To analyse the impact of voluntary rapid testing for SARS-CoV-2 antigen in Liverpool city on covid-19 related hospital admissions.Synthetic control analysis comparing hospital admissions for small areas in the intervention population with a group of control areas weighted to be similar for past covid-19 related hospital admission rates and sociodemographic factors.Liverpool city, UK, 6 November 2020 to 2 January 2021, under the intervention of Covid-SMART (systematic meaningful asymptomatic repeated testing) voluntary, open access supervised self-testing with lateral flow devices, compared with control areas selected from the rest of England.General population of Liverpool (n=498 042) and a synthetic control population from the rest of England.Weekly covid-19 related hospital admissions for neighbourhoods in England.The introduction of community testing was associated with a 43%  reduction (146 (96 to 192) in total) in covid-19 related hospital admissions in Liverpool compared with the synthetic control population  for the initial period of intensive testing with military assistance in national lockdown from 6 November to 3 December 2020. A 25% (11% to 35%) reduction (239 (104 to 333) in total) was estimated across the overall intervention period (6 November 2020 to 2 January 2021), involving fewer testing centres, before England’s national roll-out of community testing, after adjusting for regional differences in tiers of covid-19 restrictions from 3 December 2020 to 2 January 2021.The city-wide pilot of community based asymptomatic testing for SARS-CoV-2 was associated with substantially reduced covid-19 related hospital admissions. Large scale asymptomatic rapid testing for SARS-CoV-2 could help reduce transmission and prevent hospital admissions. Asymptomatic transmission of SARS-CoV-2 has been a major challenge in managing the covid-19 pandemic. Modelling studies based on the original strain had suggested that more than half of transmissions in the community may arise from people without symptoms, whether pre-symptomatic or never symptomatic.Among other non-pharmaceutical interventions, rapid testing for SARS-CoV-2 antigen using lateral flow devices has now been implemented in many countries for people without symptoms to determine if they are potentially infectious and should self-isolate,On 6 November 2020, before populations were vaccinated, the UK government piloted the first city-wide voluntary community testing programme, which was open to all residents and workers in Liverpool without symptoms of covid-19.Box 114 OctoberThe new three tier system of covid-19 restrictions begins in England, with Liverpool City Region in tier 3, the highest level of restrictions at the time31 OctoberThe UK government offers Liverpool mass testing with military assistance1 NovemberLiverpool City Council Covid-19 Strategic Coordination Group with Mersey Resilience Forum accepts in principle but with the freedom to develop a more targeted approach2 NovemberThe military arrives in Liverpool to establish test sites5 NovemberNational lockdown; a communications drive begins in Liverpool on testing, including an interactive map of testing sites and waiting times on Liverpool City Council’s website, and articles put out via digital media in response to testing uptake, feedback on engagement at testing sites, analysis of social media, and commissioned surveys6 NovemberSix sites open for lateral flow testing  testing of people with symptoms)7 NovemberSixteen sites open for lateral flow testing10 NovemberFirst meeting of Department of Health and Social Care’s convened evaluation steering group. Schools-based testing starts11 NovemberCapacity increased: 37 community sites plus schools, home PCR kits delivered , local evaluation group established20 NovemberReconfiguration of resources: 15 popular testing sites kept, other resources redeployed to smaller sites in low uptake areas23 NovemberSystem for confirmatory PCR changed from national communication and delivery of a home test kit to swabbing at one designated local testing site (with swab kits sent to residents’ homes if they could not travel) and an invitation message tailored to the local area2 DecemberLiverpool moved into tier 2, with all surrounding regions in higher tiers or with more restrictions3 DecemberHandover of management of asymptomatic testing sites from military to Liverpool City Council contractors; targeting becomes more focused as the pilot moves to Liverpool Covid-SMART brand and adapts to fewer covid-19 restrictionsPilot of visits to care homes in Liverpool begins, and the communications plan shifts priority to test-before-you-go for implementation as the population returned to high transmission risk settings Liverpool City Region roll-out of Covid-SMART begins4 DecemberTest-to-release for some key workers begins17 DecemberMore areas, including Cheshire and Warrington, move into tier 2. Hotels in Liverpool booked heavily with people from London31 DecemberMove back into tier 3, with all surrounding regions in tier 44 JanuaryNational lockdownNational roll-out of community testing beginsAlthough popular overall, uptake of this programme showed substantial differences, with lower uptake among black, Asian, and ethnic minority groups, deprived neighbourhoods, areas at a distance from test sites, and areas containing populations less confident in using internet technologies, such as older people in disadvantaged areas.In this study, we evaluated whether large scale rapid testing for asymptomatic SARS-CoV-2 infection was effective at reducing covid-19 related hospital admissions.Covid-SMART (systematic meaningful asymptomatic repeated testing)Our primary outcome was the weekly number of hospital admissions with a main diagnosis of covid-19 In England, MSOAs are standard geographical units (with an average population of 7200 people) nested within local authorities. We used hospital admissions as the primary outcome, including those in people with a main diagnosis of covid-19 who tested positive for SARS-CoV-2 (ICD-10 code U07.1) or those with a clinical diagnosis of covid-19 (code U07.2).In synthesising controls, we used data on the seven characteristics of local areas that could potentially influence uptake of testing, transmission, effectiveness of control measures, and vulnerability to hospital admission. The selection of characteristics was based on learning from extensive characterisation of differences in covid-19 outcomes and interventions in the study population.Covid-SMART was introduced after the UK government selected Liverpool to pilot large scale rapid testing for SARS-CoV-2 antigen in asymptomatic individuals. From 6 November 2020, supervised self-testing with the Innova SARS-CoV-2 rapid antigen lateral flow device was made available to everyone without symptoms living or working in the city of Liverpool. During the initial intensive testing period (6 November to 3 December) the programme was deployed with the assistance of the British Army and was advertised across multiple media channels, with communications also drawing attention to parallel PCR testing for people with symptoms. The initial plan to test 75% of the asymptomatic population in two weeks proved infeasible, but the availability of testing was popular with the public. From 3 December 2020 the service was handed over to Liverpool City Council. The overall aim of the pilot was to reduce or contain transmission of SARS-CoV-2, with testing focusing on the following purposes: test-to-protect vulnerable people and settings , test-to-release contacts of confirmed infected people sooner from quarantine than the stipulated period , and test-to-enable careful return to restricted activities to improve public health, social connections, and the economy . The public was strongly aware of, and had a largely positive attitude towards, Covid-SMART, motivated by shared identity, civic pride, and wanting to protect others.Individuals who tested positive were instructed to isolate for 10 days according to national guidance and to take a confirmatory PCR test. By 2 January 2021, 33% (n=162 745) of the population had at least one lateral flow test result registered, with 36% (n=57 827) of people testing more than once. Over this period 2113 infected individuals  were identified using lateral flow tests. Testing was particularly intensive up to 3 December 2020, when 24% (n=117 470) of the self-declared asymptomatic population were tested for the first time in less than a month. The intervention was hypothesised to reduce covid-19 related hospital admissions by preventing onward transmission resulting from the effective isolation of people who tested positive and their contacts, and from the associated publicity raising general awareness of risk behaviours associated with covid-19 and mitigation measures. A proportion of infections prevented as a result of the Covid-SMART intervention would have resulted in admissions to hospital.We applied the synthetic control method for microdata developed by Robbins et al to estimate the effect of Covid-SMART on covid-19 related hospital admissions.As a time lag would be expected between the introduction of Covid-SMART and reduced numbers of hospital admissions, we assumed the minimum plausible period from the start of the testing programme to when an impact on hospital admissions might be expected to be two weeks. We therefore compared the trend in admissions between the intervention and synthetic control areas after 19 November 2020 . We estimated the intervention effect over two periods: the initial intensive testing period with military support (6 November to 3 December 2020) and the civilian rollout involving fewer testing centres (6 November 2020 to 2 January 2021). The initial testing period coincided with the national lockdown. We used the extended period to understand the extent to which impacts were sustained. From mid-December, asymptomatic community testing was gradually extended to other areas of the country. We therefore limited the follow-up time to 2 January because after that time community testing in Liverpool was no longer being conducted at a higher rate than the rest of England, removing the intervention contrast with control areas .To construct the synthetic control group, we derived calibration weights to match the 61 MSOAs in Liverpool to areas outside Liverpool before the introduction of Covid-SMART. The weighting algorithm derives weights for all MSOAs outside Liverpool that meet two constraints. Firstly, the weighted average of each of the seven local area characteristics,  in the control group is equal to the average for Liverpool.From the pool of MSOAs used to construct the synthetic control, we excluded MSOAs within the Liverpool City Region  to avoid spill-over effects of community testing on neighbouring areas. As we wanted to estimate the effect of Covid-SMART alone, we treated Liverpool as the intervention group and excluded from the control group any local authorities with higher than the average weekly lateral flow testing rate of 1 per 100 population between 6 November 2020 and 2 January 2021. This removes influences of any unknown pilots of lateral flow tests