Non‐linear measures of heart rate variability (HRV) may provide new opportunities to monitor cardiac autonomic regulation during exercise. In healthy individuals, the HRV signal is mainly composed of quasi‐periodic oscillations, but it also possesses random fluctuations and so‐called fractal structures. One widely applied approach to investigate fractal correlation properties of heart rate (HR) time series is the detrended fluctuation analysis (DFA). DFA is a non‐linear method to quantify the fractal scale and the degree of correlation of a time series. Regarding the HRV analysis, it should be noted that the short‐term scaling exponent alpha1 of DFA has been used not only to assess cardiovascular risk but also to assess prognosis and predict mortality in clinical settings. It has also been proven to be useful for application in exercise settings including higher exercise intensities, non‐stationary data segments, and relatively short recording times.Therefore, the purpose of this systematic review was to analyze studies that investigated the effects of acute dynamic endurance exercise on DFA‐alpha1 as a proxy of correlation properties in the HR time series.The initial search identified 442 articles , of which 11 met all inclusion criteria.The included studies show that DFA‐alpha1 of HRV is suitable for distinguishing between different organismic demands during endurance exercise and may prove helpful to monitor responses to different exercise intensities, movement frequencies, and exercise durations. Additionally, non‐linear DFA of HRV is a suitable analytical approach, providing a differentiated and qualitative view of exercise physiology. Studies were excluded, (a) if subjects were recruited from non‐healthy populations, (b) if there were only analysis under resting conditions or passive recovery, (c) if there was a different study or non‐comparable method focus, (d) if there was insufficient information about the used exercise variables, (e) if there was no analysis of dynamic endurance exercise, or (f) if medication and/or other interventions were tested during exercise. Since the focus of this review is on the effects of acute bouts of exercise on short‐term scaling exponent alpha1 of DFA, we further excluded intervention studies investigating DFA only under rest conditions. No age‐ or gender‐specific restrictions were imposed in this review.Studies with cross‐sectional and longitudinal design, as well as exercise intervention studies, were eligible for this review. Eligible studies had to (a) investigate HRV and short‐term scaling exponent alpha1 of DFA ), study design (exercise mode), type of HRV measurement method, and main outcomes.3n = 38), a total of 404 articles remained. 377 articles were removed by title or abstract, remaining a total of 27 articles. In addition, 19 articles were removed after full‐text screening with reason: analysis under rest or passive recovery . After the process of removal of duplicate articles . The presented data extend the findings of this review concerning exercise intensity as there is a gradual decrease of alpha1 during graded exercise, denoted by significant changes compared to the previous intensity level, whereby degree and progression of uncorrelated HR dynamics significantly differ between trained and untrained subjects. Additionally, a crossover phenomenon may be present, as with intensities above 70% VO2peak, both trained groups (medium and high level) show a more pronounced reduction in DFA‐alpha1 compared to the untrained state, similar to the findings of Platisa et al.  of the included studies, the application of DFA might help analyze the relationship between different modes of exercise and the corresponding altered cardiac autonomic regulation. This could help overcome the limitations of strongly decreased variability and weak reproducibility of the frequency‐domain HRV measures employed during exercise (Millar et al., 6DFA‐alpha1 of HRV is suitable to distinguish between different organismic demands and may prove helpful in monitoring responses to different exercise intensities, movement frequencies, and exercise durations. Additionally, this approach provides a more systemic view on cardiac autonomic regulation in the context of complex models of exercise physiology. In this context, non‐linear fluctuations of HRV may be seen as an outcome of the complex dynamic interplay of electro‐physiological, hemodynamic, and humoral variables, along with the effects of autonomic and central nervous system regulation. Thus, the measurement of non‐linear HRV during exercise and recovery might help gain further insights into the complex heart‐brain integration response as part of a general exercise related regulation capacity. The available data suggest that DFA‐alpha1 could be used as an adequate and easy‐to‐access load measure for exercise training. From the practical perspective of training and exercise science, it would be interesting to further investigate the influence of structured training, therapeutic interventions, and different performance levels on the described processes of cardiac autonomic regulation during exercise. These findings might lead to a broader understanding of the underlying mechanisms which, in turn, could open up possibilities of new strategies to evaluate and enhance the state of health, disease, or performance level.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.TG and OH conceived and designed the study details. Both authors performed the literature analysis and study selection. TG wrote the first draft of the manuscript. OH reviewed and edited the draft critically. Both authors read and accepted the final version of the manuscript.


To assess readiness among primary public health facilities in Kenya to provide pre‐referral antimalarials for severe malaria.Nine national surveys of randomly selected primary public health facilities undertaken bi‐annually between 2017 and 2021 were analysed. The outcomes included the availability of pre‐referral antimalarial drugs at the health facilities and health worker knowledge of recommended pre‐referral treatment for severe malaria.p < 0.001) and those with access to guidelines versus those without access .A total of 1540 health workers from 1355 health facilities were interviewed. Injectable artesunate was available at 46%, injectable quinine at 7%, and artemether at 3% of the health facilities. None of the facilities had rectal artesunate suppositories in stock. A total of 960 (62%) health workers were trained on the use of injectable artesunate. 73% of the health workers who had ever referred a child with severe malaria were aware that artesunate was the recommended treatment, 49% said that intramuscular injection was the preferred route of administration, and 60% stated the correct dose. The overall knowledge level of the treatment policy was low at 21% and only slightly higher among trained than untrained health workers  availability of nationally recommended pre‐referral antimalarials; (b) appropriate training and supervision in their administration, and (c) monitoring of the entire referral process. Malaria is a disease that can rapidly evolve into severe, life‐threatening complications requiring emergency care and parenteral treatment , 2. The Randomized controlled trials have demonstrated that artesunate is superior to quinine during intravenous (IV) inpatient care  and thatThe availability of pre‐referral treatments at primary health facilities is clearly an essential prerequisite to the implementation of referral care and should be routinely monitored. Given the multiple options recommended by the WHO, the preferred treatments administered by frontline health workers should also be monitored. In this article, pre‐referral malaria treatment availability and health worker knowledge are described at primary public health facilities in Kenya between 2017 and 2021.In 2012, the malaria treatment guidelines were revised to recommend the use of parenteral artesunate for pre‐referral severe malaria treatment . In 2016Since the adoption of the new severe malaria treatment policy using artesunate, various activities have been undertaken to support the translation of the policy into practice. They included the procurement and nationwide distribution of injectable artesunate in 2014. The revision of national standard treatment guidelines in 2014 and 2016 to reflect the new treatment policy and distribution to health workers together with artesunate job aides. One‐day training sessions of frontline health workers located in hospitals  on the use of injectable artesunate were undertaken in April and May 2014. The training module covered the recognition of severe malaria signs and symptoms, pre‐referral, and inpatient severe malaria management, including video presentations on artesunate use and practical demonstrations of artesunate dilution and administration. Trained health workers cascaded the training to other health workers within their respective counties. Since 2016, the severe malaria management training module has been part of the routine annual 3‐day case management trainings managed by the Division of National Malaria Programme (DNMP) . Since 2The Kenyan DNMP has undertaken bi‐annual national, cross‐sectional health facility surveys since 2010 to monitor the implementation of the outpatient ‘test and treat’ policy described in detail elsewhere , 26, 27.The health system readiness outcomes were measured at the health facility and health worker levels. The outcome at the health facility level included the availability of injectable antimalarials on the survey day. At the health worker level, the outcomes included exposure to training, guidelines, and their knowledge about the use of IM artesunate for pre‐referral management of suspected severe malaria in children among health workers who said they had ever referred a child with severe malaria. A composite outcome defined as their knowledge about the use of artesunate in children, the recommended route of administration as IM, and dosing of IM artesunate according to weight of the children <20 kg was also examined.Descriptive analysis measuring levels was performed at the health facility and health worker levels to assess the health system readiness to implement the pre‐referral severe malaria treatment policy. Analysis has been restricted to primary health facilities managed by the public sector. Hospitals were excluded as these constitute the secondary destinations for referral. Level estimates are calculated for each year the surveys were undertaken as proportions with corresponding 95% confidence intervals (CI). Overall differences in proportions were tested using chi‐square and differences over time using simple logistic regression with time (year) as the only independent variable. All analyses were conducted using Stata version 17 .p = 0.93). A third of the health workers had access to the revised 2016 malaria guidelines, and this increased across the years (p = 0.023). A total of 345 (22%) health workers reported that they had never referred a child with severe malaria  from dispensaries and health centres managed by the public sector were interviewed at 1,355 facilities (range 153–307 per year) (Table Only 625 (46%) facilities had injectable artesunate in stock on the day of the survey, far fewer  had injectable artemether, while quinine was available in 95 (7%) facilities Table . Overallp < 0.001), IM as the preferred route decreased , and the dosing recommendations did not vary since 2017  . Similarly, the levels were higher in health workers who had access to the current malaria guidelines (29%) than those without access to the guidelines (17%) (Table p < 0.001).The overall knowledge of the pre‐referral treatment policy measured by the composite outcome of artesunate knowledge, route of administration, and dosing was low at 21% among health workers who had ever referred a child with severe malaria Table . The oveper se is not always the panacea to improved health worker performance [To effectively support pre‐referral treatment of severe paediatric malaria at primary health facilities, recommended drugs should be in stock. During the present study of 1355 primary public health facilities surveyed between 2017 and 2021, nearly half had none of the nationally recommended IM preparations available on the day of the survey. Despite a national guideline recommendation for RAS , this waformance ,however,Significant improvements have been described in the management of uncomplicated malaria in Kenya since 2010, with decreasing stock‐outs of first line therapeutics and diagnostics and increasing testing rates and compliance with national standard treatment guidelines , 26, 27.The referral process is multifaceted and requires more than simple pharmaceutical intervention, broader integrated clinical management training is required to improve detection of danger signs , EmergenThe survey did not include direct observations of practices related to the management of severe, complicated malaria. These events are rare, and observational studies of health workers in these situations has ethical concerns. Nor was the survey designed to investigate health workers knowledge of broader IMCI/ETAT danger signs and their pre‐referral treatments  or advise given to caregivers. Further studies on patients, health service providers, and facility readiness are required to specifically address referral practices, from community to primary care to hospital gates and ward admission. These studies would provide a greater depth of knowledge to support improvements in the pre‐referral care of patients with complicated malaria.The readiness of health facilities and health workers to deliver appropriate pre‐referral care to children with complicated malaria in Kenya remains inadequate. Further investments are required to ensure the availability of nationally recommended pre‐referral antimalarials, appropriate training, supervision, and mentorship in their administration and routine quality of care monitoring.


Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field‐based measures of abundance, demographic performance, and forecasted stochastic population growth (λs). Predicted climatic suitability showed a J‐shaped relationship with A. utahensis abundance, where low‐abundance populations were associated with low‐to‐intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λs from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM‐predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb  Estimates of climatic environmental suitability for the presence of a species derived from ecological niche models (ENMs) have been proposed as predictors of the abundance and demographic performance of that species across the landscape, but simultaneous tests of suitability–abundance and suitability–demography relationships across a species' geographic distribution are rare. In this study, we examined relationships between ENM‐derived climatic suitability and both the abundance and multiple metrics of demographic performance of a perennial forb across its latitudinal distribution. We found J‐shaped relationships between suitability and both abundance and overall demographic performance as measured by stochastic population growth rate, suggesting that ENM predictions of climatic suitability are not reliable indicators. Improved insight regarding conditions that support higher abundance or demographic performance of species can in turn increase understanding of the factors constraining range limits and inform conservation efforts aimed at identifying sites capable of sustaining species of conservation concern , which describe the environmental niche of a species in order to predict where suitable environmental conditions for its presence occur across the landscape. ENMs make predictions based on correlations between spatially explicit records of a species' presence (or presence and absence) and the environmental conditions at the location of the record  to southeastern Idaho, USA  show higher mean annual temperatures in the center of the latitudinal range compared with its northern and southern edges and a gradient of high to low annual precipitation from the northern edge of the range to its southern edge . Of the 106 original presence records, 83 were retained post‐thinning. We built models using a dataset consisting of the 83 thinned presence records and 830 pseudoabsences  selected randomly from fishnet cells within the study area that had not contained a presence record removed during the thinning process. Although Lobo and Tognelli , temperature seasonality and precipitation seasonality , isothermality (bio3), and mean temperature of the coldest, wettest, and driest quarters .Data describing climatic conditions from 1970 to 2000 associated with each presence and pseudoabsence record were queried from the Worldclim 2.0 dataset at a 30 arc‐second (~1 km) resolution and used as explanatory variables in ENMs . We recorded the number of individuals in each quadrat belonging to each of three life stages: seedlings (plants with identifiable cotyledons that had germinated in the year of the survey), juveniles (plants that had neither cotyledons nor developing or flowering racemes), and reproductive adults . Censuses of plant density were conducted in central and northern edge populations in 2014 and 2016, and in southern edge populations in 2015 and 2016  of 30 juvenile and 40 reproductive plants  according to the formula for the area of an ellipse. While not itself a demographic parameter, size is positively correlated with survival, growth, and reproduction in A. utahensis  and (a) log‐transformed seedling density and log‐transformed overall plant density  in 2016 only, as this was the only year in which all populations were visited, (b) log‐transformed mean density of reproductive plants, juvenile plants, and the sum of these values across the two censuses conducted in each study site, and (c) mean plant size and (d) log‐transformed per capita seed production, which were only measured in all southern, central, and northern populations in 2015. Exponential terms were removed from models where they were not at least marginally significant. Log‐transformation of density and per capita seed production was used to normalize the right‐skewed distributions of each set of data.All statistical analyses were performed using R Statistical Software  cumulative germination over three years, (b) germination rates from an experimentally established seed bank, and (c) model‐derived estimates of λs in northern and central study populations. These tests allowed us to examine additional demographic transitions that might underlie suitability–abundance or suitability–demography relationships in central and northern populations and speculate about the transitions that may drive these relationships in southern populations. We used a linear regression to examine the relationship between log‐transformed mean overall plant density and λs in northern and central study populations.Using the expanded set of demographic data collected from 2013 to 2016 in central and northern edge populations (2014–2016 in the Swan population), we tested for significant linear and exponential relationships and between suitability and (a) log‐transformed per capita seed production, (b) basal rosette growth , (c) the size of surviving seedlings, and (d) annual survival across years. To do this, we used repeated‐measures generalized linear mixed models . Model sensitivity (accurate prediction of presences) was 0.93 (unweighted mean of component models: 0.88 ± SD 0.08), and specificity (accurate prediction of pseudoabsences) was 0.88 (unweighted mean of component models: s0.69 ± SD 0.11). The relative importance of all predictors included in the models, along with their relationships with ensemble model suitability predictions, are presented in Appendix The ensemble model was highly accurate .Neither the basal rosette area nor the log‐transformed per capita seed production of plants in southern, central, and northern populations in 2015 was correlated with suitability in those populations. When measured solely in central and northern edge populations from 2013 to 2016, per capita seed production, basal rosette growth, and the size of surviving seedlings were also not correlated with suitability Figure ; Table 2s Figure ; Table 24A. utahensis density or demographic performance. At low‐to‐intermediate suitability, A. utahensis density was uniformly low, but then increased with increasing suitability scores beyond a particular threshold value. While demographic rates in central and northern edge populations showed a variety of relationships to suitability ranging from nonexistent to linear to exponential, the relationship between suitability and overall demographic performance across the center‐north portion of the distribution was quite similar to that between suitability and abundance across the entire latitudinal distribution. These results suggest that A. utahensis abundance and performance are also only influenced by climatic suitability beyond some threshold.Across the entire latitudinal range, climatic suitability was not a strong predictor of 4.1A. utahensis' latitudinal distribution contrasts with the findings of several previous studies which have demonstrated positive suitability–abundance relationships across taxonomic groups . Predispersal seed predation and pollen limitation decrease the demographic performance (and presumably the density) of A. utahensis, but the extent to which this occurs is similar across populations experiencing varying climatic suitability , but are of relatively minor importance relative to other climatic conditions in other portions of the range. A second possibility is that the observed suitability–density relationship could simply be an artifact of sampling bias: occurrence records could be more numerous where populations are larger and denser, resulting in higher suitability scores for these more visible high‐abundance populations. If bias in the number of presence records only appeared beyond a particular threshold of density, suitability may only exhibit a positive correlation with density once that threshold is reached. A third explanation for the consistently low density of populations below a particular suitability threshold may be that abundance simply does not respond strongly to climatic variation until some threshold of climatic favorability is met, regardless of the conditions that define a favorable climate in a particular region.One potential explanation for the observed pattern is that the climatic conditions associated with the suitability of an area for the presence of A. utahensis density across the distribution than the latitudinal position of a study population. This may be because our ensemble model does not adequately describe the entirety of A. utahensis' climatic niche. The ensemble model's specificity value indicates an absence was predicted where a presence had been recorded in roughly twelve percent of cases, meaning that it may often underestimate suitability for this species. Furthermore, evidence of dispersal limitation in A. utahensis , much as the abundant center hypothesis predicts abundance to be tied to geographic centrality. Although we did not observe the linear relationship between a proxy for niche centrality (suitability) and abundance, the J‐shaped relationship between density and suitability was echoed by a strong correlation between density and the latitudinal position of study populations, with higher density in central than peripheral study sites characteristic of an abundant center distribution (K.C. Baer and J.L. Maron unpublished data). This suggests that estimates of suitability derived from our ensemble ENM  are no better a predictor of 4.2λs and the suitability of central and northern edge study populations appears attributable to a combination of similar relationships in cumulative recruitment and mean annual survival and a positive linear relationship between recruitment rates from the seed bank and suitability. We previously found that significant declines in λs between central and northern edge populations were primarily attributable to three demographic rates, of which germination rates from the seed bank and total seed production at the population scale were two  or beside an irrigation canal (Meadow Creek 1 & 2), which may have led these populations to perform better than predicted by large‐scale climatic conditions if the sites in which they occurred were less water‐limited than the surrounding landscape. According to the model's suitability threshold for presence of the species (0.203), the suitability of these areas was predicted to be too low for the presence of the species, so supplemental water availability may account for their existence and persistence.As with the suitability–density relationship, the nonlinear suitability–A. utahensis tends to grow in sites that support few other species, it is possible that superior competitors in northern edge populations pushed the plants into even less suitable microsites than they inhabit at either low or high suitability.The relatively poor demographic performance of populations with intermediate levels of predicted suitability (of which most were northern edge populations) may indicate that some aspect of the local environment unrelated to climate suppresses demographic performance to a level lower than might be anticipated if the suitability–demography relationship was linear. While λs and suitability–density relationships that we observed was due in large part to high demographic performance and density in two high suitability populations near the center of the distribution (Uinta and Bountiful). As with density, it may be that demographic performance is uniformly poor below a certain threshold of climatic suitability, but responds strongly to increasing suitability beyond this threshold. If Uinta and Bountiful populations existed in areas where climatic conditions exceeded this threshold, this may have allowed them to flourish and help explain the resulting patterns we observed between suitability and both density and overall demographic performance in A. utahensis.The shape of the suitability–5In this study, we found that projected climatic suitability displayed a J‐shaped relationship with the abundance of a species across its geographic range and a similar relationship with overall demographic performance as measured by stochastic population growth rate across the center to north portion of the range. A significant correlation between local density and population growth rate in central and northern edge study populations suggested that the relationship between suitability and population growth rate across the entire latitudinal distribution would be similar to that between suitability and density, meaning that demographic performance may only respond to increasing suitability beyond a threshold that is not known in advance. This implies that suitability is not a reliable metric for estimating either the abundance or demographic performance of a species across its geographic distribution.None declared.Kathryn C. Baer: Conceptualization ; data curation (lead); formal analysis (lead); funding acquisition ; investigation (lead); methodology (lead); project administration (lead); validation (lead); visualization (lead); writing–original draft (lead); writing–review and editing (lead). John L. Maron: Conceptualization ; formal analysis (supporting); funding acquisition ; methodology (supporting); visualization (supporting); writing‐original draft (supporting); writing‐review and editing (supporting).https://osf.io/5ga32/.This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at Supplementary MaterialClick here for additional data file.


