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1.
Clocks Sleep ; 3(4): 528-535, 2021 Oct 11.
Article in English | MEDLINE | ID: covidwho-1595183

ABSTRACT

The primary aims of the present study were to examine the impact of chronotype on sleep/wake behaviour, perceived exertion, and training load among professional footballers. Thirty-six elite female professional football player's (mean ± SD: age, 25 ± 4 y; weight, 68 ± 7 kg) sleep and training behaviours were examined for 10 consecutive nights during a pre-season period using a self-report online player-management system and wrist activity monitors. All athletes completed the Morningness-Eveningness Questionnaire (rMEQ) on the first day of data collection. Eleven participants were morning types, seventeen participants were intermediate types, and three participants were evening types. Separate linear mixed models were conducted to assess differences in sleep, perceived exertion, and training behaviours between chronotype groups. Morning types woke up earlier (wake time: 07:19 ± 01:16 vs. 07:53 ± 01:01, p = 0.04) and reported higher ratings of perceived exertion compared to intermediate types (6.7 ± 1.1 vs. 5.9 ± 1.2, p = 0.01). No differences were observed between chronotype groups for bedtime, time in bed, total sleep time, sleep efficiency, training duration, or training load. In circumstances where professional female football players are required to train at a time opposing their natural circadian preference (e.g., morning type training in the evening), their perceived exertion during training may be higher than that of players that are training at a time that aligns with their natural circadian preference (e.g., evening type training in the evening). It is important for practitioners to monitor individual trends in training variables (e.g., rating of perceived exertion, training load) with relation to athlete chronotype and training time. Future research should examine the relationship between chronotype, training time, and rating of perceived exertion across different training durations.

2.
Journal of Chemical Education ; 2021.
Article in English | Scopus | ID: covidwho-1550239

ABSTRACT

Fiber materials and textiles are topics of much research and study today, with efforts being made to produce fibers that are stronger, more durable, more breathable, and better for the environment. However, the production of fibers at the laboratory scale is uncommon and difficult past the prototype phase, and to a commercial fiber production level. Most current fiber spinning systems are too large to be operated anywhere outside of a designated facility and are prohibitively expensive. Here we present the build for a simple and affordable fiber collection device adept for demonstrations, student laboratories, and early research prototyping. This paper describes a nearly laboratory ready, functional fiber collection device that was designed, built, and evaluated during the COVID pandemic. It is constructed of an Arduino microcontroller, a toy motor, and basic circuit components with an assembled cost of ∼$60. The developed spinner's rotational speed ranged from sim;120-960 rpm. Spinner functionality was tested via fiber winding, solution spinning, and melt spinning. It is estimated that the spinner could hold sim;3.5 g worth of fiber before unloading and restarting with a fresh spool. Melt spun fibers produced by the unit were measured to have an average diameter of 31 ± 6 μm. Ultimately, this system was designed to be a low-cost entry point to fiber spinning for research and more primarily for education purposes. The parts list and system design are included and could be expanded upon as part of a learning laboratory exercise around the design/build/test paradigm. The current system works effectively as a demonstration to produce low- to moderate-quality fibers. The design would need to be augmented with a higher-torque motor, and certain components would need to be replaced if higher-quality fibers are desired. © Published 2021 by American Chemical Society and Division of Chemical Education, Inc.

4.
Anaesthesia ; 76(SUPPL 6):88, 2021.
Article in English | EMBASE | ID: covidwho-1483806

ABSTRACT

The North East London Critical Care Transfer And Retrieval (NECCTAR) service was created in December 2020 in response to rapidly increasing pressures on critical care resources due to the COVID-19 pandemic [1]. The service was developed to lead capacity-related transfers within the region, providing a dedicated, skilled service at a time of unprecedented demand. It evolved to support longer-distance transfers across the nation. The model comprises a consultant, registrar, nurse/anaesthetic assistant and London Ambulance Service crew. With rotating teams performing complex inter-hospital transfers, a robust governance process was essential to maintain patient safety. Methods Existing pre-hospital expertise within the nascent service was leveraged to generate a hybrid governance model. Case analysis comprised the first layer. All cases underwent consultant review, which provided targeted feedback. Specific cases were highlighted at governance meetings with multidisciplinary scrutiny and discussion encouraged. Emergent themes guided service development with feedback disseminated at subsequent meetings. The second aspect was incident reporting. Datix was used as per Trust guidelines and a NECCTAR event report form was developed to capture lower risk 'lessons learnt' into horizontal themes for quicker dissemination. Results Open governance meetings were conducted monthly during the pandemic, with high attendance. The entire patient journey was reviewed, alongside technical, human and system factors. Discussions led to improvements in the referral process, acceptance criteria, equipment provision and management of declined transfers, and explored ethical considerations. Standard operating procedures and existing on-board training were revised. Documentation assessment has shaped a new electronic transfer record. Meetings have incorporated expert teaching on complex airways, arrhythmias and cardiogenic shock. The governance process itself was adapted to allow best reporting. Discussion Pandemic conditions did not prove a barrier to methodical capability development, nor robust governance. The process has presented an invaluable opportunity for team-wide learning through shared experience. The model has been continuously developed to disseminate learning to every team member and has informed patient safety as well as service development. The hybrid structure, with combination of case review and reporting systems, is sustainable, inclusive and generalisable.

