Pre-Exposure Prophylaxis Care Cascade Among Men Who Have Sex with Men Engaging in Partner Notification Services at a Sexually Transmitted Infections Clinic.

Partner notification services (PNS) offers opportunities to discuss HIV pre-exposure prophylaxis (PrEP) and provide referrals. We evaluated the PrEP care cascade among men who have sex with men (MSM) engaging in PNS within a sexually transmitted infections clinic. Among 121 MSM eligible for PrEP during PNS, 21% subsequently initiated PrEP.

Integration of Partner Notification Services at a Sexually Transmitted Infections Clinic.

OBJECTIVES: PNS is critical to prevent the spread of STIs. We evaluated the feasibility of integrating PNS into an STI clinic focused on MSM. DESIGN/METHODS: The RI STI Clinic, in partnership with the RIDOH, implemented a PNS program in 2019. Interviews with patients diagnosed with gonorrhea/ syphilis were conducted. RIDOH attempted outreach to partners identified. We utilized interview data among MSM diagnosed with gonorrhea/syphilis in clinic from 1/1/19-12/31/2021. Bivariate analyses/multivariable logistic regression were conducted. RESULTS: 341 MSM were diagnosed with gonorrhea/syphilis during the three-year period, and 233 (68%) interviews were completed. Partner information was provided in 173 (74%) interviews. At least one workable partner was provided in 110 (47%) interviews. No statistically significant associations between provision of workable partners and index patient age/race/ethnicity were found. CONCLUSIONS: PNS at an STI clinic was successful, but challenges led to suboptimal information. Research is needed to identify barriers to integrate/optimize PNS in STI clinics.

An Automated Bioinformatics Pipeline Informing Near-Real-Time Public Health Responses to New HIV Diagnoses in a Statewide HIV Epidemic.

Molecular HIV cluster data can guide public health responses towards ending the HIV epidemic. Currently, real-time data integration, analysis, and interpretation are challenging, leading to a delayed public health response. We present a comprehensive methodology for addressing these challenges through data integration, analysis, and reporting. We integrated heterogeneous data sources across systems and developed an open-source, automatic bioinformatics pipeline that provides molecular HIV cluster data to inform public health responses to new statewide HIV-1 diagnoses, overcoming data management, computational, and analytical challenges. We demonstrate implementation of this pipeline in a statewide HIV epidemic and use it to compare the impact of specific phylogenetic and distance-only methods and datasets on molecular HIV cluster analyses. The pipeline was applied to 18 monthly datasets generated between January 2020 and June 2022 in Rhode Island, USA, that provide statewide molecular HIV data to support routine public health case management by a multi-disciplinary team. The resulting cluster analyses and near-real-time reporting guided public health actions in 37 phylogenetically clustered cases out of 57 new HIV-1 diagnoses. Of the 37, only 21 (57%) clustered by distance-only methods. Through a unique academic-public health partnership, an automated open-source pipeline was developed and applied to prospective, routine analysis of statewide molecular HIV data in near-real-time. This collaboration informed public health actions to optimize disruption of HIV transmission.

Not all clusters are equal: dynamics of molecular HIV-1 clusters in a statewide Rhode Island epidemic.

OBJECTIVES: Molecular epidemiology is a powerful tool to characterize HIV epidemics and prioritize public health interventions. Typically, HIV clusters are assumed to have uniform patterns over time. We hypothesized that assessment of cluster evolution would reveal distinct cluster behavior, possibly improving molecular epidemic characterization, towards disrupting HIV transmission. DESIGN: Retrospective cohort. METHODS: Annual phylogenies were inferred by cumulative aggregation of all available HIV-1 pol sequences of individuals with HIV-1 in Rhode Island (RI) between 1990 and 2020, representing a statewide epidemic. Molecular clusters were detected in annual phylogenies by strict and relaxed cluster definition criteria, and the impact of annual newly-diagnosed HIV-1 cases to the structure of individual clusters was examined over time. RESULTS: Of 2153 individuals, 31% (strict criteria) - 47% (relaxed criteria) clustered. Longitudinal tracking of individual clusters identified three cluster types: normal, semi-normal and abnormal. Normal clusters (83-87% of all identified clusters) showed predicted growing/plateauing dynamics, with approximately three-fold higher growth rates in large (15-18%) vs. small (∼5%) clusters. Semi-normal clusters (1-2% of all clusters) temporarily fluctuated in size and composition. Abnormal clusters (11-16% of all clusters) demonstrated collapses and re-arrangements over time. Borderline values of cluster-defining parameters explained dynamics of non-normal clusters. CONCLUSIONS: Comprehensive tracing of molecular HIV clusters over time in a statewide epidemic identified distinct cluster types, likely missed in cross-sectional analyses, demonstrating that not all clusters are equal. This knowledge challenges current perceptions of consistent cluster behavior over time and could improve molecular surveillance of local HIV epidemics to better inform public health strategies.