Nutraceuticals could be used to increase immunity against viral infections and therefore more research should be done on them to better manage COVID‐19 and future pandemics We appreciate the letter provided by Dr. Pärnänen et al., in response to our article , and intestinal health and have triggered more investigation. They modulate immune responses in different diseases as reviewed previously (Ding et al., Whether polyphenols provide protection against COVID‐19 or any other infection should be confirmed by human intervention trials. Before these trials are designed, the effect of polyphenols on the oral cavity should be studied and a safety assessment of the applied dose should be performed (Lolayekar & Shanbhag, The authors declare no conflict of interest.


The burden of severe influenza virus infections is poorly known, for which surveillance of severe acute respiratory infection (SARI) is encouraged. Hospitalized SARI patients are however not always tested for influenza virus infection. Thus, to estimate the impact of influenza circulation we studied how influenza in primary care relates to intensive care unit (ICU) admissions using a modelling approach.We used time‐series regression modelling to estimate a) the number of SARI admissions to ICU associated with medically attended influenza infections in primary care; b) how this varies by season; and c) the time lag between SARI and influenza time series. We analysed weekly adult ICU admissions (registry data) and adult influenza incidence (primary care surveillance data) from July 2007 through June 2016.Depending on the year, 0% to 12% of annual SARI admissions were associated with influenza , up to 27% during influenza epidemics. The average optimal fitting lag was +1 week (SARI trend preceding influenza by 1 week), varying between seasons (−1 to +4) with most seasons showing positive lags.Up to 12% of yearly SARI admissions to adult ICU are associated with influenza, but with large year‐to‐year variation and higher during influenza epidemics. In most years, SARI increases earlier than medically attended influenza infections in the general population. SARI surveillance could thus complement influenza‐like illness surveillance by providing an indication of the season‐specific burden of severe influenza infections and potential early warning of influenza activity and severity. Admissions to intensive care for elective surgery or trauma were excluded, and we categorized all remaining admissions as medical admissions. We calculated the proportion of medical ICU admissions that were a SARI by dividing the number of weekly SARI by the weekly number of medical admissions. Information on influenza laboratory testing was not available in the NICE registry. ICU coverage increased during the study period from roughly 40% to near‐complete coverage of all Dutch adult ICUs in 2016.Hospital data on weekly admissions to the ICU were retrieved from the National Intensive Care Evaluation (NICE) registry, originally set up for monitoring quality of ICU care.2.2Medically attended ILI incidence data were retrieved from NIVEL Primary Care Database—sentinel general practitioner (GP) practices. This system covers approximately 0.8% of the Dutch population and is nationally representative for age, sex, regional distribution and population density.2.3NwSARI in week w  was used as outcome variable, while the weekly total number of medical ICU admissionsNwICU was included in the model as a denominator to adjust for the increasing number of ICUs participating in the NICE registry  a baseline model for possible underlying seasonal time trends  which we assumed to describe SARI admissions associated with other factors than influenza and b) an influenza model that describes the association between the weekly influenza numbers and the number of SARI admissions: The model forFirst, we selected the best fitting baseline model consisting of cyclical terms. For the cyclical trend, we evaluated sine and cosine terms with a periodicity of 1, 1/2, 1/3 and 1/4 years. The terms were always included in the model as a sine and cosine pair, thus allowing flexible phase shifts. This resulted in 16 different potential baseline models, always with an intercept, but with and without sine cosine pairs of varying periodicity (ranging from inclusion of zero up to four pairs):pwinfluenza is a bit more complicated, because the dominant influenza strain and severity outcomes  can vary from season to season.influenzaws as separate variables per season‐year into the model . Since we do not know whether SARI ICU admissions follow, coincide or precede the ILI trend, we also evaluated nine lagged values of ILI incidence per seasonILI influenzaw+jss , including maximally one lag per season. So, per season separately, we added influenza incidence to the baseline model: testing each of the nine ILI lags sj separately, that is added singularly to the baseline model (thus building nine models per season):The model with the lowest Akaike information criterion (AIC) was selected as baseline model. The model forWe repeated this influenza lag selection for each season and per season selected the influenza lag that showed the best fit (lowest AIC).All analyses were performed using the statistical package R (version 3.4.0). Model selection was performed in this manner, as R would not run all the possible different model fits at once as this produced too many combinations.We tested both positive and negative lags between influenza and SARI as the direction of this association is still poorly understood, with ICU admissions possibly being earlier.By multiplying the ILI regression coefficients with the observed weekly influenza incidence (lagged according to the season‐specific lags), we calculated the influenza‐associated proportions of SARI (per week). Further multiplying these weekly proportions by the weekly number of medical ICU admissions produced the estimated absolute numbers of weekly SARI associated with influenza. We then cumulated these weekly SARI numbers by season‐year. As the number of ICUs participating in the NICE registry increased over time these absolute numbers were not directly comparable between seasons. Therefore, we chose 2015 as the index year  and standardized all estimated numbers to the volume of medical ICU admissions observed in 2015.33.1P‐value < .0001), slightly higher than influenza preceding SARI  or after SARI . Correlations with ILI instead of influenza were similar.From July 2007 to June 2016, there were a total of 30 515 registered SARI admissions to ICUs with a weekly average of 65 admissions (standard deviation (SD) 28). To adjust for the increasing coverage of ICUs in the NICE registry, we also show the weekly number of SARI as a proportion  . Figure Using Dutch population size numbers of 2015 (as the associated numbers were standardized to year 2015), the absolute numbers translated to the following range of influenza‐associated SARI incidence rates per season‐year: 0/10 000 ‐ 0.39/10 000 (Table R2 .12 P = .78). Notably, the 2012/2013 and 2014/2015 seasons had an average coefficient size but high total number of influenza‐associated SARI while the 2009/2010 and 2010/2011 season had a high coefficient but an average number of influenza‐associated SARI.Seasons with higher model coefficients for influenza did not correspond with higher cumulated influenza‐associated SARI Figure  . However, the optimal lag varied largely from season to season from −1 to +4 weeks, almost always with positive lags (influenza lagging behind SARI)  of yearly SARI admissions to ICU are associated with medically attended influenza in the total adult Dutch population, probably reflecting the seasonal variation of circulating influenza strains. In most seasons, increases in ICU admissions occurred 1‐4 weeks earlier than increase of influenza incidence in primary care.Over the past 10 years, there has been a concerted effort by WHO and ECDC to fill the knowledge gap in our understanding of severe influenza complications requiring hospitalization.A strength of our study is that we used data from primary care ILI surveillance which is the gold standard for influenza surveillance in the Netherlands and most other Western European countries. Therefore, we assume the model to give the best possible estimate of adult SARI admissions to ICU that are associated with influenza circulation in the general adult population. However, we lacked data to differentiate between influenza cases caused by different types, sub‐types and lineages of circulating influenza viruses. Thus, our estimates provide an average effect in those seasons that multiple influenza viruses played an important role in influenza circulation. There appeared to be no clear association between numbers of influenza‐associated SARI and the dominant circulating influenza virus(es) Table . The assThis study is a population‐level  study comparing two trends. Although this is currently the best available approach due to a lack of structural laboratory testing of SARI patients for influenza virus, a pitfall in such time‐series analyses is finding associations that may be due to other underlying time trends. To counter this, in the model we included a seasonal baseline assuming that any associations between SARI and other seasonal aspects  are accounted for by this baseline. These cyclical terms compete with the influenza