among the 15% of non-Liverpool local authorities testing above this level (see supplementary figure SF2). Overall, 142 MSOAs were excluded in this way , leaving 6290 MSOAs to comprise the synthetic control group.The average treatment effect for the treated was then estimated as the difference in cumulative number of hospital admissions in the post-intervention period in Liverpool compared with the (weighted) cumulative number of admissions in the synthetic control group. We used permutation samples, by repeating the analysis through 250 placebo iterations randomly allocating MSOAs outside Liverpool to the intervention group, to estimate the sampling distribution of the treatment effect and calculating permuted P values and 95% confidence intervals.After the national lockdown ended on 2 December 2020, a three tiered system of local restrictions was implemented. Liverpool entered less stringent tier 2  restrictions owing to lower levels of covid-19, while most similar areas entered tier 3  restrictions, which appeared to have a relatively large impact on transmission.All analyses were performed using R version 4.0.3 and the Microsynth package.In sensitivity analysis we repeated the synthetic control models for the upper and lower plausible estimates of the potential effect of less stringent tier 2 restrictions in Liverpool. These were based on the upper (21%) and lower (13%) bounds of the 95% confidence interval of our estimate of the tiered effect (see supplementary file part 4 for results). We also replicated the analysis without excluding places with mean weekly lateral flow test rates >1 per 100 population (see supplementary file part 5 for results).To account for the potential bias from our synthetic control group being constructed from a dispersed non-adjacent set of neighbourhoods, while our intervention group was the contiguous neighbourhoods of Liverpool, we conducted a sensitivity analysis. In this analysis we used a different synthetic control approach with aggregated local authority data, comparing Liverpool to a group of similar cities and towns (see supplementary file part 7 for results). We also conducted sensitivity analyses to check whether our choice of matching variables was robust by incorporating the proportion of women (see supplementary file part 8) and the education, skills, and training deprivation domain score rather than the composite score of the index of multiple deprivation (see supplementary file part 9), respectively.https://www.liverpool.ac.uk/coronavirus/research-and-analysis/covid-smart-pilot/.The implementation of Covid-SMART in Liverpool involved regular focus groups with residents run by Liverpool City Council with the University of Liverpool. Further details are available at Over the initial intensive testing period (6 November to 3 December 2020) (model 1), admission rates in Liverpool were 43% lower than in the synthetic control group . In absolute numbers this 43% reduction is the equivalent of 146 (96 to 192) fewer admissions in the period up to 3 December 2020.When extending the analysis to the period up to 2 January 2021 (model 2), we observed a smaller, estimated effect of Covid-SMART in reducing admissions by 16% , or −133 (−239 to −3) in absolute terms, in Liverpool compared with control areas. After adjusting for the anticipated effect of tier 3 restrictions on covid-19 hospital admissions using our central estimate, the impact of community testing was observed to increase, and hospital admissions reduced by 25% , or 239 (104 to 333) in absolute terms (model 3).Sensitivity analyses using the upper and lower plausible estimates of the potential tier effect showed coherent and similar results with those of model 3 (see supplementary file part 4 for more details). We also repeated our analysis by including areas with mean weekly lateral flow testing rates >1 per 100 population; findings were similar to those in This study found that the introduction of community testing for SARS-CoV-2 in Liverpool, ahead of its wider implementation across the UK, was associated with a reduction in covid-19 related hospital admissions compared with what would have been expected in the absence of this intervention. This effect was observed to be greater when analysis was restricted to the first month of implementation, when testing was more intensive through military assistance and before Liverpool entered a lower level of restrictions than most other cities, at the same time as the alpha variant of SARS-CoV-2 spread nationally. This suggests that widespread community testing has an effect at reducing transmission and consequently covid-19 related hospital admissions. We also found similar effects when we explored the impact of the early roll-out of community testing across the wider Liverpool City Region using an equivalent synthetic control analysis, where we estimated a 32%  reduction in covid-19 related hospital admissions.Our analysis has several strengths. We were able to use small area data to construct a control group with similar characteristics to our intervention population. The synthetic control approach ensured that control areas were similar for both level and prior trends in hospital admissions, indicating that these areas were likely to have been affected by similar SARS-CoV-2 transmission patterns before the introduction of Covid-SMART in Liverpool. This is important as the parallel trends assumptions of simple difference-in-differences methods are not sufficient for analysis of infectious diseases, where the rate of change is intrinsically linked to the levels of infection at baseline.Our study also has several limitations. Firstly, although we were able to match areas to ensure a good balance of potential confounding factors before the intervention, it is possible that concurrent changes in the intervention or control populations, or both, could bias the results. The major policy change that affected transmission at this time was the introduction of tiered restrictions, and we have sought to adjust for these in our analysis and present sensitivity analysis assuming different effects of this policy on transmission. The adjustments we made for these differences in restrictions assumed that the effect of tier 2 restrictions on SARS-CoV-2 transmission in Liverpool was the same as the average effect across tier 2 areas in England. The effect could, however, have been greater in Liverpool, because unlike other tier 2 areas, most of the areas surrounding Liverpool were in tier 3. The lower restrictions in Liverpool might have encouraged populations from surrounding areas to use the restaurants and other facilities open in Liverpool that were closed in their own areas at the time. In addition, more restrictive tier 4 restrictions were applied in some other areas within the synthetic group in late December 2020. Therefore our estimates for the effect of Covid-SMART may be overly conservative. Secondly, there are potential spill-over effects, with community testing affecting transmission beyond Liverpool—particularly as testing was available to people working in Liverpool. We sought to account for that by excluding surrounding areas from the control group. Thirdly, our synthetic control group was made up of a non-adjacent set of neighbourhoods, which in aggregate had shown similar trends in hospital admissions to those in the contiguous neighbourhoods of Liverpool—although we found similar results when matching Liverpool to larger local authority areas (see supplementary file part 7). In our analysis we did not consider potential effects on transmission of these differences in the spatial dispersion of the intervention and control neighbourhoods. One might expect that this would lead to a more rapid increase in transmission in Liverpool compared with the synthetic control areas, as neighbourhoods in Liverpool tended to be adjacent to areas with high case rates, whereas the synthetic control neighbourhoods tended to be adjacent to areas with lower case rates—that is, this would be expected to dilute the intervention effect. Fourthly, we were only able to use data on small neighbourhood areas rather than on individuals and therefore were not able to investigate how effects of community testing varied by individual or household characteristics. Fifthly, the causal inference cannot be applied to the use of rapid antigen tests alone because the extensive communication required to implement community testing may have affected covid-19 risk behaviours in those not taking tests.Finally, our study predated vaccination and the omicron variant with higher transmissibility but lower hospital admissions.Debate about the potential benefits and harms of mass testing using lateral flow tests in response to covid-19 has been widespread.It is plausible that the main effect in our analysis is causally related to the Covid-SMART intervention, especially as the study period pre-dates the main roll-out of covid-19 vaccination. Over the full follow-up period a 25% reduction of what would have been without Covid-SMART is the equivalent to an absolute reduction of about 239 hospital admissions in Liverpool. Assuming an infection hospital admission ratio of 3.5%,Although many countries have implemented large scale rapid testing for SARS-CoV-2 antigen, evaluation of its impact on transmission and hospital admissions have been limited. A modelling study found that one round of mass testing might reduce daily infections by 20-30% but that these effects are likely to be relatively short term, with infections returning to pre-mass testing levels shortly after an initial wave of testing.Similar to previous studies, we found that effects seem to have been greatest early on in the programme when large numbers of tests were administered to a large number of people within a relatively short period.The voluntary, city-wide SARS-CoV-2 rapid antigen testing pilot in Liverpool was associated with a substantial reduction in covid-19 related hospital admissions. Community asymptomatic testing for SARS-CoV-2 antigen with lateral flow devices has been a useful addition to the measures for mitigating risks of covid-19. The success of such control measures relies on high levels of uptake and effective support to enable isolation of infectious people and their close contacts. For successful public health responses to covid-19, large scale community testing is more than a test. It is a complex intervention comprising communication, technology, and social responses, which when combined may reduce SARS-CoV-2 transmission beyond the individual effects of tests on early identification and isolation of test positive individuals.Previous studies on managing the spread of SARS-CoV-2 identified asymptomatic transmission as major challenges for controlling the pandemicAlong with non-pharmaceutical measures, many countries rolled out population based asymptomatic testing programmes to further limit transmissionEvidence on whether large scale voluntary testing of communities for covid-19 reduces severe disease by disrupting transmission is lackingThis study found that large scale rapid antigen testing of communities for SARS-CoV-2, within an agile local public health campaign, can potentially reduce transmission and prevent hospital admissionsThe policy implications are that testing during a pandemic is best integrated within local public health programmes, supporting those required to isolate and adapting to prevailing biological, behavioural, and environmental circumstances


