HMS Scholarly Articles

Background: Fentanyl is a synthetic opioid that is widely used in anesthesiology, but its illicit use is rapidly increasing. At high doses fentanyl induces unconsciousness and muscle rigidity, the mechanisms of which are poorly understood. Since animal models are needed to study these effects, the aim of this study was to establish a rat model of fentanyl abuse and investigate the effects of repeated high-dose fentanyl injections on loss of righting reflex, heart rate, respiratory depression, muscle, and brain activity. Methods: Male and female Sprague-Dawley rats were studied (n=40). A bolus of 100µg/kg fentanyl was administered intravenously twice a week for five consecutive weeks. Time to return of righting reflex (RORR) after fentanyl injection and changes in EMG/EEG activity as well as heart rate were analyzed. Additionally, arterial blood gas analysis for evaluation of ventilation was performed. Mixed-effect models with Dunnet’s test and effect sizes were used for statistical analysis. Results: Repeated injections resulted in a U-shaped change in time to RORR with the longest latency after the first exposure (median: 50[1st-3rd quartile:36-56]min) and the shortest after the fifth exposure (16[13-33]min). Following fentanyl administration, heart rate dropped immediately by 225[95%CI: 179, 271]bpm (F=3952.16, p<.001), while EMG activity increased by 291[95%CI: 212, 370]% (F=27.51, p<0.001) and PaCO2 inclined by 49.4[95%CI: 40.6, 58.2]mmHg (F=75.97, p<0.001) within 5 minutes after injection. Additionally, pH decreased by 0.48[95%CI: 0.41, 0.54] (F=142.00, p<0.01), and PaO2 decreased by 50.4[40.8, 60.0]mmHg (F=57.90, p<0.001). Repeated fentanyl exposures did not significantly affect the extent of these changes (EMG: F=1.63, p=0.237; PaCO2: F=1.23, p=0.312; HR: F=1.05, p=0.400; pH: F=3.05, p=0.066; pO2: F=3.35, p=0.052). EEG analysis revealed that repeated fentanyl exposures elicited significantly higher absolute power in frequencies >20Hz as indicated by an area under the receiver operator characteristics curve >0.7. Conclusion: We established a rodent model of repeated, high-dose fentanyl administration. Overall, significant evidence of tolerance was not observed after ten exposures of high-dose fentanyl for any of the analyzed parameters. These results suggest that tolerance does not develop for fentanyl-induced unconsciousness, muscle rigidity, or respiratory depression.

Access to timely, pediatric-specific medical care is critical for every acutely ill child to prevent complications, long-term disability, and untimely death. This is particularly important in contexts such as immigration detention facilities, which pose unique risks to children. A retrospective observational study was conducted of 165 children who were detained at the Karnes Family Residential Facility from June 2018 to October 2020. Acute care visits completed at the facility were reviewed. Chart notes for three of the top six chief complaints (i.e. cough, fever, and diarrhea) were analyzed for a series of quality measures derived from national clinical guidelines. The analysis revealed significant deviations from clinical standards, including incomplete clinical assessment, a failure to determine a clinical diagnosis, and inappropriate prescribing. These deviations were noted with alarming frequency, suggesting a systemic failure in adherence to standards of care. Detention is never in the best interest of the child and must end. However, as long as immigrant children remain detained in the US, they must receive age-appropriate healthcare that meets quality standards. Critical review, external oversight, and reforms of medical care in immigration detention are essential to ensure that children are protected from the preventable increased morbidity and mortality associated with this setting. Ample research has documented the inadequacy of healthcare in U.S. immigration detention for adults, however empiric data on pediatric care in these facilities remain limited. This study is the first to examine pediatric acute care using primary data from children’s medical records.

Cleavage factor I mammalian (CFIm) complex, composed of cleavage and polyadenylation specificity factor 5 (CPSF5) and serine/arginine-like protein CPSF6, regulates alternative polyadenylation (APA). Loss of CFIm function results in proximal polyadenylation site usage, shortening mRNA 3  untranslated regions (UTRs). Although CPSF6 plays additional roles in human disease, its nuclear translocation mechanism remains unresolved. Two  - karyopherins, transportin (TNPO) 1 and TNPO3, can bind CPSF6 in vitro, and we demonstrate here that while the TNPO1 binding site is dispensable for CPSF6 nuclear import, the arginine/serine (RS)-like domain (RSLD) that mediates TNPO3 binding is critical. The crystal structure of the RSLD-TNPO3 complex revealed potential CPSF6 interaction residues, which were confirmed to mediate TNPO3 binding and CPSF6 nuclear import. Both binding and nuclear import were independent of RSLD phosphorylation, though a hyperphosphorylated mimeticmutant failed to bind TNPO3 and mislocalized to the cell cytoplasm. Although hypophosphorylated CPSF6 largely supported normal polyadenylation site usage, a significant number of mRNAs harbored unnaturally extended 3  UTRs, similar to what is observed when other APA regulators, such as CFIIm component proteins, are depleted. Our results clarify the mechanism of CPSF6 nuclear import and highlight differential roles for RSLD phosphorylation in