variable in the model, which also exhibits a roughly cyclical pattern and the cyclical terms could potentially over‐adjust, leading to an underestimation of the association of interest: between SARI and influenza. Despite this risk of underestimation, we assume the model more valid than when leaving out baseline seasonality because other respiratory pathogens that circulate in autumn and winter can cause severe respiratory symptoms too.Our data reflect that pressure on ICU is not only defined by the magnitude of the modelled coefficient (the number of SARI expected for every observed influenza) but by the combination with the cumulated incidence of influenza. This is reflected by the 2014/2015 season (with a long 20‐week influenza epidemic) which had an average association with influenza incidence but a high total number of influenza‐associated SARI , while the 2010/2011 season had a relatively high coefficient but a roughly average number of influenza‐associated SARI. This confirms that multiple measures are required to understand influenza severity and burden in secondary carelater than ILI in primary care, thus being a potentially early indicator for influenza virus activity. SARI surveillance could allow preventive measures and preparedness for increasing pressure on secondary care. This is similar to the finding from a pilot in three Dutch hospitals showing that SARI admissions to hospital (not only in ICU) peaks before ILI . Perhaps vulnerable individuals progress to severe illness more rapidly, or other epidemiological characteristics  may differ from those in the healthier general community. Whether the direction of the time shift is also informative of influenza severity is not clear as only one season in our data showed SARI in ICU lagging behind ILI . That was incidentally also the season with the highest influenza‐associated number and percentage of SARI . This might suggest that in the other years, when influenza burden on ICU was lower, ICU admittance may have been more accessible leading to earlier admissions and thus explaining the lead times of ICU over primary care. However, of the two seasons with coinciding ILI and SARI trends, one had high numbers (2014/2015) and the other had low numbers (2009/2010) of SARI associated with influenza.Population‐level data as used in this study can provide insight in the timing of trends of SARI admissions relative to medically attended influenza in primary care. While at an individual level a patient is not expected to be admitted to an ICU for an influenza‐associated SARI and thereafter to visit his family physician for ILI, at the population level, trends in severe illness do not necessarily follow trends in mild illness. Literature shedding light on the timing of these trends relative to each other is sparse but reports sometimes suggest that ICU admissions for SARI might actually provide an early indication of severe influenza cases.The NICE registry was set up for benchmarking and improving ICU quality. It provides a wealth of data that have potential for additional use. Our results show that it could have additional value for understanding the severity of influenza epidemics. On retrospective data, end‐of‐season estimates can be made as we have done in our current study. Would the data flow be transferred to a more real‐time system—which the registry is aiming to do—it could be used for prospective monitoring of SARI. This would complement the weekly ILI surveillance in primary care and help fill our current knowledge gap on severe influenza complications. Such knowledge is crucial for prevention and response and for estimating the burden and societal cost of influenza epidemics or a pandemic.L van Asten, AL Luna Pinzon, J. van de Kassteele, G. Donker, DW de Lange, and W. van der Hoek: None to declare. DA Dongelmans is the chairman of the National Intensive Care Evaluation (NICE) registry. NF de Keizer is a board member of the National Intensive Care Evaluation (NICE) registry. NF de Keizer is an employee of the department of medical informatics of the Amsterdam University Medical Center; this department is responsible for processing, maintaining and analysing data of the NICE registry.Liselotte van Asten: Conceptualization ; Formal analysis ; Investigation ; Methodology ; Writing‐original draft (lead). Angie Luna Pinzon: Data curation ; Formal analysis ; Investigation ; Methodology ; Writing‐review & editing . Jan van de Kassteele: Methodology ; Writing‐review & editing . Gé Donker: Writing‐review & editing . Dylan de Lange: Writing‐review & editing . Dave A. Dongelmans: Writing‐review & editing . Nicolette F. de Keizer: Writing‐review & editing . Wim van der Hoek: Conceptualization ; Writing‐review & editing .


Overall, both status and monetary downward comparisons activated regions associated with reward processing (striatum) while upward comparisons yielded loss‐related activity. These findings provide partial support for the common currency hypothesis in that downward and upward comparisons from both monetary and status domains resemble gains and losses, respectively. Furthermore, status upward and monetary downward comparisons revealed concordant orbitofrontal cortical activity, an area associated with evaluating the value of goals and decisions implicated in both lesion and empirical fMRI studies investigating social hierarchy. These findings may offer new insight into how people relate to individuals with higher social status and how these social comparisons deviate across monetary and social status domains.The ability to accurately infer one's place with respect to others is crucial for social interactions. Individuals tend to evaluate their own actions and outcomes by comparing themselves to others in either an upward or downward direction. We performed two fMRI meta‐analyses on monetary (  For both status and monetary domains, we expect to find more reward‐related brain activity  for downward comparisons, while upward comparisons will yield regions associated with losses . From our results, we aim to shed light on how social comparison engages similar brain regions across status and monetary domains.To overcome these limitations, we attempt to perform separate fMRI meta‐analyses on monetary and status social comparisons to determine the concordance of functional brain activation across studies and thereby re‐testing the common‐currency hypothesis. The separation of these types of social comparisons will allow us to test the common currency hypothesis for both monetary and status domains, independently. We will examine how upward and downward social status and monetary comparisons differ in functional neural activity, and how these comparisons overlap in the brain by performing additional contrast and conjunction analyses, respectively. We adopt the hypothesis put forth by Luo et al.  in that 2http://www.webofknowledge.com) on May 31st, 2018. These three searches yielded a total of 37 articles. Three articles were duplicated across the three searches, and the remaining 34 articles were screen for eligibility. An additional search in review articles yielded 10 more studies, totaling to 44 articles. Our exclusion criteria excluded contrasts that: (a) did not report foci in Talairach or Montreal Neurological Institute (MNI) standard stereotactic coordinate space, (b) did not use whole‐brain fMRI analysis, (c) did not report healthy human participants or (d) did not capture a comparison of social status. Both researchers reached agreement on which experiments meet the general and specific inclusion and exclusion criteria. In total, 26 studies were deemed eligible for inclusion.Two independent searches were performed for separate meta‐analyses on social status comparisons and monetary social comparisons. To compile studies measuring social status we performed several searches using the key terms: “social hierarchy” AND fMRI, schadenfreude AND fMRI, and “social comparison” AND fMRI into web of knowledge database . We used this meta‐analysis toolbox rather than the conventional method  in SDM was set at the default (20 mm) to control for false positives . Statistical maps were then thresholded at p = .0005 to control for family‐wise error rate.We performed co‐ordinate‐based meta‐analyses by using effect‐size Seed‐based d Mapping (ES‐SDM) software from the SDM project  of the combinations of studies, it is considered reliable .Test–retest reliability was assessed by performing jackknife sensitivity analysis; thresholded at 33.1Twenty‐three articles were compiled to create a stereotaxic map of social status comparisons. Ten articles reported foci on social status instructing participants to view and rate profiles of inferior or superior real or computer simulated players , regions associated with monetary losses . These meta‐analyses suggest that there are overlapping as well as distinct brain networks associated with social comparisons in monetary and social status domains. Our meta‐analysis results, however, should be interpreted with caution due to potential reverse inference. Future empirical research may directly compare social comparisons in different domains in the same study. Nevertheless, our findings and interpretations may inform current models on social comparisons in competitive social settings and improve our understanding of the neural mechanisms that are associated with these behaviors.


