Video-rate fluorescence diffuse optical tomography for in vivo sentinel lymph node imaging

We have developed a fiber-based, video-rate fluorescence diffuse optical tomography (DOT) system for noninvasive in vivo sentinel lymph node (SLN) mapping. Concurrent acquisition of fluorescence and reference signals allowed the efficient generation of ratio-metric data for 3D image reconstruction. Accurate depth localization and high sensitivity to fluorescent targets were established in to depths of >10 mm. In vivo accumulation of indocyanine green (ICG) dye was imaged in the region of the SLN following intradermal injection into the forepaw of rats. These results suggest that video-rate fluorescence DOT has significant potential as a clinical tool for noninvasive mapping of SLN

Non-invasive monitoring of arthritis treatment response via targeting of tyrosine-phosphorylated annexin A2 in chondrocytes

BACKGROUND: The development and optimization of therapies for rheumatoid arthritis (RA) is currently hindered by a lack of methods for early non-invasive monitoring of treatment response. Annexin A2, an inflammation-associated protein whose presence and phosphorylation levels are upregulated in RA, represents a potential molecular target for tracking RA treatment response. METHODS: LS301, a near-infrared dye-peptide conjugate that selectively targets tyrosine 23-phosphorylated annexin A2 (pANXA2), was evaluated for its utility in monitoring disease progression, remission, and early response to drug treatment in mouse models of RA by fluorescence imaging. The intraarticular distribution and localization of LS301 relative to pANXA2 was determined by histological and immunohistochemical methods. RESULTS: In mouse models of spontaneous and serum transfer-induced inflammatory arthritis, intravenously administered LS301 showed selective accumulation in regions of joint pathology including paws, ankles, and knees with positive correlation between fluorescent signal and disease severity by clinical scoring. Whole-body near-infrared imaging with LS301 allowed tracking of spontaneous disease remission and the therapeutic response after dexamethasone treatment. Histological analysis showed preferential accumulation of LS301 within the chondrocytes and articular cartilage in arthritic mice, and colocalization was observed between LS301 and pANXA2 in the joint tissue. CONCLUSIONS: We demonstrate that fluorescence imaging with LS301 can be used to monitor the progression, remission, and early response to drug treatment in mouse models of RA. Given the ease of detecting LS301 with portable optical imaging devices, the agent may become a useful early treatment response reporter for arthritis diagnosis and drug evaluation

Binocular Goggle Augmented Imaging and Navigation System provides real-time fluorescence image guidance for tumor resection and sentinel lymph node mapping

The inability to identify microscopic tumors and assess surgical margins in real-time during oncologic surgery leads to incomplete tumor removal, increases the chances of tumor recurrence, and necessitates costly repeat surgery. To overcome these challenges, we have developed a wearable goggle augmented imaging and navigation system (GAINS) that can provide accurate intraoperative visualization of tumors and sentinel lymph nodes in real-time without disrupting normal surgical workflow. GAINS projects both near-infrared fluorescence from tumors and the natural color images of tissue onto a head-mounted display without latency. Aided by tumor-targeted contrast agents, the system detected tumors in subcutaneous and metastatic mouse models with high accuracy (sensitivity = 100%, specificity = 98% ± 5% standard deviation). Human pilot studies in breast cancer and melanoma patients using a near-infrared dye show that the GAINS detected sentinel lymph nodes with 100% sensitivity. Clinical use of the GAINS to guide tumor resection and sentinel lymph node mapping promises to improve surgical outcomes, reduce rates of repeat surgery, and improve the accuracy of cancer staging

Molecular genetic contributions to self-rated health

Poorer self-rated health (SRH) predicts worse health outcomes, even when adjusted for objective measures of disease at time of rating. Twin studies indicate SRH has a heritability of up to 60% and that its genetic architecture may overlap with that of personality and cognition.We carried out a genome-wide association study (GWAS) of SRH on 111 749 members of the UK Biobank sample. Univariate genome-wide complex trait analysis (GCTA)-GREML analyses were used to estimate the proportion of variance explained by all common autosomal single nucleotide polymorphisms (SNPs) for SRH. Linkage disequilibrium (LD) score regression and polygenic risk scoring, two complementary methods, were used to investigate pleiotropy between SRH in the UK Biobank and up to 21 health-related and personality and cognitive traits from published GWAS consortia.The GWAS identified 13 independent signals associated with SRH, including several in regions previously associated with diseases or disease-related traits. The strongest signal was on chromosome 2 (rs2360675, P = 1.77 x 10 -10 ) close to KLF7 . A second strong peak was identified on chromosome 6 in the major histocompatibility region (rs76380179, P = 6.15 x 10 -10 ). The proportion of variance in SRH that was explained by all common genetic variants was 13%. Polygenic scores for the following traits and disorders were associated with SRH: cognitive ability, education, neuroticism, body mass index (BMI), longevity, attention-deficit hyperactivity disorder (ADHD), major depressive disorder, schizophrenia, lung function, blood pressure, coronary artery disease, large vessel disease stroke and type 2 diabetes.Individual differences in how people respond to a single item on SRH are partly explained by their genetic propensity to many common psychiatric and physical disorders and psychological traits

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score.

OBJECTIVE: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN: Prospective observational cohort study. SETTING: International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. PARTICIPANTS: Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. MAIN OUTCOME MEASURE: In-hospital mortality. RESULTS: 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). CONCLUSIONS: An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. STUDY REGISTRATION: ISRCTN66726260