The Effects of pH on the Kinetics of the Follow-up Reaction of Dopamine o-quinone

The electrochemical studies of dopamine have been conducted for many years due to dopamine’s importance as a neurotransmitter and its function in daily life for individuals. Dopamine undergoes electrochemical redox reactions in which the different products can be detected by cyclic voltammetry.3 The focus of the experiments was to determine the pH range at which dopamine o-quinone would undergo cyclization as well as the relationship between the rate of cyclization as pH in the physiological range. The measurements were taken using a gold working electrode vs. a Ag/AgCl (1 M KCl) reference electrode. It was observed that the peaks corresponding to the redox reactions for aminochrome and leukoaminochrome formed at pH 5.77 but not pH 5.60. From this data, the pH range at which cyclization of dopamine o-quinone occurred was between pH 5.60 and 5.77. Pre-peaks (appearing as shoulders) were noticed before the oxidation peak pertaining to the oxidation of dopamine when using dopamine solution that had darkened from being exposed to light. Measurements were taken at a pH range from 7.20 to 7.85 to determine the relationship between rate of cyclization and pH. A linear relationship was established such that the rate of cyclization was dependent upon the pH, and that as the pH increased, the rate of cyclization also increased. However, the data points for pH’s 7.50 and 7.70 did not fit into the linearity due to the measurements taken using dirty electrodes as well as unknown factors, hence were determined to be outliers. Despite this, it was observed that at pH 7.85, the rate of cyclization is 0.0332 s-1, which was the largest rate observed when looking at the linear relationship between the rate of cyclization and pH. Overall, from the experiments performed, we were able to determine both the threshold at which cyclization of dopamine o- quinone began as well as the relationship between the rate of cyclization and pH values within the physiological range

Investigating the Impact of Bound-Water Exclusion on the PARACEST MRI and Optical Properties of Lanthanide (III) Complexes

Lanthanide (III) complexes exhibit both paramagnetic and photophysical properties which make them attractive for Magnetic Resonance Imaging (MRI) and optical imaging applications. The combination of these two properties presents an opportunity to develop a single imaging agent that is applicable in two different modalities. The goal of the project is to develop Ln (III) complexes comprising a nonadentate ligand and a lanthanide ion, that can serve as bimodal agents. The main characteristic differentiating our proposed agents from traditional imaging agents is the exclusion of the water molecule typically associated with the lanthanide ion. Such a complex has the potential to facilitate the image-guided delineation of tumor boundaries during surgery. So far, three of the six synthetic steps have been successfully completed, and the identities of the products obtained have been verified by 1H-NMR and 13C-NMR Spectroscopy. Future work includes completion of the Ln(III) complex syntheses, and evaluation of the NMR and luminescence properties

Deprivation, essential and non-essential activities and SARS-CoV-2 infection following the lifting of national public health restrictions in England and Wales [version 1; peer review: awaiting peer review]

BACKGROUND: Individuals living in deprived areas in England and Wales undertook essential activities more frequently and experienced higher rates of SARS-CoV-2 infection than less deprived communities during periods of restrictions aimed at controlling the Alpha (B.1.1.7) variant. We aimed to understand whether these deprivation-related differences changed once restrictions were lifted. METHODS: Among 11,231 adult Virus Watch Community Cohort Study participants multivariable logistic regressions were used to estimate the relationships between deprivation and self-reported activities and deprivation and infection (self-reported lateral flow or PCR tests and linkage to National Testing data and Second Generation Surveillance System (SGSS)) between August – December 2021, following the lifting of national public health restrictions. RESULTS: Among 11,231 adult Virus Watch Community Cohort Study participants multivariable logistic regressions were used to estimate the relationships between deprivation and self-reported activities and deprivation and infection (self-reported lateral flow or PCR tests and linkage to National Testing data and Second Generation Surveillance System (SGSS)) between August – December 2021, following the lifting of national public health restrictions. CONCLUSIONS: The lack of association between deprivation and infection is likely due to the increased engagement in non-essential activities among the least deprived balancing the increased work-related exposure among the most deprived. The differences in activities highlight stark disparities in an individuals’ ability to choose how to limit infection exposure

The changing contributory role to infections of work, public transport, shopping, hospitality and leisure activities throughout the SARS-CoV-2 pandemic in England and Wales