5.
Movement Disorders ; 36:S2-S2, 2021.
Article in English | Web of Science | ID: covidwho-1436760
6.
PLoS One ; 16(8): e0256063, 2021.
Article in English | MEDLINE | ID: covidwho-1354765

ABSTRACT

The COVID-19 pandemic incited unprecedented restrictions on the behavior of society. The aims of this study were to quantify changes to sleep/wake behavior and exercise behavior, as well as changes in physiological markers of health during COVID-19 physical distancing. A retrospective analysis of 5,436 US-based subscribers to the WHOOP platform (mean age = 40.25 ± 11.33; 1,536 females, 3,900 males) was conducted covering the period from January 1st, 2020 through May 15th, 2020. This time period was separated into a 68-day baseline period and a 67-day physical distancing period. To provide context and allow for potential confounders (e.g., change of season), data were also extracted from the corresponding time periods in 2019. As compared to baseline, during physical distancing, all subjects fell asleep earlier (-0.15 hours), woke up later (0.29 hours), obtained more sleep (+0.21 hours) and reduced social jet lag (-0.13 hours). Contrasting sleep behavior was seen in 2019, with subjects falling asleep and waking up at a similar time (-0.01 hours; -0.03 hours), obtaining less sleep (-0.14 hours) and maintaining social jet lag (+0.06 hours) in corresponding periods. Individuals exercised more intensely during physical distancing by increasing the time spent in high heart rate zones. In 2020, resting heart rate decreased (-0.90 beats per minute) and heart rate variability increased (+0.98 milliseconds) during physical distancing when compared to baseline. However, similar changes were seen in 2019 for RHR (-0.51 beats per minute) and HRV (+2.97 milliseconds), suggesting the variation may not be related to the introduction of physical distancing mandates. The findings suggest that individuals improved health related behavior (i.e., increased exercise intensity and longer sleep duration) during physical distancing restrictions. While positive changes were seen to cardiovascular indicators of health, it is unclear whether these changes were a direct consequence of behavior change.


Subject(s)
Exercise/physiology , Health Behavior , Physical Distancing , Sleep/physiology , Wearable Electronic Devices , Adult , COVID-19 , Female , Health Promotion , Humans , Male , Middle Aged , Pandemics , Retrospective Studies
7.
Irish Medical Journal ; 114(5), 2021.
Article in English | EMBASE | ID: covidwho-1326537

ABSTRACT

Presentation A 40-year-old healthcare worker (HCW) presented with cough, headache, sore throat, fatigue and myalgia seven months after primary infection with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Symptoms were milder and recovery was faster on the second episode. Diagnosis Reinfection with phylogenetically distinct SARS-CoV-2 was confirmed by whole-genome sequencing (WGS). Treatment Management involved symptomatic treatment and self-isolation. Discussion The incidence of SARS-CoV-2 reinfection is not well characterised. Infection control precautions may still be required in healthcare facilities, even in previously infected and possibly in vaccinated individuals while SARS-CoV-2 remains in circulation. Further research on the nature and duration of immunity is required to inform public health and infection control policy.

8.
Physics Education ; 56(5), 2021.
Article in English | Scopus | ID: covidwho-1281837

ABSTRACT

During the coronavirus pandemic, there have been significant challenges in the remote teaching and demonstration of experiments, especially those that require laboratory testing equipment. With a desire to give students a feel for our materials laboratory on open days and allow them to gain a deeper understanding of what materials science and engineering is about, we have designed an experiment focused on composite materials that can be performed remotely and without specialist equipment. This enabled students to experience a bend test sensorily through seeing, hearing and feeling it, creating a strong link to then being able to relate it to the pre-prepared experimental data taken in the laboratory. This fun, easy-to-run and engaging experiment allowed a shared experience and encouraged a discussion about students' observations, differences in results and implications of the bend strength of sandwich composites. We have found it not only works well universally by all ages but can be used with younger children to think about words such as 'stronger', 'stiffer' and 'flexible' and how materials can be different in different directions. © 2021 The Author(s). Published by IOP Publishing Ltd.

