Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck:Bayesian probability versus neural network

Purpose: The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least-squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM-NET, and a version of the neural network modified to increase consistency, IVIM-NETmod. Methods: Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient (Formula presented.), perfusion fraction (Formula presented.), and pseudo-diffusion coefficient (Formula presented.)) from each fit method were determined in the tonsils and in the pterygoid muscles. Within-subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance. Results: The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of (Formula presented.) in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM-NET, and 11.2% for IVIM-NETmod. However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM-NET were 15% for both (Formula presented.) and (Formula presented.), and 94% for (Formula presented.); for IVIM-NETmod, these values improved to 5%, 9%, and 62%, respectively. Conclusion: Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck

International Care programs for Pediatric Post-COVID Condition (Long COVID) and the way forward

Background: Pediatric Post-COVID-Condition (PPCC) clinics treat children despite limited scientific substantiation. By exploring real-life management of children diagnosed with PPCC, the International Post-COVID-Condition in Children Collaboration (IP4C) aimed to provide guidance for future PPCC care. // Methods: We performed a cross-sectional international, multicenter study on used PPCC definitions; the organization of PPCC care programs and patients characteristics. We compared aggregated data from PPCC cohorts and identified priorities to improve PPCC care. // Results: Ten PPCC care programs and six COVID-19 follow-up research cohorts participated. Aggregated data from 584 PPCC patients was analyzed. The most common symptoms included fatigue (71%), headache (55%), concentration difficulties (53%), and brain fog (48%). Severe limitations in daily life were reported in 31% of patients. Most PPCC care programs organized in-person visits with multidisciplinary teams. Diagnostic testing for respiratory and cardiac morbidity was most frequently performed and seldom abnormal. Treatment was often limited to physical therapy and psychological support. // Conclusions: We found substantial heterogeneity in both the diagnostics and management of PPCC, possibly explained by scarce scientific evidence and lack of standardized care. We present a list of components which future guidelines should address, and outline priorities concerning PPCC care pathways, research and international collaboration

Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes

Abstract: Purpose: This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science. Methods: Web of Science and Google Scholar were used to review published papers spanning the period 2013–2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018–2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017. Scope: Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing. Conclusions: The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach

Long COVID exhibits clinically distinct phenotypes at 3–6 months post-SARSCoV-2 infection: results from the P4O2 consortium

Background Four months after SARS-CoV-2 infection, 22%–50% of COVID-19 patients still experience complaints. Long COVID is a heterogeneous disease and finding subtypes could aid in optimising and developing treatment for the individual patient. Methods Data were collected from 95 patients in the P4O2 COVID-19 cohort at 3–6 months after infection. Unsupervised hierarchical clustering was performed on patient characteristics, characteristics from acute SARSCoV-2 infection, long COVID symptom data, lung function and questionnaires describing the impact and severity of long COVID. To assess robustness, partitioning around medoids was used as alternative clustering. Results Three distinct clusters of patients with long COVID were revealed. Cluster 1 (44%) represented predominantly female patients (93%) with pre-existing asthma and suffered from a median of four symptom categories, including fatigue and respiratory and neurological symptoms. They showed a milder SARS-CoV-2 infection. Cluster 2 (38%) consisted of predominantly male patients (83%) with cardiovascular disease (CVD) and suffered from a median of three symptom categories, most commonly respiratory and neurological symptoms. This cluster also showed a significantly lower forced expiratory volume within 1 s and diffusion capacity of the lung for carbon monoxide. Cluster 3 (18%) was predominantly male (88%) with pre-existing CVD and diabetes. This cluster showed the mildest long COVID, and suffered from symptoms in a median of one symptom category. Conclusions Long COVID patients can be clustered into three distinct phenotypes based on their clinical presentation and easily obtainable information. These clusters show distinction in patient characteristics, lung function, long COVID severity and acute SARS-CoV-2 infection severity. This clustering can help in selecting the most beneficial monitoring and/or treatment strategies for patients suffering from long COVID. Follow-up research is needed to reveal the underlying molecular mechanisms implicated in the different phenotypes and determine the efficacy of treatment

On-line combination of liquid chromatography and capillary gas chromatography : preconcentration and analysis of organic compounds in aqueous samples

This paper describes the design of a new, versatile, and low-cost on-line LC-GC interface that allows the fast and reliable introduction of large sample volumes onto a capillary GC column. The sample introduction procedure consists successively of: evaporation of the entire sample (LC fraction), selective removal of the solvent and simultaneously cold-trapping of the solutes, splitless transfer of the solutes to the GC column, on-column focusing, GC separation and detection. Quantitative and qualitative aspects of various experimental parameters are evaluated and optimum conditions are reported. The applicability of the method is demonstrated on a synthetic aqueous sample of chlorinated pesticides