N=142; sampled at two time points) is associated with a long-lasting shift in microbiota composition and metabolism. The shift includes depletion of Actinobacteria, increase in Bacteroidetes and Proteobacteria, decrease in bile-salt hydrolase and increase in macrolide resistance. Furthermore, macrolide use in early life is associated with increased risk of asthma and predisposes to antibiotic-associated weight gain. Overweight and asthmatic children have distinct microbiota compositions. Penicillins leave a weaker mark on the microbiota than macrolides. Our results support the idea that, without compromising clinical practice, the impact on the intestinal microbiota should be considered when prescribing antibiotics.Early-life antibiotic use is associated with increased risk for metabolic and immunological diseases, and mouse studies indicate a causal role of the disrupted microbiome. However, little is known about the impacts of antibiotics on the developing microbiome of children. Here we use phylogenetics, metagenomics and individual antibiotic purchase records to show that macrolide use in 2–7 year-old Finnish children ( The impact of antibiotics on the microbiome and health of children is poorly understood. Here, Korpela et al. study the gut microbiome of 142 children and show that the use of macrolides, but not penicillins, is associated with long-lasting shifts in microbiota composition and increased risk of asthma and overweight. Antibiotics are the most commonly used drugs in the pediatric populations of western countries14589101315We show that antibiotic use in childhood is associated with marked changes in the intestinal microbiota composition, which persist for over 6 months. Macrolides, particularly, appear to modify the microbiota and their functions, being the strongest driver of inter-individual differences in microbiota composition in our cohort. Among the children who received macrolides in early life, we find a positive correlation between overall lifetime antibiotic use and body mass index (BMI), as well as an increased risk of asthma, suggesting that macrolide use may alter the microbiota in infants in a way that predisposes to antibiotic-associated weight gain and asthma in later childhood.Our cohort consists of 236 Finnish children aged 2–7 years (median age 5 years), attending day care at the time of the study. A total of 257 fecal samples were obtained from 142 children  who donaBifidobacterium as the dominant genus, was reduced in this group, in many cases to below detectability, and the abundances of the Gram-negative phyla Bacteroidetes and Proteobacteria were increased. These changes were largely resolved in the M12 and M24 groups, indicating that the phylum-level balance of the microbiota recovered within 1 year after a macrolide course. The penicillin-user groups  did not have a distinctly different phyla composition. The genus-level principal coordinates analysis (PCoA) indicated that the main driver determining the overall microbiota composition was macrolide use: most of the M6 samples clustered together with low scores on component 1, whereas the rest of the samples showed less clear patterns , indicating that the beta diversity among these samples was associated with recovery from the most recent macrolide course. Penicillin use was not strongly associated with the principal components. The same patterns were evident in both the 2–4- and 5–7-year-old children, indicating that the dominant effect of macrolide exposure on the microbiota was not age-dependent. Furthermore, the pattern was evident regardless of previous antibiotic exposure background. We thus conclude that macrolides appear to set the microbiota to a certain state, regardless of the baseline composition.Although the indications for penicillin and macrolide courses were the same—both were prescribed mainly for respiratory infections—macrolide use specifically was associated with a clear shift in the microbiota composition . The gropatterns . The timAntibiotic use, and macrolide use in particular, was associated with a long-term reduction in microbial richness, which did not reach the level of the control samples even 12–24 months after the course . The agez-score and health , 18 of the 48 genera and 7 of the 14 orders that were detected in >30% of the samples were significantly associated with recent antibiotic use, that is, were significantly different in the groups M6 or P6 as compared with the control group (Eggerthella) and three decreased 4–10-fold  in the group M6. Of these, Collinsella was significantly reduced in all groups compared with the control group, suggesting that this genus is strongly affected by antibiotics. Among the Bacteroidetes, Bacteroides was twofold elevated in the group M6 and Parabacteroides in the groups M6, M12, P6 and P24. Among the other Gram-negative bacteria, a twofold increase in Proteobacteria in the group M6 was notable, but apparently distributed among several genera with a member of Enterobacteriaceae as the most significantly affected . Among the Firmicutes, bacteria