Zoonotic transmission of Chlamydia felis from domestic cats; A case series of chronic follicular conjunctivitis in humans.

We present three cases of chronic follicular conjunctivitis resulting from the zoonotic transmission of Chlamydia felis from domestic cats. Our objective is to raise awareness regarding the potential zoonotic transmission of Chlamydia felis from domestic cats and describe the methodology for definitive pathogen identification using Polymerase Chain Reaction (PCR) and subsequent sequence analysis, a useful tool in the identification of these rare pathogens. We discuss the factors that could be contributing to the potential under-diagnosis of zoonotic C. felis infections and propose a treatment regime for cases of C. felis-related conjunctivitis.

Molecular epidemiology of a Parainfluenza Type 3 virus outbreak: Informing infection control measures on adult hematology wards.

OBJECTIVES: Parainfluenza virus type 3 (PIV3) outbreaks among hematology patients are associated with high morbidity and mortality. Prompt implementation of infection prevention (IP) measures has proven to be the most efficacious approach for controlling PIV3 outbreaks within this patient population. The most suitable IP measures can vary depending on the mode of virus transmission, which remains unidentified in most outbreaks. We describe the molecular epidemiology of an outbreak of PIV3 among hematology patients and the development of a new method that allows for the differentiation of outbreak and community strains, from which a closed outbreak could be inferred. METHODS: Patients were screened for respiratory viruses using multiplex-PCR. PIV3 positive samples with a cycle threshold (Ct)-value of <31 underwent a retrospective characterization via an in-house developed sequence analysis of the hemagglutinin-neuraminidase (HN) gene. RESULTS: Between July and September 2022, 31 hematology patients were identified with PIV3. Although infection control measures were implemented, the outbreak persisted for nine weeks. Sequencing the HN gene of 27 PIV3 strains from 27 patients revealed that all outbreak strains formed a distinct cluster separate from the control strains, suggestive of a nosocomial transmission route. CONCLUSIONS: Sequencing the HN gene of PIV3 strains in an outbreak setting enables outbreak strains to be distinguished from community strains. Early molecular characterization of PIV3 strains during an outbreak can serve as a tool in determining potential transmission routes. This, in turn, enables rapid implementation of targeted infection prevention measures, with the goal of minimizing the outbreak's duration and reducing associated morbidity and mortality.

Enhancement and Comparison of (Ceftazidime-)Avibactam Plus Aztreonam Susceptibility Tests for Stenotrophomonas maltophilia in Clinical Diagnostics.

Stenotrophomonas maltophilia is naturally resistant to many antimicrobials. We evaluated the in vitro activity and reproducibility of two different super-position methods of aztreonam in combination with ceftazidime-avibactam for S. maltophilia and compared these results with the recently available aztreonam-avibactam gradient strip. We recommend an improved super-position method that avoids the possible risk of handling a contaminated aztreonam strip. In addition, we report that the cefazidime-avibactam and aztreonam super-position method showed increased in vitro activity in comparison with aztreonam-avibactam indicating activity of the ceftazidime component in vitro.

Live cell in situ lysosomal GCase activity correlates to alpha-synuclein levels in human differentiated neurons with LRRK2 and GBA1 mutations.

Introduction: Heterozygous mutations in GBA1, which encodes the lysosomal hydrolase glucocerebrosidase (GCase), are a common risk factor for the neurodegenerative movement disorder Parkinson's disease (PD). Consequently, therapeutic options targeting the GCase enzyme are in development. An important aspect of this development is determining the effect of potential modifying compounds on GCase activity, which can be complicated by the different methods and substrate probes that are commonly employed for this purpose. Methods: In this study, we employed the GCase substrate probe 5-(pentafluorobenzoylamino)fluorescein di-D-glucopyranoside (PFB-FDGlu) in combination with live cell imaging to measure GCase activity in situ in the lysosome. Results: The live cell assay was validated using the GCase inhibitor conduritol-B-epoxide and with GBA1 knockout neural cells and was then used to assess GCase activity in iPSC differentiated into neural stem cells and neurons that were obtained from idiopathic PD patients and PD patients with the LRRK2 G2019S and GBA N370S mutations, as well as controls (n = 4 per group). Heterogeneity in GCase activity was observed across all groups. However, a significant inverse correlation between GCase activity and levels of alpha-synuclein protein was observed. Discussion: The live cell imaging assay for GCase activity could be useful for further understanding the role of GCase in PD and screening potential modifying compounds in differentiated human cell models.