Beyond HIV outbreaks: protocol, rationale and implementation of a prospective study quantifying the benefit of incorporating viral sequence clustering analysis into routine public health interventions.

INTRODUCTION: HIV continues to have great impact on millions of lives. Novel methods are needed to disrupt HIV transmission networks. In the USA, public health departments routinely conduct contact tracing and partner services and interview newly HIV-diagnosed index cases to obtain information on social networks and guide prevention interventions. Sequence clustering methods able to infer HIV networks have been used to investigate and halt outbreaks. Incorporation of such methods into routine, not only outbreak-driven, contact tracing and partner services holds promise for further disruption of HIV transmissions. METHODS AND ANALYSIS: Building on a strong academic-public health collaboration in Rhode Island, we designed and have implemented a state-wide prospective study to evaluate an intervention that incorporates real-time HIV molecular clustering information with routine contact tracing and partner services. We present the rationale and study design of our approach to integrate sequence clustering methods into routine public health interventions as well as related important ethical considerations. This prospective study addresses key questions about the benefit of incorporating a clustering analysis triggered intervention into the routine workflow of public health departments, going beyond outbreak-only circumstances. By developing an intervention triggered by, and incorporating information from, viral sequence clustering analysis, and evaluating it with a novel design that avoids randomisation while allowing for methods comparison, we are confident that this study will inform how viral sequence clustering analysis can be routinely integrated into public health to support the ending of the HIV pandemic in the USA and beyond. ETHICS AND DISSEMINATION: The study was approved by both the Lifespan and Rhode Island Department of Health Human Subjects Research Institutional Review Boards and study results will be published in peer-reviewed journals.

Patient and physician preferences for non-invasive diagnostic cardiovascular imaging technologies: a discrete choice experiment.

PURPOSE: Diagnostic imaging techniques have to be selected for their accuracy, efficiency, cost-efficiency, and impact on outcome. But beyond that, the choice of non-invasive cardiovascular imaging tests for diagnosing coronary artery disease also has to respect patient safety and comfort. In this study, we investigated patient and physician preference in relation to the choice of cardiovascular imaging tests. RESULTS: A total of 211 subjects (148 cardiac patients and 63 physicians) were enrolled and completed a discrete choice experiment. Tests and modalities were deconstructed into 6 attributes (risks and side effects, diagnostic accuracy, patient out-of-pocket cost, type of procedure, type of scanner and test duration). A Sawtooth software choice-based conjoint analysis with hierarchical Bayes estimation was performed and showed the risks and side effects attribute was assigned the most relative importance (30%) when considering patients' preference. Patients gave notably high value to tests with milder side effects, while preferring to avoid exposure to ionizing radiation and risks associated the use of pharmacological agents inducing direct coronary arteriolar vasodilation. Physicians allocated more importance to the patient out-of-pocket cost attribute (29%). Both patients and physicians valued tests' risks and side effects, diagnostic accuracy, patient out-of-pocket cost as the three most important attributes, but in diverging order. A market simulation comparing current cardiovascular imaging tests revealed breathing maneuver-enhanced cardiac magnetic resonance had the highest shares of preference in both patients (59.6%) and physicians (32.7%). CONCLUSION: A patients' preference for a particular cardiovascular imaging test was most determined by the risks and side effects, while physicians prioritized less costly tests for their patients. In shared decision-making with patients, physicians should therefore focus on a balanced discussion of risks and side effects associated with cardiovascular imaging tests. Both, patients and physicians would prefer a cardiovascular MR imaging test using a vasoactive breathing maneuver instead of currently used alternatives that require intravenous contrast agents, pharmacological stress, or radiation.

