Although the coronavirus disease 19 (COVID-19) pandemic has now impacted the world for over two years, the persistent secondary neuropsychiatric effects are still not fully understood. These “long COVID” symptoms, also referred to as post-acute sequelae of SARS-CoV-2 infection (PASC), can persist for months after infection without any effective treatments. Long COVID involves a complex heterogenous symptomology and can lead to disability and limit work. Long COVID symptoms may be due to sustained inflammatory responses and prolonged immune response after infection. Interestingly, vagus nerve stimulation (VNS) may have anti-inflammatory effects, however, until recently, VNS could not be self-administered, at-home, noninvasively.ClinicalTrials.gov under the identifier: NCT04638673.We created a double-blind, noninvasive transcutaneous auricular VNS (taVNS) system that can be self-administered at home with simultaneous remote monitoring of physiological biomarkers and video supervision by study staff. Subsequently, we carried out a pilot (n = 13) randomized, sham-controlled, trial with this system for four weeks to treat nine predefined long covid symptoms . No in-person patient contact was needed, with informed consent, trainings, ratings, and all procedures being conducted remotely during the pandemic (2020–2021) and equipment being shipped to individuals’ homes. This trial was registered onFour-weeks of at-home self-administered taVNS  was feasible and safe. Although our trial was not powered to determine efficacy as an intervention in a heterogenous population, the trends in the data suggest taVNS may have a mild to moderate effect in reducing mental fatigue symptoms in a subset of individuals. This innovative study demonstrates the safety and feasibility of supervised self-administered taVNS under a fully contactless protocol and suggests that future studies can safely investigate this novel form of brain stimulation at-home for a variety of neuropsychiatric and motor recovery applications. The worldwide impact of the novel coronavirus disease COVID-19) has been well documented over the prior two years of what became a global pandemic9 has bee. The acuThe World Health Organization defines Long COVID as “a condition that occurs in individuals with a history of probable or confirmed SARS CoV-2 infection, usually 3 months from the onset of COVID-19, with symptoms and that lasts for at least 2 months and cannot be explained by an alternative diagnosis.” Long COVID has many symptoms, often involving central and peripheral systems and results in fatigue, respiratory difficulty, musculoskeletal pain, loss of taste and smell, fever, brain fog, and new onset of neuropsychiatric conditions like anxiety and depression–12. AlthNon-invasive brain stimulation (NIBS) has been suggested as a possible approach to manage COVID-19–15. VariThe onset of the COVID-19 pandemic provided an opportunity to accelerate investigating the use of completely remote, self-administered, telemedicine approaches to brain stimulation studies. Building on that concept, we created an at-home, remote-monitored, self-administrable taVNS system, integrated with telehealth and biomarker monitoring, to manage symptoms associated with Long COVID in individuals who had prior infection with SARS CoV-2 virus. We investigated whether remote-monitored taVNS was feasible, tolerable, and whether taVNS self-administered twice daily for up to four weeks reduced symptoms associated with Long COVID.ClinicalTrials.org (NCT04638673). All participants signed written informed consent.We conducted a 4-week, double-blind, sham-controlled, transcutaneous auricular vagus nerve stimulation (taVNS) trial exploring the effects of at-home, self-administered taVNS to manage long COVID symptoms . This stWe consented and 13 individuals (8 women) who previously tested positive for COVID-19 into this remote-monitored at-home trial. Because this study was conducted during the COVID-19 pandemic from November 2020 to August 2021, no procedures were conducted in person. One participant was unable to provide a laboratory confirmed COVID positive test, and was not randomized into the study, thus we randomized and treated 12 total participants. All study procedures conducted by participants  were completed via virtual methods , and the taVNS devices and monitoring equipment were shipped to their home.The inclusion criteria were as follow: over the age of 18; laboratory-confirmed COVID-19 infection; afebrile; new onset of at least one of the following nine neuropsychiatric symptoms associated with long COVID ; no damage to either left or right ear anatomy; no unstable hemodynamic effects; no ischemic or haemorrhagic stroke after developing COVID-19; ability to provide informed consent, follow instructions, read, write and speak English; attest to having reliable access to Wi-Fi internet at home.To safely and effectively deliver taVNS at-home, in a manner that is user-friendly and portable, the study team designed a hard-shell briefcase containing all study related equipment. This included stimulation equipment, real time physiology monitoring equipment, and telecommunications devices required for remote monitoring .A detailed list of the contents of the briefcase are as follow: one taVNS stimulator , 100 + pre-packaged taVNS electrodes , 100 + alcohol prep pads (70% ETOH), six rechargeable lithium ion AAA batteries and charger, one vital monitoring tablet , vital monitoring device , three vAfter completing the virtual consent and baseline visit utilizing HIPAA-compliant telemedicine software , subjects were informed that they would be shipped a neurostimulation briefcase and simultaneously e-mailed three training videos that they were instructed to watch prior to a planned future orientation session. These videos covered overall guidance on how to use the mobile neurostimulation briefcase, including: 1) welcome and unboxing of briefcase, 2) how to use the vital monitoring device, and 3) how to use the taVNS device.After receiving the briefcase, participants were instructed to charge all internal electronic components. Subsequently, participants then attended a virtual orientation session with a study team member during which they were trained on how to use the systems provided in the briefcase. During this orientation, the study team covered three main overarching topics: 1) the purpose of each piece of equipment; 2) how to operate the vital monitoring device; 3) how to place the taVNS electrodes, turn on the stimulator and input the code to activate the stimulation device for a treatment.Upon successful completion of this orientation visit, the study team scheduled the first treatment visit. Participants were instructed that they will be virtually monitored for compliance and safety during at least their first three days . Furthermore, participants were given instructions on how to contact the study team during normal business hours for any ongoing technical support.All taVNS was administered using adhesive hydrogel electrodes  attached to the left ear of participants . First, All taVNS sessions utilized the following parameters: 25Hz, 500us pulse width, tonically on for 1 hour, twice per day, 6 days per week. Current intensity was set to 2X individual perceptual threshold (PT), self-determined via methods described in our prior work. PerceptWe monitored the safety of taVNS by measuring blood pressure and heart rate during the first six 1-hour taVNS sessions for each participant. Safety monitoring was conducted in real-time using a dedicated tablet connected to WIFI, which communicated with a wrist-worn pneumatic device that measured heart rate and blood pressure in real time using a finger cuff attached to the middle finger of the nondominant hand of the participant . The research staff was able to remotely connect and monitor the vitals using a web browser. Monitoring was performed for the duration of each monitored session. The study staff-maintained visual and phone communication with the participant to understand qualitative metrics of comfort, tolerability, and adverse events. All quantitative heart rate data was collected and stored for analysis of bradycardia events.We created a battery of outcomes to track heterogenous symptom improvements. We primarily focused on mood and anxiety effects, however due to the broad range of long-COVID impacts on the body and brain, we also included several other measures of fatigue, smell, and cognition. Our battery included the following assessments: General Anxiety Disorder-7 (GAD7), Clinical Global Impression Improvement (CGI-I), Clinical Global Impression Severity (CGI-S), Global Assessment of Functioning (GAF), COVID questionnaire, Connor Davidson Resilience Scale (CDRS), abbreviated PTSD Checklist (PCL6), Perceived Stress Scale (PSS10), Patient Health Questionnaires , pain scale, mental fatigue scale, fatigue severity scale, modified fatigue impact scale, subjective smell assessment, and the Montreal Cognitive Assessment (MOCA). Participants completed all assessments, which were virtually administered by research staff remotely via provided tablet.We enrolled and consented 13 individuals, however one participant was dropped out of the study before being randomized