from the order Gemellales were significantly and consistently reduced in the penicillin-user groups. The order Lactobacillales was increased in all macrolide user groups. This was largely owing to an increase in Streptococcus, whereas Lactobacillus was decreased. Lactobacillus was also decreased in the groups P6 and P12. Erysipelotrichales as an order, and its member genus Eubacterium, were elevated in the group M6. An unassigned member of Clostridiales, a member related to Christensenella, and Anaerostipes were reduced in the group M6, whereas the genera Clostridium and Dorea were increased.After controlling for age, BMI ol group . Four ofP<0.001 in a generalized linear model). Hence, after controlling for recent antibiotic use, the cumulative lifetime use had a minimal association with the microbiota composition. Four genera, all in the order Clostridiales, were significantly positively associated with total lifetime macrolide use . Megamonas was also positively associated with lifetime penicillin use (P=0.003). Microbial richness was not associated with lifetime antibiotic use after controlling for the most recent antibiotic course.In addition to stratifying the children by the most recent antibiotic course, we investigated the possibility of cumulative effects of lifetime antibiotic exposure (number of antibiotic courses per year of life). Recent antibiotic use correlated with lifetime use: all antibiotic user groups had higher lifetime use than the control group, as the control group was selected partly based on low lifetime antibiotic use . There was a clear positive correlation between qPCR-measured abundance of bsh genes and time since the last macrolide course  compared with the non-exposed (N=116) was 6.11 . We also observed a strong correlation between total lifetime antibiotic use and the BMI z-score in the children with >2 macrolide courses before the age of 2 years  and overweight (N=9) children with those of matched healthy and normal-weight controls. The asthmatic cases were distinguished from the healthy controls by a set of three bacterial genera with significantly different abundances: Blautia, Rothia and Coprobacillus (Clostridium (Erysipelotrichaceae), Clostridium (Clostridiaceae), Akkermansia and Enterococcus . When antibiotics are used annually or more frequently, the microbiota may not have time to recover and the antibiotic-associated microbiota composition may persist.We observed clear differences in the microbiota composition in the antibiotic-treated children as compared with those who were not exposed to antibiotics for >2 years. Some aspects of the microbiota, such as the abundance of The children receiving antibiotics had infections, whereas those not receiving antibiotics did not have bacterial infections, requiring antibiotic treatment—although they may have had viral infections— and hence we considered the possibility that the microbiota changes could be attributed to the infections. However, both macrolide and penicillin antibiotics were prescribed mostly for respiratory infections, but were associated with clearly different, even opposite, changes in the microbiota. Furthermore, it has previously been shown that fever does not alter the microbiota composition of children8913In an earlier mouse study, it was shown that although the microbiota recover when antibiotic administration is ceased, the metabolic changes persistz-scores, specifically in a group of children that were exposed to macrolides in early life. The growth-promoting effect of antibiotics in animals224z-scores. Furthermore, it does not explain why priming specifically with macrolides predisposes to the antibiotic-associated weight gain. Rather, the weight gain is likely to occur via macrolide-associated changes in the microbiota, which promote excessive weight gain, as demonstrated experimentally with miceBifidobacteriumChristensenellaWe found a strong positive association between recorded antibiotic use and BMI Bile acid metabolism is one of the key functions performed by the intestinal bacteria, with strong effects on host energy metabolism29Lactobacillus and/or Bifidobacterium3738Bacteroides fragilisEggerthella spp. observed after macrolide exposure. Most Eggerthella spp. are pathogens9Previous birth-cohort studies and large international studies have found an association between asthma and early-life antibiotic useTo conclude, macrolide use was associated with microbiota characteristics that have previously been associated with the risk of immunological and metabolic diseases, as well as obesity. Furthermore, macrolide use promoted a marked increase in macrolide resistance of the microbiota. Our results confirm and extend previous results from mouse experiments10z-scores were calculated according to the LMS parameters obtained from the Centers of Disease Control and Prevention. Data on allergies were obtained from questionnaires filled out by the parents. Nearly all (>95%) of the children had received breastfeeding (>70% for at least 6 months), as this is highly promoted in Finland where mothers