Electroencephalogram (EEG) microstates that represent quasi‐stable, global neuronal activity are considered as the building blocks of brain dynamics. Therefore, the analysis of microstate sequences is a promising approach to understand fast brain dynamics that underlie various mental processes. Recent studies suggest that EEG microstate sequences are non‐Markovian and nonstationary, highlighting the importance of the sequential flow of information between different brain states. These findings inspired us to model these sequences using Recurrent Neural Networks (RNNs) consisting of long‐short‐term‐memory (LSTM) units to capture the complex temporal dependencies. Using an LSTM‐based auto encoder framework and different encoding schemes, we modeled the microstate sequences at multiple time scales  aiming to capture stably recurring microstate patterns within and across subjects. We show that RNNs can learn underlying microstate patterns with high accuracy and that the microstate trajectories are subject invariant at shorter time scales (≤400 ms) and reproducible across sessions. Significant drop in the reconstruction accuracy was observed for longer sequence lengths of 2,000 ms. These findings indirectly corroborate earlier studies which indicated that EEG microstate sequences exhibit long‐range dependencies with finite memory content. Furthermore, we find that the latent representations learned by the RNNs are sensitive to external stimulation such as stress while the conventional univariate microstate measures  fail to capture such changes in brain dynamics. While RNNs cannot be configured to identify the specific discriminating patterns, they have the potential for learning the underlying temporal dynamics and are sensitive to sequence aberrations characterized by changes in metal processes. Empowered with the macroscopic understanding of the temporal dynamics that extends beyond short‐term interactions, RNNs offer a reliable alternative for exploring system level brain dynamics using EEG microstate sequences. These states are referred to as microstates and have been suggested to be the “building blocks of brain functions”  that are known to be a rich and flexible methodology to learn complex temporal dependencies without making any assumption on the temporal characteristics of the signal. Deep neural networks with a recurrent structure  have been used successfully to model various temporal sequences  to capture potentially existing long‐range dependencies. Specifically, we explore the temporal dynamics of the microstate sequences using an LSTM‐based AE neural network, that is, trained to reconstruct its input to the output, by first compressing the input into a latent‐space representation and then using this representation to reconstruct the output. Effectiveness of the proposed model in representing the complex dynamic structure is demonstrated through accurate reconstruction of microstate sequences. Further, we try to study the patterns learned by the RNNs by visualizing LSTM cells that react to specific patterns in microstate trajectories to gain intuition into the internal learning mechanisms and the patterns of EEG microstates that govern the temporal structure of microstates. We show that the model reacts to the changes in microstate sequences after stress induction and that it has the ability to categorize stress‐induced condition from baseline microstate sequences which further demonstrates the potential of the learned representations for applications such as classification and cross‐modality estimations. Finally, as RNNs have the sequence prediction capability, we attempted to forecast future states in the microstate sequence by combining the historical sequence information with the learned internal representation. Relatively low prediction accuracies beyond a few milliseconds corroborates the nonstationary nature of the resting state microstate sequences due to irregular structure of microstate durations.22.1Here, we used two datasets to assess the temporal structure of EEG microstates. The first dataset is from a study which employs EEG data with simultaneous Functional magnetic resonance imaging (fMRI) where we have access to the resting state recorded pre and post stress condition which is of interest to study its effect on temporal properties of EEG microstates. Furthermore, possible shortcomings of EEG artifact correction recorded inside magnetic resonance imaging (MRI) scanner were then controlled using the second dataset which is recorded outside MRI scanner.Dataset 1A: Data were obtained from simultaneous 3T EEG‐fMRI recordings of 12‐min eyes‐closed resting‐state of 34 healthy male volunteers (mean age 44.06 ± 9.96). EEG data were acquired using the BrainAmp MR system (Brain Products) with a 64‐channel Easycap augmented with six carbon‐wire‐loops . EEG and fMRI data were acquired with the same procedure as in Dataset 1A with the only difference that resting‐state data was recorded after subjects underwent a psychosocial stress paradigm. The stress paradigm was an adapted version of the ScanSTRESS task as described by  where after the baseline measurements subjects took either placebo or an herbal medicinal product (Neurexan) in a counterbalanced order. Participants who received placebo on the first day took Neurexan on the second day and vice versa. This article only reports results analyzed for the days on which placebo was taken. The data from five subjects in each resting state were excluded from the current analysis because of the problems with recording and/or the low quality of their available EEG data.Dataset 2 EEG data were obtained in a shielded cabin from 15‐min eyes‐closed resting‐state in 11 healthy male volunteers (mean age = 24.42 ± 3.05). EEG data were acquired using a BrainAmp (Brain Products) with 64‐channel actiCap. Two bipolar electrodes placed on the right and the left arm were used for ECG detection and two further bipolar electrodes with galvanic skin response‐module input were used for skin conductance measurements. FCz was used as reference electrode and AFz as ground electrode. The electrode PO10 was used for eye movement detection and was excluded from the further analysis. The sampling rate was 2,500 Hz, but data were down‐sampled to 1,000 Hz.2.2Datasets 1 and 2 respectively, and the trials containing muscle and head movement artifacts were removed from the dataset. Data segmentation was necessary to allow removal of the data containing muscle and head‐movement‐related artefacts. Because Dataset 1 contains MRI artefact, we aligned EEG segmentation to the repetition time of the simultaneous MRI scanner. Dataset 2 was recorded outside the scanner and therefore we were able to use a finer segmentation (here 1 s), that allows us to be more precise in the artefact removal and keep more data.Artifact rejection for EEG data was done in a semiautomatic process using custom MATLAB scripts. First, the raw EEG data was bandpass filtered between 0.3 and 200 Hz. Then, EEG was cleaned from MRI gradient artifacts by motion informed template subtraction technique . Artifact‐free EEG was band‐pass filtered between 1 and 40 Hz, down‐sampled to 250 Hz, and the peaks of the global field power (GFP) were determined after convolving the GFP time series with a Gaussian filter of 10 time‐points window length. We use GFP to assign the microstate labels as they are suggested to be the best representation of instantaneous EEG topographies . To further validate that the proposed LSTM networks are in fact learning the underlying patterns in EEG sequences, the experiments were repeated on two types of surrogate datasets. First, random sequences of microstates were generated where each state was independently sampled with equal probability of occurrence. Second, for a more realistic imitation, a sequence of microstates was modeled as a discrete autoregressive process  is considered as an exact match is not always possible due to the encoding process. To train a model for each subject, 70% of the data was used for training and the remaining were used as the test set. Then each set was further divided to overlapping segments of preset length and then randomly shuffled. We repeat this procedure for the intermediate representation as well. The performance of the models is measured using reconstruction accuracy which is defined as:We first analyzed the The mean reconstruction accuracies across all subjects are depicted in Figure Dataset 1) and outside (Dataset 2) scanner. We compare the accuracies of our RNN analysis between Dataset 1 and Dataset 2 (results presented in Appendix B) that are obtained from EEG data recorder inside and outside the MRI scanner and observe no significant difference. Additionally, we find no significant difference in the conventional metrics of microstate dynamics between the data recorded inside and outside the MRI scanner.The reconstruction accuracy shows high stability for shorter sequence lengths of 200–400 ms and as expected starts to decline for 800 ms and drops significantly for sequence length of 2,000 ms. Our preliminary ablation studies (Appendix D) also indicate that varying the number units or layers of the LSTM network does not improve the performance of the model significantly for longer sequences of 2000 ms. Given that this decrease in accuracy is evident for both encoding schemes used here, this could not be attributed to the capacity of RNN. Here, to control for possible confounding effect of MRI artefact on the results of RNN microstate analysis, we compare the dynamics of microstates that are based on EEG recorded inside , the accuracies for either intrasubject or intersubject reconstructions do not differ significantly from random auto‐correlated sequences. This observation suggests that memory effect in the microstate sequences decays rapidly beyond this duration.3.2Reconstruction accuracy for random sequences is significantly lower than real EEG sequences Figure . While t3.3Here, further analysis is done to test the extent to which microstate sequences are comparable across subjects. To do this, intersubject analysis is conducted where microstate sequences extracted from 80% of the subjects were used to train the RNNs and data from the remaining 20% of the subjects were used for testing the performance of the trained models with fivefold cross validation. Figure The higher reconstruction accuracy for intersubject as compared to intrasubject experiment can be attributed to the substantially greater number of training samples available to train the model. As microstate sequences from different subjects are pooled together, the large training sample enables the learning model to generalize better by capturing inherent variations more effectively.3.4RNNs, composed of a large number of individual cells combined in complex ways to solve challenging tasks, are still majorly black boxes. With proliferation of large‐scale neural networks, interpreting them has become one of the most challenging and active areas of research  to dark blue (positive), respectively. Although many LSTM cells were too complex for visual interpretation, we were able to find multiple interpretable cells that robustly identified high‐level patterns. Remarkably, some of these patterns correlated with transition dynamics of EEG microstates. For example, Figure For a more objective interpretation of these cells, we looked at how the activations were correlated with the temporal dynamics of the sequences. As a measure of state transition probability, average activation value for each transition (across a batch of sequences) for each cell Figure 3.5Several studies have shown that temporal dynamics of the EEG microstate sequences are altered due to disturbances of mental processes associated with neurological and psychiatric conditions. Specifically, statistics such as duration and occurrence of microstates would be affected in such conditions. More recently, variations in transition probabilities between microstates have also been associated with aberrant neural dynamics. In this section, we use the previous RNN model to see if trajectories of the microstates are different in the resting state data following an exposure to a psychosocial stress task compared to baseline resting state. The stress response to the psychosocial stress is induced using the ScanSTRESS paradigm , the test accuracy of the model trained on data with preceding stress is significantly (p < .023) lower when tested on the session with no preceding stress. Interestingly, this drop in the accuracy is only observed when we cross tested the two models trained on the longer sequence length of 800 ms. These results suggest that RNNs trained on EEG data following the stress condition have less ability to generalize to data with no preceding stress and thus, further substantiating the idea of suppressed brain states under stress conditions.To further illustrate the sensitivity of LSTMs to the trajectories of microstates, we conducted a cross‐conditional analysis. We tested the generalizability  patterns and hence be trackable. Previous studies on EEG microstate transitions has indeed shown that the matrix of transitions among microstates is nonrandom, asymmetric, and systematically affected in different neuropsychiatric disorders  and that the reconstruction accuracy of the model decreases gradually with increasing sequence lengths. In particular, our results suggest that for longer sequence lengths , the accuracies for either intra or intersubject reconstructions do not differ significantly from random auto‐correlated sequences. Interestingly, this approximation is in line with both  for each subject to predict the next 400 ms (for details see Appendix C). The results confirm our hypothesis and indicate that prediction accuracies are relatively low for forecast lengths beyond 40 ms. Interestingly, relevant LSTM literature  unit described in . LSTMs have a chain‐like structure, but the basic repeating unit has a special internal structure that supports long‐ or short‐term memory. Each unit is composed of a memory cell, which is responsible for “remembering” and a set of gates that regulate the flow of information through the chain. At a particular time step t and previous hidden state Ht − 1. Each unit maintains two states, cell state Ct and hidden state Ht that transfer information to the next unit. Additionally, each unit consists of input gate It, forget gate ft and output gate Ot that are responsible for adding, removing and filtering relevant information to the cell state respectively. The gates are composed of either sigmoid (σ) or tanh activation functions to optionally let information through. The detailed process of carrying information and memory forward is done using recursive process . While Xt represents the microstate at a particular time point, all others are internal parameters that are learned during the training of the network.Figure S2 Intra‐subject reconstruction (A) and prediction (B) accuracy for different lengths of microstate sequences. Graphs depict mean reconstruction and prediction accuracies across all subjects and error bars represent standard deviations. Dotted line indicates the chance prediction accuracy of 25% for four microstates. Differences between EEG data collected inside and outside the MRI scanner are statistically insignificant.Figure S3 Inter‐subject microstate sequence prediction accuracies for time scales ranging from 4 ms to 400 ms. As hypothesized, the prediction accuracy gradually decreases and stabilizes at approximately 40% for sequence lengths greater than 150 ms. EEG versus its intermediate representation versus surrogate data: For all different lengths of microstate sequences, the prediction (A) accuracies are higher for EEG sequences as compared to random and random auto‐correlated (AC) sequences, indicating the existence of underlying patterns predictable to certain extent. (B) indicates inter‐subject prediction accuracy for different lengths of microstate sequences of EEG in original representation (OR) and its intermediate representation (IR). Here, dotted line indicates the chance prediction accuracy of 25% for four microstates.Figure S4 Intra‐Subject reconstruction accuracies: (A) For different sequence lengths as a function of number of units in a single layered LSTM network (B) For sequence length of 2000 ms as a function of number of layers in the LSTM framework with different number of units in each layer. The trends above indicate that varying the number units or layers does not improve the performance of the model significantly for longer sequences of 2000 ms.Figure S5 Microstate duration distributions: (A) The durations of consecutive occurrences of Microstate A depicts irregular bursts (B) Histogram of durations for all the four microstates shows heavy‐tailed distribution suggesting long‐range dependence.Table S1. Reconstruction performance of  RNNS when trained and tested on different sessions with and without preceding stress condition. Reported p‐values are uncorrected. The experiment was repeated with two different sequence lengths of 100 and 200 which correspond to a sequence duration of 400 ms and 800 ms respectively.Click here for additional data file.