to receive any intervention due to an inability to provide a positive COVID test. Thus, 12 individuals were randomized, and all participants completed the study without dropout.This study was designed for primary outcomes of feasibility and safety, with secondary outcomes exploring symptom improvement in nine pre-identified Long COVID symptoms. Feasibility measures were assessed by objectively rating self-administration procedures during remote-monitored pre-stimulation orientation visit, as well as the first six treatment sessions. Research staff indicated whether a participant required assistance during self-administration and scored the assistance needed for each participant for both the physiology monitoring and taVNS on a scale of 0 = no help needed, 1 = minor help needed 2 = major help needed.Tolerability and safety outcomes were quantified by analysing participant real-time heart rate (hr) during stimulation in their first six sessions receiving at-home stimulation, regardless of randomization group assignment. For clinical measures, individual symptom improvement trends are described in a raw, individual comparison format to show trends for future trials to build upon. All statistical analysis were conducted in performed using GraphPad Prism version 8.0.0 for Windows, GraphPad Software, San Diego, California USA.Of randomized participants, there were no dropouts, and the blind was maintained until the final participant completed all study procedures, after which the entire study team was unblinded to the conditions.All 12 randomized participants  completed all required study visits without dropout. Feasibility was monitored remotely, and findings reveal both the at-home heart rate monitoring and taVNS training provided before and during this trial resulted in participants who could confidently self-administer this novel intervention in a short period of time. At the initial pre-stimulation orientation period, 91% of users required assistance using the remote heart rate monitoring, and all users required assistance with taVNS setup. The amount of assistance required for both physiology monitoring and taVNS reduced each session, so that 100% of users were able to self-administer all study procedures without assistance by the 5th session (third day of the 28-day intervention) .Furthermore, participants were asked to complete two, one-hour taVNS sessions per day, for a period of 4 weeks, with a total of 48 sessions to be administered over this period. A compliance analysis exploring the percentage of completed sessions out of the total possible number of sessions by group reveals that within the 2-week randomized period, both active and sham groups maintained a high level of compliance . Compliance numbers were reduced in the subsequent 2-week open-label phase, with the initial sham group maintaining only 84% compliance, however the initially active group maintained a 94% compliance rate.taVNS systems monitor the real-time within-session use data. These data were analysed to determine the overall average successful minutes out of the possible 60 min taVNS session. In the double-blind phase, participants in the sham group received an average of 52.3 minutes of sham stimulation in each session, whereas the active group received an average of 55.8 minutes of active stimulation. In the open-label phase, again, use was reduced in both groups, with the original sham group receiving on average 46 minutes of the possible 60 minutes of active stimulation in each open-label session, and the original active group receiving 52.3 minutes of active stimulation in each open-label session.Stimulation intensities were not significantly different between randomized intervention group. The mean (± SD) perceptual thresholds were Sham (n = 6): 0.3 ± 0.17 mA and Active (n = 6): 0.317 ± 0.08 mA. The treatment stimulation intensity was set to a 2X multiplier of the initial perceptual threshold value, however on rare occasions, if this dose was uncomfortable, a 0.1 mA reduction was initiated. The mean treatment intensities were Sham: 0.5 ± 0.21 mA Active: 0.6 ± 0.14 mA.No unanticipated adverse events occurred throughout the trial. There were 2 instances of mild skin irritation (redness from prolonged stimulation that would not resolve for 24 hours), and thus that participant switched to self-administer stimulation on the right ear until this resolved.taVNS did not produce any adverse cardiac events. Heart rate was recorded during the first 6 taVNS sessions (of the randomized period) throughout the duration of the treatment period. We monitored the symptoms of nine specific Long COVID symptoms . Due to the heterogeneity of Long COVID, participants did not present with all nine symptoms, however we calculated the overall percentage of these nine symptoms as a meta-indicator of Long COVID severity. At baseline, the sham group reported a higher number of symptoms present . At completion of the 2-week blinded phase, the sham group showed no improvement in symptoms present (68%), however the active group had a reduced number of reported symptoms (31%). After the 4-week treatment phase, both groups  reported 38% of the nine symptoms. Interestingly, during the follow-up phase, the initial sham group who only received 2 weeks of active treatment worsened. They increased to a self-reported 56% of symptoms, whereas the initial active group who received 4 total weeks of treatment reported 23% .Although this study was not powered to demonstrate effectiveness of taVNS on any one individual symptom of Long COVID, interesting individual trends were revealed in in mental fatigue. In this trial, we designed and developed a completely remote, double-blind, telemedicine controlled, transcutaneous auricular vagus nerve stimulation system (taVNS) with companion real-time heart rate monitoring. We then investigated the use of this novel, self-administrable taVNS system during the early COVID-19 pandemic (2020–2021) to understand its safety, feasibility, and potential to manage Long COVID symptoms in the home setting. Each participant self-administered taVNS twice daily, in one-hour sessions, six days a week for up to 4 weeks. This completely remote and virtual (no in-person visits) brain stimulation approach was feasible, with participants learning how to reliably self-administer stimulation within their first five sessions. Furthermore, stimulation was safe, even at home, with no bradycardia or serious adverse events occurring during the stimulation sessions. Lastly, there was a mild improvement in overall self-reported Long COVID symptoms, as well as mental fatigue, although this small study was not powered to detect clinical effects.It has been over two years since the beginning of the COVID-19 pandemic, but the persistent, long-term impacts of the SARS-CoV-2 virus are still not understood. Long COVID is a complex and heterogenous disorder that involves several central and peripheral symptoms that are difficult to individually address from a mechanistic perspective. Even with these challenges, a main underlying hypothesis is that these prolonged symptoms are due to extended neuroinflammatory response. Interestingly, although vagus nerve stimulation (VNS) has been used in humans since 1997 for treating refractory epilepsy, there rEarly evidence from an alternative noninvasive VNS trial  suggests that stimulation of the vagus nerve has mild anti-inflammatory effects in 97 COVID-19 patients. AlthougThis small pilot trial has several limitations, many arising from the exploratory science conducted during an unprecedented time where innovation and deployment of interventions were quite rapid. Long COVID at the time this study began, and still today, is not well understood, and the heterogeneity of the sample reduced our ability to detect any significant behavioural impact. In larger, follow-up studies, a narrower inclusion criterion may be beneficial, however this heterogeneity may introduce confounding variables in an otherwise narrow inclusion criterion. Aside from our small sample size and lack of power to determine behavioural effects, this study was intended create a new completely remote brain stimulation technology that could continue to be researched in Long COVID.taVNS is still in its infancy as a neurostimulation modality and the dosing considerations are yet to be established. We decided to deliver two, one-hour sessions daily for four weeks. Although tolerable and safe, and demonstrated to have high compliance, this may have been burdensome to participants. Increasing the number of sessions or length of sessions may perhaps bolster behavioural effects, however skin irritation may emerge as a limiting factor.This study successfully built and deployed a completely remote, at-home, supervised taVNS system that was tolerable, safe, and used with exceptionally high compliance rates in a small sample of Long COVID patients. Over four weeks, 12 participants were able to successfully self-administer taVNS with limited training and were self-sufficient within two days. Furthermore, compliance was high, and no reports of adverse cardiac effects. Future investigations and randomized trials should be conducted using similar methodology in a larger sample of Long COVID patients.