The primary contributor to these differences could be the structural differences between the lower limbs. Despite the presence of different coordination features in the stance and swing phases between the lower limbs, no significant difference in the coordination patterns of the thigh-shank coupling was observed. This may be a compensation strategy for achieving coordination patterns with improved symmetry between the lower limbs. The results of this study provide novel insights into the sprinting movement patterns of individuals with uTFA.Understanding the sprinting patterns of individuals with unilateral transfemoral amputation (uTFA) is important for designing improved running-specific prostheses and for prosthetic gait rehabilitation. Continuous relative phase (CRP) analysis acquires clues from movement kinematics and obtains insights into the sprinting coordination of individuals with uTFA. Seven individuals with uTFA sprinted on a 40 m runway. The spatio-temporal parameters, joint and segment angles of the lower limbs were obtained, and CRP analysis was performed on thigh-shank and shank-foot couplings. Subsequently, the asymmetry ratios of the parameters were calculated. Statistical analyses were performed between the lower limbs. Significant differences in the stance time, stance phase percentage, ankle joint angles and CRP of the shank-foot coupling ( For pMovement patterns arise from the organization of the neuromuscular system and involve multiple joints and segments. Investigating the isolated joint and segments might not effectively reflect the interaction effects or coordination of the musculoskeletal system because the compensatory mechanisms are often spread among several body parts . The cooTo improve the running performance of individuals with unilateral transfemoral amputation (uTFA), running-specific prostheses are widely used. Coordinating asymmetries between lower limbs during sprinting is challenging for individuals with amputations . HoweverTherefore, this study aimed to understand the coordination patterns of lower limbs in individuals with uTFA during sprinting to improve running-specific prosthesis design and prosthetic gait rehabilitation. Following the typical approach, we modelled the lower limb segments in the pendulum and incorporated the concept of dynamic system theory . We focu. 2. 2.1−1. The inclusion criteria of the individuals with uTFA included no neuromuscular disorders, no lower limb functional limitations in either limb, and regular exercise or training for at least 1 year before the experiment. This study was approved by the local ethics committee, and all procedures followed the Declaration of Helsinki (1983). Participants were informed of the test content, and their consent was obtained.Seven individuals with uTFA participated in the study . Partici. 2.2Before the experiment, participants performed warm-up exercises to familiarize themselves with the experimental environment. All participants performed static and dynamic stretching and several types of locomotion, including walking, skipping, hopping and jogging, for more than 15 min. Thereafter, each participant performed the maximum sprinting trials. Subsequently, they performed maximal sprinting on a 40 m indoor straight runway. Seven 60 cm × 40 cm force plates  were set on the ground. A motion capture system  with 20 cameras and an effective capture distance of approximately 22 m from the starting line was used. The results from each trial were collected for further analysis. Only trials in which the participant stepped within the force platform boundaries were counted as successful. There were two to three successful trials for each leg. Participants were allowed adequate rest intervals between trials.. 2.3Before the experiment, 58 retroreflective markers were attached to the body of each participant . MarkersThe gait cycle was normalized to 101 points. The GRF data and three-dimensional marker positions were collected at sampling frequencies of 2000 and 200 Hz, respectively. A fourth-order zero-lag Butterworth filter was applied to the raw GRF data at a cut-off frequency of 75 Hz and raw three-dimensional marker positions at a cut-off frequency of 20 Hz. The GRF data were used to define gait events by setting a threshold value of 40 N . For stei and t represent the ith and tth points in the analytical data, respectively. A custom-made MATLAB script was used to conduct the Hilbert transform of the signal in the previous step (equations (2.3) and (2.4)), where j represents the imaginary part. The ‘unwarp’ function in MATLAB was applied to calculate the phase angle (equation (2.5)). The results of the arctan function ranged between ±90° by definition; however, the phase angle of a polarized coordinate must have a full range of 360°. The unwarp function ensured that the final phase angle would retain the previous value and not skip to the ±90° range. The CRP angles of the thigh-shank and shank-foot couplings were calculated by subtracting the proximal angle from the distal one (equation 2.6). CRP angles with ranges outside ±180° were adjusted to ±180° by adding or subtracting 360°. The MARP and DP of each gait cycle were calculated based on the CRP values obtained in the last step (equations (2.7) and (2.8)). MARP evaluates the coordination pattern, and DP represents the variability of the overall coordination at a specific time or phase of the gait cycle. A MARP (or CRP) value of 0° indicates that the coupling performs an in-phase coordination pattern, while an increasing distance from 0° indicates an out-of-phase relationship in the coupling [The Hilbert transform method was applied for CRP analysis . The segcoupling .2.1θ¯=θ−patterns .Subsequently, the asymmetry ratio for each gait parameter was calculated . For ind. 2.4t-test was performed to investigate differences between the lower limbs. For gait parameters without a normal distribution, the Wilcoxon signed-rank test was used to analyse the differences between the limbs. The statistical analyses were performed using SPSS  with a significance level of p < 0.05. Subsequently, the significance of the paired t-test and Wilcoxon signed-rank test were adjusted by false discovery rate correction. The effect size was calculated using Cohen's d and Cliff's delta methods for the normal and non-normal distributed parameters, respectively.The Shapiro–Wilk test was conducted to verify data normality. For each gait parameter with a normal distribution, a paired For the CRP curves (thigh-shank and shank-foot), SPM  was then applied to investigate the significance between the prosthetic and intact limbs . The sig. 3−1.The demographic data of the seven participants are listed in . 3.1p = 0.24). However, the stance time and stance phase percentage were significantly lower for the intact limb than for the prosthetic limb, each with p = 0.01.As listed in a–c, respectively) illustrate the kinematics of the ankle, knee and hip joints. There were no significant differences in peak ankle dorsiflexion, hip flexion and extension between prosthetic and intact limbs. The ankle joint showed a significantly higher peak of plantarflexion and range of motion in the intact limb than in the prosthetic limb (p < 0.01). For the knee joint, significant differences were observed between the lower limbs. The intact limb only performed knee flexion throughout the gait cycle, while the prosthetic limb had an extension of −5.41 ± 2.35°. There were significantly higher peaks of flexion and range of motion in the knee on the intact limb than on the prosthetic limb . The peak flexion and range of motion of the hip joint were significantly higher for the intact limb than for the prosthetic limb (p = 0.01).For the spatio-temporal parameters, the step length on the intact limb was larger than that on the prosthetic limb, and the stance time and stance phase duration were longer on the prosthetic limb than the intact limb . For the kinematics, the maximum ankle plantarflexion and range of motion were close to zero while the maximum ankle dorsiflexion was greater than one and was the largest value among all asymmetry ratios . The knee and hip joint parameters were all larger for the intact limb , even though the maximum hip extension was very close to symmetrical (0.99 for maximum hip extension).. 3.2p < 0.01). There were no significant differences between the intact and prosthetic lower limbs in the MARP of the thigh-shank coupling or the DP of either thigh-shank or shank-foot coupling. The asymmetry ratios of the MARP of thigh-shank and shank-foot couplings were 0.92 ± 0.22 and 0.41 ± 0.08, respectively.Among the coordination measures, only the MARP of the shank-foot on the intact limb demonstrated a significantly greater out-of-phase pattern than that of the prosthetic limb  slope indicates that the distal  one is leading the other [p = 0.01). Two other clear features are shown in this plot. First, the intact limb was observed with a shank-leading pattern between 0% to 10% of the gait cycle, whereas the prosthetic limb had the thigh leading during the entire stance phase. Second, a shank-leading pattern was observed on the intact limb throughout the swing phase, whereas the prosthetic limb maintained a shank-leading pattern for approximately 80% of the gait cycle and then demonstrated a thigh-leading pattern.The CRP curves are depicted in figure 2he other ,12. In te, a transition of shank-leading pattern to foot-leading pattern at around 6% of the gait cycle from the initial contact was observed in both lower limbs, with no significant difference found in the changing time (p = 0.53). The intact limb ended the foot-leading pattern later than the prosthetic limb, but this is not significant (p = 0.07). The intact limb then retained a shank-leading pattern until the end of the gait cycle, whereas the prosthetic limb fluctuated around 0° until the end of the swing phase, and then demonstrated a shank-leading pattern to the end of the gait cycle.In the shank-foot coupling, as shown in figure 2a). In the shank-foot coupling, significant differences are observed from 20% to almost the end of the gait cycle .The SPM analysis results are shown in figure 3. 