obtain leave of absence for up to 3 years with job guarantees. All children that developed asthma had received breastfeeding, and all but one received it for 6 months or more. The children received three daily meals at the day-care centre; the majority of their diet was thus largely similar. Furthermore, income inequality in Finland is low compared with other western countriesOur cohort consists of 236 Finnish children aged 2–7 years (median age 5 years), attending the same day-care centres at the time of the study. Register-based information and full background information was available for all children; 142 children donated fecal samples. The children are part of a larger cohort originally recruited for a probiotic trialIn Finland, antibiotics are only available by prescription. Information on antibiotic purchases was obtained from the records of the Finnish Social Insurance Institution, which subsidizes health-care costs. We collected data on all antibiotics purchased for the study children from the date of birth to the date of donation of the last fecal sample. Individuals with chronic illnesses are eligible for special reimbursement of their drug purchases, and the eligibility information is stored in the national database. We collected data on diagnosed asthma and allergic dermatitis (until the end of 2012), the most common developing chronic illnesses in the study cohort. The antibiotics were grouped into penicillins (amoxicillin with or without clavulanic acid and penicillin V), macrolides (azithromycin and clarithromycin), first-generation cephalosporins and sulphonamide–trimethoprim. The latter two groups of antibiotics were very seldom used, and therefore we focused on the penicillin and macrolide use. Azithromycin and clarithromycin became available in Finnish ambulatory care in 1994 and 1996, respectively, that is, before the birth of the study children. In our cohort, 50% of all antibiotic purchases were penicillins, 24% macrolides and the rest cephalosporins and sulfonamide–trimethoprim. These figures correspond to the population level data from FinlandBased on the parent-reported symptoms during the 7-month interval, we were able to assign potential indications for the use of antibiotics during the interval period. Respiratory infections were the most common apparent indication, occurring in association with 88% of the courses; other infections (mainly of the urinary tract) were associated with 5% and no concurrent reported symptoms with 7% of the courses. The antibiotic courses were not prescribed for gastrointestinal infections; pediatric gastrointestinal infections in Finland are nearly always viral and hence not treated with antibiotics. According to the physician in charge of the study, concurrent symptoms, indications for the antibiotics, symptom severity or disease history of the children receiving macrolides during the interval period did not differ from those receiving penicillins. Macrolides were typically prescribed due to presumed penicillin allergy or parents' request owing to easy administration or previous experience.z-score were assessed using Pearson correlations. Associations between antibiotic use during the first 2 years of life and asthma (N=15), and allergic dermatitis (N=5) were assessed using the Fisher's test.Associations between health and antibiotic use were analysed using the full cohort of 236 children. Associations between antibiotic use and BMI −1.The fecal samples were collected at home and transported immediately to the study centre for storage in −70 °C. DNA was extracted from the fecal samples using the Promega Wizard Genomic DNA Purification Kit as describedDe novo operational taxonomic unit (OTU) picking was done using Qiime version 1.8.0 . Colonies were counted on each plate after 2-day incubation at 37 °C, and the fraction of resistant colonies was calculated as the number of colony-forming units (c.f.u.'s) per 1 g of sample on the antibiotic plate divided by the c.f.u. on the control plate.Phenotypic antibiotic-resistant analysis was conducted by cultivating bacteria anaerobically from 80 fecal samples as mixed cultures. Bacteria were grown as dilution series on Brain-Heart Infusion agar (Oxoid) with or without 10 mg mlbsh, ermB and ermF were performed with primers specified in ermB and ermF genes have been previously publishedbsh primers to target this gene in the dominant phyla Firmicutes and Bacteroidetes. We focused on species that have confirmed bile-salt hydrolase activity and no penicillin V amidase activitybsh genes encoded by Bacteroides ovatus, Ruminococcus obeum and Eubacterium ventriosum based on sequence data obtained from GenBank using BLAST. The optimal primer concentrations and annealing temperatures were determined for each assay, and the specificity of the primer pairs was verified by melting curve analysis as well as agarose gel electrophoresis to confirm the correct product size. Reactions were run in triplicate on iCycler iQ Real-Time PCR Detection System  in a volume of 25 μl. Each reaction contained 1 × HOT FIREPol EvaGreen