In the mid‐20th century, two Swedish biologists—Åke Franzén and Bjorn Afzelius—significantly advanced the study of sperm biology through the investigation of sperm ultrastructure using the newly developed electron microscope. Franzén studied sperm in some 200 (mostly marine) invertebrate species, linking sperm form and structure to the fertilization environment. Most notably, Franzén found that sperm of external fertilizers were relatively small and of the “primitive” type, while animals with internal sperm transfer tended to have more elongated and modified sperm morphologies Franzén , 1956b. Given the striking variation in sperm size and shape observed across the animal kingdom—the sperm cell is now recognized as the most diverse cell type known , John Fitzpatrick (Stockholm University), David Hosken (University of Exeter), Scott Pitnick (Syracuse University), Lukas Schärer (University of Basel), and Nina Wedell (University of Exeter)—this new venue was a resounding success. All the things that have made previous BoS meetings so successful were carried over to Sweden. With no concurrent sessions and presentations focused on unpublished and in‐progress research with 15 min allocated to discussion, the meeting provided the perfect environment for the cross‐fertilization of research ideas and discussion of emerging topics and methodologies. BoS15 also continued the tradition of inviting 2–3 speakers whose research offers new perspectives and approaches from other disciplines. An amazing scientific program, combined with a venue that allowed for discussion long into the night and a walk along the beautiful Nynäshamn coast, meant that BoS15 was the perfect blend of the old and the new.Kicking off the BoS15 scientific program, Tim Birkhead (University of Sheffield) transitioned the 80 BoS delegates from the Peak District of England to the Swedish coastal town of Nynäshamn with the greatest of ease with his opening plenary talk. By first acknowledging the contributions of Franzén and Afzelius to sperm biology, it was almost as if BoS was “back home again.” Birkhead then took us on a stroll down memory lane, reliving the highlights of BoS over the years and reminding attendees of why this meeting is just so good, and the reasons for why we all keep coming back. It has been said by many a BoS attendee, that this meeting is their favorite professional conference. The warm and welcoming environment, provided by the steering committee and attendees, makes this conference feel like a family “catch‐up,” not to mention the high‐quality research presented and thought‐provoking new ideas that keep the study of gamete biology moving forward in new directions. Once bitten by a BoS meeting, there is no turning back.SpermTree.org). Finally, Sara Calhim (University of Jyvaskyla) reminded us of how much more we have to learn about sperm variation and the benefit of studying “novel” animal groups by introducing to us the weird and wonderful world of tardigrade sperm. Sperm with no apparent mitochondria or floating mitochondria. Sperm with baton, spiral, or filamentous head shapes. Not to mention the morphological changes sperm undergo when they are inside the female versus in the male testis. Importantly, anyone can contribute to this work by sending samples of moss (the home to these little water bears) to Calhim. Check out how to do that here: https://tinyurl.com/sendusyourmoss.The 15th BoS meeting merged the old and the new in more ways than one. Following in the footsteps of Frankén and Afzelius, several talks focused on explaining the causes and consequences of sperm variation. Kristin Hook (University of Maryland) combined electron microscopy with computer‐assisted‐sperm‐analysis methods to unravel the functional significance of complex sperm morphology and sperm aggregate behavior, as well as the role female promiscuity plays in the evolution of these traits. Using modern phylogenetic and evolutionary analysis methods, Ariel Kahrl (Stockholm University) shed new light on the role of the fertilisation environment for the evolution of sperm size. Compiling data on more than 3,000 animal species, this work linked evolutionary transitions in fertilisation environment to shifts in both sperm size and the rate of sperm evolution, providing compelling evidence for the evolution of longer sperm, and a higher rate of evolutionary change in sperm size in internally fertilizing taxa compared with those with external fertilisation. Exemplifying the community nature of these BoS meeting, Kahrl et al plan to make this resource publicly available in the future . Extavour presented an incredible collection of data on egg size and shape variation in insects, where egg volume ranges across eight orders of magnitude, and demonstrated the link between the evolution of egg morphological diversity and ecology , created a vibrant discussion about postmating immune responses. Ahmed‐Braimah demonstrated that mating triggers immune responses in the female reproductive tract, with ejaculates from heterospecific males mounting a greater immune response than conspecific ejaculates.Since the early days of the BoS meetings, researchers have understood the need to better integrate female‐mediated processes into the study of sperm biology and sperm competition  showed us that male–female interactions in the cabbage white butterfly can be a veritable “battle of the sexes.” In this system, males deposit a large spermatophore, which consists of a virtually indestructible hard outer shell with a soft nutritious inner shell surrounding a ball of sperm, in the female reproductive tract (bursa copulatrix). The spermatophore's nutritious inner shell acts as a nuptial gift. However, because the female cannot mate when the bursa copulatrix is filled and it takes 3 days for the female to break down the hard outer shell of the spermatophore, the spermatophore functions to prevent female remating. To combat this, female butterflies produce proteases in the bursa copulatrix which help to chemically digest the spermatophore and, even more impressively, the bursa copulatrix contains an organ called the signum, “a tooth‐like structure” which mechanically chews through the spermatophore's outer shell. To top it off, Clark demonstrated that both the female proteases and male spermatophore proteins are rapidly evolving. Altogether, this was an amazing story of sexual conflict and cooperation.Male–female interactions are also critical in external fertilizers. Neil Gemmell (University of Otago) highlighted the importance of female–male interactions as the ovarian fluid, surrounding the unfertilized ova, contains proteins that can speed up or slow down the sperm from “hooknose” male chinook salmon. Similarly, using a broadcast spawner, the blue mussel, Jon Evans  showed that female derived water surrounding the eggs, can also hinder or enhance the sperm function. Egg water acts as a chemoattract to guide sperm, but also acts to select against extreme combinations of sperm length and sperm swimming speed.Drosophila seminal fluid and the idea of copulation complementation. It seems that Drosophila males exploit seminal fluid sex‐peptides produced by rival males, with the second male to mate effectively “rescuing” the first male's fertility. Stefan Lüpold (University of Zurich) moved the conversation forward again by elegantly demonstrating the complexities of male–male–female interactions and highlighting the multivariate nature of selection on sperm form and function.Sperm function and performance can also be influenced by seminal fluid, setting the stage for complex male–male interactions within the female reproductive tract. This was beautifully demonstrated by Mariana Wolfner (Cornell University), who intrigued us with her research on The environment also impacts reproduction, and several talks on the final afternoon focused on the consequences of changes in the thermal environment for gamete biology and fertility or the impact of social environment on reproductive plasticity. Ramakrishnan Vasudeva (University of East Anglia) showed that temperature increases through adult development resulted in males producing shorter sperm and females producing larger eggs. Moreover, Vasudeva found that this gamete plasticity is adaptive, with pairs showing greater reproductive performance when males and females were exposed to matching thermal conditions. Next up, Benjamin Walsh (University of Liverpool) introduced the concept of “thermal fertility limits”  and the role of female body condition on cryptic female choice via ovarian fluid in wrasse . Finally, several of this year's posters highlighted research on postmating prezygotic reproductive barriers in a range of invertebrate systems, including butterflies , Drosophila , and beetles .As in previous years, the poster sessions were a critical component of BoS15. Kicking of each of the two posters sessions, presenters “advertised” their posters with a 1‐min research pitch that infused a generous dose of fun into the sessions, and John Fitzpatrick was poised nearby with the timer to catch out anyone who went over the 1‐min mark. The posters showcased a diversity of high‐quality research covering a broad range of topics, including cognitive mechanisms of sperm allocation in junglefowl , environmental effects on sperm gene expression , and sperm adaptation to microbes . The female side of reproduction was also well‐represented, with posters covering topics such as female reproductive tract protein evolution in https://www.su.se/zoologi/english/research/conferences/welcome‐to‐bos). Though BoS meetings are typically small, with just 60–80 delegates, new attendees are always welcome and encouraged to inject new ideas and enthusiasm for the study of sperm biology. So mark down the dates for the 16th BoS meeting in your calendar now.Alas, after three and a half days of cutting‐edge science and rousing discussion, our meeting was over, and a merry group of gamete biologists farewelled each other and commenced their journey home. We are already looking forward to the next meeting, which will again be held in Nynäshamn on September 6–10th, 2021 (The authors declare that there are no conflict of interests.


