Reconstruction-based speech enhancement from robust acoustic features

This paper proposes a method of speech enhancement where a clean speech signal is reconstructed from a sinusoidal model of speech production and a set of acoustic speech features. The acoustic features are estimated from noisy speech and comprise, for each frame, a voicing classification (voiced, unvoiced or non-speech), fundamental frequency (for voiced frames) and spectral envelope. Rather than using different algorithms to estimate each parameter, a single statistical model is developed. This comprises a set of acoustic models and has similarity to the acoustic modelling used in speech recognition. This allows noise and speaker adaptation to be applied to acoustic feature estimation to improve robustness. Objective and subjective tests compare reconstruction-based enhancement with other methods of enhancement and show the proposed method to be highly effective at removing noise

Estimating acoustic speech features in low signal-to-noise ratios using a statistical framework

Accurate estimation of acoustic speech features from noisy speech and from different speakers is an ongoing problem in speech processing. Many methods have been proposed to estimate acoustic features but errors increase as signal-to-noise ratios fall. This work proposes a robust statistical framework to estimate an acoustic speech vector (comprising voicing, fundamental frequency and spectral envelope) from an intermediate feature that is extracted from a noisy time-domain speech signal. The initial approach is accurate in clean conditions but deteriorates in noise and with changing speaker. Adaptation methods are then developed to adjust the acoustic models to the noise conditions and speaker. Evaluations are carried out in stationary and nonstationary noises and at SNRs from -5dB to clean conditions. Comparison with conventional methods of estimating fundamental frequency, voicing and spectral envelope reveals the proposed framework to have lowest errors in all conditions tested

Determinants of recovery from post-COVID-19 dyspnoea: analysis of UK prospective cohorts of hospitalised COVID-19 patients and community-based controls

Background The risk factors for recovery from COVID-19 dyspnoea are poorly understood. We investigated determinants of recovery from dyspnoea in adults with COVID-19 and compared these to determinants of recovery from non-COVID-19 dyspnoea. Methods We used data from two prospective cohort studies: PHOSP-COVID (patients hospitalised between March 2020 and April 2021 with COVID-19) and COVIDENCE UK (community cohort studied over the same time period). PHOSP-COVID data were collected during hospitalisation and at 5-month and 1-year follow-up visits. COVIDENCE UK data were obtained through baseline and monthly online questionnaires. Dyspnoea was measured in both cohorts with the Medical Research Council Dyspnoea Scale. We used multivariable logistic regression to identify determinants associated with a reduction in dyspnoea between 5-month and 1-year follow-up. Findings We included 990 PHOSP-COVID and 3309 COVIDENCE UK participants. We observed higher odds of improvement between 5-month and 1-year follow-up among PHOSP-COVID participants who were younger (odds ratio 1.02 per year, 95% CI 1.01–1.03), male (1.54, 1.16–2.04), neither obese nor severely obese (1.82, 1.06–3.13 and 4.19, 2.14–8.19, respectively), had no pre-existing anxiety or depression (1.56, 1.09–2.22) or cardiovascular disease (1.33, 1.00–1.79), and shorter hospital admission (1.01 per day, 1.00–1.02). Similar associations were found in those recovering from non-COVID-19 dyspnoea, excluding age (and length of hospital admission). Interpretation Factors associated with dyspnoea recovery at 1-year post-discharge among patients hospitalised with COVID-19 were similar to those among community controls without COVID-19. Funding PHOSP-COVID is supported by a grant from the MRC-UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research (NIHR) rapid response panel to tackle COVID-19. The views expressed in the publication are those of the author(s) and not necessarily those of the National Health Service (NHS), the NIHR or the Department of Health and Social Care. COVIDENCE UK is supported by the UK Research and Innovation, the National Institute for Health Research, and Barts Charity. The views expressed are those of the authors and not necessarily those of the funders

Assessing chemical mechanisms underlying the effects of sunflower pollen on a gut pathogen in bumble bees