qPCR Mix Plus , 0.5 μM of each primer and 25 ng of fecal DNA. The amplification protocol involved one cycle at 95 °C for 5 min for initial denaturation followed by 40 cycles of denaturation at 95 °C for 20 s, primer annealing for 20 s, extension at 72 °C for 30 s and an additional incubation step at 80–82 °C for 30 s to collect the fluorescence data. The mean Ct value per sample  was used as a proxy for relative abundance of the target gene.The metagenomic analysis indicated that apart from an increase in macrolide resistance, macrolide use was associated with a decrease in bile-salt hydrolase genes. We therefore conducted qPCR analyses to quantify the abundances of these genes in a total of 130 DNA samples from 117 children. Quantification of bacterial genes The fecal samples were grouped based on antibiotic use . The conMicrobiota richness was calculated as the number of species-level OTUs (97% similarity cutoff) detected. Microbiota diversity was calculated as the inverse Simpson diversity index based on the species-level data. PCoAs were conducted using the genus-level data and Bray–Curtis dissimilarities. The associations of the first principal components with background variables such as antibiotic use were visualized by inverse distance-weighted interpolation of the variable values over the component space. Microbiota maturity index, which has previously been shown to differentiate between healthy children and those with health issues58P value testing and unreliable results. The detected abundance of rare genera is likely to be influenced considerably by chance and therefore less reliable than the abundance of common genera. The main focus of interest was to assess how the different groups (z-score of the child (which is likely to reflect lifestyle and diet at home), health status  and lifetime antibiotic use (when comparing antibiotic user groups) or antibiotic user group (when assessing the cumulative effect of lifetime antibiotic use). False disovery rate (FDR)-corrected P valuesP value <0.15) from the control group after controlling for all the above-mentioned variables, were considered potentially influenced by antibiotic use.Generalized linear models with negative binomial distribution (function glm.nb in the library MASS in R) were used to identify individual bacterial taxa that were associated with antibiotic use, either as being significantly different in the antibiotic user groups compared with the control group or significantly linearly associated with the total lifetime number of macrolide or penicillin courses (per years of life). We focused only on the 48 genera that we detected in >30% of the samples, in order to avoid unnecessary t groups  differ iN=8), and two age- and antibiotic use history-matched healthy controls for each (N=16). For analysis of the microbiota–overweight association, we selected the samples from all cases with BMI z-score >2 (N=9) and two (if available) age and antibiotic use history-matched normal-weight controls for each (N=16). For two overweight individuals, only one matching control case was available. For the asthma association analysis, we calculated the average microbiota composition between the first and second time point samples, if two samples were available. For the overweight analysis, we used only the first time point sample, as the weight and height were only recorded once at the beginning of the study. To find the bacterial groups that best distinguished asthma or overweight cases from healthy or normal-weight cases, we first fitted binomial models with asthma or overweight as the response variable, and each genus-level bacterial group separately as an explanatory variable. We used P values from these models as indicators of discriminating potential, and selected all bacterial groups with P<0.2 for further analysis. These groups were combined as explanatory variables in one model. AIC-based stepwise model selection was then used to find the set of bacterial groups that best discriminated between the asthma/overweight and healthy/normal-weight cases.To determine whether the asthmatic cases had distinct features in their microbiota composition, we selected the samples from all cases with current or developing asthma  under the study name PRJEB11685.How to cite this article: Korpela, K. et al. Intestinal microbiome is related to lifetime antibiotic use in Finnish pre-school children. Nat. Commun. 7:10410 doi: 10.1038/ncomms10410 (2016).Supplementary Figures 1-5, Supplementary Tables 1-4 and Supplementary References