This study examined the psychometric properties of the seven-item mastery scale among 392 family caregivers of care dependent older adults in a tertiary hospital in Singapore. Item response theory (IRT) analysis and confirmatory factor analysis (CFA) were used to assess the scale’s psychometric properties. Construct validity was assessed based on correlations between mastery and caregiver burden, depression, and quality of life. Data from the seven-item mastery scale showed acceptable reliability and model fit while IRT analysis showed that response categories were ordered but reflected poor fit for the two positively worded items. Without these two items, responses on the five-item version showed acceptable model fit and had acceptable reliability and high correlation with those on the seven-item version. Item responses on both the seven- and five-item versions show logical correlations with carer self-report on burden, depression, and quality of life. Further psychometric studies of the seven-item mastery scale are warranted. For practical applications such as caregiver screening during hospital admissions, the five-item mastery scale is fit for purpose. Mastery is the degree to which individuals feel that they have control over their life situations . Unlike The protective effects of mastery have been documented in several populations. In caregivers of older adults who require assistance with daily living such as dementia patients, mastery has been shown to be negatively associated with caregiver burden, anxiety and depression, and positively associated with health-related quality of life (HRQoL) ,5. This Pearlin and Schooler’s personal mastery scale  is the mWhile past studies have found that the mastery scale has acceptable psychometric properties, a common finding was the poor performance of the two positively worded items, (item no. 4 and 6). In particular, a Japanese study conducted with residents in the community, showed that removing the two positively worded items would result in better reliability and confirmatory factor analysis (CFA) fit statistics . This waSpecifically, while the mastery scale has been frequently used in research involving caregivers of care dependent older adults ,18,19,20The current sample combines two cohorts of family caregivers of hospitalized older adults from a 1700 bed tertiary hospital in Singapore ,15. In bThe seven-item personal mastery scale developed by Pearlin and Schooler  was usedPerceived burden was assessed using the Zarit burden interview (ZBI) . The ZBIDepressive symptoms were measured by the depression subscale of the hospital anxiety and depression scale (HADS-D), which has been shown to reliably assess depressive symptoms in clinical and general populations. HADS-D contains seven items rated on a four-point scale from 0 to 3 . The totHealth related quality of life (HRQoL) was measured using the short form-12 version 2 (SF-12v2). The SF12v2 is widely used and well validated in a variety of population groups as a quality of life measure. The SF-12v2 comprises 12 items which can be aggregated into a physical component summary (PCS) and a mental component summary (MCS), which measure physical and mental HRQoL, respectively . The comCaregiver demographics including age, gender, education level, patient-caregiver relationship, living arrangements, and presence of domestic helpers were also collected.Analyses were performed using IBM SPSS Statistics for Windows, version 25.0  and the Confirmatory factor analysis (CFA) was conducted to assess whether the scale conformed to the one-factor model. As the mastery scale responses were treated as categorical data, the robust weighted least squares and variance adjusted (WLSMV) estimator was used. Acceptable model fit for CFA was assessed by a combination of indices (with the cut-off criteria within brackets): comparative fit index (CFI ≥ 0.95), and Tucker–Lewis index (TLI > 0.90), root mean square error of approximation (RMSEA < 0.08), and standardized root mean square residual (SRMR ≤ 0.08) ,34,35.x-axis representing the mastery level being measured and the y-axis representing the probability of endorsing a particular option to an item, describes the relationship between an individual’s mastery trait and their responses to an item. An item which performs well has a shape where the category thresholds are arranged in an ordered manner .After testing the CFA model, Samejima’s graded response model (GRM)  was usedy-axis) and how the sensitivity varies depending on whether individuals have below average, average, and above average mastery (x-axis) [The IIC shows the level of sensitivity of a mastery item ((x-axis) . In gene(x-axis) .Subsequently, the reliability and construct validity of the five-item mastery scale was also compared against the original seven-item mastery scale. We used McDonald’s omega (ω) as it provides better estimates of reliability than Cronbach’s alpha , especiaOf the 489 caregivers approached, 97 refused participation yielding a final sample of 392 caregivers. Their mean age was 57.6 years old (SD = 11.5). The majority were female (66.3%), Chinese (84.4%), children of the care-recipients (72.7%), and living with their care-recipients (78.3%). About 50% of the participants were working either full or part-time and had a live-in domestic helper. Their mastery levels covered the entire spectrum of possible mastery scores, ranging from 7 to 28 . The sample characteristics are presented in p < 0.001) and ranged from 0.32 to 0.75. Items 4 and 6 had the lowest factor loadings of 0.32 and 0.41, respectively, as compared to the other 4 items with factor loadings of ≥0.63.Overall, results of the CFA of the seven-item mastery scale showed moderate fit for a one-factor structure . Factor loadings for all items were significant  and ranged from 0.64 to 0.77.The CFA of the five-item mastery scale showed moderate fit to the data . Factor loadings for all items were significant . Notably, both five-item and seven-item versions of the mastery scale were negatively correlated with HADS-D and burden , and positively correlated with HRQoL .Results of the Pearson correlations between both versions of the mastery scales and the caregiver outcomes are presented in Our study examined psychometric properties of the Pearlin Mastery scale  amongst As hypothesized, the two positively worded items (items four and six) in the seven-item scale did not perform well, prompting further analysis of the five-item version. CFA analysis of the seven-item scale showed that the two positively worded items had the lowest factor loadings (≤0.41). IRT results also revealed that the two positively worded items have the lowest discriminative ability and lowest item information across the range of mastery levels.There was a moderate negative association between mastery and burden. This notable finding could be attributed to caregivers with higher levels of mastery perceiving caregiving challenges as less stressful as compared to those with lower levels of mastery ,41. In aThe poor performance of the two positively worded items mirrors past studies which reflect poorer model fit and reliability for the seven-item version as compared to the five-item version ,12,13,14Mastery is a construct with positive connotations. Hence, it may raise some concerns when the original seven-item scale has only two positively worded items while the five-item version has no positively worded items. Here, it is important to consider the context in which the Pearlin Mastery scale was developed. It was initially developed to assess individuals in stressful roles  and subsAfter reviewing the items in the scale, no conclusive reasons were found to suggest that the positive items systematically differed from the negative ones , leading to their poor fit. A possible reason for their poor performance could be wording effects which affect these reverse-worded items, leading to the measurement of an unrelated artefact that was not intended to be measured ,45,46,47Our work extends the use of Pearlin mastery tool beyond community dwelling individuals and patient populations ,10,11,12Our study was conducted amongst family caregivers of hospitalized older adults. Hence, our findings may be more applicable to this sample of caregivers. Furthermore, hospitalization of one’s care-recipient may be a stressful period for caregivers. Nevertheless, mastery is a rather stable construct and may not be affected by the setting which it is measured in . Future The seven-item Pearlin’s Mastery scale was tested to be a valid and reliable tool to be used among the caregiver population, particularly in assessing family caregivers of care dependent older adults in the Singapore setting. This study has demonstrated evidence of a brief five-item scale that maintains the reliability and validity of the original scale, which will be valuable for academic research and practical survey implementation.