Many pollinator species are declining due to a variety of interacting stressors including pathogens, sparking interest in understanding factors that could mitigate these outcomes. Diet can affect host-pathogen interactions by changing nutritional reserves or providing bioactive secondary chemicals. Recent work found that sunflower pollen (Helianthus annuus) dramatically reduced cell counts of the gut pathogen Crithidia bombi in bumble bee workers (Bombus impatiens), but the mechanism underlying this effect is unknown. Here we analyzed methanolic extracts of sunflower pollen by LC-MS and identified triscoumaroyl spermidines as the major secondary metabolite components, along with a flavonoid quercetin-3-O-hexoside and a quercetin-3-O-(6-O-malonyl)-hexoside. We then tested the effect of triscoumaroyl spermidine and rutin (as a proxy for quercetin glycosides) on Crithidia infection in B. impatiens, compared to buckwheat pollen (Fagopyrum esculentum) as a negative control and sunflower pollen as a positive control. In addition, we tested the effect of nine fatty acids from sunflower pollen individually and in combination using similar methods. Although sunflower pollen consistently reduced Crithidia relative to control pollen, none of the compounds we tested had significant effects. In addition, diet treatments did not affect mortality, or sucrose or pollen consumption. Thus, the mechanisms underlying the medicinal effect of sunflower are still unknown; future work could use bioactivity-guided fractionation to more efficiently target compounds of interest, and explore non-chemical mechanisms. Ultimately, identifying the mechanism underlying the effect of sunflower pollen on pathogens will open up new avenues for managing bee health

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

Background No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge. Methods The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing. Findings 2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7–9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46–0·99]), obesity (0·50 [0·34–0·74]) and invasive mechanical ventilation (0·42 [0·23–0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74–1·00]), at 5 months (0·74 [0·64–0·88]) to 1 year (0·75 [0·62–0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters. Interpretation The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials. Funding UK Research and Innovation and National Institute for Health Research

Accelarated immune ageing is associated with COVID-19 disease severity

Background The striking increase in COVID-19 severity in older adults provides a clear example of immunesenescence, the age-related remodelling of the immune system. To better characterise the association between convalescent immunesenescence and acute disease severity, we determined the immune phenotype of COVID-19 survivors and non-infected controls. Results We performed detailed immune phenotyping of peripheral blood mononuclear cells isolated from 103 COVID-19 survivors 3–5 months post recovery who were classified as having had severe (n = 56; age 53.12 ± 11.30 years), moderate (n = 32; age 52.28 ± 11.43 years) or mild (n = 15; age 49.67 ± 7.30 years) disease and compared with age and sex-matched healthy adults (n = 59; age 50.49 ± 10.68 years). We assessed a broad range of immune cell phenotypes to generate a composite score, IMM-AGE, to determine the degree of immune senescence. We found increased immunesenescence features in severe COVID-19 survivors compared to controls including: a reduced frequency and number of naïve CD4 and CD8 T cells (p < 0.0001); increased frequency of EMRA CD4 (p < 0.003) and CD8 T cells (p < 0.001); a higher frequency (p < 0.0001) and absolute numbers (p < 0.001) of CD28−ve CD57+ve senescent CD4 and CD8 T cells; higher frequency (p < 0.003) and absolute numbers (p < 0.02) of PD-1 expressing exhausted CD8 T cells; a two-fold increase in Th17 polarisation (p < 0.0001); higher frequency of memory B cells (p < 0.001) and increased frequency (p < 0.0001) and numbers (p < 0.001) of CD57+ve senescent NK cells. As a result, the IMM-AGE score was significantly higher in severe COVID-19 survivors than in controls (p < 0.001). Few differences were seen for those with moderate disease and none for mild disease. Regression analysis revealed the only pre-existing variable influencing the IMM-AGE score was South Asian ethnicity ( = 0.174, p = 0.043), with a major influence being disease severity ( = 0.188, p = 0.01). Conclusions Our analyses reveal a state of enhanced immune ageing in survivors of severe COVID-19 and suggest this could be related to SARS-Cov-2 infection. Our data support the rationale for trials of anti-immune ageing interventions for improving clinical outcomes in these patients with severe disease