A public health collaboration between medical professionals and Japan's professional football league for rubella awareness. To the Editor,Japan experienced a nationwide outbreak of rubella between 2012 and 2013, resulting in 17 000 cases of rubella and 45 cases of congenital rubella syndrome.However, as of 30 September 2019, the use of free rubella antibody testing remained quite low at less than 13%.We believe that antibody testing by medical professionals on the sidelines of sports events may be a useful strategy to access at‐risk populations who have little public health knowledge of rubella or ready access to antibody testing. We look forward to sharing a full report of this important public health intervention when the data become available.This event was funded by LINK‐J SCOOP 2019 and ANA Wonder FLY.Author TN was supported by research funding by LINK‐J SCOOP 2019 (200 thousand yen) and ANA Wonder FLY (372 thousand yen).


Direct electrical stimulation (DES) at 50 Hz is used as a gold standard to map cognitive functions but little is known about its ability to map large‐scale networks and specific subnetwork. In the present study, we aim to propose a new methodological approach to evaluate the specific hypothesis suggesting that language errors/dysfunction induced by DES are the result of large‐scale network modification rather than of a single cortical region, which explains that similar language symptoms may be observed after stimulation of different cortical regions belonging to this network. We retrospectively examined 29 patients suffering from focal drug‐resistant epilepsy who benefitted from stereo‐electroencephalographic (SEEG) exploration and exhibited language symptoms during a naming task following 50 Hz DES. We assessed the large‐scale language network correlated with behavioral DES‐induced responses (naming errors) by quantifying DES‐induced changes in high frequency activity  outside the stimulated cortical region. We developed a probabilistic approach to report the spatial pattern of HFA modulations during DES‐induced language errors. Similarly, we mapped the pattern of after‐discharges (3–35 Hz) occurring after DES. HFA modulations concurrent to language symptoms revealed a brain network similar to our current knowledge of language gathered from standard brain mapping. In addition, specific subnetworks could be identified within the global language network, related to different language processes, generally described in relation to the classical language regions. Spatial patterns of after‐discharges were similar to HFA induced during DES. Our results suggest that this new methodological DES‐HFA mapping is a relevant approach to map functional networks during SEEG explorations, which would allow to shift from “local” to “network” perspectives. We adopted a new probabilistic brain mapping approach based on direct cortical stimulation and high frequency activity measures during naming task. Our results suggest that this new methodological direct electrical stimulation‐high frequency activity mapping is a relevant approach to map functional networks during stereo‐electroencephalographic explorations, which would allow to shift from “local” to “network” perspectives. The significance of these differences was evaluated in relation to the variability of fluctuations within each time segment. The data features we compared were the fluctuations in HFA (70–150 Hz), shown to be a potential specific biological support of cognitive function  induced by 50 Hz DES during language disturbances. The method is largely inspired by the one already developed by our group to map ictal HFAs  who carried out standard presurgical evaluations and experienced language symptoms elicited by DES Table .2.2www.fil.ion.ucl.ac.uk/spm). Visual inspection of the contact locations was also used to check whether each electrode contact was located in gray or white matter. Furthermore, to be able to perform group analysis, we used regions of interest (ROIs) in the automated anatomical labeling (AAL) parcellation system . Electrodes implantation was strictly related with individual clinical hypothesis. A preoperative MRI and postoperative MRI or CT scan were co‐registered to assess the locations of the electrode contacts for each patient using a coordinate system in relation to the anterior commissure/posterior commissure plane. Electrode contact positions were finally expressed in the Montreal Neurological Institute (MNI) coordinate system to allow group analyses after brain spatial normalization using Statistical Parametric Mapping 12 software  that allowed to simultaneously record up to 256 monopolar contacts, so that a large range of mesial and cortical areas, as well as fissural cortices, was sampled for each patient. Sampling rate was 512 Hz, with an acquisition band‐pass filter between 0.1 and 200 Hz. Data were acquired using a referential montage with reference electrode chosen in the white matter. All other recording sites were chosen in the gray matter. For data analysis, we used a bipolar montage between adjacent contacts of the same electrode to improve sensitivity to local current generators. Coordinates of virtual bipolar contacts that were used to construct images (see below) were chosen to be at an equal distance of two successive contacts.2.4Stimulations at 50 Hz were applied between two contiguous contacts at different levels along the axis of each electrode, chosen to be in the gray matter according to visual inspection of spontaneous SEEG signals. A bipolar montage was used to help eliminate the signal common to adjacent electrode contacts and to avoid artifacts coming from distant sources. Bipolar stimuli were delivered using a repetitive biphasic square wave electric currents of 1–3 ms pulse width designed for a safe diagnostic stimulation of the human brain (Micromed), according to parameters proved to produce no structural damage. The intensity used was usually 3 mA or less (down to 1 mA), for a maximum duration of 5 s, or less depending on the type of the induced clinical response.2.5Patients were required, in others, to overtly perform a picture‐naming task in black and white drawing images representing objects from several semantic categories  classify the language error (see above), allowing several errors to occur in the same trial and (b) add events to each SEEG files that will be used in further processing of SEEG data (see below). The events aimed at quoting Figure :The star2.7.2The processing of single SEEG trials was derived from the procedure we developed to map epileptogenicity, that is, fast oscillatory activity at seizure onset  up to the termination of the after‐discharge.For mapping after‐discharges, similar analyses as for DES‐induced HFA were performed but the frequency band was set to 3–45 Hz, and the period of interest was set from the end of the stimulation period (t‐test) was directly obtained by the family‐wise error‐corrected associated p‐values. By applying a threshold on this p‐value (.05 corrected for multiple comparison), it was possible to determine the regions showing significant fast discharges concomitantly to the language symptoms during DES, for each trial.Knowing SEEG electrode positions in a standardized coordinate system (MNI coordinates) and SEEG power values for each electrode, it is possible to create images of SEEG power by local spatial interpolation  and nonactive (0) parcels was produced for each event. For this study, we used the AAL scheme  and 0 (ROI found to never show any significant symptom‐related increase of HFA power when recorded). We called those maps “HFA maps.”n divided by the number of times ROI n was stimulated). We call those maps “DES maps.” For display purposes, those HFA and DES maps are shown in figures on a canonical inflated brain.A similar methodology was applied in order to produce maps of the probability to induce a particular symptom with DES for each ROI  and 0 . This ROI‐based analysis was duplicated to map the propagation of after‐discharges.Finally, we used HFA maps to evaluate probabilistic functional cooccurrence of HFA elicited during naming symptoms on a language network composed of five ROIs. These five ROIs were significantly stimulated and recorded in our dataset: inferior frontal gyrus at the pars 33.1Visual analysis of DES responses as illustrated in Figure 3.2Figure 3.3To quantify the involvement of an ROI during naming errors we first reported the probability to observe a naming error, when stimulating the ROI Table . This pr3.4t test) between: before and during induced DES naming errors  showed in relation with this ROI were observed in six left lateralized frontal regions . Stimulation of the left inferior frontal gyrus at the pars triangularis ROI also induced HFA modification in a fronto‐parieto‐temporal network, but with a more restricted number of brain regions compared with the pars opercularis ROI. Indeed, strongest probabilities  were showed in five left cortical regions . Stimulation of the left insula ROI showed HFA modification in an extended bilateral fronto‐parieto‐temporal network, in which the strongest probabilities (p = 1) were observed in left and right frontal . The middle temporal gyrus ROI was related to response patterns in fronto‐parieto‐temporal network and the strongest probability (p = 1) is only observed in this same region. Finally, stimulation of the superior temporal gyrus ROI showed HFA modification in an extended bilateral fronto‐parieto‐temporal network, in which strongest probabilities were observed in eight regions including left and right frontal  and left temporal  regions.We showed that stimulation of the left inferior frontal gyrus at the pars opercularis ROI was related with HFA modification in a large left fronto‐parieto‐temporal network , in agreement with the left hemisphere specialization for language processing , and the less prevalent was SP Table . In lineThe common network observed in the present study during DES for the three types of language symptoms could be explained by the low rate of PP and SP types of errors , similarly to previous DES findings  and lateral temporal cortices; SP errors were observed during DES performed on insula and lateral temporal cortices  is related with an extended left lateralized network including cortical regions identified as related with the three of the four linguistic processing involved on naming. Specifically, coactivated regions including medial temporal cortices and the temporal pole , phonological representations  and motor, premotor and inferior frontal regions (motor planning and speech articulation). A recent study revisiting the brain subnetwork involved during naming process identified the inferior frontal gyrus (pars opercularis) as core region on the phonological, syntactic and cognitive control hub supported by the extended anatomical connectivity with frontal, temporal and prefrontal regions  was found. The ACC/msFC which is known to be a key region of the cingulo‐opercular network, which is one of the two top‐down (control) networks in human and is specifically involved in set maintenance and in monitoring (making choices) in accordance with the task goal [see Dosenbach, Fair, Cohen, Schlaggar, & Petersen, p = 1) for lateral temporal regions. Others regions with less probability were observed in the medial temporal cortex , lateral and medial parietal cortex . This result suggests a semantic subnetwork . Although this cohort is large for an SEEG study, SEEG anatomical implantation is different between patients, as they depend on clinical assumptions. This implies that a larger number of patients would have been needed to be able to have a good anatomical coverage of the full‐language network. The limited number of patients included in the study prompted us to conduct an analysis in terms of ROIs. This ROI analysis is also a major limitation of our study because we decreased the inherent anatomical precision of SEEG. Another limitation of the present study is related to the more important left hemisphere sampling, including 1,481 sites on the left and 599 sites in the right hemisphere. This suggests that even if the majority of the included patients (28/29) presented a left hemisphere specialization for language, the results related to the hemispheric involvement during naming should be taken with caution due to the sampling bias in favor of the left hemisphere. Finally, to have better insight into the specificity of induced fast oscillations for language function, it would have been extremely relevant to contrast the responses to the same stimulated sites with versus without induced symptoms. However, asymptomatic electrophysiological DES data was not available in our clinical setup and we could not proceed to this type of analysis.One major limitation of the present study is the limited number of patients included  unveil brain regions connected to the stimulated site with a better specificity than other frequency band. These results may open a new window onto the assessment of functional connectivity as a reflect of functional integrity of a cognitive subnetworks in a clinical context.The authors declare no conflicts of interest.Patients provided written informed consent to participate in the study, which was approved by the local ethics committee.AppendixS1 Supporting InformationClick here for additional data file.