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

Contributions of viral oncogenes of HPV-18 and hypoxia to oxidative stress and genetic damage in human keratinocytes.

Infection with high-risk human papillomaviruses like HPV-16 and HPV-18 is highly associated with the development of cervical and other cancers. Malignant transformation requires viral oncoproteins E5, E6 and E7, which promote cell proliferation and increase DNA damage. Oxidative stress and hypoxia are also key factors in cervical malignant transformation. Increased levels of reactive species of oxygen (ROS) and nitrogen (RNS) are found in the hypoxic tumor microenvironment, promoting genetic instability and invasiveness. In this work, we studied the combined effect of E5, E6 and E7 and hypoxia in increasing oxidative stress and promoting DNA damage and nuclear architecture alterations. HaCaT cells containing HPV-18 viral oncogenes (HaCaT E5/E6/E7-18) showed higher ROS levels in normoxia and higher levels of RNS in hypoxia compared to HaCaT parental cells, as well as higher genetic damage in hypoxia as measured by γH2AX and comet assays. In hypoxia, HaCaT E5/E6/E7-18 increased its nuclear dry mass and both cell types displayed marked heterogeneity in nuclear dry mass distribution and increased nuclear foci. Our results show contributions of both viral oncogenes and hypoxia to oxidative stress, DNA damage and altered nuclear architecture, exemplifying how an altered microenvironment combines with oncogenic transformation to promote tumor progression.

Early Detection and Surveillance of the SARS-CoV-2 Variant BA.2.86 - Worldwide, July-October 2023.

Early detection of emerging SARS-CoV-2 variants is critical to guiding rapid risk assessments, providing clear and timely communication messages, and coordinating public health action. CDC identifies and monitors novel SARS-CoV-2 variants through diverse surveillance approaches, including genomic, wastewater, traveler-based, and digital public health surveillance (e.g., global data repositories, news, and social media). The SARS-CoV-2 variant BA.2.86 was first sequenced in Israel and reported on August 13, 2023. The first U.S. COVID-19 case caused by this variant was reported on August 17, 2023, after a patient received testing for SARS-CoV-2 at a health care facility on August 3. In the following month, eight additional U.S. states detected BA.2.86 across various surveillance systems, including specimens from health care settings, wastewater surveillance, and traveler-based genomic surveillance. As of October 23, 2023, sequences have been reported from at least 32 countries. Continued variant tracking and further evidence are needed to evaluate the full public health impact of BA.2.86. Timely genomic sequence submissions to global public databases aided early detection of BA.2.86 despite the decline in the number of specimens being sequenced during the past year. This report describes how multicomponent surveillance and genomic sequencing were used in real time to track the emergence and transmission of the BA.2.86 variant. This surveillance approach provides valuable information regarding implementing and sustaining comprehensive surveillance not only for novel SARS-CoV-2 variants but also for future pathogen threats.

Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis.

Rheumatoid arthritis (RA) is a systemic autoimmune disease with currently no universally highly effective prevention strategies. Identifying pathogenic immune phenotypes in 'At-Risk' populations prior to clinical disease onset is crucial to establishing effective prevention strategies. Here, we applied mass cytometry to deeply characterize the immunophenotypes in blood from At-Risk individuals identified through the presence of serum antibodies to citrullinated protein antigens (ACPA) and/or first-degree relative (FDR) status (n=52), as compared to established RA (n=67), and healthy controls (n=48). We identified significant cell expansions in At-Risk individuals compared with controls, including CCR2+CD4+ T cells, T peripheral helper (Tph) cells, type 1 T helper cells, and CXCR5+CD8+ T cells. We also found that CD15+ classical monocytes were specifically expanded in ACPA-negative FDRs, and an activated PAX5 low naïve B cell population was expanded in ACPA-positive FDRs. Further, we developed an "RA immunophenotype score" classification method based on the degree of enrichment of cell states relevant to established RA patients. This score significantly distinguished At-Risk individuals from controls. In all, we systematically identified activated lymphocyte phenotypes in At-Risk individuals, along with immunophenotypic differences among both ACPA+ and ACPA-FDR At-Risk subpopulations. Our classification model provides a promising approach for understanding RA pathogenesis with the goal to further improve prevention strategies and identify novel therapeutic targets.

Syndromes associated with frontotemporal lobar degeneration change response patterns on visual analogue scales.