9.
J Clin Transl Sci ; 5(1): e100, 2021 Apr 20.
Article in English | MEDLINE | ID: covidwho-1253823

ABSTRACT

INTRODUCTION: The COVID-19 pandemic prompted the development and implementation of hundreds of clinical trials across the USA. The Trial Innovation Network (TIN), funded by the National Center for Advancing Translational Sciences, was an established clinical research network that pivoted to respond to the pandemic. METHODS: The TIN's three Trial Innovation Centers, Recruitment Innovation Center, and 66 Clinical and Translational Science Award Hub institutions, collaborated to adapt to the pandemic's rapidly changing landscape, playing central roles in the planning and execution of pivotal studies addressing COVID-19. Our objective was to summarize the results of these collaborations and lessons learned. RESULTS: The TIN provided 29 COVID-related consults between March 2020 and December 2020, including 6 trial participation expressions of interest and 8 community engagement studios from the Recruitment Innovation Center. Key lessons learned from these experiences include the benefits of leveraging an established infrastructure, innovations surrounding remote research activities, data harmonization and central safety reviews, and early community engagement and involvement. CONCLUSIONS: Our experience highlighted the benefits and challenges of a multi-institutional approach to clinical research during a pandemic.

10.
Nat Commun ; 12(1): 2055, 2021 04 06.
Article in English | MEDLINE | ID: covidwho-1171493

ABSTRACT

Identification of protective T cell responses against SARS-CoV-2 requires distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity to other coronaviruses. Here we show a range of T cell assays that differentially capture immune function to characterise SARS-CoV-2 responses. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) are found in 168 PCR-confirmed SARS-CoV-2 infected volunteers, but are rare in 119 uninfected volunteers. Highly exposed seronegative healthcare workers with recent COVID-19-compatible illness show T cell response patterns characteristic of infection. By contrast, >90% of convalescent or unexposed people show proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on assay and antigen selection. Memory responses to specific non-spike proteins provide a method to distinguish recent infection from pre-existing immunity in exposed populations.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/immunology , COVID-19/virology , Cross Reactions/immunology , Immunoassay/methods , SARS-CoV-2/physiology , T-Lymphocytes/immunology , CD4-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/immunology , COVID-19/epidemiology , Cell Proliferation , Cytokines/metabolism , HEK293 Cells , Health Personnel , Humans , Immunoglobulin G/immunology , Immunologic Memory , Interferon-gamma/metabolism , Pandemics , Peptides/metabolism , SARS-CoV-2/drug effects
11.
BMJ Open ; 11(3): e048317, 2021 03 17.
Article in English | MEDLINE | ID: covidwho-1140339

ABSTRACT

INTRODUCTION: The emergence and rapid spread of COVID-19 have caused widespread and catastrophic public health and economic impact, requiring governments to restrict societal activity to reduce the spread of the disease. The role of household transmission in the population spread of SARS-CoV-2, and of host immunity in limiting transmission, is poorly understood. This paper describes a protocol for a prospective observational study of a cohort of households in Liverpool City Region, UK, which addresses the transmission of SARS-CoV-2 between household members and how immunological response to the infection changes over time. METHODS AND ANALYSIS: Households in the Liverpool City Region, in which members have not previously tested positive for SARS-CoV-2 with a nucleic acid amplification test, are followed up for an initial period of 12 weeks. Participants are asked to provide weekly self-throat and nasal swabs and record their activity and presence of symptoms. Incidence of infection and household secondary attack rates of COVID-19 are measured. Transmission of SARS-CoV-2 will be investigated against a range of demographic and behavioural variables. Blood and faecal samples are collected at several time points to evaluate immune responses to SARS-CoV-2 infection and prevalence and risk factors for faecal shedding of SARS-CoV-2, respectively. ETHICS AND DISSEMINATION: The study has received approval from the National Health Service Research Ethics Committee; REC Reference: 20/HRA/2297, IRAS Number: 283 464. Results will be disseminated through scientific conferences and peer-reviewed open access publications. A report of the findings will also be shared with participants. The study will quantify the scale and determinants of household transmission of SARS-CoV-2. Additionally, immunological responses before and during the different stages of infection will be analysed, adding to the understanding of the range of immunological response by infection severity.