The host chromatin-binding factor LEDGF/p75 interacts with HIV-1 integrase and directs integration to active transcription units. To understand how LEDGF/p75 recognizes transcription units, we sequenced 1 million HIV-1 integration sites isolated from cultured HEK293T cells. Analysis of integration sites showed that cancer genes were preferentially targeted, raising concerns about using lentivirus vectors for gene therapy. Additional analysis led to the discovery that introns and alternative splicing contributed significantly to integration site selection. These correlations were independent of transcription levels, size of transcription units, and length of the introns. Multi-variate analysis with five parameters previously found to predict integration sites showed that intron density is the strongest predictor of integration density in transcription units. Analysis of previously published HIV-1 integration site data showed that integration density in transcription units in mouse embryonic fibroblasts also correlated strongly with intron number, and this correlation was absent in cells lacking LEDGF. Affinity purification showed that LEDGF/p75 is associated with a number of splicing factors, and RNA sequencing (RNA-seq) analysis of HEK293T cells lacking LEDGF/p75 or the LEDGF/p75 integrase-binding domain (IBD) showed that LEDGF/p75 contributes to splicing patterns in half of the transcription units that have alternative isoforms. Thus, LEDGF/p75 interacts with splicing factors, contributes to exon choice, and directs HIV-1 integration to transcription units that are highly spliced.

This presentation examines the correlation between R-loops and HIV-1 integration, highlighting experimental results generated in our study. The work was presented at the Behavior of HIV in Viral Environments (B-HIVE) Center Face-to-Face Meeting.

Background: In the study of coronary artery disease, the mechanisms underlying atherosclerosis initiation and progression or regression remain incompletely understood. Our research conceptualized the cardiovascular system as an integrated network of pumps and pipes, advocating for a paradigm shift from static imaging of coronary stenosis to dynamic assessments of coronary flow. Further review of fluid mechanics highlighted the water hammer phenomenon as a compelling analog for processes in coronary arteries. Methods: In this review, the analytical methodology employed a comprehensive, multifaceted approach that incorporated a review of fluid mechanics principles, in vitro acoustic experimentation, frame-by-frame visual angiographic assessments of in vivo coronary flow, and an artificial intelligence (AI) protocol designed to analyze the water hammer phenomenon within an acoustic framework. In the analysis of coronary flow, the angiograms were selected from patients with unstable angina if they had previously undergone one or more coronary angiograms, allowing for a longitudinal comparison of dynamic flow and phenomena. Results: The acoustic investigations pinpointed pockets of contrast concentrations, which might correspond to compression and rarefaction zones. Compression antinodes were correlated to severe stenosis, due to rapid shifts from low-pressure diastolic flow to high-pressure systolic surges, resulting in intimal injury. Rarefaction antinodes were correlated with milder lesions, due to de-escalating transitions from high systolic pressure to lower diastolic pressure. The areas of nodes remained without lesions. Based on the locations of antinodes and nodes, a coronary acoustic action map was constructed, enabling the identification of existing lesions, forecasting the progression of current lesions, and predicting the development of future lesions. Conclusions: The results suggested that intimal injury was likely induced by acoustic retrograde pressure waves from the water hammer phenomenon and developed new lesions at specifically exact locations.

In the study of coronary artery disease (CAD), the mechanism of plaque formation and development is still an important subject for investigation. A limitation of current coronary angiography (CAG) is that it can only show static images of the narrowing of arterial channels without identifying the mechanism of the disease or predicting its progression or regression. To address this limitation, the CAG technique has been modified. The new approach emphasizes identifying and analyzing blood flow patterns, employing methodologies akin to those used by hydraulic engineers for fluid or gas movement through domestic or industrial pipes and pumps. With the new technique, various flow patterns and arterial phenomena—such as laminar, turbulent, antegrade, retrograde, and recirculating flow and potentially water hammer shock and vortex formation—are identified, recorded, and classified. These phenomena are then correlated with the presence of lesions at different locations within the coronary vasculature. The formation and growth of these lesions are explained from the perspective of fluid mechanics. As the pathophysiology of CAD and other cardiovascular conditions becomes clearer, new medical, surgical, and interventional treatments could be developed to reverse abnormal coronary flow dynamics and restore laminar flow, leading to improved clinical outcomes.

Background: In the research of coronary artery disease, the precise initial injury that starts the atherosclerotic cascade remains unidentified. Moreover, the mechanisms governing the progression or regression of coronary plaque are not yet fully understood. Based on the concept that the cardiovascular system is a network of pumps and pipes, could fluid mechanics principles and practices elucidate the question of atherosclerosis using flow dynamics images from a novel angiographic technique, focusing on antegrade and retrograde flows and their collisions in iliac and coronary arteries?