Statewide Longitudinal Trends in Transmitted HIV-1 Drug Resistance in Rhode Island, USA.

BACKGROUND: HIV-1 transmitted drug resistance (TDR) remains a global challenge that can impact care, yet its comprehensive assessment is limited and heterogenous. We longitudinally characterized statewide TDR in Rhode Island. METHODS: Demographic and clinical data from treatment-naïve individuals were linked to protease, reverse transcriptase, and integrase sequences routinely obtained over 2004-2020. TDR extent, trends, impact on first-line regimens, and association with transmission networks were assessed using the Stanford Database, Mann-Kendall statistic, and phylogenetic tools. RESULTS: In 1123 individuals, TDR to any antiretroviral increased from 8% (2004) to 26% (2020), driven by non-nucleotide reverse transcriptase inhibitor (NNRTI; 5%-18%) and, to a lesser extent, nucleotide reverse transcriptase inhibitor (NRTI; 2%-8%) TDR. Dual- and triple-class TDR rates were low, and major integrase strand transfer inhibitor resistance was absent. Predicted intermediate to high resistance was in 77% of those with TDR, with differential suppression patterns. Among all individuals, 34% were in molecular clusters, some only with members with TDR who shared mutations. Among clustered individuals, people with TDR were more likely in small clusters. CONCLUSIONS: In a unique (statewide) assessment over 2004-2020, TDR increased; this was primarily, but not solely, driven by NNRTIs, impacting antiretroviral regimens. Limited TDR to multiclass regimens and pre-exposure prophylaxis are encouraging; however, surveillance and its integration with molecular epidemiology should continue in order to potentially improve care and prevention interventions.

KRAS G12C fragment screening renders new binding pockets.

KRAS genes belong to the most frequently mutated family of oncogenes in cancer. The G12C mutation, found in a third of lung, half of colorectal and pancreatic cancer cases, is believed to be responsible for a substantial number of cancer deaths. For 30 years, KRAS has been the subject of extensive drug-targeting efforts aimed at targeting KRAS protein itself, but also its post-translational modifications, membrane localization, protein-protein interactions and downstream signalling pathways. So far, most KRAS targeting strategies have failed, and there are no KRAS-specific drugs available. However, clinical candidates targeting the KRAS G12C protein have recently been developed. MRTX849 and recently approved Sotorasib are covalent binders targeting the mutated cysteine 12, occupying Switch II pocket.Herein, we describe two fragment screening drug discovery campaigns that led to the identification of binding pockets on the KRAS G12C surface that have not previously been described. One screen focused on non-covalent binders to KRAS G12C, the other on covalent binders.

Machine learning takes a village: Assessing neighbourhood-level vulnerability for an overdose and infectious disease outbreak.

BACKGROUND: Multiple areas in the United States of America (USA) are experiencing high rates of overdose and outbreaks of bloodborne infections, including HIV and hepatitis C virus (HCV), due to non-sterile injection drug use. We aimed to identify neighbourhoods at increased vulnerability for overdose and infectious disease outbreaks in Rhode Island, USA. The primary aim was to pilot machine learning methods to identify which neighbourhood-level factors were important for creating "vulnerability assessment scores" across the state. The secondary aim was to engage stakeholders to pilot an interactive mapping tool and visualize the results. METHODS: From September 2018 to November 2019, we conducted a neighbourhood-level vulnerability assessment and stakeholder engagement process named The VILLAGE Project (Vulnerability Investigation of underlying Local risk And Geographic Events). We developed a predictive analytics model using machine learning methods (LASSO, Elastic Net, and RIDGE) to identify areas with increased vulnerability to an outbreak of overdose, HIV and HCV, using census tract-level counts of overdose deaths as a proxy for injection drug use patterns and related health outcomes. Stakeholders reviewed mapping tools for face validity and community distribution. RESULTS: Machine learning prediction models were suitable for estimating relative neighbourhood-level vulnerability to an outbreak. Variables of importance in the model included housing cost burden, prior overdose deaths, housing density, and education level. Eighty-nine census tracts (37%) with no prior overdose fatalities were identified as being vulnerable to such an outbreak, and nine of those were identified as having a vulnerability assessment score in the top 25%. Results were disseminated as a vulnerability stratification map and an online interactive mapping tool. CONCLUSION: Machine learning methods are well suited to predict neighborhoods at higher vulnerability to an outbreak. These methods show promise as a tool to assess structural vulnerabilities and work to prevent outbreaks at the local level.