Integrated care pathways (ICP) in stroke management are increasingly being implemented to improve outcomes of acute stroke patients. We evaluated the effect of implementing a 72 hour stroke care bundle on early outcomes among patients admitted within seven days post stroke to the national referral hospital in Uganda.In a one year non-randomised controlled study, 127 stroke patients who had ‘usual care’ (control group) were compared to 127 stroke patients who received selected elements from an ICP (intervention group). Patients were consecutively enrolled  into each group over 5 month periods and followed to 30-days post stroke. Incidence outcomes  were compared using chi square test and adjusted for potential confounders. Kaplan Meier survival estimates and log rank test for comparison were used for time to death analysis for all strokes and by stroke severity categories. Secondary outcomes were in-hospital mortality, median survival time and median length of hospital stay.Mortality within 7 days was higher in the intervention group compared to controls . There was no difference in 30-day mortality between the two groups . There was better 30-day survival in patients with severe stroke in the intervention group compared to controls (P = 0.018). The median survival time was 30 days (IQR 29–30 days) in the control group and 30 days (IQR 7–30 days) in the intervention group. In the intervention group, 41patients (32.3%) died in hospital compared to 23 (18.1%) in controls (P < 0.001). The median length of hospital stay was 8 days (IQR 5–12 days) in the controls and 4 days (IQR 2–7 days) in the intervention group. There was no difference in functional outcomes between the groups .While implementing elements of a stroke-focused ICP in a Ugandan national referral hospital appeared to have little overall benefit in mortality and functioning, patients with severe stroke may benefit on selected outcomes. More research is needed to better understand how and when stroke protocols should be implemented in sub-Saharan African settings.PACTR201510001272347Pan African Clinical Trials Registry  Across the world, integrated care pathways (ICP) in stroke management are increasingly being implemented to assist health care professionals to manage acute stroke patients in order to achieve pre-specified patient goals efficiently while improving quality of life –4. ICPs The protocol for this trial and supporting TREND checklist, are available as supporting information  into each group over 5 month periods.The control group was managed with ‘usual care’ and the intervention group received a 72-hour stroke care bundle followed by ‘usual care’ thereafter. Patients in both groups were followed to the 30-day from stroke onset. A randomised control study was deemed unethical/impractical in our study setting  and thusPatients were enrolled in the accident and emergency unit (A&E) at Mulago hospital which has a bed capacity of 1,500. Mulago hospital is located in Kampala the capital city of Uganda with a population of 1,516,210 . The hosThe study was approved by Makerere University College of Health Sciences’ School of Medicine higher degrees research and ethics committee, Mulago national referral hospital’s research and ethics committee, and The Uganda National Council for Science and Technology. All participants/or family provided written informed consent before participation in the study. All consent forms were approved by the above mentioned research and ethics committees.pactr.org. PACTR201510001272347.The study is in accordance with the Transparent Reporting of Evaluations with Nonrandomised Designs (TREND) statement , 14. AltPatients presenting to the A&E unit with suspected stroke on ‘usual care’ may not receive timely clinical and technology based assessments and interventions as well as routine physiological monitoring and management. Initial stroke screening depends on availability or vigilance of a clinician and brain CT scan may be delayed hours to days. Service limitations are largely due to human resource constraints, insufficient equipment and technology access as well as lack of a formal acute stroke care pathway to standardize clinical care and improve its efficiency and effectiveness . On the As shown in One week prior to commencement of recruitment of patients in the control group, two internal medicine physicians  and the principal investigator were trained in participant consenting, administration of the questionnaires, comprehensive clinical assessment, investigations and follow-up procedures.th July to 21st July). The nurses were trained to do physiological monitoring and management. The head nurse was in charge of the nurses.At the end of the control group recruitment period, a stroke care bundle team comprising two physicians (recruited patients in the control group), one medical officer (looked after control group patients as part of accident and emergency attending team) and fourteen neurology unit nurses (looked after control group patients on the neurology unit) was instructed in protocol bundle implementation and adherence for 3 days  the spouse, 2) live-in companion, 3) biological child  parent, 5) sibling, and lastly 6) a close friend of the patient. We excluded patients who were unconscious or unable to communicate  with no valid proxy. Stroke was defined according to the criteria of the World Health Organisation (WHO) as sudden onset of focal and at times global neurological deficits, with symptoms lasting more than 24 hours or leading to death, with no apparent cause other than that of vascular origin . Brain CPatients in