The severity of the symptoms associated with COVID-19 is highly variable, and has been associated with circulating amino acids as a group of analytes in metabolomic studies. However, for each individual amino acid, there are discordant results among studies. The aims of the present study were: (i) to investigate the association between COVID-19-symptom severity and circulating amino-acid concentrations; and (ii) to assess the ability of circulating amino-acid levels to predict adverse outcomes . We studied a sample of 736 participants from the Biobanque Québécoise COVID-19. All participants tested positive for COVID-19, and the severity of symptoms was determined using the World-Health-Organization criteria. Circulating amino acids were measured by HPLC-MS/MS. We used logistic models to assess the association between circulating amino acids concentrations and the odds of presenting mild vs. severe or mild vs. moderate symptoms, as well as their accuracy in predicting adverse outcomes. Patients with severe COVID-19 symptoms were older on average, and they had a higher prevalence of obesity and type 2 diabetes. Out of 20 amino acids tested, 16 were significantly associated with disease severity, with phenylalanine (positively) and cysteine (inversely) showing the strongest associations. These associations remained significant after adjustment for age, sex and body mass index. Phenylalanine had a fair ability to predict the occurrence of adverse outcomes, similar to traditionally measured laboratory variables. A multivariate model including both circulating amino acids and clinical variables had a 90% accuracy at predicting adverse outcomes in this sample. In conclusion, patients presenting severe COVID-19 symptoms have an altered amino-acid profile, compared to those with mild or moderate symptoms. The symptoms associated with coronavirus disease 2019 (COVID-19) are very heterogenous. Around 80% of people infected are asymptomatic or present mild symptoms and do not require hospitalization [Since the beginning of the pandemic, an impressive number of studies investigating metabolomics in relation to COVID-19 have been published. Most of the studies aimed to either define the unique metabolic signature of COVID-19 or to predict the severity of and/or mortality from the disease. Reviews of this literature are now available ,3,4 and Studies have demonstrated that patients living with obesity are at greater risk of presenting severe symptoms when infected with SARS-CoV-2, compared to those without obesity . MoreoveWe studied a sample of the Biobanque Québécoise COVID-19 (BQC19) , a biobaCOVID-19 severity was determined at inclusion based on the World Health Organization (WHO) Clinical Progression Scale as mild, moderate, severe or deceased . There wFor the present study, we excluded: (i) patients without metabolomic measurement from blood taken within 7 days of inclusion; (ii) patients who tested negative for COVID-19; (iii) patients without a disease-severity score at inclusion; and (iv) pregnant women and children. This resulted in a sample of 736 individuals. A flowchart of patient selection is presented in To determine the ability of amino acids to predict adverse outcomes, we considered a subsample of 476 hospitalized patients with data on ICU admission and/or vital status at discharge, and for whom metabolomic measurements were carried out using plasma collected before their ICU admission or death. We defined adverse outcomes as admission to the intensive care unit (ICU) or hospital death.Plasma samples were analyzed by Metabolon Inc. . BrieflyWe focus on circulating amino acids for two reasons. First, abdominal obesity has previously been associated with COVID-19 severity, and we have previously demonstrated that circulating concentrations of some amino acids are correlated with central fat accumulation. Second, the existing literature shows that amino acids, as a group, are almost invariably altered in the context of severe COVID-19, although results for specific amino acids are heterogeneous. When more than one metabolomic measurement was available in our 7-day timeframe, we used the closest to study inclusion.We compared patient characteristics and comorbidities between severity groups, using Krustal–Wallis and chi-squared tests. To examine the association between disease severity and circulating-amino-acid levels, we used univariate and adjusted logistic-regression models comparing mild patients to moderate and severe patients. We reported the results as odd ratios (OR) for each 1 SD increment in circulating amino acids. We compared the level of metabolites annotated to the TCA and urea cycle between severity groups using the Krustal–Wallis test.To determine the ability of individual amino-acid levels to predict adverse outcomes, we performed univariate logistic-regression models and computed receiving-operator-characteristic (ROC) curves. The latter is a graphical tool that allows the visualization of the trade-off between sensitivity and specificity of a given predictor. It also allows the calculation of the area under the ROC curve (ROC_AUC), which is a metric of the ability of the predictor to discriminate between two groups. For example, a ROC_AUC of 0.70 indicates that the predictor has 70% accuracy at classifying observations in the correct group. A predictor is considered good when it has a ROC_AUC above 0.8, and excellent above 0.9 . We did We also ran univariate logistic analysis on clinical variables for comparison purposes. Additionally, we built a multivariate logistic-regression model using circulating-amino-acid levels and the clinical variables significantly associated with the outcome in univariate analysis as candidate predictors. Missing values were imputed using multivariate imputation by chained equations using predictive mean matching for continuous variables and logistic regression for ordinal variables. Predictive variables were scaled, and those with ≥50% missing values were discarded. Fifty imputations were run, and forward as well as backward logistic-models were fit with the candidate variables on each imputation. The variables used in the majority (≥50%) of models were selected for the final model. The final model was run on the imputed data, and the results were pooled.p-value below 0.05 was considered significant, except for post hoc analyses, where the Bonferroni correction was applied.A Overall, 736 individuals were included for analysis . AccordiSample characteristics by severity are presented in Among comorbidities see , the pren = 179 overall), 118 (66%) also had one or more metabolic comorbidities . The prevalence of individuals with obesity and a metabolic comorbidity was significantly higher in the moderate and severe COVID-19-symptom severity groups, compared to the mild group .Among the participants living with obesity (The number of participants taking angiotensin-converting enzyme (ACE) inhibitors, corticosteroids, anticoagulants and oral hypoglycemic agents or insulin at inclusion was significantly higher in the moderate and severe groups, compared to the mild group .The mean number of days between study inclusion (and therefore disease-severity assessment) and blood draw for metabolomics measurement was 4 days. We first evaluated the association between circulating-amino-acid concentrations and COVID-19 severity, using univariate logistic-models. The results from this analysis are presented as the odds of having mild vs. severe or mild vs. moderate symptoms for each increment of 1 SD in the circulating amino acid .Out of the 20 amino acids tested, 16 were significantly associated with COVID-19 severity. In this univariate analysis, the amino acids most strongly associated with severe symptoms were phenylalanine (positively associated) and cysteine (inversely associated). Concentrations of the 3 BCAAs and glutamate were also significantly associated with severity, but to a lesser extent.To evaluate the impact of potentially cofounding variables on the association between amino acids and disease severity, we adjusted the logistic models for characteristics found to be significantly different between severity groups. The results of this analysis are presented in Adjustments for albumin levels had the greatest impact on the association between circulating amino acids and COVID-19 severity; even associations with the most significant amino-acid levels were no longer significant, once adjusted for this covariate. Overall, age, sex and body mass index (BMI) had little impact on the association between amino-acid concentrations and COVID-19-symptom severity.We also ran models adjusted for comorbidities and medication intake at inclusion see . OverallAmong the 476 participants with data on ICU admission and/or vital status at discharge, 26 were admitted to the ICU and 76 died in the hospital, giving a total of 102 patients with adverse outcomes. Blood was drawn on average 19 days before death (range: 1 to 111 days) and 3 days before ICU admission (range: 1 to 21 days).The characteristics, comorbidities, medication at inclusion and medication during