Background: Understanding how non-household activities contributed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections under different levels of national health restrictions is vital. // Methods: Among adult Virus Watch participants in England and Wales, we used multivariable logistic regressions and adjusted-weighted population attributable fractions (aPAF) assessing the contribution of work, public transport, shopping, and hospitality and leisure activities to infections. // Results: Under restrictions, among 17,256 participants (502 infections), work [adjusted odds ratio (aOR) 2.01 (1.65–2.44), (aPAF) 30% (22–38%)] and transport [(aOR 1.15 (0.94–1.40), aPAF 5% (-3–12%)], were risk factors for SARS-CoV-2 but shopping, hospitality and leisure were not. Following the lifting of restrictions, among 11,413 participants (493 infections), work [(aOR 1.35 (1.11–1.64), aPAF 17% (6–26%)] and transport [(aOR 1.27 (1.04–1.57), aPAF 12% (2–22%)] contributed most, with indoor hospitality [(aOR 1.21 (0.98–1.48), aPAF 7% (-1–15%)] and leisure [(aOR 1.24 (1.02–1.51), aPAF 10% (1–18%)] increasing. During the Omicron variant, with individuals more socially engaged, among 11,964 participants (2335 infections), work [(aOR 1.28 (1.16–1.41), aPAF (11% (7–15%)] and transport [(aOR 1.16 (1.04–1.28), aPAF 6% (2–9%)] remained important but indoor hospitality [(aOR 1.43 (1.26–1.62), aPAF 20% (13–26%)] and leisure [(aOR 1.35 (1.22–1.48), aPAF 10% (7–14%)] dominated. // Conclusions: Work and public transport were important to transmissions throughout the pandemic with hospitality and leisure’s contribution increasing as restrictions were lifted, highlighting the importance of restricting leisure and hospitality alongside advising working from home, when facing a highly infectious and virulent respiratory infection

Symptom profiles of community cases infected by influenza, RSV, rhinovirus, seasonal coronavirus, and SARS-CoV-2 variants of concern

Respiratory viruses that were suppressed through previous lockdowns during the COVID-19 pandemic have recently started to co-circulate with SARS-CoV-2. Understanding the clinical characteristics and symptomatology of different respiratory viral infections can help address the challenges related to the identification of cases and the understanding of SARS-CoV-2 variants' evolutionary patterns. Flu Watch (2006-2011) and Virus Watch (2020-2022) are household community cohort studies monitoring the epidemiology of influenza, respiratory syncytial virus, rhinovirus, seasonal coronavirus, and SARS-CoV-2, in England and Wales. This study describes and compares the proportion of symptoms reported during illnesses infected by common respiratory viruses. The SARS-CoV-2 symptom profile increasingly resembles that of other respiratory viruses as new strains emerge. Increased cough, sore throat, runny nose, and sneezing are associated with the emergence of the Omicron strains. As SARS-CoV-2 becomes endemic, monitoring the evolution of its symptomatology associated with new variants will be critical for clinical surveillance

Inequalities in access to paid sick leave among workers in England and Wales

Background: It is poorly understood which workers lack access to sick pay in England and Wales. This evidence gap has been of particular interest in the context of the Covid-19 pandemic given the relationship between presenteeism and infectious disease transmission. // Method: This cross-sectional analysis (n = 8874) was nested within a large community cohort study based across England and Wales (Virus Watch). An online survey in February 2021 asked participants in work if they had access to paid sick leave. We used logistic regression to examine sociodemographic factors associated with lacking access to sick pay. // Results: Only 66% (n = 5864) of participants reported access to sick pay. South Asian workers (adjusted odds ratio [OR] 1.40, 95% confidence interval [CI] 1.06–1.83) and those from Other minority ethnic backgrounds (OR 2.93, 95% CI 1.54–5.59) were more likely to lack access to sick pay compared to White British workers. Older workers (OR range 1.72 [1.53–1.93]–5.26 [4.42–6.26]), workers in low-income households (OR 2.53, 95% CI 2.15–2.98) and those in transport, trade, and service occupations (OR range 2.03 [1.58–2.61]–5.29 [3.67–7.72]) were also more likely to lack access to sick pay compared respectively to workers aged 25–44, those in high income households and managerial occupations. // Discussion: Unwarranted age and ethnic inequalities in sick pay access are suggestive of labour market discrimination. Occupational differences are also cause for concern. Policymakers should consider expanding access to sick pay to mitigate transmission of Covid-19 and other endemic respiratory infections in the community, and in the context of pandemic preparation

Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales

BACKGROUND: Workers across different occupations vary in their risk of SARS-CoV-2 infection, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase. METHODS: Data from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR). RESULTS: Increased risk was seen in nurses (aRR = 1.44, 1.25-1.65; AF = 30%, 20-39%), doctors (aRR = 1.33, 1.08-1.65; AF = 25%, 7-39%), carers (1.45, 1.19-1.76; AF = 31%, 16-43%), primary school teachers (aRR = 1.67, 1.42- 1.96; AF = 40%, 30-49%), secondary school teachers (aRR = 1.48, 1.26-1.72; AF = 32%, 21-42%), and teaching support occupations (aRR = 1.42, 1.23-1.64; AF = 29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020-May 2021) and attenuated later (June-October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves. CONCLUSIONS: Occupational differences in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions

Settings for non-household transmission of SARS-CoV-2 during the second lockdown in England and Wales – analysis of the Virus Watch household community cohort study [version 1; peer review: 2 approved]

Background: "Lockdowns" to control serious respiratory virus pandemics were widely used during the coronavirus disease 2019 (COVID-19) pandemic.  However, there is limited information to understand the settings in which most transmission occurs during lockdowns, to support refinement of similar policies for future pandemics. / Methods: Among Virus Watch household cohort participants we identified those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outside the household.  Using survey activity data, we undertook multivariable logistic regressions assessing the contribution of activities on non-household infection risk.  We calculated adjusted population attributable fractions (APAF) to estimate which activity accounted for the greatest proportion of non-household infections during the pandemic's second wave. / Results: Among 10,858 adults, 18% of cases were likely due to household transmission.  Among 10,475 participants (household-acquired cases excluded), including 874 non-household-acquired infections, infection was associated with: leaving home for work or education (AOR 1.20 (1.02 - 1.42), APAF 6.9%); public transport (more than once per week AOR 1.82 (1.49 - 2.23), public transport APAF 12.42%); and shopping (more than once per week AOR 1.69 (1.29 - 2.21), shopping APAF 34.56%).  Other non-household activities were rare and not significantly associated with infection. / Conclusions: During lockdown, going to work and using public or shared transport independently increased infection risk, however only a minority did these activities.  Most participants visited shops, accounting for one-third of non-household transmission.  Transmission in restricted hospitality and leisure settings was minimal suggesting these restrictions were effective.   If future respiratory infection pandemics emerge these findings highlight the value of working from home, using forms of transport that minimise exposure to others, minimising exposure to shops and restricting non-essential activities

Bayesian reconstruction of SARS-CoV-2 transmissions highlights substantial proportion of negative serial intervals

BACKGROUND: The serial interval is a key epidemiological measure that quantifies the time between the onset of symptoms in an infector-infectee pair. It indicates how quickly new generations of cases appear, thus informing on the speed of an epidemic. Estimating the serial interval requires to identify pairs of infectors and infectees. Yet, most studies fail to assess the direction of transmission between cases and assume that the order of infections - and thus transmissions - strictly follows the order of symptom onsets, thereby imposing serial intervals to be positive. Because of the long and highly variable incubation period of SARS-CoV-2, this may not always be true (i.e an infectee may show symptoms before their infector) and negative serial intervals may occur. This study aims to estimate the serial interval of different SARS-CoV-2 variants whilst accounting for negative serial intervals. METHODS: This analysis included 5 842 symptomatic individuals with confirmed SARS-CoV-2 infection amongst 2 579 households from September 2020 to August 2022 across England & Wales. We used a Bayesian framework to infer who infected whom by exploring all transmission trees compatible with the observed dates of symptoms, based on a wide range of incubation period and generation time distributions compatible with estimates reported in the literature. Serial intervals were derived from the reconstructed transmission pairs, stratified by variants. RESULTS: We estimated that 22% (95% credible interval (CrI) 8-32%) of serial interval values are negative across all VOC. The mean serial interval was shortest for Omicron BA5 (2.02 days, 1.26-2.84) and longest for Alpha (3.37 days, 2.52-4.04). CONCLUSIONS: This study highlights the large proportion of negative serial intervals across SARS-CoV-2 variants. Because the serial interval is widely used to estimate transmissibility and forecast cases, these results may have critical implications for epidemic control