Longitudinal typing of molecular HIV clusters in a statewide epidemic.

BACKGROUND: HIV molecular epidemiology is increasingly integrated into public health prevention. We conducted cluster typing to enhance characterization of a densely sampled statewide epidemic towards informing public health. METHODS: We identified HIV clusters, categorized them into types, and evaluated their dynamics between 2004 and 2019 in Rhode Island. We grouped sequences by diagnosis year, assessed cluster changes between paired phylogenies, t0 and t1, representing adjacent years and categorized clusters as stable (cluster in t0 phylogeny = cluster in t1 phylogeny) or unstable (cluster in t0 ≠ cluster in t1). Unstable clusters were further categorized as emerging (t1 phylogeny only) or growing (larger in t1 phylogeny). We determined proportions of each cluster type, of individuals in each cluster type, and of newly diagnosed individuals in each cluster type, and assessed trends over time. RESULTS: A total of 1727 individuals with available HIV-1 subtype B pol sequences were diagnosed in Rhode Island by 2019. Over time, stable clusters and individuals in them dominated the epidemic, increasing over time, with reciprocally decreasing unstable clusters and individuals in them. Conversely, proportions of newly diagnosed individuals in unstable clusters significantly increased. Within unstable clusters, proportions of emerging clusters and of individuals in them declined; whereas proportions of newly diagnosed individuals in growing clusters significantly increased over time. CONCLUSION: Distinct molecular cluster types were identified in the Rhode Island epidemic. Cluster dynamics demonstrated increasing stable and decreasing unstable clusters driven by growing, rather than emerging clusters, suggesting consistent in-state transmission networks. Cluster typing could inform public health beyond conventional approaches and direct interventions.

Heme oxygenase-1 in blood and saliva during acute psychosis: A pilot study.

Despite the extensive prevalence of psychosis and schizophrenia spectrum disorders, their biological underpinnings remain largely unexplained. Recently, the overproduction of heme oxygenase-1 (HO-1), an enzyme that catalyzes the degradation of heme, was associated with oxidative stress and a neurologic phenotype similar to schizophrenia in transgenic mice. We sought to evaluate, by comparing patients experiencing an acute psychotic episode, and age/sex-matched healthy control participants, whether there was an association between HO-1 overexpression and psychosis. This cross-sectional pilot study included 16 patients and 17 control participants. Enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction were used to quantify HO-1 expression in blood and saliva. Four psychiatric questionnaires were used to measure psychiatric symptoms in participants. Higher levels of salivary HO-1 expression were detected in patients experiencing an acute psychotic episode when compared to control participants (84.01 vs. 61.26 ng/ml, p = 0.026), but plasma and lymphocyte HO-1 expression did not significantly differ between groups. Overexpression of HO-1 in saliva specimens was also positively associated with psychiatric symptom severity and disability. The overexpression of HO-1 in the saliva of patients with psychosis suggests that it may serve as a potential biomarker for this symptom which should be explored in larger clinical trials.

Empirical comparison of analytical approaches for identifying molecular HIV-1 clusters.

Public health interventions guided by clustering of HIV-1 molecular sequences may be impacted by choices of analytical approaches. We identified commonly-used clustering analytical approaches, applied them to 1886 HIV-1 Rhode Island sequences from 2004-2018, and compared concordance in identifying molecular HIV-1 clusters within and between approaches. We used strict (topological support ≥ 0.95; distance 0.015 substitutions/site) and relaxed (topological support 0.80-0.95; distance 0.030-0.045 substitutions/site) thresholds to reflect different epidemiological scenarios. We found that clustering differed by method and threshold and depended more on distance than topological support thresholds. Clustering concordance analyses demonstrated some differences across analytical approaches, with RAxML having the highest (91%) mean summary percent concordance when strict thresholds were applied, and three (RAxML-, FastTree regular bootstrap- and IQ-Tree regular bootstrap-based) analytical approaches having the highest (86%) mean summary percent concordance when relaxed thresholds were applied. We conclude that different analytical approaches can yield diverse HIV-1 clustering outcomes and may need to be differentially used in diverse public health scenarios. Recognizing the variability and limitations of commonly-used methods in cluster identification is important for guiding clustering-triggered interventions to disrupt new transmissions and end the HIV epidemic.