hospitalization, including treatment used for COVID-19, are presented in p = 0.6001) for tyrosine to 0.72 (p = 3.5 × 10−11) for phenylalanine. Clinical variables had similar or better predictive-abilities, with ROC_AUC ranging from 0.51 for ALT (p = 0.1763) to 0.82 for procalcitonin (p = 0.0019).We evaluated the ability of amino acids to distinguish participants who would suffer from adverse outcomes from those who would not, using logistic-regression models and reporting the predictive ability as ROC_AUC. To compare the performance of amino acids to that of variables often measured in a clinical context, we also ran this analysis for clinical variables significantly different across disease-severity categories. Results are presented in 2), SBP, phenylalanine, tryptophan, arginine, lysine, glutamate and serine. The final model is presented in We used the circulating-amino-acid levels and clinical variables significantly associated with adverse outcome in the univariate models as candidate variables for the multivariate model. After removal of variables with ≥50% missing values, scaling and imputation, we used backward and forward stepwise-models to identify 10 variables to include in the final model: CRP, urea, arterial oxygen saturation (SaOIn this analysis, we aimed to determine whether circulating-amino-acid concentrations were associated with COVID-19-symptom severity, and whether they could predict adverse outcomes in hospitalized patients. We found that 16 out of 20 amino acids were different between severe and mild COVID-19 symptoms. The strongest positive association was observed for phenylalanine, and the strongest inverse association was observed for cysteine. Phenylalanine also had a fair ability to predict adverse outcomes. To our knowledge, this is the largest study investigating circulating amino acids in the context of COVID-19.A summary of the existing literature on circulating amino acids and COVID-19 severity is provided in Considering that obesity is associated with greater risk of suffering from severe COVID-19 symptoms, we hypothesized that circulating amino acids previously linked to obesity would be the strongest correlates of symptom severity and the best at predicting adverse outcomes. However, this hypothesis did not hold true, as the strongest associations with symptom severity were found for phenylalanine and cysteine, which are not systematically associated with obesity. Moreover, our results showed that the associations between amino-acid levels and disease severity remained significant after adjusting for BMI. Finally, although we would expect amino acids previously reported to be positively associated with adiposity to be also positively associated with COVID-19 severity, this was not always the case. For example, tryptophan is generally positively associated with measurements of adiposity , but it We did not find circulating-amino-acid concentrations to be good predictors of ICU admission and hospital death. Indeed, other lab measurements that have been validated in the literature and are much more accessible had similar or better predicting-abilities ,28,29. FThe strengths of this study include the rather large sample-size and the use of the WHO symptom-severity scale. Limitations include the absence of an uninfected control group and the large number of missing data for some variables. Other limitations include the lack of measurement of body-fat distribution and the variability in elapsed time between blood draw and adverse-outcome occurrence. Finally, we acknowledge that amino acids are more easily and frequently measured in metabolomics studies compared to other classes of metabolites, and this has probably contributed to the abundance of studies linking amino acids and COVID-19. Whether amino acids are better than other metabolites at predicting COVID-19 severity or adverse outcomes should be investigated further.In conclusion, severe COVID-19 symptoms are associated with altered levels of many circulating amino acids, possibly hinting at global changes in nitrogen metabolism. These associations are mostly independent of age, sex and BMI.


Recent genome-wide association studies (GWASs) of COVID-19 patients of European ancestry have identified genetic loci significantly associated with disease severity. Here, we employed the detailed clinical, immunological and multi-omics dataset of the Human Functional Genomics Project (HFGP) to explore the physiological significance of the host genetic variants that influence susceptibility to severe COVID-19. A genomics investigation intersected with functional characterization of individuals with high genetic risk for severe COVID-19 susceptibility identified several major patterns: i. a large impact of genetically determined innate immune responses in COVID-19, with ii. increased susceptibility for severe disease in individuals with defective cytokine production; iii. genetic susceptibility related to ABO blood groups is probably mediated through the von Willebrand factor (VWF) and endothelial dysfunction. We further validated these identified associations at transcript and protein levels by using independent disease cohorts. These insights allow a physiological understanding of genetic susceptibility to severe COVID-19, and indicate pathways that could be targeted for prevention and therapy. The novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)  and antiCCR9, CXCR6, and XCR1 and the locus controlling the ABO blood type to be associated with severe symptoms of COVID-19  , 17 and ex-vivo stimulation of PBMCs with microbial stimuli.In the present study, 451 and 313 healthy European individuals from the 500FG and 300BCG cohort  of the H-4) were excluded. The detailed QC steps have been published in reference , cryptic relatedness (π>0.185) were removed. SNPs with a low genotyping rate (<95%), with low minor allele frequency (<0.001), deviation from Hardy-Weinberg equilibrium .We used the FUMA pipeline  to identAs part of the FUMA pipeline, we used these mapped genes to generate gene expression heatmaps using GTEx v8 . Gene expression values with a pseudocount of 1 were normalized across tissue types using winsorization at 50 and log2 transformed. Using the hypergeometric test, we tested for significant enrichment of our input genes in DEG sets for the different tissue types using a Bonferroni corrected p-value ≤ 0.05. Finally, we tested for overrepresentation of our input genes in predetermined gene-sets using hypergeometric tests. Gene-sets were obtained from MsigDB, WikiPathways, and GWAS-catalog reported gene-sets. We used Benjamini-Hochberg FDR correction for each of the categories within these gene-set sources separately using a threshold of 0.05 for our adjusted p value.-5, 1×10-6 and 1×10-7). Enrichment p values were obtained after FDR correction.Based on the Roadmap 15-core epigenetic state database , we usedUsing nominally significant QTL’s we linked COVID-19 risk alleles to pathogenically stimulated cytokine production risk alleles. We then clumped all variants within a 250kb, 500kb, or 1Mb window around the respective top COVID-19 risk allele at the 3p21.31 loci. We clumped using a stringent 0.01 LD threshold to make sure all associations were independent of each other. Lastly, a binomial test was performed to see whether the amount of down-regulated cytokine production associations was greater than the upregulated ones.Hospitalized patients with presumed COVID-19 disease were included in a prospective cohort between March and April 2020 at the Radboudumc . Disease severity was defined based on the patient’s need for intensive care at the time of sampling. The inclusion and clinical characteristics of this patient cohort have been previously described in detail . The bast test was used to compare protein levels after excluding all samples are above upper detection limit.According to the manufacturer’s protocol, plasma concentrations of CXCL16 were measured using commercially available enzyme-linked immunosorbent assays  according to the manufacturer’s protocol, with a lower and upper detection limit of 0.055 and 40 ng/mL, respectively. Plasma concentrations of VWF were measured using a commercially available ELISA , with a lower and upper detection limit of 0.055 and 40 µg/mL, respectively. Values under or above the range of detection were replaced with the lower or upper detection limits, respectively. The basic characteristics of the studies samples are shown in Seurat v3.2.2 . Instead of limiting the analyses to the very few genome-wide significant variants, we used all suggestive associations  as earlier proposed   are assoproposed  in the fproposed Table S1proposed . The SNPproposed , 34. Morproposed  that COVproposed .Pathway analysis of these 115 genes showed strong enrichment in chemokine binding and chemokine receptors binding . In addi-5) based on their location with histone marks and chromatin states of 24 blood cell types in the Roadmap Epigenome Project  with the 32 independent loci were significantly enriched in the non-coding intronic region  Table S4 Project .We then tested the enrichment of any specific