4This study investigated the coordination of the lower limbs of individuals with uTFA during sprinting. We proposed two hypotheses, namely, in thigh-shank coupling, the prosthetic limb should exhibit a larger DP than the intact limb, and in shank-foot coupling, the prosthetic limb might demonstrate a more in-phase relationship during swing phase than the intact limb, since the prosthetic limb is a blade with limited degrees of freedom. Hypothesis I was not supported as thigh-shank coupling demonstrated both similar coordination patterns and variability of the coordination throughout the gait cycle, as evidenced by the similar MARP and DP in thigh-shank couplings. Hypothesis II was supported since the MARP in shank-foot coupling on the prosthetic limb demonstrated a significant in-phase coordination pattern during the gait cycle, and the SPM plot also revealed significant differences between the two lower limbs from the swing phase.During sprinting, individuals with uTFA demonstrated significant differences in the spatio-temporal and kinematic parameters between the lower limbs. In the spatio-temporal parameters, the prosthetic limb showed a longer stance time and phase than the intact limb. This finding is in line with a previous study on individuals with transtibial amputation . A possia). There was no significant difference in the MARP (thigh-shank), DP (thigh-shank) and DP (shank-foot), meaning that the thigh-shank parts of both limbs had a similar out-of-phase relationship during the entire gait cycle [Symmetrical coordination was achieved by individuals with uTFA, as thigh-shank coupling can maintain the MARP at a symmetrical level (0.92 for thigh-shank MARP asymmetry ratio) between the prosthetic and intact limbs. The SPM revealed the same results as MARP (thigh-shank) between the lower limbs during the gait cycle as no significant differences were found during the whole gait cycle a. There it cycle . In the it cycle . This red). For the thigh-shank coupling, the intact limb started with a shank-leading pattern until 10% of the gait cycle, followed by a thigh-leading pattern during the stance phase. Meanwhile, the prosthetic limb adopted a thigh-leading pattern throughout the entire stance phase. This difference might be the compensatory strategy that the prosthetic limb cannot actively generate force in the shank part, and thus the coupling can only use the thigh-leading pattern during the stance phase. During the swing phase, the intact limb maintained a shank-leading pattern until the end of the gait cycle. However, the prosthetic limb showed a shank-leading pattern, then switched to a thigh-leading pattern at approximately 80% of the gait cycle and maintained this to the end of the cycle. The prosthetic knee reached full extension earlier than the biological knee, at 80% of the gait cycle (b) and this may explain the reversion to a thigh-leading pattern in the prosthetic limb. At this point in the gait cycle, there is no space for the shank to extend the knee angle; hence, the thigh segment compensates to complete the swing phase by moving and leading the shank segment to the original position. Consequently, individuals with amputation maintained symmetrical coordination in thigh-shank coupling between the lower limbs with different coordination features in the stance and swing phases.The compensatory strategies might be suggested through the coordination patterns in the two lower limbs. Individuals with transfemoral amputation achieved symmetrical coordination  with asymmetrical spatio-temporal and kinematic parameters. Despite the consistency in the coordination patterns of the lower limbs in thigh-shank coupling (no significance in MARP thigh-shank), there were different coordination features between the prosthetic limb and intact limb during the stance and swing phases d. For thit cycle b and thiThe more in-phase coordination pattern on the prosthetic limb in MARP (shank-foot) suggested different coordination patterns in the shank-foot coupling. This might suggest that the compensation in the shank-foot coupling is not effective enough to reach symmetrical coordination patterns. For the CRP curve of shank-foot coupling, the same feature (shank leading to foot leading at 6% of the gait cycle) was observed during the stance phase and swing phase. Both limbs demonstrated a shank-leading pattern at the beginning of the gait cycle, which was then converted to a foot-leading pattern in the middle of the stance phase. During the swing phase, the prosthetic limb generally demonstrated in-phase coordination (around 0 phase angle), while the intact limb demonstrated a shank-leading pattern and returned to the original phase position. The in-phase relationship in the prosthetic limb during the swing phase was supported by the fact that the shank and foot segments of the prosthetic limb are combined as a single solid blade which will not flex when it is not in contact with the ground.This study has several limitations. First, the causes of amputation and the residual limb length of the participants were not the same. These differences might be confounding factors. For example, compared with the traumatic type of amputation, the vascular type was suggested to result in slower walking speed and shorter stride length . The femThe findings of this study should provide a novel insight into the coordination patterns for prosthesis design and prosthetic gait rehabilitation. There are biological and functional asymmetries between lower limbs in individuals with uTFA. It is not reasonable to completely match the prosthetic limb to the intact limb since the conventional prosthetic limb cannot actively generate forces. However, recently some rehabilitation exoskeletons and powered prostheses have overcome the lack of force generation in prosthetic limbs ,34. Whil. 5In summary, individuals with uTFA may sprint by coordinating their intact and prosthetic limbs using compensatory strategies in thigh-shank coupling during the stance and swing phases to achieve similar coordination patterns. To compensate for the lack of force generation in the prosthetic shank, the prosthetic thigh-shank adopted a thigh-leading pattern throughout the whole stance phase, while the intact limb had an exchange from shank leading to thigh leading during the stance phase. During the swing phase, the prosthetic limb applied the same exchange as the intact limb performed during the stance phase, while the intact limb maintained shank leading throughout the whole swing phase. These different coordination features compensated for asymmetries to achieve symmetrical coordination. In shank-foot coupling, the prosthetic limb demonstrated a more in-phase coordination pattern, as the prosthetic ankle joint was absent in this type of prosthetic limb. The findings of this study provide novel insights into the design of prostheses and prosthetic gait rehabilitation in terms of lower limb movement coordination control.


Understanding the photophysical properties and stability of near-infrared fluorescent proteins (NIR FPs) based on bacterial phytochromes is of great importance for the design of efficient fluorescent probes for use in cells and in vivo. Previously, the natural ligand of NIR FPs biliverdin (BV) has been revealed to be capable of covalent binding to the inherent cysteine residue in the PAS domain (Cys15), and to the cysteine residue introduced into the GAF domain (Cys256), as well as simultaneously with these two residues. Here, based on the spectroscopic analysis of several NIR FPs with both cysteine residues in PAS and GAF domains, we show that the covalent binding of BV simultaneously with two domains is the reason for the higher quantum yield of BV fluorescence in these proteins as a result of rigid fixation of the chromophore in their chromophore-binding pocket. We demonstrate that since the attachment sites are located in different regions of the polypeptide chain forming a figure-of-eight knot, their binding to BV leads to shielding of many sites of proteolytic degradation due to additional stabilization of the entire protein structure. This makes NIR FPs with both cysteine residues in PAS and GAF domains less susceptible to cleavage by intracellular proteases. Genetically encoded protein fluorescent markers are routinely used to study biological processes by selectively labeling cellular targets  involved in these processes ,2. An inMost of the currently available NIR biomarkers are developed from NIR fluorescent proteins (NIR FPs), which consist of chromophore-binding domains composed of two full-length bacterial phytochrome domains, PAS (Per-ARNT-Sim) and GAF (cGMP PDE/AC/FhlA) ,4. The cPAS). However, these NIR FPs have a very low fluorescence quantum yield. To increase the fluorescence quantum yield, a mutant form of NIR FP was created that has a cysteine residue in the GAF domain (CysGAF), in a position equivalent to the attachment site of the plant and cyanobacteria photoreceptor (Cys256). The spectral properties of dimeric NIR FPs with all possible combinations of CysPAS and CysGAF have been studied [PAS and CysGAF. Crystallography of the monomeric protein miRFP670, containing both CysPAS and CysGAF, has revealed the covalent attachment of BV to these two residues simultaneously [PAS and CysGAF compared to other BV-containing NIR FPs.When BV interacts with NIR FP, it incorporates into the so-called chromophore-binding pocket formed by the PAS and GAF domains and covalently binds to inherent Cys15 in the N-terminal region of the PAS domain (Cystor Cys25. The spe studied . It has aneously . This ty−1) [PAS and CysGAF, and to more accurately determine the spectral characteristics of these proteins. These NIR FPs include a monomeric protein BphP1-FP, and dimeric proteins iRFP713/V256C and iRFP670 derived from bacterial phytochromes RpBphP1, RpBphP2, and RpBphP6 from Rhodopseudomonas palustris, respectively. In this work, we analyzed the resistance of NIR FPs containing two cysteine residues to proteases and revealed the reasons for their high resistance to proteolytic cleavage.To date, this assumption has been confirmed only by analyzing the Raman spectra of the iRFP682 (by the band shift at 1656 cm−1) . We were2 atom of BV to CysGAF (BV-CysGAF) and covalently simultaneously through the C31 atom of BV to CysGAF and the C32 atom of BV to CysPAS (CysGAF-BV-CysPAS). The ratio of NIR FP molecules, in which the mode of BV binging differs, is approximately equimolar. The presence of two types of protein molecules in approximately equal amounts is evidenced by two bands of the same total intensity on the gels visualizing the separation of these proteins under denaturing conditions . The absorption and fluorescence spectra of NIR FPs enriched in CysGAF-BV-CysPAS almost coincided with the spectra of the original NIR FPs  is directly involved in the hydrogen bond network with the chromophore and other amino acids in NIR FPs and, in addition, can affect the number of water molecules inside the pocket of the GAF domain, also impacting the proton wire proteins [Taken together, the obtained data confirm that Cysed state ,21. Thesed state . Accordin pocket . The infn pocket ,23. In pproteins ,25,26,27GAF-BV-CysPAS by selective denaturation of monomers with CysGAF-BV in the parent NIR FPs implies that the cross-linking of the PAS and GAF domains through simultaneous binding of cysteine residues in them to the chromophore indeed stabilizes the NIR FP structure. The stability of the biomarker in the cell, in addition to the stability of its structure, is affected by its resistance to the action of proteolytic enzymes. Therefore, we analyzed the influence of proteases, trypsin, and chymotrypsin, on the structure of NIR FPs containing both cysteine residues in the PAS and GAF domains using iRFP670 as an example. Protease-treated samples were