Self-report scales are widely used in cognitive neuroscience and psychology. However, they rest on the central assumption that respondents engage meaningfully. We hypothesise that this assumption does not hold for many patients, especially those with syndromes associated with frontotemporal lobar degeneration. In this study we investigated differences in response patterns on a visual analogue scale between people with frontotemporal degeneration and controls. We found that people with syndromes associated with frontotemporal lobar degeneration respond with more invariance and less internal consistency than controls, with Bayes Factors = 15.2 and 14.5 respectively indicating strong evidence for a group difference. There was also evidence that patient responses feature lower entropy. These results have important implications for the interpretation of self-report data in clinical populations. Meta-response markers related to response patterns, rather than the values reported on individual items, may be an informative addition to future research and clinical practise.

Towards Understanding Long COVID: SARS-CoV-2 Strikes the Host Cell Nucleus.

Despite what its name suggests, the effects of the COVID-19 pandemic causative agent "Severe Acute Respiratory Syndrome Coronavirus-2" (SARS-CoV-2) were not always confined, neither temporarily (being long-term rather than acute, referred to as Long COVID) nor spatially (affecting several body systems). Moreover, the in-depth study of this ss(+) RNA virus is defying the established scheme according to which it just had a lytic cycle taking place confined to cell membranes and the cytoplasm, leaving the nucleus basically "untouched". Cumulative evidence shows that SARS-CoV-2 components disturb the transport of certain proteins through the nuclear pores. Some SARS-CoV-2 structural proteins such as Spike (S) and Nucleocapsid (N), most non-structural proteins (remarkably, Nsp1 and Nsp3), as well as some accessory proteins (ORF3d, ORF6, ORF9a) can reach the nucleoplasm either due to their nuclear localization signals (NLS) or taking a shuttle with other proteins. A percentage of SARS-CoV-2 RNA can also reach the nucleoplasm. Remarkably, controversy has recently been raised by proving that-at least under certain conditions-, SARS-CoV-2 sequences can be retrotranscribed and inserted as DNA in the host genome, giving rise to chimeric genes. In turn, the expression of viral-host chimeric proteins could potentially create neo-antigens, activate autoimmunity and promote a chronic pro-inflammatory state.

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy.

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

Schema Playground: a tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data.

BACKGROUND: Biomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging Schema.org could benefit biomedical research resource providers, but it can be challenging to apply Schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize Schema.org or other biomedical schema projects. RESULTS: Our browser-based tool includes features which can help address many of the barriers towards Schema.org-compliance such as: The ability to easily browse for relevant Schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema-a large multi-class schema for harmonizing various COVID-19 related resources. CONCLUSIONS: We have created a browser-based tool to empower biomedical research resource providers to leverage Schema.org classes to make their research outputs more FAIR.

Evaluation of plasma levels of NFL, GFAP, UCHL1 and tau as Parkinson's disease biomarkers using multiplexed single molecule counting.

Objective biomarkers for Parkinson's Disease (PD) could aid early and specific diagnosis, effective monitoring of disease progression, and improved design and interpretation of clinical trials. Although alpha-synuclein remains a biomarker candidate of interest, the multifactorial and heterogenous nature of PD highlights the need for a PD biomarker panel. Ideal biomarker candidates include markers that are detectable in easily accessible samples, (ideally blood) and that reflect the underlying pathological process of PD. In the present study, we explored the diagnostic and prognostic PD biomarker potential of the SIMOA neurology 4-plex-A biomarker panel, which included neurofilament light (NFL), glial fibrillary acid protein (GFAP), tau and ubiquitin C-terminal hydrolase L1 (UCHL-1). We initially performed a serum vs plasma comparative study to determine the most suitable blood-based matrix for the measurement of these proteins in a multiplexed assay. The levels of NFL and GFAP in plasma and serum were highly correlated (Spearman rho-0.923, p < 0.0001 and rho = 0.825, p < 0.001 respectively). In contrast, the levels of tau were significantly higher in plasma compared to serum samples (p < 0.0001) with no correlation between sample type (Spearman p > 0.05). The neurology 4-plex-A panel, along with plasma alpha-synuclein was then assessed in a cross-sectional cohort of 29 PD patients and 30 controls. Plasma NFL levels positively correlated with both GFAP and alpha-synuclein levels (rho = 0.721, p < 0.0001 and rho = 0.390, p < 0.05 respectively). As diagnostic biomarkers, the control and PD groups did not differ in their mean NFL, GFAP, tau or UCHL-1 plasma levels (t test p > 0.05). As disease state biomarkers, motor severity (MDS-UPDRS III) correlated with increased NFL (rho = 0.646, p < 0.0001), GFAP (rho = 0.450, p < 0.05) and alpha-synuclein levels (rho = 0.406, p < 0.05), while motor stage (Hoehn and Yahr) correlated with increased NFL (rho = 0.455, p < 0.05) and GFAP (rho = 0.549, p < 0.01) but not alpha-synuclein levels (p > 0.05). In conclusion, plasma was determined to be most suitable blood-based matrix for multiplexing the neurology 4-plex-A panel. Given their correlation with motor features of PD, NFL and GFAP appear to be promising disease state biomarker candidates and further longitudinal validation of these two proteins as blood-based biomarkers for PD progression is warranted.