epigenetic regulatory state compared to all other states. We found that the COVID-19 genetic loci were strongly enriched for enhancer markers and weakly enriched in promoter markers Table S5in vitro stimulation of PBMC, macrophages, and whole blood cells with different pathogenic stimuli   , 46. As -20) , our resex-vivo stimulations  in response to various ulations .” In addPolygenic risk scores (PRS) combine multiple risk alleles and capture an individual’s load of common genetic variants associated with a disease phenotype . Using tAt first, we assessed if men have a higher genetic risk compared to women in 500FG. Hereby, we defined people with top 10% PRS as a high-risk group and those with bottom 10% PRS as a low-risk group. As shown in As obesity or overweight has been reported as a risk factor for serious illness or death from COVID-19, we also tested if the PRS is associated with BMI  (OAS1 (2’-5’-Oligoadenylate Synthetase 1) shows higher expression in patients with mild symptoms  during the disease course (from high to low), while the severe symptom patients show an increasing pattern of expression in cytokine genes  with time (from low to high). Such a pattern may suggest that mild patients have a sufficiently good response in the first phase of the infection, which inhibits efficiently the viral replication, subsequently resulting in decreased inflammation. On the contrary, severe patients show defective activation of antiviral innate immunity in the first phase of the disease, leading to prolongation of the disease process with inefficient and deleterious inflammatory response in the end. This observation is in line with the recent findings of immunosuppression in severely affected patients . We observed a significantly lower expression of CCL25   and found they were significantly higher  in the ICU patients . Thirdly, in our analysis of the stimulated cytokine response, we make use of the 500FG cQTL data. This dataset was obtained in the years before the COVID-19 pandemic, which limits our capacity to study cytokine expression in response to SARS-CoV-2 itself, and more studies are warranted to evaluate this. Finally, our genetic score did not include the sex chromosomes: many immune genes are located on the X-chromosomes, and we cannot exclude a sex-biased genetic susceptibility for severe COVID-19 involving such genes, as recently shown for TLR7-deficiency in young men .Collectively, our data demonstrate that genetic variability explains an important component of the increased susceptibility to severe COVID-19. The genetic risk for severe COVID-19 is associated with defective cytokine production capacity, dysregulated endothelial function, and defective lymphocytosis. By pointing to potential pathways to be engaged by future immunotherapies, these findings may contribute to the development of novel treatment and prevention strategies for severe COVID-19.https://ega-archive.org/ under the accession numbers EGAS00001004571 and EGAS00001005348 and https://hfgp.bbmri.nl/, 500FG data.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The studies involving human participants were reviewed and approved by Arnhem-Nijmegen Medical Ethical Committee (300BCG (NL58553.091.16) and 500FG (NL42561.091.12)). The patients/participants provided their written informed consent to participate in this study.MN, C-JX, and YL designed the study. YK and XC performed statistical analyses supervised by YL and C-JX, MJ, SM, VK, VM, LB, QM, and LJ established the cohorts, helped with the data analysis and interpretation of results. BZ, VK, MKG, AN, IG, and NJ performed the validation. C-JX, MN, YL, YK, and XC wrote the manuscript with input from all authors. All authors contributed to the article and approved the submitted version.MN was supported by an ERC Advanced Grant (833247) and a Spinoza Grant of the Netherlands Organization for Scientific Research. YL was supported by an ERC starting Grant (948207) and a Radboud University Medical Centre Hypatia Grant (2018). C-JX was supported by Helmholtz Initiative and Networking Fund (1800167). This work was also partly supported by the German Federal Ministry of Education and Research, NaFoUniMedCovid19”—COVIM [01KX2021].The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Working memory is a cognitive process that involves short-term active maintenance, flexible updating, and processing of goal- or task-relevant information. All frequency bands are involved in working memory. The activities of the theta and gamma frequency bands in the frontoparietal network are highly involved in working memory processes; theta oscillations play a role in the temporal organization of working memory items, and gamma oscillations influence the maintenance of information in working memory. Transcranial alternating current stimulation (tACS) results in frequency-specific modulation of endogenous oscillations and has shown promising results in cognitive neuroscience. The electrophysiological and behavioral changes induced by the modulation of endogenous gamma frequency in the prefrontal cortex using tACS have not been extensively studied in the context of working memory. Therefore, we aimed to investigate the effects of frontal gamma-tACS on working memory outcomes. We hypothesized that a 10-min gamma tACS administered over the frontal cortex would significantly improve working memory outcomes. Young healthy participants performed Luck–Vogel cognitive behavioral tasks with simultaneous pre- and post-intervention EEG recording (Sham versus 40 Hz tACS). Data from forty-one participants: sham (15 participants) and tACS (26 participants), were used for the statistical and behavioral analysis. The relative changes in behavioral outcomes and EEG due to the intervention were analyzed. The results show that tACS caused an increase in the power spectral density in the high beta and low gamma EEG bands and a decrease in left-right coherence. On the other hand, tACS had no significant effect on success rates and response times. Conclusion: 10 min of frontal 40 Hz tACS was not sufficient to produce detectable behavioral effects on working memory, whereas electrophysiological changes were evident. The limitations of the current stimulation protocol and future directions are discussed in detail in the following sections. Brain  oscillations refer to the rhythmic and repetitive electrical activities of a large number of neuronal populations in the brain . NeuronaWorking memory (WM) is a cognitive process that involves short-term active maintenance, flexible updating, and processing of goal- or task-relevant information  in a capacity-limited and interference-resistant manner ,16. WM iAll brain oscillations are involved in the WM processing, particularly theta and gamma frequency bands ,27; thetTranscranial electrical stimulation (tES) is a noninvasive brain stimulation technique that delivers weak electrical currents to the scalp . tES is tDCS is thought to modulate resting membrane potentials and thereby alter spontaneous cortical activity. Unlike tACS, tDCS cannot be tailored to directly modulate specific brain network activity. In most studies, tDCS has been used in a polarity-specific manner,  ,44,45,46per se [tACS modulates cortical activity by affecting neuronal membrane potentials through oscillatory electrical stimulation at specific frequencies, thereby interacting with ongoing rhythmic cortical activity during cognitive processes ,58. tACSper se . Frequenper se ,67, motoper se ,69,70,71per se , cognitiper se ,74,75, nper se , creativper se , fluid iper se . Left frper se ,80,81. Tper se .Several studies have demonstrated tACS-induced EEG changes ,79,83,84In most tACS studies of cognitive function modulation, midband frequencies have been used across participants, e.g., 6 Hz for “theta-band stimulation” ,87. HoweTheta oscillations play an essential role in local processing and functional connectivity . TherefoThe synchronization of cortical oscillations in different frequency bands has been proposed as an important mechanism for high-level cognitive processes. The importance of phase synchronization (coherence) of native oscillations and tACS was demonstrated by several studies ,99,100. The analogous role of EEG gamma oscillation was demonstrated in the study of the modulation of EEG power and phase synchronization by auditory stimulation at beat frequencies corresponding to dominant EEG rhythms using intracranial recordings in preoperative epilepsy patients. Becher and colleagues found that the most striking increases in EEG power occurred after stimulation with 40 Hz monaural beats . In healSeveral studies investigated the effect of gamma-tACS on WM outcomes ,107,108.The multiplexing-buffer model of WM assumes that short-term information is represented by the ordered activity of cell assemblies and that the multiple elements stored in WM are organized by theta-interleaved gamma subcycles . The CFCBased on the results of the studies summarized above, we hypothesized that brief (10 min) frontal exposure of healthy subjects to tACS at gamma frequency (40 Hz) will positively affect both