interacting with a physical robot, a virtual agent, and a human counterpart to assess their linguistic skills; (iii) an 8-week longitudinal study involving children with autism and language disorders who interacted either with a physical or a virtual robot to rehabilitate their linguistic skills; and (iv) an empirical study to aid the assessment of mental well-being in children. These findings can inform and help the child-robot interaction community design and develop new adaptive robots to help assess and rehabilitate linguistic skills and mental well-being in children.

From bench to clinic – Translating fundamental neuroscience into real-life healthcare practices, and developing nationally recognised life science companies

Dr. Ryan C.N. D’Arcy is a Canadian neuroscientist, researcher, innovator and entrepreneur. Dr. D'Arcy co-founded HealthTech Connex Inc. and serves as President and Chief Scientific Officer. HealthTech Connex translates neuroscience advances into health technology breakthroughs. D'Arcy is most known for coining the term "brain vital signs" and for leading the research and development of the brain vital signs framework. Dr. D’Arcy also holds a BC Leadership Chair in Medical Technology, is a full Professor at Simon Fraser University, and a member of the DM Centre for Brain Health at the University of British Columbia. He has published more than 260 academic works, attracted more than $85 Million CAD in competitive research and innovation funding, and been recognized through numerous awards and distinctions. Please join us for an exciting virtual talk with Dr. D'Arcy who will speak on some of the current research he is involved in, how he is translating this research into real-life applications, and the development of HealthTech Connects Inc.

Inclusive Data Science

A single person can be the source of billions of data points, whether these are generated from everyday internet use, healthcare records, wearable sensors or participation in experimental research. This vast amount of data can be used to make predictions about people and systems: what is the probability this person will develop diabetes in the next year? Will commit a crime? Will be a good employee? Is of a particular ethnicity? Predictions are simply represented by a number, produced by an algorithm. A single number in itself is not biased. How that number was generated, interpreted and subsequently used are all processes deeply susceptible to human bias and prejudices. This session will explore a philosophical perspective of data ethics and discuss practical steps to reducing statistical bias. There will be opportunity in the last section of the session for attendees to discuss and troubleshoot ethical questions from their own analyses in a ‘Data Clinic’.

Portable neuroscience: using devices and apps for diagnosis and treatment of neurological disease

Scientists work in laboratories; comfortable spaces which we equip and configure to be ideal for our needs. The scientific paradigm has been adopted by clinicians, who run diagnostic tests and treatments in fully equipped hospital facilities. Yet advances in technology mean that that increasingly many functions of a laboratory can be compressed into miniature devices, or even into a smartphone app. This has the potential to be transformative for healthcare in developing nations, allowing complex tests and interventions to be made available in every village. In this talk, I will give two examples of this approach from my recent work. In the field of stroke rehabilitation, I will present basic research which we have conducted in animals over the last decade. This reveals new ways to intervene and strengthen surviving pathways, which can be deployed in cheap electronic devices to enhance functional recovery. In degenerative disease, we have used Bayesian statistical methods to improve an algorithm to measure how rapidly a subject can stop an action. We then implemented this on a portable device and on a smartphone app. The measurement obtained can act as a useful screen for Parkinson’s Disease. I conclude with an outlook for the future of this approach, and an invitation to those who would be interesting in collaborating in rolling it out to in African settings.

Harnessing Mindset in 21st Century Healthcare

Mindsets are core assumptions about the nature and workings of things in the world that orient us to a particular set of attributions, expectations, and goals. Our study of mindsets is, in part, inspired by research on the placebo effect, a robust demonstration of the ability of mindsets, conscious or subconscious, to elicit physiological changes in the body. This talk will explore the role of mindsets in three stages of chronic disease progression: genetic predisposition, behavioral prevention, and clinical treatment. I will discuss the mechanisms through which mindsets influence health as well as the myriad ways that mindsets can be more effectively leveraged to motivate healthy behaviors and improve 21st century healthcare.

European University for Brain and Technology Virtual Opening

The European University for Brain and Technology, NeurotechEU, is opening its doors on the 16th of December. From health & healthcare to learning & education, Neuroscience has a key role in addressing some of the most pressing challenges that we face in Europe today. Whether the challenge is the translation of fundamental research to advance the state of the art in prevention, diagnosis or treatment of brain disorders or explaining the complex interactions between the brain, individuals and their environments to design novel practices in cities, schools, hospitals, or companies, brain research is already providing solutions for society at large. There has never been a branch of study that is as inter- and multi-disciplinary as Neuroscience. From the humanities, social sciences and law to natural sciences, engineering and mathematics all traditional disciplines in modern universities have an interest in brain and behaviour as a subject matter. Neuroscience has a great promise to become an applied science, to provide brain-centred or brain-inspired solutions that could benefit the society and kindle a new economy in Europe. The European University of Brain and Technology (NeurotechEU) aims to be the backbone of this new vision by bringing together eight leading universities, 250+ partner research institutions, companies, societal stakeholders, cities, and non-governmental organizations to shape education and training for all segments of society and in all regions of Europe. We will educate students across all levels (bachelor’s, master’s, doctoral as well as life-long learners) and train the next generation multidisciplinary scientists, scholars and graduates, provide them direct access to cutting-edge infrastructure for fundamental, translational and applied research to help Europe address this unmet challenge.

The early impact of COVID-19 on mental health and community physical health services and their patients’ mortality in Cambridgeshire and Peterborough, UK

COVID -19 has affected social interaction and healthcare worldwide. This talk will focus on the impact of the pandemic and “lockdown” on mental health services, community physical health services, and patient mortality in Cambridgeshire and Peterborough, based on the analysis of de-identified data from the primary NHS provider of secondary care mental health services to this population (~0.86 million)

Burnout evaluation in the healthcare workers during the covid-19

Quantitative Aversive Cognitive Testing (QACT): a new toolkit for digital healthcare

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