Subject(s)
COVID-19/epidemiology , COVID-19/immunology , COVID-19/transmission , Humans , Observational Studies as Topic , Prospective Studies , Research Design , State Medicine , United Kingdom/epidemiology
12.
Sexual Health ; 17(5):IV-IV, 2020.
Article in English | Web of Science | ID: covidwho-1001050
13.
PLoS One ; 15(12): e0243693, 2020.
Article in English | MEDLINE | ID: covidwho-968239

ABSTRACT

COVID-19, the disease caused by the SARS-CoV-2 virus, can cause shortness of breath, lung damage, and impaired respiratory function. Containing the virus has proven difficult, in large part due to its high transmissibility during the pre-symptomatic incubation. The study's aim was to determine if changes in respiratory rate could serve as a leading indicator of SARS-CoV-2 infections. A total of 271 individuals (age = 37.3 ± 9.5, 190 male, 81 female) who experienced symptoms consistent with COVID-19 were included- 81 tested positive for SARS-CoV-2 and 190 tested negative; these 271 individuals collectively contributed 2672 samples (days) of data (1856 healthy days, 231 while infected with COVID-19 and 585 while negative for COVID-19 but experiencing symptoms). To train a novel algorithm, individuals were segmented as follows; (1) a training dataset of individuals who tested positive for COVID-19 (n = 57 people, 537 samples); (2) a validation dataset of individuals who tested positive for COVID-19 (n = 24 people, 320 samples); (3) a validation dataset of individuals who tested negative for COVID-19 (n = 190 people, 1815 samples). All data was extracted from the WHOOP system, which uses data from a wrist-worn strap to produce validated estimates of respiratory rate and other physiological measures. Using the training dataset, a model was developed to estimate the probability of SARS-CoV-2 infection based on changes in respiratory rate during night-time sleep. The model's ability to identify COVID-positive individuals not used in training and robustness against COVID-negative individuals with similar symptoms were examined for a critical six-day period spanning the onset of symptoms. The model identified 20% of COVID-19 positive individuals in the validation dataset in the two days prior to symptom onset, and 80% of COVID-19 positive cases by the third day of symptoms.


Subject(s)
COVID-19/physiopathology , Lung/physiopathology , Respiratory Rate , SARS-CoV-2/isolation & purification , Adult , COVID-19/diagnosis , Female , Heart Rate , Humans , Male , Middle Aged , Prognosis
14.
Am J Emerg Med ; 42: 203-210, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-959453

ABSTRACT

STUDY OBJECTIVE: Emergency Department (ED) visits decreased significantly in the United States during the COVID-19 pandemic. A troubling proportion of this decrease was among patients who typically would have been admitted to the hospital, suggesting substantial deferment of care. We sought to describe and characterize the impact of COVID-19 on hospital admissions through EDs, with a specific focus on diagnosis group, age, gender, and insurance coverage. METHODS: We conducted a retrospective, observational study of aggregated third-party, anonymized ED patient data. This data included 501,369 patient visits from twelve EDs in Massachusetts from 1/1/2019-9/9/2019, and 1/1/2020-9/8/2020. We analyzed the total arrivals and hospital admissions and calculated confidence intervals for the change in admissions for each characteristic. We then developed a Poisson regression model to estimate the relative contribution of each characteristic to the decrease in admissions after the statewide lockdown, corresponding to weeks 11 through 36 (3/11/2020-9/8/2020). RESULTS: We observed a 32% decrease in admissions during weeks 11 to 36 in 2020, with significant decreases in admissions for chronic respiratory conditions and non-orthopedic needs. Decreases were particularly acute among women and children, as well as patients with Medicare or without insurance. The most common diagnosis during this time was SARS-CoV-2. CONCLUSION: Our findings demonstrate decreased hospital admissions through EDs during the pandemic and suggest that several patient populations may have deferred necessary care. Further research is needed to determine the clinical and operational consequences of this delay.