analyzed using the Tricine-SDS polyacrylamide gel electrophoresis, used to separate peptides over a wide range of molecular weights [GAF-BV and CysGAF-BV-CysPAS  was observed ,32,33 F, gel 4. GAF residue. According to the calculation, the solution of iRFP670 not hydrolyzed by chymotrypsin at Y213 and F247 sites should contain peptides with a covalently attached chromophore with a molecular weight of 6.99 (peptide B-BV) and 12.04 kDa (peptide B-BV-peptide A)  . The pro protein , which w protein . The W28F domain . In the F domain . At the expected .GAF-BV-CysPAS, and almost complete cleavage of the monomer with CysGAF-BV  treated with chymotrypsin in the presence of ProteaseMAX™ Surfactant, short peptides with a size between 4.6 and 10 kDa were detected . AccordiPAS and CysGAF enhances significantly the stabilizing effect of the knot, making these proteins almost insensitive to the action of proteases.Our findings also highlight the possible function of the knot in the polypeptide chain of the chromophore-binding domain of phytochromes in increasing the resistance of these proteins to proteolytic degradation. Our data also show that the simultaneous covalent binding of BV to both domains of the NIR FPs with two cysteine residues CysPAS and CysGAF contributes to their higher molecular brightness compared to NIR FPs bearing one of these two cysteine residues or without them [In this work, we analyzed the effect of the covalent binding of BV to two cysteine residues in the PAS and GAF domains in NIR FPs on the structural and spectral properties of these proteins. Previously, the allosteric influence of protein monomers in dimeric NIR FPs on each other’s structure has been shown to govern the nature of BV binding in them . Indeed,out them .PAS and CysGAF corroborated with earlier studies of individual NIR FPs of this group [GAF is significantly higher in proteins containing both CysGAF and CysPAS [PAS and CysGAF compared to other BV-containing NIR FPs. The analysis in the current work of several NIR FPs with two cysteine residues Cysis group ,9, indicd CysPAS . In thatd CysPAS . Thus, sPAS and CysGAF leads to the screening of many sites of proteolytic degradation in them. As a result, covalent binding of BV in NIR FPs simultaneously with two cysteine residues CysPAS and CysGAF not only stabilizes their structure but also increases their resistance to proteolytic degradation in the cell, which is important for their use as fluorescent tags in the cell.Our data indicate that the covalent binding of BV simultaneously to two regions of the polypeptide chain, which additionally forms a figure-of-eight knot, in NIR FPs with two cysteine residues CysGuanidine hydrochloride (GdnHCl), buffer components, and trypsin from bovine pancreas were purchased from Sigma  and used without further purification. Chymotrypsin and ProteaseMAX™ Surfactant (Trypsin Enhancer) were purchased from Promega .NIR FP genes, containing N-terminal polyhistidine tag, were amplified and cloned into a pBAD/His-B vector  using BglII and EcoRI sites expression in LMG194 host cells . NIR FPs are expressed and purified as previously described [2HPO4, 22 mM KH2PO4, 19 mM NH4Cl, 8.5 mM NaCl, 2% casamino acids, 1 mM MgCl2, 1 mM thiamine) supplemented with ampicillin was used for the expression of NIR FPs in the apoforms. Ampicillin and kanamycin were included in the culture medium for the expression of NIR FPs in holoform. Arabinose and rhamnose, respectively, were used for induction of the NIR FPs and HO expression. Cell lysates were purified with sequential affinity chromatography on a His Gravitrap column  and ion-exchange chromatography on a MonoQ column . The purity of the proteins was tested by SDS-PAGE using 15% polyacrylamide gels [The target escribed ,39. Brieide gels . The proAbsorption spectra of NIR FPs were acquired using a U-3900H spectrophotometer  with microcells 101.016-QS 5 × 5 mm .−1·cm−1). The fluorescence quantum yield of NIR FPs was calculated using iRFP713 as standard.The fluorescence spectra were measured using a Cary Eclipse spectrofluorimeter  with cells 10 × 10 × 4 mm . The raw fluorescence intensity of BV was corrected for the secondary inner filter effect . The extA = I320/I365, i.e., the ratio of fluorescence intensities on two slopes of the protein tryptophan fluorescence spectrum [Tryptophan fluorescence spectra of NIR FPs were recorded using 295 nm excitation wavelengths and corrected for instrument sensitivity. The position of these spectra was determined by recording the parameter spectrum . With thex = 375 nm) or LDH-C-660 (λex = 660 nm). The fitting of fluorescence decay curves was performed using the standard convolute-and-compare nonlinear least-squares procedure [Chromophore fluorescence decay curves NIR FPs were collected using a spectrometer FluoTime 300  with the Laser Diode Head LDH-C-375 . The far-UV CD spectra were recorded in a 1 mm path length cell from 250 to 190 nm, with a step size of 0.1 nm. The near-UV CD spectra were recorded in a 10 mm path length cell from 320 to 250 nm, with a step size of 0.1 nm. The visible CD spectra were scanned from 800 to 320 nm, with a step size of 0.1 nm, using a 10 mm path length cell. An average of three scans was obtained for all spectra. The CD spectra of the appropriate buffer solution were recorded and subtracted from the protein spectra.The chromophore binding with NIR FPs was assayed by zinc-induced fluorescence and staining with Coomassie blue of protein samples separated by SDS-PAGE . The conProtease-treated samples were analyzed by the 16/6% Tricine-SDS polyacrylamide gel electrophoresis, used to separate peptides over a wide range of molecular weights . The pepRpBphP2  were us


At our institution, radiation oncologists routinely treat early-stage oral cancer with low-dose-rate brachytherapy (LDR-BRT) using Au-198 grains. In this report, we show a unique case of a patient with a gold grain located within the submandibular gland, found incidentally during follow-up after LDR-BRT for floor of mouth cancer. One month after the implant, he showed sialadenitis-like symptoms, but the pain resolved two months later. All the grains were detected around the anterior sublingual area by computed tomography (CT) four months after the implant. Unexpectedly, 11 months after the implant, CT revealed that a grain was located in an intraglandular site of the submandibular gland. This finding clearly demonstrates that the grain entered Wharton’s duct and retrogradely migrated to the submandibular gland through the duct. As a mechanism of the calculus formation within Wharton’s duct, retrograde migration of foreign bodies to the inside of the duct has been proposed. Our incidental finding after LDR-BRT highlights the need for monitoring post-LDR-BRT using Au-198 grains for the treatment of floor of mouth cancer and sheds additional light on retrograde theory within Wharton’s duct. Brachytherapy (BRT) is performed for early-stage oral cancer as a definitive radiotherapy. In addition to being equivalent to the local control achieved by surgery, it retains oral function, resulting in a high quality of life with minimal side effects -4. This A 63-year-old Japanese man noticed a mass on the left side of the floor of his mouth in November 2020. Past medical history was unremarkable. The patient visited the oral surgeon at our hospital and was diagnosed by biopsy with squamous cell carcinoma (SCC). He was referred to our department for brachytherapy in December 2020. Clinical examination revealed a 1.2 × 0.7 cm exophytic mass in the left anterior floor of the mouth Figure . On palp18F-FDG PET/CT) revealed uptake in the left floor of the mouth (SUVmax=5.6) , and contrast-enhanced magnetic resonance imaging (MRI) could not detect the tumor. Fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography  Figure . No evid) Figure , and dra) Figure . The patAfter S-1 (tegafur/gimeracil/oteracil) oral chemotherapy , in February 2021, eight Au-198 grains were implanted into the left side of the floor of the mouth under local anesthesia, and the patient was hospitalized in isolation for four days. The number of grains was determined as follows. The treatment target area was set as a circle of 2 cm in diameter Figure , and theAfter the LDR-BRT, we followed the patient in an outpatient setting. In March 2021, while apparent mucositis due to acute toxicity had almost resolved, he had recurrent pain in the left distal floor of his mouth after drinking water, and it resolved after 20 minutes. Saliva from the orifice exhibited good flow, but the sublingual fold was hard on palpation. In May 2021, while the pain had disappeared, salivary outflow from the left sublingual caruncle was not clear. In June 2021, four months after the implantation, CT showed no evidence of recurrence in the floor of the mouth and no cervical lymph node metastasis. Implanted gold grains were detected in the left floor of the mouth Figure . The patIn January 2022, after a careful follow-up, CT showed a sialolith-like structure in the left submandibular gland Figure . During Five months later, MRI showed saliva throughout Wharton’s duct, but the apparent flow was still unclear near the left sublingual caruncle. In addition, the left submandibular gland showed high signal intensity in the T2-weighted fat-suppressed MRI, suggesting the existence of inflammation Figure .Except for the short-term pain after drinking water approximately one month after the implant, he had unclear salivary outflow from the left sublingual caruncle and no other significant subjective symptoms. Moreover, he exhibited no radiographic or clinical evidence of cancer recurrence. During our follow-up, he received radiation therapy for primary lung cancer and surgery for gastric cancer, and neither of them recurred.-14 MBq when it moved to the submandibular gland. Therefore, the direct effect of radioactivity from the Au-198 grain on the submandibular gland can be considered negligible. Fortunately, the patient currently shows no significant subjective symptoms, but we need to carefully follow up to see if submandibular adenitis or duct obstruction worsens in the future.The Au-198 grain consists of an Au pellet and a sheath of Pt coated on platinum plating Figure . In addiGold grains were not detected in the left submandibular gland before BRT Figure  or four There are some reports that foreign bodies including a fish bone , shrimp Our case may be the first report of a foreign body traveling in a retrograde fashion almost the full length of Wharton’s duct presumably from the site near the orifice to the center of the submandibular gland. Based on this rare experience, it may be recommended to carefully check the running direction of Wharton’s duct or insert a bougie into Wharton’s duct during the implant to avoid direct implant to the duct. This case report calls attention to using LDR-BRT with Au-198 grains, and also, unexpectedly, the existence of a potential function of Wharton’s duct, which has the ability to generate forces and pressures sufficient to produce retrograde flow toward the submandibular gland. Our new clinical findings may shed additional light on the retrograde theory.


