Characterizing Long COVID: Deep Phenotype of a Complex Condition

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

AlphaTracker: a multi-animal tracking and behavioral analysis tool

Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics

Characterizing Long COVID: Deep Phenotype of a Complex Condition.

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

Recombinant forms of Leishmania amazonensis excreted/secreted promastigote surface antigen (PSA) induce protective immune responses in dogs

International audiencePreventive vaccination is a highly promising strategy for interrupting leishmaniasis transmission that can, additionally, contribute to elimination. A vaccine formulation based on naturally excreted secreted (ES) antigens was prepared from L. infantum promastigote culture supernatant. This vaccine achieved successful results in Phase III trials and was licensed and marketed as CaniLeish. We recently showed that newly identified ES promastigote surface antigen (PSA), from both viable promastigotes and axenically-grown amastigotes, represented the major constituent and the highly immunogenic antigen of L. infantum and L. amazonensis ES products. We report here that three immunizations with either the recombi-nant ES LaPSA-38S (rPSA) or its carboxy terminal part LaPSA-12S (Cter-rPSA), combined with QA-21 as adjuvant, confer high levels of protection in naive L. infantum-infected Beagle dogs, as checked by bone marrow parasite absence in respectively 78.8% and 80% of vaccinated dogs at 6 months post-challenge. The parasite burden in infected vaccinated dogs was significantly reduced compared to placebo group, as measured by q-PCR. Moreover, our results reveal humoral and cellular immune response clear-cut differences between vaccinated and control dogs. An early increase in specific IgG2 antibodies was observed in rPSA/QA-21-and Cter-rPSA/QA-21-immunized dogs only. They were found functionally active in vitro and were highly correlated with vaccine protection. In vaccinated protected dogs, IFN-γ and NO productions, as well as anti-leishmanial macrophage activity, were increased. These data strongly suggest that ES PSA or its carboxy-terminal part, in recom-binant forms, induce protection in a canine model of zoonotic visceral leishmaniasis by inducing a Th1-dominant immune response and an appropriate specific antibody response. These data suggest that they could be considered as important active components in vaccine candidates

The Knee Clinical Assessment Study – CAS(K). A prospective study of knee pain and knee osteoarthritis in the general population

BACKGROUND: Knee pain affects an estimated 25% of the adult population aged 50 years and over. Osteoarthritis is the most common diagnosis made in older adults consulting with knee pain in primary care. However, the relationship between this diagnosis and both the current disease-based definition of osteoarthritis and the regional pain syndrome of knee pain and disability is unclear. Expert consensus, based on current evidence, views the disease and the syndrome as distinct entities but the clinical usefulness of these two approaches to classifying knee pain in older adults has not been established. We plan to conduct a prospective, population-based, observational cohort study to investigate the relative merits of disease-based and regional pain syndrome-based approaches to classification and prognosis of knee pain in older adults. METHODS: All patients aged 50 years and over registered with three general practices in North Staffordshire will be invited to take part in a two-stage postal survey. Respondents to this survey phase who indicate that they have experienced knee pain within the previous 12 months will be invited to attend a research clinic for a detailed assessment. This will consist of clinical interview, physical examination, digital photography, plain x-rays, anthropometric measurement and a brief self-complete questionnaire. All consenting clinic attenders will be followed up by (i) general practice medical record review, (ii) repeat postal questionnaire at 18-months

The relationships between exogenous and endogenous antioxidants with the lipid profile and oxidative damage in hemodialysis patients

Background: We sought to investigate the relationships among the plasma levels of carotenoids, tocopherols, endogenous antioxidants, oxidative damage and lipid profiles and their possible effects on the cardiovascular risk associated with hemodialysis (HD) patients. Methods: The study groups were divided into HD and healthy subjects. Plasma carotenoid, tocopherol and malondialdehyde (MDA) levels, as well as erythrocyte reduced glutathione (GSH), were measured by HPLC. Blood antioxidant enzymes, kidney function biomarkers and the lipid profiles were analyzed by spectrophotometric methods. Results: Plasma lycopene levels and blood glutathione peroxidase (GPx) activity were significantly decreased in HD patients compared with healthy subjects. Total cholesterol, low-density lipoprotein cholesterol (LDL-c), creatinine, urea, MDA, GSH, superoxide dismutase (SOD) and catalase (CAT) were significantly increased in HD (p < 0.05). Lycopene levels were correlated with MDA (r = -0.50; p < 0.01), LDL-c (r = -0.38; p = 0.01) levels, the LDL-c/HDL-c index (r = -0.33; p = 0.03) and GPx activity (r = 0.30; p = 0.03). Regression models showed that lycopene levels were correlated with LDL-c (β estimated = -31.59; p = 0.04), while gender was correlated with the TC/HDL-c index and triglycerides. Age did not present a correlation with the parameters evaluated. GPx activity was negatively correlated with MDA levels and with the LDL-c/HDL-c and CT/HDL-c indexes. Conclusions: Lycopene may represent an additional factor that contributes to reduced lipid peroxidation and atherogenesis in hemodialysis patients