Methods: From January 2023 to May 2024, coronary angiograms of all hemodynamically stable patients with stable or unstable angina were screened. The angiograms displaying either no lesions (normal) or mild-to-moderate lesions were selected. Each patient underwent an evaluation of flow dynamics and arterial phenomena in both iliac and right coronary arteries. For each artery, data were categorized based on the following parameters: laminar versus non-laminar flow, presence versus absence of collisions, and presence versus absence of retrograde flow. Additionally, in two sub-studies, we analyzed the relationship between retrograde flow and blood pressure, and artificial intelligence algorithms were used to detect the retrograde flow in the right coronary artery.

Results: A total of 95 patients were screened, and 51 were included in this study. The results comprised quantitative data (prevalence of laminar flows, collisions, and retrograde flows) and qualitative data (morphological characteristics of antegrade laminar flow, retrograde contrast flow, and instances of flow collision). The results showed that in the iliac artery, laminar flow was observed in 47.06% (24/51) of cases, with collisions noted in 23.53% (12/51). Retrograde flow was present in 47.06% (24/51) of cases, and notably, 75% (18/24) of these cases were associated with uncontrolled diastolic blood pressure (DBP) above 80 mmHg (p < 0.001). Conversely, in the RCA, laminar flow was observed in 54.9% (28/51) of cases, with collisions noted in only 3.92% (2/51). Retrograde flow was identified in 7.84% (4/51) of cases, and all these cases (100%, 4/4) were associated with uncontrolled systolic blood pressure (SBP) above 120 mmHg, though statistical significance was not reached due to the small sample size (p > 0.05).

Conclusions: Based on the concept that the cardiovascular system is a network of pumps and pipes, this research methodology provides intriguing insights into arterial flow behaviors by integrating fluid mechanics practices with novel angiographic observations. The preliminary results of this study identified laminar flow as the predominant pattern, with retrograde flow and collisions occurring infrequently. The implications of vortex, collision, and disorganized flow highlight potential mechanisms for endothelial damage and atherosclerosis initiation. Moreover, the correlation with blood pressure underscores the critical role of hypertension management in preventing adverse hemodynamic events. Future directions include refining imaging techniques and further exploring the mechanistic links between flow dynamics and vascular pathophysiology to enhance diagnostic and therapeutic strategies for cardiovascular diseases.

Word Embeddings In Mental Health

Mental health related diagnoses have been on the rise these last years, especially since the pandemic. In the CELEHS laboratory, we analyze electronic health records to help clinicians identify at-risk patients requiring follow-up. In this talk I will present the results of Glove word embeddings on 8,000 open-access suicide-related publications, using the text2vec, opticskxi and sgraph R packages. I developed a novel methodology based on random projections to efficiently find diverse clusters of related concepts in unstructured text data, and evaluate the results by predicting pairs of related concepts, and comparing them to clinician-based known relationships. While many biomedical natural language processing approaches focus on the analysis of specific known concepts, as the ones indexed by the Unified Medical Language System (UMLS), the analysis of the complete text can enable to find novel relationships and borderline concepts.

The Diagnostic and Statistical Manual of Mental Disorders (DSM) is the main reference for clinicians to diagnose mental health diseases, and describes sets of symptoms that form the required diagnostic criteria for each disease. The DSM emphasizes that many patients are diagnosed with multiple conditions, and that current diagnoses could benefit from introducing multidimensional assessments, by taking into account the severity, intensity, duration, and combinations of symptoms, to form more precise diagnostics and help treatment. The DSM also underlines the necessity for diagnoses that take into account the spectrum and gradients of disorders observed, as in schizoaffective and autism spectrum disorders. To this end, the analysis of unstructured text data can help identify clusters of conditions and enable new multidimensional classifications of mental health disorders.

My talk will first present an overview of the problematic as underlined in the DSM and introduce Glove word embeddings using the text2vec package on a set of 8,000 open-access suicide-related publications. I then demonstrate how to explore the embeddings using vector operations to manually find clusters of related concepts, and in a second step automate the discovery of such clusters using the density-based clustering package opticskxi, and visualize the clusters as graphs using the sgraph network visualization package. Further clusters are then discovered by applying semi-directed vector operations, a novel method inspired by random projections. In a last step, I introduce ways to evaluate such clusters, using a database of 17,000 known concepts pairs curated by clinicians with expert knowledge, by predicting pairs of related concepts using a false positive threshold cut-off on cosine similarities.

Novel methodologies in natural language processing will enable us to further understand mental health disorders and their interactions. Specific disorders have been associated to personality traits, as schizophrenia with neuroticism and autism with obsessive-compulsive, and the modeling of such interactions and the further discovery of novel interactions will enable us to enhance the treatment of mental health disorders and identify clinically-actionable features.

Main Sections

00:00 Introduction, Center for Suicide Research and Prevention project 05:42 Text processing and embeddings computation 18:11 Exploration of embeddings, vector operations 29:51 Density-based clustering with OPTICS k-Xi 36:20 Evaluation and knowledge graph generation

More Resources

Center for Suicide Research and Prevention: https://csrp.mgh.harvard.edu/ Git repository of demo: https://gitlab.com/thomaschln/psychclust_rmed24 OPTICS k-Xi density based clustering R package: https://cran.r-project.org/package=opticskxi Knowledge graphs R package: https://cran.r-project.org/package=kgraph