Serious measures, including mass vaccination, have been taken to ensure sufficient hospital capacity during the COVID-19 pandemic. Due to high hospitalization risk in the oldest age groups, most countries prioritized elderly for vaccines. The aim of this study is to broaden the understanding of how vaccination in younger age groups relieved the strain on hospitals during the pandemic.N=2 419) or unvaccinated (N=55 168) with comparison groups of vaccinated (N=4 818) and unvaccinated (N= 97 126) individuals without COVID-19. To evaluate whether vaccination itself contributed to a strain in hospitals, we use a similar design to study hospitalization rates before and after vaccination by comparing individuals vaccinated with the first dose (N=67 687) to unvaccinated individuals (N=130 769). These estimates were incorporated into a simulation of hospitalization days with different vaccine scenarios to show how the estimated results might have mattered for the hospitals and their capacity.To determine the impact of vaccination on hospitalization, we relied on individual level data on health care use and vaccination from the Norwegian Emergency Preparedness Register Beredt C19. Using a pre-post design, we estimated the increase in hospitalization days from before to after confirmed COVID-19 for individuals aged 18-64 who were fully vaccinated (Hospitalization days increased by 0.96 percentage point each day during the first week and 1.57 percentage points during the second week after testing positive for COVID-19 for unvaccinated individuals. The corresponding increase was 0.46 and 0.32 for vaccinated individuals, i.e., a substantial difference. The increase was significantly higher for those aged 45-64 than for those aged 18-25. We find no increase in hospitalization days due to vaccination. Simulation results show that vaccination reduced hospitalization days by 25 percent, mainly driven by age 45-64.Our findings indicate that vaccination of individuals aged 18-64 did alleviate pressure on hospitals. Whereas there was a substantial relieve from vaccinating the 45-64 age group, there was no such contribution from vaccinating the 18-25 age group. Our study highlights how simulation models can be useful when evaluating alternative vaccine strategies.The online version contains supplementary material available at 10.1186/s12913-022-08541-x. Maintaining sufficient hospital capacity has been a key concern during the Coronavirus Disease 2019 (COVID-19) pandemic. To ensure hospitals’ ability to provide sufficient levels of treatment and handle a potential influx of COVID-19 patients, governments worldwide have implemented strict infection control measures and initiated mass vaccination to limit the spread of SARS-CoV-2.Although overall infection rates have generally been higher for young adults in Norway, the single most important predictor of COVID-19 resulting in hospitalization or death is high age . VaccineBy October 2021, the entire adult population had been offered at least one dose of a COVID-19 vaccine in Norway, and the vaccine uptake among these was around 90% . Despiteth, 2021 using four different scenarios: 1) without any vaccination in the period, 2) with everyone being vaccinated the whole period, 3) a gradual increase in the vaccination rates equal the observed vaccination status in Norway in the period of study, and 4) an alternative vaccine strategy that solely prioritizes by decreasing age. Our simulation approach highlights the magnitude of the estimates for the given population, and describe to what extent different vaccination strategies matter for the strains on hospitals using estimated causal changes at the individual level.Furthermore, we incorporated these estimates into a micro simulation model that estimated number of hospitalization days from January 1st 2021 to October 30We utilized nation-wide individual-level data from the BEREDT C19 registerst, 2021  unvaccinated and who had confirmed COVID-19, B) vaccinated and who had confirmed COVID-19 after the second dose and C) vaccinated with the first dose of a COVID-19 vaccine (Table day zero), respectively, and followed each patient for 28 days prior to and 28 days after day zero. The outcome variable was coded one from the date of admission up to and including the discharge date and zero otherwise. Vaccines should not be administered to individuals with infection and fever on or 10 days before the vaccination day, and we therefore excluded observations from 10 days before to 5 days after date of vaccination, as this otherwise may lead to selection of somewhat healthier individuals into our treatment groups.We studied all-cause hospitalization days , restricted to acute inpatient care. We organized our data in a relative-day structure with date of confirmed COVID-19/date of vaccination set as the point of reference  on the given day, divided by the number of person days, from 28 days prior to and after day zero (date of confirmed COVID-19/vaccination). We did this separately for the three treatment and three comparison groups, as defined above.Furthermore, we studied how hospital strain was affected after COVID-19/vaccination in separate analyses using an event study design operationalized as a generalized difference-in-difference (DiD) approach. DiD analyses evaluate the effect of an event  by comparing the change in the outcome for the affected group before and after the event, to the change over the same time span in a group not affected by the event –20. It cWhere We thus generalized the traditional DiD method by extending from one period before and one after the event (confirmed COVID-19/ vaccination) to four separate estimates for each week after the event, comparing to the hospitalization days in the 28-day period before –22. In aTo investigate group differences, we also split the sample into four mutually exclusive age groups based on age prioritizations in the Norwegian vaccination program; 18-24, 25-39, 39-44, and 45-64, and did the regressions with DiD-specifications as described above.To quantify to what degree the burden on hospitals was relieved by vaccination, we incorporated our DiD-estimates into a model that simulated what the hospitalization days would be in four different scenarios; 1) without any vaccination in the period, 2) with everyone being vaccinated the whole period, 3) with the actual vaccine roll-out in the period of study, and 4) an alternative roll-out that solely prioritizes by decreasing age, where we redistribute vaccines so that those in the age group 45-65 got their first and second dose before those in the age group 40-44 and so on . As intended, there were only small differences on variables predicting positive COVID-19 test between the treatment and comparison group Table  column AOur DiD estimates show that this corresponds to a 0.96 ((1.04 - 0.09) - (0.11 - 0.11)) percentage points increase the first week after testing positive for COVID-19 among the unvaccinated, compared to the matched control group Table A.Table 3Hospitalization days after COVID-19 for unvaccinated individuals was found to differ between different age groups Fig.  A. WhileN=4 818) from the pre period to week 1-4 after date of confirmed COVID-19, while it increased from 0.08 to 0.59 from the pre period to week 1 after date of confirmed COVID-19 in the treatment group (N=2 419)  hospitalization remained stable in the comparison group (19) Fig.  column B19) Fig.  column B group N= 419  Fig. B. Those N= 67 687) there was a slight decrease in hospitalization days from the pre period to the weeks after vaccination  is unrealistic in the period of study due to limited availability on vaccines. However, it illustrates the magnitude to which vaccination may reduce the burden on hospitals in the future, if such limitations no longer exist. Clearly, our results shows that full vaccine coverage reduce the burden on hospital  times higher for those aged 45-64 compared to those aged 18-24. There was no increase in hospitalization days after vaccination.Conservative simulation results show that the actual vaccine roll-out reduced hospital days with 25 percent. Our results also show that an alternative vaccine roll-out that solely prioritizes by decreasing age could potentially have reduced hospitalization days with an additional 8 percent compared to the actual vaccine roll out. However, there are several other good reasons why age should not be the only priority criterion when distributing vaccines. Vaccination of health care workers was prioritized due to their crucial role in keeping the health care system operational, and medical risk groups were prioritized as they were more likely to get severe COVID-19 complications if infected. This simple simulation does not capture such priorities. Further research could also evaluate vaccine strategies that prioritize by other characteristics that are correlated with higher probability of being infected and/or higher probability of being hospitalized.Our results both confirm and shed new light on the degree to which vaccination has relived the capacity strain on hospitals. A modelling study based on individuals in New York City used an age-stratified agent-based model of COVID-19 to simulate the counterfactual scenario of no vaccination and compared the resulting disease burden with the number of cases, hospitalizations and deaths reported under the actual pace of vaccination. Without vaccination, they projected that the total numbers of hospitalizations and deaths would have been over 2-fold higher than what was reported in the period of study .To our knowledge this study is the first to explore to what degree vaccination of different age groups have relived the capacity strain on hospitals using nationwide observational data to estimate causal effects of vaccination on hospitalization days and incorporating these estimates into a simulation model. For the government and health authorities, our findings primarily show that ensuring vaccine uptake in the population aged above 45 is the key strategy in preventing future capacity constraints on hospitals. Important strengths of our study include the large sample size, the inclusion of both unvaccinated individuals with confirmed COVID-19, vaccinated individuals with confirmed COVID-19 individuals vaccinated with COVID-19 and vaccinated individuals with confirmed COVID-19, as well as the use of three comparison groups. Another strength is the use of routinely collected, daily nation-wide data from health registers that are mandated by law. Our methodological approach, where we studied acute overnight hospitalizations both before and after date of confirmed COVID-19 or vaccination also add to the strengths of the study, as it allowed us to provide estimates of what may happen to hospital capacity in the absence of vaccination, while controlling for time-variant confounders, such as seasonal changes to health care use that impact both groups to the same extent. We also incorporate these estimates into a simulation model that allow us to predict hospitalization days in different vaccine prioritization scenarios.st to October 30th, 2021, which implicitly assumes that factors affecting the probability of COVID-19 infection and post-infection hospitalizations remain similar over time. This is, however, a strong assumption, as factors such as new virus variants, changes in infection control measures and vaccine effectiveness due to vaccine waning did vary over time. Finally, the simulation design is based on observed data and does not account for non-linear or dynamic effects, like e.g., poorer treatment due to operating closer to capacity limits, which might again lead to even more strain at the healthcare system, and so on.However, there are also certain limitations to our analysis. First, the vaccine should not be administered to individuals with infection and fever on or before the vaccination day, leading to selection of somewhat healthier individuals in the treatment group containing individuals vaccinated for COVID-19. We have therefore excluded observations 10 days prior to vaccine and 5 days after. Additionally, individuals who are eligible for the comparison groups are always infected/vaccinated later than those in the treatment group. However, it is not random who are infected/vaccinated first. If factors associated with time of infection/vaccination are also correlated with the probability of being hospitalized after infection, this could lead to bias in our estimates. For instance, individuals in medical risk groups were prioritized for vaccination, and they also had a higher underlying probability of hospitalization after COVID-19 infection. We addressed this when constructing the treatment group of vaccinated individuals by excluding the first 20 percent of the vaccinees. Second, this study does not consider waning immunity of the vaccine. Since we only study a limited time period this is probably of minor importance. However, countries including Norway have already started vaccination with a third dose, and waning immunity is therefore important when evaluating different vaccine strategies going forward. Additionally, in this study, we estimated the individual effect of vaccination on hospitalizations. However, the total effect of vaccination also contain positive externalities, such as reduced spread of infection and herd immunity that comes in addition to the individual effect. Vaccination can also help alleviate strict infection prevention and control measures kept in place to avoid strain on hospital capacity. More research is needed to understand the overall effects of vaccination. Our simulation model used data from before January 2021 to predict COVID-19 infection rates and hospitalizations from January 1By studying health care use after COVID-19 and vaccination, we have shown that the hospitalization days was highly relived by vaccination, especially by vaccination of individuals aged 45-64. Our study thus illustrates that the individual utility of vaccination is highest among the elderly population and that vaccination of the elderly population is the key strategy in preventing hospital collapse. By incorporating causal estimates into a simulation model, we have also illustrated how simulation models can be used to evaluate alternative vaccine strategies. The simulation results shows that the observed vaccination in this age group averted more than 6 000 hospital days compared to the case of no vaccination. On the other hand, with full vaccine coverage in this age group, close to 19 000 hospital days could have been averted, although not realistic in this time period.Additional file 1: Supplemental Figure S1. Vaccine roll-out scenarios. Supplemental Figure S2. Impact of vaccination on hospitalization days. Supplemental Table S1. Impact of confirmed COVID-19 and vaccination on hospitalization, by age groups. Supplemental Figure S3. Impact of vaccination on hospitalization days by age. Supplemental Figure S4. Simulated infection rates. Simulated infection rates under the assumption that no one is vaccinated based on aggregate data from October 1st, 2020 to October 30th, 2021 for the age groups specified in the analysis. We control for age group, vaccine share within age groups and infection-rates in the preceding week, as well as calendar-week fixed effects.