Tamoxifen-Induced Cre-loxP Recombination Is Prolonged in Pancreatic Islets of Adult Mice

Tamoxifen (Tm)-inducible Cre recombinases are widely used to perform gene inactivation and lineage tracing studies in mice. Although the efficiency of inducible Cre-loxP recombination can be easily evaluated with reporter strains, the precise length of time that Tm induces nuclear translocation of CreERTm and subsequent recombination of a target allele is not well defined, and difficult to assess. To better understand the timeline of Tm activity in vivo, we developed a bioassay in which pancreatic islets with a Tm-inducible reporter (from Pdx1PB-CreERTm;R26RlacZ mice) were transplanted beneath the renal capsule of adult mice previously treated with three doses of 1 mg Tm, 8 mg Tm, or corn oil vehicle. Surprisingly, recombination in islet grafts, as assessed by expression of the β-galactosidase (β-gal) reporter, was observed days or weeks after Tm treatment, in a dose-dependent manner. Substantial recombination occurred in islet grafts long after administration of 3×8 mg Tm: in grafts transplanted 48 hours after the last Tm injection, 77.9±0.4% of β-cells were β-gal+; in β-cells placed after 1 week, 46.2±5.0% were β-gal+; after 2 weeks, 26.3±7.0% were β-gal+; and after 4 weeks, 1.9±0.9% were β-gal+. Islet grafts from mice given 3×1 mg Tm showed lower, but notable, recombination 48 hours (4.9±1.7%) and 1 week (4.5±1.9%) after Tm administration. These results show that Tm doses commonly used to induce Cre-loxP recombination may continue to label significant numbers of cells for weeks after Tm treatment, possibly confounding the interpretation of time-sensitive studies using Tm-dependent models. Therefore, investigators developing experimental approaches using Tm-inducible systems should consider both maximal recombination efficiency and the length of time that Tm-induced Cre-loxP recombination occurs

A case of mistaken identity: HSPs are no DAMPs but DAMPERs

Until recently, the immune system was seen solely as a defense system with its primary task being the elimination of unwanted microbial invaders. Currently, however, the functional significance of the immune system has obtained a much wider perspective, to include among others the maintenance and restoration of homeostasis following tissue damage. In this latter aspect, there is a growing interest in the identification of molecules involved, such as the so-called danger or damage-associated molecular patterns (DAMPs), also called alarmins. Since heat shock proteins are archetypical molecules produced under stressful conditions, such as tissue damage or inflammation, they are frequently mentioned as prime examples of DAMPs (Bianchi, J Leukoc Biol 81:1–5, 2007; Kono and Rock, Nat Rev Immunol 8:279–289, 2008; Martin-Murphy et al., Toxicol Lett 192:387–394, 2010). See for instance also a recent review (Chen and Nunez, Science 298:1395–1401, 2010). Contrary to this description, we recently presented some of the arguments against a role of heat shock protein as DAMPs (Broere et al., Nat Rev Immunol 11:565-c1, 2011). With this perspective and reflection article, we hope to elaborate on this debate and provide additional thoughts to further ignite this discussion on this critical and evolving issue

Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges

Radiomics leverages existing image datasets to provide non-visible data extraction via image post-processing, with the aim of identifying prognostic, and predictive imaging features at a sub-region of interest level. However, the application of radiomics is hampered by several challenges such as lack of image acquisition/analysis method standardization, impeding generalizability. As of yet, radiomics remains intriguing, but not clinically validated. We aimed to test the feasibility of a non-custom-constructed platform for disseminating existing large, standardized databases across institutions for promoting radiomics studies. Hence, University of Texas MD Anderson Cancer Center organized two public radiomics challenges in head and neck radiation oncology domain. This was done in conjunction with MICCAI 2016 satellite symposium using Kaggle-in-Class, a machine-learning and predictive analytics platform. We drew on clinical data matched to radiomics data derived from diagnostic contrast-enhanced computed tomography (CECT) images in a dataset of 315 patients with oropharyngeal cancer. Contestants were tasked to develop models for (i) classifying patients according to their human papillomavirus status, or (ii) predicting local tumor recurrence, following radiotherapy. Data were split into training, and test sets. Seventeen teams from various professional domains participated in one or both of the challenges. This review paper was based on the contestants' feedback; provided by 8 contestants only (47%). Six contestants (75%) incorporated extracted radiomics features into their predictive model building, either alone (n = 5; 62.5%), as was the case with the winner of the “HPV” challenge, or in conjunction with matched clinical attributes (n = 2; 25%). Only 23% of contestants, notably, including the winner of the “local recurrence” challenge, built their model relying solely on clinical data. In addition to the value of the integration of machine learning into clinical decision-making, our experience sheds light on challenges in sharing and directing existing datasets toward clinical applications of radiomics, including hyper-dimensionality of the clinical/imaging data attributes. Our experience may help guide researchers to create a framework for sharing and reuse of already published data that we believe will ultimately accelerate the pace of clinical applications of radiomics; both in challenge or clinical settings