Subject(s)
COVID-19/epidemiology , Emergency Service, Hospital/statistics & numerical data , Patient Admission/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Diagnosis-Related Groups/statistics & numerical data , Facilities and Services Utilization , Female , Humans , Infant , Infant, Newborn , Male , Massachusetts , Middle Aged , Retrospective Studies , Socioeconomic Factors , Young Adult
15.
Preprint in English | medRxiv | ID: ppmedrxiv-20202929

ABSTRACT

A major issue in identification of protective T cell responses against SARS-CoV-2 lies in distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity generated by exposure to other coronaviruses. We characterised SARS-CoV-2 T cell immune responses in 168 PCR-confirmed SARS-CoV-2 infected subjects and 118 seronegative subjects without known SARS-CoV-2 exposure using a range of T cell assays that differentially capture immune cell function. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) were found in those who had been infected by SARS-CoV-2 but were rare in pre-pandemic and unexposed seronegative subjects. However, seronegative doctors with high occupational exposure and recent COVID-19 compatible illness showed patterns of T cell responses characteristic of infection, indicating that these readouts are highly sensitive. By contrast, over 90% of convalescent or unexposed people showed proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on the choice of assay and antigen. Memory responses to specific non-spike proteins provides a method to distinguish recent infection from pre-existing immunity in exposed populations.

16.
JACC Case Rep ; 2(10): 1651-1653, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-716780
17.
Preprint in English | medRxiv | ID: ppmedrxiv-20131417

ABSTRACT

COVID-19, the disease caused by the SARS-CoV-2 virus, can cause shortness of breath, lung damage, and impaired respiratory function. Containing the virus has proven difficult, in large part due to its high transmissibility during the pre-symptomatic incubation. The studys aim was to determine if changes in respiratory rate could serve as a leading indicator of SARS-CoV-2 infections. A total of 271 individuals (age = 37.3 {+/-} 9.5, 190 male, 81 female) who experienced symptoms consistent with COVID-19 were included - 81 tested positive for SARS-CoV-2 and 190 tested negative; these 271 individuals collectively contributed 2672 samples (days) of data (1856 healthy days, 231 while infected with COVID-19 and 585 while infected with something other than COVID-19). To train a novel algorithm, individuals were segmented as follows; (1) a training dataset of individuals who tested positive for COVID-19 (n=57 people, 537 samples); (2) a validation dataset of individuals who tested positive for COVID-19 (n=24 people, 320 samples) ; (3) a validation dataset of individuals who tested negative for COVID-19 (n=190 people, 1815 samples). All data was extracted from the WHOOP system, which uses data from a wrist-worn strap to produce validated estimates of respiratory rate and other physiological measures. Using the training dataset, a model was developed to estimate the probability of SARS-CoV-2 infection based on changes in respiratory rate during night-time sleep. The models ability to identify COVID-positive individuals not used in training and robustness against COVID-negative individuals with similar symptoms were examined for a critical six-day period spanning the onset of symptoms. The model identified 20% of COVID-19 positive individuals in the validation dataset in the two days prior to symptom onset, and 80% of COVID-19 positive cases by the third day of symptoms.

18.
Preprint in English | medRxiv | ID: ppmedrxiv-20124685

ABSTRACT

The COVID-19 pandemic incited unprecedented restrictions on the behavior of society. The aims of this study were to quantify changes to sleep/wake behavior and exercise behavior, as well as changes in physiological markers of health during COVID-19 physical distancing. A retrospective analysis of 5,436 US-based subscribers to the WHOOP platform (mean age = 40.25 {+/-} 11.33; 1,536 females, 3,900 males) was conducted covering the period from January 1st, 2020 through May 15th, 2020. This time period was separated into a 68-day baseline period and a 67-day physical distancing period. To provide context and allow for potential confounders (e.g., change of season), data were also extracted from the corresponding time periods in 2019. As compared to baseline, during physical distancing, all subjects fell asleep earlier (-0.25 hours), woke up later (0.48 hours), obtained more sleep (+0.35 hours) and reduced social jet lag (-0.21 hours). Contrasting sleep behavior was seen in 2019, with subjects falling asleep and waking up at a similar time (-0.01 hours; -0.05 hours), obtaining less sleep (-0.14 hours) and maintaining social jet lag (0.01 hours) in corresponding periods. Individuals exercised more intensely during physical distancing by increasing the time spent in high heart rate zones. In 2020, resting heart rate decreased (-0.9 beats per minute) and heart rate variability increased (+0.98 milliseconds) during physical distancing when compared to baseline. However, similar changes were seen in 2019, suggesting the variation may not be related to the introduction of physical distancing mandates. The findings suggest that changes in societal commitments (e.g., daily commute; working from home) during physical distancing may have resulted in changes to health-related behavior (i.e., increased exercise intensity and longer sleep duration). As the COVID-19 pandemic eases, maintenance of certain aspects of physical distancing (e.g., working from home) may allow for positive changes to sleep/wake and exercise behaviors.

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