It is well appreciated that traditional analgesic delivery routes used to treat pain associated with temporomandibular disorder (TMD) often have harmful unintended side effects as a consequence of systemic distribution. Further, localized delivery of analgesic medication via intra‐articular injections involves a different set of issues limiting their clinical viability. As an option, transdermal analgesic delivery provides for prolonged pain relief and flexibility in dose administration, while limiting systemic exposure and minimizing adverse events. Incorporation of a novel electroporation technique may further increase transdermal drug penetration into synovial tissue/fluid and enhance pain reduction. The present feasibility study compares the effectiveness of an electroporation‐enhanced transdermal application of diclofenac sodium to a conventional intra‐articular injection of triamcinolone acetonide suspension (corticosteroids) to treat patients with TMD associated pain.Pre‐ and post‐treatment maximal incisal mouth opening (MIO), pain visual analog scale (VAS) and surface electromyography (EMG) of 22 patients treated with electroporation‐enhanced diclofenac and 37 patients treated with corticosteroids injections were collected and analyzed.p‐value = .01) compared to the standard treatment, but both methods were similarly effective for improvement of MIO  and improvement of all EMG indices .In general, patients treated with electroporation exhibited better results in terms of pain improvement (corrected The enhancing effect of electroporation in transdermal delivery of diclofenac sodium was demonstrated by decreased pain, increase MIO and EMG improvement to normal values. Its analgesic and inflammatory results are comparable with standard treatment offered by corticosteroids. Additionally, NLC/TDD offers controlled and continuous administration of the drugs, which is particularly useful in drugs with short biological half‐lives  administration in relieving TMD related pain and improving jaw joint function.2This study followed the ethical principles of Declaration of Helsinki guideline and all patients were given a thorough explanation regarding the procedures. After answering all their questions, patients signed a written consent form. The protocol was approved by the ethical committees from each of the two units (IRB012019 MQ03AL01 and UCSFIRB 241418).SD 13.2 years) who were treated with two electroporation‐enhanced  who received a one‐time intra‐articular injection of triamcinolone acetonide injectable suspension at the Oral and Maxillofacial Surgery Department at the San Francisco Veterans Health Care System in San Francisco, California, from January 1, 2019 to the end of June 2019 .Inclusion criteria:A painful joint(s) during mastication  in which 1 (no pain) and 10 (the greatest possible pain).Limitation during opening  or during left and right excursion or protrusion <7 mm.Additional inclusion criteria:If patients had received any TMJ treatment in previous the 6 months.If the patients have an existing allergy, sensitivity, cross‐function or contraindications with the experimental drug.Exclusion criteria:2.1The pre and post treatment assessment of patients was made by a clinician blinded to the actual treatment modality. Patient's clinical history was collected according to the Research Diagnostic Criteria for TMD  for inter‐group differences of described study design was calculated using GPower software (version 3.1.9.4) and reached 56%. Moreover, the calculated effect size resulted in 0.49 for Mann–Whitney U test and 0.24 for Wilcoxon signed‐rank test.All patient's data were assessed quantitatively in IBM SPSS Statistics 25 software. Nonparametric Wilcoxon signed‐rank test was used to compare the initial and final MIO and VAS scores of each patient, and pre‐ and post‐treatment EMG data. Student 3p‐value < .05) in sex and age distribution from a statistical point of view. Patients treated with electroporation enhanced diclofenac were significantly younger (mean age 36.5 years) compared to patients who received a one‐time intra‐articular injection of triamcinolone acetonide injectable suspension (mean age of 53.7 years). Two groups of patients without significant differences in the initial MIO, VAS and EMG scores were compared . Table Twenty‐two and thirty‐seven patients were finally recruited because there was a lack of patients fulfilling inclusion criteria and several patients did not consent. The two groups were composed of Caucasian patients in order to be considered homogenous in terms of ethnicity (the only ethnicity available from the two study locations). The groups significantly differed . Similar result of pain decrease was observed in the comparator group of patients treated with the conventional care (corticosteroids injections) , however, the improvement in MIO was not significant  in electroporation group and 2.16 VAS score points (SD 1.58) in the comparator group. The mean improvement in MIO was 5.55 mm (SD 6.45) in electroporation group and 2.19 mm (SD 6.79) in the comparator group  and millimeters (for MIO) between two patient groups. The mean improvement in VAS score reached 4.64 VAS points (All patients treated with electroporation enhanced diclofenac delivery reported a decrease in pain and 95% (21/22) of those patients showed also improvement in MIO. One patient showed lower MIO after the treatment. In the comparator group, 86% of patients (32/37) reported a decrease in pain, 10% (4/37) of patients reported the same pain and 1 patient (3.7%) reported increased pain. Similarly, 68% of patients (25/37) showed improvement in the MIO after the treatment, 24% showed (9/37) decreased mouth opening and 8% of patients (3/37) did not show any improvement.p‐values > .05). In the comparator group treated with corticosteroids, the improvement was observed in all variables. The statistically significant improvement was detected in a bilateral symmetry coefficient for temporalis muscles  ‐ indices ranged in normal values after the treatment. The significant improvement was also found in Torque coefficient, coefficient  however, both pre‐ and post‐ mean values of TORS ranged in normal values over 80%. In terms of improvement, the actual pre‐ and post‐treatment EMG score differences were compared between two patient groups for each observed index. Overall, no significant differences were found in the overall improvements of all indexes ; cell fusion; gene therapy and DNA vaccination; and for general TDD  muscle sides. Value 80% is considered as normal function of the masseter and temporal muscles with standardized muscular symmetry  in larger multi‐centric studies. This fundamental step is essential in order to better establish the procedure limitations as an adjuvant tool in the non‐invasive therapy of our patients.In the future, all possible variables should be controlled and the influence of age, sex, ethnicity, menstrual cycle or severity of disease should be studied. Side effects of single and repeated application of electroporation to TMJ must be described. Our preliminary data showed the potential of electroporation in the treatment of TMJ diseases and further investigations on this procedure are being planned. Similarly, the study described effects of electroporation‐enhanced diclofenac 1 week after two applications. In the described feasibility study no side effects were observed. Future 6 months recall appointments were planned for patient to evaluate its long‐lasting effects. Future studies of repeated application of electroporation must be also performed to assess safety of such approach and its possible advantages/disadvantages compared to a control group using placebo in order to better define the effect of drug electroporation per se and prognostic time set in TMD arthralgia patients. This is a feasibility study designed to reduce the economical and biological cost and at the same time enlist the highest number of patients looking for a clinical solution in a defined time frame. The lack of a control group, and significant differences in age and sex of patients are the weakness of this protocol and further investigations in this direction are being planned because the feasibility approach was encouraging. This age difference might be caused mainly due to the experimental nature of diclofenac electroporation application, as older patients preferred not to undergo it. On the other hand, this is the first description, to our knowledge, regarding the application of this technique in dentistry and a cautious approach on the study design was planned to reduce the risk of patients' treatment failure.5Acute arthralgia is a well‐identified disease in the taxonomy of TMD problems with very good prognosis with early diagnosis and treatment. TDD is one of the treatment options with two advantages. In the foreground, it is fast and secondly, it is economic, and thus it allows us to help the patients more efficiently. With the limitation of this study, TDD demonstrated to be a useful tool compared to standard intraarticular injection for its non‐invasiveness and minimal discomfort. Further clinical trials are indicated to better define the clinical technique and applications along a broader cohort of TMD patients.All authors have no conflict of interest.