the control group (details have been described before) , and theAll investigations were done at no cost to the patients in the intervention group. Patients in the control group paid for the brain CT scan.Patients in both groups were followed for 30-days post stroke. Discharged patients were scheduled for a neurology outpatient clinic review that coincided with the 30-day follow-up. Prior to the 30-day review date, weekly calls to patients were made to assess general clinical status. BI assessment was done at 30-day follow-up in the neurology clinic. Individuals unable to come to the clinic had the 30-day follow-up conducted in their home. Date of death was obtained for those that died before 30-day follow up.The primary outcome measures were (i) mortality within 3 days from stroke, (ii) mortality within 7 days from stroke, (iii) mortality at 30-days from stroke, and (iv) functional outcome at 30 days as measured by the BI. The BI reflects functional consequences for daily activities that are immediately important to a patient  includinThe study was designed to test the hypothesis that the stroke care bundle would reduce the risk of 30-day mortality compared to ‘usual care’ in patients presenting with acute stroke at Mulago hospital. Using the PASS 2008 software for two independent proportions (null case) power analysis –28, and Univariate analysis was used to describe the social demographic, clinical and laboratory characteristics of the study patients. The primary outcomes at 30-days from stroke onset were death defined as the proportion of stroke events that were fatal within 30-days of stroke onset and satisfactory outcome defined as a BI score of ≥60. Secondary outcomes were in-hospital mortality, median survival time, and median length of hospital stay. Time at risk of death was calculated from time of stroke onset to time of death or censor and time at risk of a satisfactory outcome was calculated from time of stroke onset to time of the outcome/censor. Incidence outcomes at 7 days and 30 days were compared using a chi square test and adjusted for potential confounders namely gender, level of education, stroke severity at admission, fasting blood sugar, total cholesterol, LDL, HDL, time to hospital presentation from stroke onset. Measures of association were expressed as risk ratios and a p value ≤0.05 was considered statistically significant. Kaplan Meier survival estimates and log rank test for comparison were used for time to death analysis for all strokes and by stroke severity categories. A significant P value from the log rank test was set at ≤.05. Data were analysed using Stata version 12.0 software .th February 2014 to 19th July 2014, 127 acute stroke patients were consecutively recruited into the control group out of 139 patients that presented to the A&E unit with neurological deficits suggestive of acute stroke. As illustrated in  The study clinician was readily available to do a rapid initial stroke screen within 15 minutes from patient presentation to the accident and emergency unit; 2) the ABCDD assessment of patients who presented within 24 hours of symptom onset was done concurrently with the initial stroke screening; 3) Of 127 patients recruited during the intervention period, 11 (8.7%), presented to hospital with CT scan of the brain already done at another hospital before they were referred to Mulago hospital. The median time to CT scan for patients in the intervention group was 2 hours (IQR 0.5–12) as compared to the control group 34.5 hours (IQR 24–60) (p = <0.001); 4) Swallow evaluation is not ‘usual care’ and hence none of the control group patients were assessed for swallowing ability. All the 127 patients in the intervention group were evaluated for pre-feeding requirements for a swallow evaluation. Fifty six (44.1%) patients met the pre-feeding requirements and all of them had a bedside swallow evaluation performed within 24 hours of admission; 5) Aspirin was promptly prescribed for all the 75 patients in the intervention group, in whom haemorrhagic stroke was excluded on CT scan; 6) monitoring and management of neurological status, BP, blood glucose, temperature, hydration status was complete for the first 72 hours of admission in 87 patients out of 127 patients  in the control group and 12.6% (95% CI 7.9%–19.5%) in the intervention group. Regarding secondary outcomes, in-hospital mortality was 41 (32.2%) in intervention group and 23 (18.1%) in the control group with absolute change -14.1(95% CI-24.5–-3.5); P<0.001. The median survival time was 30 days (IQR 29–30 days) in the control group and 30 days (IQR 7–30 days) in the intervention group. The median length of stay was 8 days (IQR 5–12 days) in controls and 4 days (IQR 2–7 days) in the intervention group. Among patients that did not die in hospital, the median length of hospital stay was 8 days (IQR 5–12 days) in controls and 5 days (IQR 3–8 days) in the intervention group.As illustrated in , the KapIn this study, we demonstrated fidelity in implementing the stroke care bundle in a resource limited setting. The