Comprehensive identification of possible target cells for viruses is crucial for understanding the pathological mechanism of virosis. The susceptibility of cells to viruses depends on many factors. Besides the existence of receptors at the cell surface, effective expression of viral genes is also pivotal for viral infection. The regulation of viral gene expression is a multilevel process including transcription, translational initiation and translational elongation. At the translational elongation level, the translational efficiency of viral mRNAs mainly depends on the match between their codon composition and cellular translational machinery . Thus, codon adaptation for viral ORFs in different cell types may be related to their susceptibility to viruses. In this study, we selected the codon adaptation index (CAI) which is a common codon adaptation-based indicator for assessing the translational efficiency at the translational elongation level to evaluate the susceptibility to two-pandemic viruses (HIV-1 and SARS-CoV-2) of different human cell types. Compared with previous studies that evaluated the infectivity of viruses based on codon adaptation, the main advantage of our study is that our analysis is refined to the cell-type level. At first, we verified the positive correlation between CAI and translational efficiency and strengthened the rationality of our research method. Then we calculated CAI for ORFs of two viruses in various human cell types. We found that compared to high-expression endogenous genes, the CAIs of viral ORFs are relatively low. This phenomenon implied that two kinds of viruses have not been well adapted to translational regulatory machinery in human cells. Also, we indicated that presumptive susceptibility to viruses according to CAI is usually consistent with the results of experimental research. However, there are still some exceptions. Finally, we found that two viruses have different effects on cellular translational mechanisms. HIV-1 decouples CAI and translational efficiency of endogenous genes in host cells and SARS-CoV-2 exhibits increased CAI for its ORFs in infected cells. Our results implied that at least in cases of HIV-1 and SARS-CoV-2, CAI can be regarded as an auxiliary index to assess cells’ susceptibility to viruses but cannot be used as the only evidence to identify viral target cells. It is currently known that both HIV-1 and SARS-CoV-2 can infect different types of target cells in humans. For HIV-1, CD4+ T cells which aid the activity of other immune cells in the adaptive immune response are believed to be its major targets . The decFor SARS-CoV-2, the problem of its target cells is more complex. Although COVID-19 is originally thought to be a respiratory infectious disease characterized by pneumonia, its symptoms can appear in various organs of the human body . In the Normally, infection of viruses to target cells depends on the existence of specific receptors at the cell surface. For HIV-1, the T cell surface receptor CD4 is the major receptor and two chemokine receptors CXCR4 and CCR5 are known coreceptors at the surface of CD4+ T lymphocytes . And forExcept for experimental research, biostatistical methods including several statistical indicators have been proposed to evaluate the efficiency of viral mRNA translation. In this paper, for providing indirect evidence for the susceptibility of different human cell types to HIV-1 and SARS-CoV-2, we utilized the codon adaptation index (CAI) as a measure of viral ORFs’ translational efficiency at the translational elongation level in these cell types . This pa22.1For a specific RNA in a specific cell type with corresponding high-expression protein-coding  gene set, the expression of the original version of CAI while it was proposed  is:k’ is the usage frequency of the k-th sense codon (from the initiation codon to the last sense codon before the termination codon) in the ORF of concerned RNA in all synonym codons of the high-expression gene set. ‘qk’ is the max usage frequency of the synonym codon of the k-th codon in the ORF of concerned RNA in all synonym codons of the high-expression gene set.‘L’ is the number of sense codons  in the ORF of concerned RNA. ‘pk and qk in the CAI expression to pk+0.01 and qk+0.01. Second, for three kinds of amino acids with six corresponding codons , their codons can be divided into two smaller groups according to the first two bases. In these conditions, the same amino acid coded by different groups of codons can be considered as different amino acids in the calculation of CAI  were selected for constructing corresponding datasets. The detailed process for selecting datasets is mentioned in Supplemental Methods . The pipeline of this process is mentioned in Supplemental Methods.  For singhttps://github.com/Renruohan/CAIvirus). For two single-cell RNA-seq datasets, the corresponding relationship between cells and cell types/large groups was also listed in Github. Also, intermediate results of single-cell RNA-seq datasets by Seurat including cell clustering and visualization in low-dimension space, ratio or number of cells belonging to each cell type/large group and markers to identify each cell type/large group were shown in Gene-level expression data (raw counts and FPKM) for all RNA-seq datasets used in this study is provided in Github  with the highest mean FPKM level in biological repetitions (for bulk RNA-seq datasets) or cells (for single-cell RNA-seq datasets) for a cell type to construct the high-expression gene set of this cell type. Also, we found that expression levels of some genes changed significantly in different biological repetitions or cells of the same cell type. Hence, before selecting high-expression genes as mentioned above, we removed genes whose standard deviations of the expression levels are large than the average value. The selected top 200 high-expression gene sets and their normalized expression level (FPKM) for all RNA-seq datasets used in this study are provided in 2.2.4k and qk in this expression of CAI could be acquired from this table. CDS sequences of the isoform with the highest approximate FPKM of each gene in high-expression gene sets for all RNA-seq datasets used in this study are provided in Different from prokaryotic genes, mRNAs transcripted from eukaryotic genes usually experience complex processing including splicing. Because of the existence of alternative splicing, the same mRNA precursor can be processed to different mature mRNAs and translated to different protein products. As a result, it is necessary to discriminate different splicing isoforms of genes in the high-expression gene set. The process of calculating the approximate expression level of splicing isoforms of high-expression genes is mentioned in Supplemental Methods. For each gene, only the isoform with the highest approximate expression level of each gene was utilized to construct the codon usage frequency table of the high-expression gene set, then p2.2.5For verifying if CAI can represent genes’ translational efficiency, we calculated the CAI of the top 5000 highly expressed genes (except genes that are not detected in Ribo-seq experiments) in two groups of paired RNA-seq and Ribo-seq datasets of control cells and cells infected with HIV-1 or SARS-CoV-2 for a certain time. Also, we calculated the translational efficiency by dividing their normalized expression values (FPKM) in Ribo-seq datasets by values in RNA-seq datasets of these genes and then took the logarithm. Then we performed a linear regression analysis between genes’ CAI and translational efficiency in each cell type. Furthermore, for verifying if the CAI of endogenous genes calculated by cell type-specific background gene sets correlated better with translational efficiency than CAI based on commonly used nonspecific background gene sets, we constructed a nonspecific background gene set reference to previously mentioned methods. First, typical housekeeping genes-ribosomal protein genes were selected. Then, we filtered them according to expression patterns, preserving only the ribosomal genes that were present in the top 200 highly expressed genes of at least one cell type (except cells infected by virus or stimulated by cytokines and paired control groups in the same dataset). The CAI of endogenous genes based on this nonspecific background gene set and the correlation between this ‘nonspecific’ CAI and translational efficiency is calculated in the same way as above. In CAI calculation, for each gene in the nonspecific background gene set, one isoform from all isoforms that appear in the top 200 highly expressed gene set of at least one cell type was selected randomly and utilized in the construction of the codon usage frequency table.Data processing for Ribo-seq datasets is mentioned in Supplemental Methods .Gene-level expression data (raw counts and FPKM) for all Ribo-seq datasets used in this study is provided on the Github page. The CAIs and the translational efficiency of the top 5000 highly-expressed genes for all RNA-seq/Ribo-seq pair datasets in this study are provided in 2.3https://www.hiv.lanl.gov/content/sequence/HIV/mainpage.html). There are 21 known subtypes  for HIV-1. Because all genome sequences of subtype K in the database do not meet our standards, this subtype of viruses was not collected and included in the analysis below. For every other subtype, 2-3 genomic sequences were collected to remove random bias. Finally, 58 genomic sequences of HIV-1 were collected for further analysis. Because some collected HIV-1 genomic sequences do not contain all functional ORFs, we exclude some ‘problematic’ ORFs in CAI calculation and further analysis . Major information  and ORFs’ sequences for all 58 HIV-1 strains used in this study are provided in For HIV-1, genomic sequences were collected from the HIV sequence database  (https:/https://www.ncbi.nlm.nih.gov/nuccore ) and five variants of concerns  identified by the World Health Organization (WHO) were collected from GISAID influenza virus and SARS-CoV-2 sequences database (https://www.gisaid.org ). For each variant of concern, 5 genomic sequences were collected to remove random bias. There are six ORFs for essential primary protein products  and six ORFs for non-essential primary protein products  in SARS-CoV-2 genomes  that can infect humans, genomic sequences were collected from the NCBI nucleotide database. For each