Design and Optimization of a Monkeypox virus Specific Serological Assay.

Monkeypox virus (MPXV), a member of the Orthopoxvirus (OPXV) genus, is a zoonotic virus, endemic to central and western Africa that can cause smallpox-like symptoms in humans with fatal outcomes in up to 15% of patients. The incidence of MPXV infections in the Democratic Republic of the Congo, where the majority of cases have occurred historically, has been estimated to have increased as much as 20-fold since the end of smallpox vaccination in 1980. Considering the risk global travel carries for future disease outbreaks, accurate epidemiological surveillance of MPXV is warranted as demonstrated by the recent Mpox outbreak, where the majority of cases were occurring in non-endemic areas. Serological differentiation between childhood vaccination and recent infection with MPXV or other OPXVs is difficult due to the high level of conservation within OPXV proteins. Here, a peptide-based serological assay was developed to specifically detect exposure to MPXV. A comparative analysis of immunogenic proteins across human OPXVs identified a large subset of proteins that could potentially be specifically recognized in response to a MPXV infection. Peptides were chosen based upon MPXV sequence specificity and predicted immunogenicity. Peptides individually and combined were screened in an ELISA against serum from well-characterized Mpox outbreaks, vaccinee sera, and smallpox sera collected prior to eradication. One peptide combination was successful with ~86% sensitivity and ~90% specificity. The performance of the assay was assessed against the OPXV IgG ELISA in the context of a serosurvey by retrospectively screening a set of serum specimens from the region in Ghana believed to have harbored the MPXV-infected rodents involved in the 2003 United States outbreak.

Developing a standardized but extendable framework to increase the findability of infectious disease datasets.

Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such as Schema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.

Outbreak.info Research Library: a standardized, searchable platform to discover and explore COVID-19 resources.

Outbreak.info Research Library is a standardized, searchable interface of coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) publications, clinical trials, datasets, protocols and other resources, built with a reusable framework. We developed a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public application programming interface (API) and R package.

Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations.

In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info , a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.info can be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales.

Neurophysiological consequences of synapse loss in progressive supranuclear palsy.

Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from preclinical to clinical models of pathology and quantitative assays for experimental medicine. Such biophysical models can also disclose hidden neuronal dynamics generating neurophysiological observations such as EEG and magnetoencephalography. Here, we augment a biophysically informed mesoscale model of human cortical function by inclusion of synaptic density estimates as captured by 11C-UCB-J PET, and provide insights into how regional synapse loss affects neurophysiology. We use the primary tauopathy of progressive supranuclear palsy (Richardson's syndrome) as an exemplar condition, with high clinicopathological correlations. Progressive supranuclear palsy causes a marked change in cortical neurophysiology in the presence of mild cortical atrophy and is associated with a decline in cognitive functions associated with the frontal lobe. Using parametric empirical Bayesian inversion of a conductance-based canonical microcircuit model of magnetoencephalography data, we show that the inclusion of regional synaptic density-as a subject-specific prior on laminar-specific neuronal populations-markedly increases model evidence. Specifically, model comparison suggests that a reduction in synaptic density in inferior frontal cortex affects superficial and granular layer glutamatergic excitation. This predicted individual differences in behaviour, demonstrating the link between synaptic loss, neurophysiology and cognitive deficits. The method we demonstrate is not restricted to progressive supranuclear palsy or the effects of synaptic loss: such pathology-enriched dynamic causal models can be used to assess the mechanisms of other neurological disorders, with diverse non-invasive measures of pathology, and is suitable to test the effects of experimental pharmacology.