behavior  and electrophysiological parameters  of the visual WM. We decided to stimulate the frontal cortex with gamma tACS because most studies stimulated the frontal cortex with theta tACS or the parietal cortex with gamma tACS. None of these studies examined the combined effect of frontal gamma-tACS on WM behavioral outcomes and electrophysiological coherence between the right and left cortices.Seventy-nine healthy, right-handed, non-colorblind young adult volunteers were recruited for the study after having given written informed consent. All participants have normal or corrected-to-normal vision, and all were right-handed, according to the Edinburgh handedness inventory. Participants were assigned into two groups (sham and tACS). None of the participants had symptoms or a history of psychiatric or neurological disorders, drug-dependent chronic diseases, or brain injury. All experiments were conducted in accordance with the Declaration of Helsinki and with the approval of the ethics committee of the Third Faculty of Medicine, Charles University in Prague.The experiment consisted of three consecutive parts  performeParticipants performed the visual WM task: the Luck and Vogel paradigm (Luck and Vogel 1997). The details of the task can be found in . During ® wireless hybrid EEG/tCS 8-channel neurostimulator system with NIC 1.4.9 Software  and a neoprene headcap. EEG was recorded using gel-filled electrodes at positions Fp1, Fp2, F7, and F8 (with the Cz electrode serving as a reference) using the 10–10 system. Electrode impedances were kept below 5 kΩ. Sponge stimulation electrodes  were located at F3 and F4, with grounding at the earlobes. The intensity of stimulation AC was 1.5 mA peak-to-peak (5 ms RAMP in and 5 ms RAMP out) at a frequency of 40 Hz. To maintain the signal quality, electrode impedances were continuously checked, and participants were instructed to avoid blinking, swallowing, chewing, talking, and all possible expressions that could produce EEG artifacts.EEG recordings and electrical stimulation were performed using a StarstimThe reaction time (RT) and success rate (SR) were calculated. To avoid extreme values, the median RT was calculated rather than the average. RT is defined as the time span between the appearance of the screen with the target cue  were excluded from further analysis and the data were re-referenced to the average. Power spectral density (PSD) for the correct answers before and after the intervention (tACS or sham) was calculated in the whole signal as a continuum where the frequencies out of interest (>80 Hz) were cut off.The linear model was used to simulate the effect of stimulation on RT. Based on the dataset with 14,681 epochs , a linear mixed model with interactions was constructed in R with a t-test with Satterthwaite’s method. EEG data were processed using EEGLAB 14.1.2 . Since tIn order to inspect the synchronization of the left and right frontal activity, the coherences Fp1–Fp2 and F7–F8 were computed from each correct answer signal segment as a minimum variance distortionless response . To comData analysis was performed on 41 subjects: 21 females (age 18–22), 15 subjects in the sham group, and 26 subjects in the tACS group, because 27 subjects were excluded from the further analysis due to technical problems ; eight subjects were excluded due to heavy biological artifacts; and three subjects were also excluded due to incomplete datap < 0.001 in between sessions without group interaction, so SR in the Luck–Vogel task before and after the intervention did not differ significantly t(77) = 1.57, p = 0.18. A t-test with the use of Satterthwaite’s method has been used to calculate behavioral statistics. There was no significant behavioral effect t(77) = −0.57, p = 0.57 of the 10-min-lasting tACS that we have applied during the study on working memory.The success rate (SR) improved after sham by 3.4% and after tACS by 3.9% that correspond to simple learning only. There was a predictable effect of learning with t(77) = 9.13, The reaction times (RTs) to the Luck–Vogel task before and after the intervention were shortened in both groups (tACS or sham). On average, the subjects after tACS were faster by 23 ms compared to subjects after sham, but, considering the 17 ms difference between tACS and sham before the intervention, the final difference was not significant . The calA power spectral density analysis revealed that the tACS group had significantly higher high beta (20–28 Hz) and low gamma (30–40 Hz) activities than the sham group. Compared to the sham group, high beta activity differs at F7, whereas low gamma EEG activity differs at Fp1, F7, Fz, and F8 in the tACS groups . These dAnalysis of coherence for each trial showed a decrease after both interventions, but significantly more after tACS; Fp1-Fp2 coherence decreased by 27.3% after tACS, whereas it decreased by only 11.0% after sham. Similarly, F7–F8 coherence decreased by 22.5% after tACS, whereas it decreased by 6.8% after sham .Contrary to our expectations, the application of gamma-tACS over the frontal cortex did not affect the WM behavioral outcomes significantly. On the other hand, gamma-tACS elicited electrophysiological changes, especially at higher EEG frequencies. The behavioral and electrophysiological results of tACS are discussed in the following sections.In this study, a single session of 10 min −40 Hz- tACS administered over the prefrontal cortex in healthy subjects was not sufficient to boost WM. Compared to other studies in which gamma-tACS was administered over the DLPFC, Hoy et al. (2015) found that 40 Hz gamma-tACS administered for 20 min over the DLPFC selectively improved participants’ performance on higher cognitive load tasks (3-back task) . On the In this study, we investigated how gamma waves affect prefrontal cortex activity, with particular attention to WM. We found that gamma-tACS applied over frontal areas caused a significant increase in EEG activity at high beta and low gamma frequencies.As Alekseichuk and colleagues showed, the amplification of high gamma oscillations during peaks or troughs of the theta wave would enhance or attenuate endogenous coupling, facilitating or impeding information processing in the affected brain area. They have shown that the simultaneous stimulation of theta and gamma waves in the prefrontal cortex enhances spatial WM only when repeated gamma bursts (particularly at 80–100 Hz) are phase-locked to the peaks of the theta rhythm.This could imply that the tACS intervention has physiological effects on higher frequency bands associated with a cognitive task. Given that the subjects were subjected to a high-demand cognitive task, we would expect beta and higher frequencies to be more prominent, whereas alpha and lower frequencies would only occur as a result of fatigue. This phenomenon was observed in the tACS group, which demonstrated enhanced frontal lobe activity at higher frequencies. A more profound effect of gamma-tACS could be achieved by a finer individual tuning of the stimulation frequency (gamma-tACS), which may involve the gamma band, as suggested in some studies ,120. SpeConclusion: A 10-min session of 40-Hz tACS administered to healthy young participants was not sufficient to produce detectable behavioral improvement in WM , whereas this brief exposure to gamma tACS produced electrophysiological changes, evidenced by an increase in power spectral density in the high beta and low gamma EEG bands and a decrease in left-right coherence.The current study is limited by the fact that a non-individualized fixed gamma frequency (40 Hz-tACS) was applied to all participants  by the uIn future studies, it is reasonable to (1) use a within-subject design because it eliminates the effects of differences in baseline characteristics on measured outcomes ; (2) construct a longer baseline of at least 500 ms, in the Luck and Vogel’s paradigm; (3) consider a different design of tACS, especially in terms of duration and the location of stimulation, personalized stimulation frequency , and mul