species, only the reference genomic sequence was collected. For each of these sequences, all ORFs annotated in corresponding species are functional and are involved in downstream analysis. ORFs’ sequences for all six other coronaviruses used in this study are provided in 2.4After sequence collection, the CAI of ORFs of all HIV-1, SARS-CoV-2 and other coronavirus strains above was calculated according to Part 1 in Methods. Results for three groups of viruses are provided in For HIV-1, we compared the CAIs of their ORFs in several groups of different cell types (1) 16 cell types and 3 large groups in the lung. (2) 7 cell types of peripheral blood mononuclear cells (PBMC) (3) 12 cell types of the monocyte-macrophage system (4) 4 subtypes of CD4+ T lymphocytes (5) 5 cell types from two key metabolic organs. To test if the CAI can reflect the evolutionary relationship of different viral strains, hierarchical clustering algorithms were utilized to cluster HIV-1 viral strains based on their ORFs’ standardized (z-score) CAIs in different cell types. For visualizing the results of our analysis, the R package ggplot2 (version: 3.3.6) was utilized.For SARS-CoV-2 subtypes and six other coronavirus species, we compared the CAIs of their ORFs in the lung dataset (16 cell types and 3 large groups in the lung). We also showed the CAI distribution of SARS-CoV-2 in glomerulus-podocytes and mesangial cells because the kidney was reported as an affected organ of COVID-19 . In addi33.1The first part of our study was constructing high-expression gene sets for different cell types. As discussed in the ‘Methods’ part above, for comparing the translational efficiency of viruses in different cell types, except for housekeeping high-expression genes , these gene sets should include enough cell type-specific genes which can represent unique gene expression patterns of these cell types. To verify if the high-expression gene sets we constructed met these conditions, we performed GO-BP  and KEGG enrichment analysis which can reflect which biological processes these genes are involved in. Results of the dataset corresponding to three types of cells  according to the previous mentioned bulk RNA-seq datasets and scRNA-seq datasets. As discussed earlier, because HIV-1 can modulate cellular tRNA pools and improve the translational efficiency of its ORFs , results3.2.2in vitro. The second lowest CAI appears in Langerhans cells which are tissue-resident specialized macrophages of the skin. However, it has been reported that in vitro differentiated macrophage is susceptible to HIV-1 and in vitro HIV-1 infection models based on this cell type have been established  in the liver and adipocytes (the major type of cell that stores lipids in adipose tissue) for CAI calculation and further analysis Figure 9atocytes . An in vte cells . However3.2.3During the evolution of viruses, their infectious capacity to different target cells changes gradually. These changes may be manifested in the adaptation of the translational regulatory system of host cells. It was reported that patterns of codon usage can reflect basic features of molecular evolution . Therefo3.33.3.1We are now focusing on SARS-CoV-2, the pathogen of the COVID-19 pandemic. We calculated the CAI values of SARS-CoV-2 with five VOCs  and a reference  in the lung scRNA-seq dataset . As discWe also found an interesting relationship. Among the essential genes transcribed from subgenome mRNA (sg mRNA), the N gene has the highest expression level, while the E gene has the lowest expression level in the conclusion drawn from the SARS-CoV-2 coding capacity experiment . What’s In addition, we also counted the relative levels of CAI values corresponding to ORFs of different SARS-CoV-2 subtypes in the lung dataset. The results are shown in in vitro study has proved that podocytes can be infected by SARS-CoV-2 with the help of ACE2 and BSG/CD147 at their cell surface , NK cells, and mast cells in lung immune cells are relatively high, suggesting that the destructive power of the coronaviruses inside such cells may be high. This is likely due to the co-evolution of virus and host defense mechanisms during natural evolution. Some existing experimental results can confirm this result, such as SARS-CoV-2, SARS-CoV and MERS-CoV can cause a large decrease in lymphocytes . InfectiHowever, in the CAI value results, the CAI value of lung AT2 cells is relatively low. And we know that AT2 is one of the main host cells of SARS-CoV-2 and SARS-CoV. This shows that AT2 is their main host cell, probably because the virus can enter such cells more easily. However, its translation efficiency and destruction ability in AT2 cells are probably not higher than those in other cells. In addition, some experiments have shown that T cells are resistant to SARS-CoV infection . HoweverIf we evaluate the pathogenic ability of different coronaviruses from the overall CAI value in 4In this study, we tried to utilize the CAI to evaluate the infection ability of HIV-1 and SARS-CoV-2 in different cell types. The core hypothesis of this study is if a virus has a higher CAI in a certain type of cell, then it is likely to be better adapted to the translation system of that type of cell. This assumption has been verified by the significantly positive correlation between CAI and translational efficiency of endogenous genes. Compared to the top 5000 highly expressed endogenous genes, the relatively low CAI of viral ORFs indicates that both two viruses have been not well adapted to endogenous translational regulatory machinery in human cells. We also tried to compare the infectious capacity of two kinds of viruses to different human cell types according to CAI. Although many results show that the putative susceptibility to viruses based on CAI is consistent with the results of previous reports, there are still some exceptions. Hence, it seems that at least in the example of HIV-1 and SARS-CoV-2, CAI can provide some clues about cells’ susceptibility to viruses but cannot be used as a single indicator to postulate viral target cells. We also analyzed the effect of viral infection on the cellular translational mechanism and found significant differences between the two viruses. For HIV-1, its infection can decouple CAI and the translational efficiency of endogenous genes. While for SARS-CoV-2, the CAI of its ORFs increases after the establishment of infection. It is expected that both mechanisms are beneficial for the virus to overcome the defects in codon adaptation in human cells and achieve effective gene expression.in vivo than the analysis based on whole organs. In our study, we quantitatively analyzed the gene expression levels of different cell types in the human body based on bulk RNA-seq and single-cell RNA-seq data and obtained the specific high-expression gene sets to each cell type for CAI analysis. Thus, compared with previous similar studies, our study may reveal the translational elongation activity of the viral ORFs in different human cell types and estimate the susceptibility of these cell types to viruses.Compared with previous studies that evaluated the infectivity of viruses based on codon adaptation, the main advantage of our study is that our analysis is refined to the cell-type level. First, previous studies usually selected a predefined set of highly expressed genes   as the bThere are several reasons which may explain why codon adaptation cannot be used as a single indicator to postulate viral target cells. First, as we discussed in the ‘Results’ part, the translational efficiency may not be the limiting factor for these two viruses to infect human cells. For example, in our analysis of the scRNA-seq dataset of PBMC, HIV-1 ORFs exhibit the highest CAI in B cell which is not susceptible to HIV-1. This contradiction can be simply attributed to the lack of CD4 or other possible HIV-1 receptors at B cell surfaces. Second, regulation of gene expression is due to complex factors in multilevel. It is possible that differences in regulatory mechanisms of gene expression in different human cell types are mainly manifested in pre-translation  and translation initiation levels. However, CAI mainly reflects the regulation at the translational elongation (codon adaptation) level so it cannot summarize all regulatory mechanisms which can affect the expression of ORFs in the virus genome. Third, viruses can manipulate the translation machinery of cells e.g., through modulating cellular tRNA pools . This prIn conclusion, we calculated CAI for two kinds of pandemic RNA viruses in the background of different human cell types. Although previous studies related to CAI or other indexes utilized in the translational efficiency estimation mostly stayed at the species level, our studies refined the estimation of translation efficiency by CAI calculation to the cell type level. We found that although CAI cannot be used as the only indicator to postulate viral target cells alone, it really provides some clues about cells’ susceptibility to viruses from the aspect of codon adaptation. Additionally, we took CAI calculations down to the cellular level for HIV-1 and SARS-CoV-2, and considered alternative splicing in the construction of high-expression gene sets in each cell type. This is beneficial to make the calculation of CAI more reasonable. Next, we presented the CAI patterns of these two viruses in various cells. In addition, we also studied the changes of CAI before and after viral infection, and found that in most datasets, the gene expression of cells after viral infection will lead to the increase of SARS-CoV-2 ORFs' CAIs, which indicates that the translational system may be more suitable for the virus translational elongation after viral infection. Furthermore, both viruses were found to have the highest CAI values in immune cells (T cells), suggesting a co-evolutionary or adaptive relationship between viruses and immune cells.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 in the article/HZ (first author): programming, data curation, result analysis and visualization, writing - original draft, and revising. RR (first author): programming, result analysis and visualization, writing - original draft, and revising. SY (corresponding author): conceptualization, methodology, funding acquisition, project administration, writing - review & editing. All authors contributed to the article and approved the submitted version.