Genetically detoxified pertussis toxin displays near identical structure to its wild-type and exhibits robust immunogenicity.

The mutant gdPT R9K/E129G is a genetically detoxified variant of the pertussis toxin (PTx) and represents an attractive candidate for the development of improved pertussis vaccines. The impact of the mutations on the overall protein structure and its immunogenicity has remained elusive. Here we present the crystal structure of gdPT and show that it is nearly identical to that of PTx. Hydrogen-deuterium exchange mass spectrometry revealed dynamic changes in the catalytic domain that directly impacted NAD+ binding which was confirmed by biolayer interferometry. Distal changes in dynamics were also detected in S2-S5 subunit interactions resulting in tighter packing of B-oligomer corresponding to increased thermal stability. Finally, antigen stimulation of human whole blood, analyzed by a previously unreported mass cytometry assay, indicated broader immunogenicity of gdPT compared to pertussis toxoid. These findings establish a direct link between the conserved structure of gdPT and its ability to generate a robust immune response.

Public Health Approaches Toward Eliminating Hepatitis C Virus in Rhode Island.

Hepatitis C Virus (HCV) continues to be a cause of significant morbidity and mortality around the world surpassing HIV, Tuberculosis and Malaria as the leading cause of death by an infectious disease. In the United States, advances in screening, testing and treatment have put the goal set by the World Health Organization (WHO) to HCV elimination within reach. Rhode Island has taken an innovative public health approach to eliminating HCV by improving disease surveillance activities, supporting disease reduction strategies and removing barriers across the continuum of care, particularly for populations that are disproportionately impacted by the disease. Through the coordination of the Rhode Island Hepatitis C Action Coalition, the Rhode Island Department of Health (RIDOH), the Executive Office of Health and Human Services (EOHHS), community organizations, and clinical leaders, important steps have been taken to reduce transmission of the disease and work toward HCV elimination.

Considerations for STI Clinics During the COVID-19 Pandemic.

Coronavirus disease (COVID-19) is responsible for a global pandemic. It is important to balance the need for access to healthcare services, including testing and treatment for sexually transmitted infections. Sexually transmitted infection programs must consider how to use limited resources and implement novel approaches to provide continued access to care.

Challenges in evaluating the use of viral sequence data to identify HIV transmission networks for public health.

Great efforts are devoted to end the HIV epidemic as it continues to have profound public health consequences in the United States and throughout the world, and new interventions and strategies are continuously needed. The use of HIV sequence data to infer transmission networks holds much promise to direct public heath interventions where they are most needed. As these new methods are being implemented, evaluating their benefits is essential. In this paper, we recognize challenges associated with such evaluation, and make the case that overcoming these challenges is key to the use of HIV sequence data in routine public health actions to disrupt HIV transmission networks.

Trispecific antibodies enhance the therapeutic efficacy of tumor-directed T cells through T cell receptor co-stimulation.

Despite the significant therapeutic advances provided by immune-checkpoint blockade and chimeric antigen receptor T cell treatments, many malignancies remain unresponsive to immunotherapy. Bispecific antibodies targeting tumor antigens and activating T cell receptor signaling have shown some clinical efficacy; however, providing co-stimulatory signals may improve T cell responses against tumors. Here, we developed a trispecific antibody that interacts with CD38, CD3 and CD28 to enhance both T cell activation and tumor targeting. The engagement of both CD3 and CD28 affords efficient T cell stimulation, whereas the anti-CD38 domain directs T cells to myeloma cells, as well as to certain lymphomas and leukemias. In vivo administration of this antibody suppressed myeloma growth in a humanized mouse model and also stimulated memory/effector T cell proliferation and reduced regulatory T cells in non-human primates at well-tolerated doses. Collectively, trispecific antibodies represent a promising platform for cancer immunotherapy.