Our study aims to assess the uptake of COVID-19 vaccination and its associated factors among Chinese college students. A web-based cross-sectional study was conducted from 18 May to 17 June 2022. A total of 3916 participants were included. The coverage of the first dose, complete vaccination and booster vaccination among college students was 99.49%, 81.96% and 79.25%, respectively. College students with an older age , non-medical major  and studying in north-east China  were less likely to complete vaccination. Individuals who were female  and received a recombinant subunit vaccine  were more likely to complete vaccination. Non-medical students  and students studying in north-east China  were less likely to receive a booster dose, while female students  had a higher likelihood. The main reason for being unvaccinated was “contraindication” (75.00%), and the main reason for not receiving a booster dose was “being too busy to attend to it” (61.37%). This study demonstrated a high adherence to the COVID-19 vaccination policy among Chinese college students. Targeted strategies should be applied to remove barriers to COVID-19 vaccination among college students. The coronavirus disease 2019 (COVID-19), a respiratory syndrome caused by SARS-CoV-2, has brought about a worldwide pandemic since its breakout in 2019. As of 9 November 2022, there were over 600 million confirmed cases of COVID-19, including nearly 7 million deaths globally. In China, these figures were over 9 million and nearly 29 thousand [COVID-19 cases in young adults, including college students, are more likely to be asymptomatic or paucisymptomatic carriers of SARS-CoV-2 compared to their older counterparts . In addiThree types of COVID-19 vaccines are available in China, including the single-dose adenovirus vector vaccine, the 2-dose inactivated vaccine and the 3-dose recombinant subunit vaccine. However, with the emergence of Omicron variant (B.1.1.529), full vaccination may not be enough to prevent infection. Receiving a booster dose is of great importance in the context of the Omicron wave . To addrPrevious studies found that the willingness to get COVID-19 vaccination was high among college students, but vaccine hesitancy was also common ,13,14. NFrom 18 May to 17 June 2022, we conducted an online survey on college students in China. A questionnaire was set up via “Wenjuanxing”, a Chinese online platform providing survey functions. A poster of our survey was distributed via WeChat and QQ (two of the most popular instant messaging platforms in China). By scanning the QR code on the posters, college students who were interested in our research could access the online questionnaire.Given an alpha value of 0.05 and the permissible error δ of 0.02, and assuming the proportion of college students already having received a COVID-19 booster dose was 60%, a minimum of 2305 subjects were required to provide sufficient statistical power .Individuals who met the following criteria were eligible in this study: (1) college students  individuals aged 16 years and older but younger than 35 years old. By checking the IP address, questionnaires from countries and regions other than the Chinese mainland were excluded. Questionnaires with an illogical answer to the question “Why haven’t you completed the vaccination?” were regarded as being invalid.The following information was self-reported by participants: (1) socio-demographic information, including gender , age (in years), ethnicity (Han/others), college location , education (junior college student or undergraduate student/graduate student), major  and family monthly income ; (2) COVID-19 vaccination status (unvaccinated/vaccinated); (3) reasons for not receiving a first-dose and booster vaccination  were also collected.Those who received at least one dose of a COVID-19 vaccine were required to offer detailed information about the received vaccine, including its production company and the number of received doses. According to this, the COVID-19 vaccination status among vaccinated individuals was further classified. A full COVID-19 vaccination referred to receiving one dose for the adenovirus vector vaccine, two doses for the inactivated vaccine and three doses for the recombinant subunit vaccine. Since the booster dose was only required for people who received the adenovirus vector vaccine and inactivated vaccine in China, a complete COVID-19 vaccination referred to getting a full COVID-19 vaccination with the booster dose for the adenovirus vector vaccine or the inactivated vaccine, or getting a full COVID-19 vaccination for the recombinant subunit vaccine.The primary outcome was the completion of COVID-19 vaccination, which reflected college students’ adherence to vaccination guidelines. All vaccinated participants were included and classified according to the COVID-19 vaccination status.The secondary outcome was the uptake of COVID-19 booster dose. The analysis was based on participants who got a full vaccination with the adenovirus vector vaccine and inactivated vaccine. They were classified as fully vaccinated with a booster dose and fully vaccinated without a booster dose according to the uptake of the booster dose. Exploratory outcomes included reasons for not getting vaccinated or not receiving the booster dose.The coverage was reported from three dimensions, including first-dose vaccination, full vaccination and booster vaccination.p-value less than 0.10 in the bivariate analyses were introduced in multivariable logistic regression models. All effects were estimated with 95% CI and p-values. Statistical significance was taken as two-sided p-values < 0.05. All analyses were performed using SPSS 20.0  and Excel 2010 .In the descriptive analyses, characteristics of the study participants were expressed using frequencies and percentages. A chi-square test was applied for bivariate analyses. Logistic regression was used to further examine factors associated with complete COVID-19 vaccination and the uptake of the booster dose. Variables with a This research was approved by the Ethical Review Committee of School of Public Health (Shenzhen), Sun Yat-sen University (SYSU-PHS-2022025). Electronic informed consent was obtained from all participants before commencing the survey. Participants who completed the questionnaire entered a lottery to receive up to 50 CNY (approximately 7 USD) of reimbursement.In general, 4613 questionnaires were collected over the study period. After excluding invalid questionnaires, a total of 3916 participants were included in the study . Table 1Among the respondents who got vaccinated, 2607 students got a full vaccination with the adenovirus vector vaccine or inactivated vaccine, and the coverage of the booster vaccination was 79.25%. As shown in To the best of our knowledge, this is the first nationwide study on the COVID-19 vaccination status and associated factors among Chinese college students that included booster vaccination. Our study found that the coverage of first-dose vaccination, complete vaccination and booster vaccination among the respondents was 99.49%, 81.96% and 79.25%, respectively, as of June 2022. A complete COVID-19 vaccination and uptake of the booster dose was associated with gender, major and college location.We found that the coverage of first-dose vaccination among the respondents was 99.49%, which is consistent with the data released by the Chinese government (over 95% among students aged 18 years and older) . With thPrevious studies have shown that female students and medical students had better knowledge and acceptability towards COVID-19 vaccination ,24,25,26Age is another factor associated with college students’ COVID-19 vaccination. Younger students were more likely to complete the COVID-19 vaccination. Previous studies showed that vaccine hesitancy was more prevalent among senior students ,30. ThisMoreover, similar to previous studies ,15, the Another important result in our study is that complete vaccination was associated with the type of received vaccine. The coverage of complete vaccination for respondents who did not require a booster dose  was higher than that for those who required one . We also found that the coverage of booster vaccination was commonly suboptimal, regardless of the type of received vaccine. This is consistent with a previous study, according to which vaccine hesitancy increased significantly with the promotion of booster vaccination . Lai et This study has some limitations. First, this study was limited by its cross-sectional nature and could not establish causal relationships. Second, this study was a web-based survey based on convenience sampling, and selection bias was inevitable. Respondents in our study may be more concerned about information about COVID-19 vaccination and may therefore be more likely to complete vaccination. Third, we only focused on the differences in terms of a complete vaccination and an uptake of the booster dose between students with different socio-demographic characteristics, but the questionnaire may not be comprehensive enough to explain the underlying reasons. Finally, the vaccination status was self-reported by respondents, which may not be as accurate as clinical vaccination records. However, since personal vaccination records can be easily found via smartphone in China and the vaccination information was required to be reported in detail, information bias in this study is unlikely to be significant.The current study demonstrated a high adherence to the COVID-19 vaccination policy among college students in China, but the coverage of the booster vaccination was suboptimal. Male students, non-medical students and students studying in north-east China were associated with a lower coverage of complete vaccination and booster vaccination. It is necessary to foster further systematic and continuous health education about COVID-19 vaccination on campus. Colleges should set up separate, well-supplied and professional health stations and vaccination sites for emergencies. Meanwhile, targeted vaccination strategies among college students should be applied in order to address barriers to COVID-19 vaccination, especially students’ curriculum schedules.