processes of care were consistently performed with a 17 fold reduction in time to CT scan.In spite of the 72 hour stroke focused care, 7-day mortality was higher in the intervention group compared to the controls, and there was no significant difference in 30-day mortality and functional outcome between groups. This is consistent with findings in a Cochrane review  with somFindings in this preliminary study suggest that the stroke care bundle might reduce mortality in some patients with severe strokes. Patients with severe stroke in the intervention group were significantly more likely to be alive at 30 days post stroke compared to patients with severe stroke in the control group. It is possible that the more aggressively implemented care (as represented by the stroke care bundle) is most helpful for individuals with a great amount of impairment and highest risk of complications. Additional research is needed to more conclusively determine if there may be optimal patient populations on which to focus ICPs.Hospital stay was significantly shorter in the intervention group. This was in agreement with multiple studies  but in dFacilitators to implementation of the intervention included adequate funding which ensured readily available resources for stroke focused care. The stroke care protocol streamlined patient flow from the accident and emergency unit to the neurology, neurosurgery units and the general ICU. Training of nurses and explaining the rationale for implementation of the care pathway made them more knowledgeable about acute stroke care guidelines, clearly defined the roles of doctors and nurses, and enhanced their involvement in patient care. Weekly meetings and senior team supervision ensured continued adherence to the study protocols. The main barrier to implementation of the stroke care pathway was the impression of appearing overly prescriptive and additional to the pre-existing burden of care on an already over-stretched nursing staff. An ICU bed was not always readily available and so some admissions were delayed.There are limitations of our study. The non-randomised design may not have been able to account for temporal differences that could have occurred at our facility during the study time frame or even guarantee complete removal of bias, despite standard methods of case-mix adjustment. The stroke care bundle provided specific stroke–focused care for 72 hours only and this could have been an example of “too little, too late” especially for those with delayed hospital admission to begin with. There could also have been differences in informal supports available to the patients in the intervention and control groups such as care delivered by family. The sample size was small given the wide confidence intervals.This preliminary study in Uganda using a stroke care bundle did not find improved mortality or functional outcomes, although there were improved outcomes in some stroke patient sub-groups. Given the fact that stroke burden in the resource limited settings is expected to increase, it will be important to further develop and test ICPs that can facilitate delivery of stroke care that is efficient, practical, and may be able to generally improve patient outcomes. However, interventions to prevent severe strokes should be studied and emphasized as a preferred way to reduce stroke burden.S1 File(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Publications from the Avon Longitudinal Study of Parents and Children that used empirically derived dietary patterns were reviewed. The relationships of dietary patterns with socioeconomic background and childhood development were examined. Diet was assessed using food frequency questionnaires and food records. Three statistical methods were used: principal components analysis, cluster analysis, and reduced rank regression. Throughout childhood, children and parents have similar dietary patterns. The “health-conscious” and “traditional” patterns were associated with high intakes of fruits and/or vegetables and better nutrient profiles than the “processed” patterns. There was evidence of tracking in childhood diet, with the “health-conscious” patterns tracking most strongly, followed by the “processed” pattern. An “energy-dense, low-fiber, high-fat” dietary pattern was extracted using reduced rank regression; high scores on this pattern were associated with increasing adiposity. Maternal education was a strong determinant of pattern score or cluster membership; low educational attainment was associated with higher scores on processed, energy-dense patterns in both parents and children. The Avon Longitudinal Study of Parents and Children has provided unique insights into the value of empirically derived dietary patterns and has demonstrated that they are a useful tool in nutritional epidemiology. The derivation of dietary patterns to describe diet, as opposed to investigating individual foods or nutrients, has become popular in nutritional epidemiology. Dietary patterns facilitate the study of the whole diet, recognizing that people consume foods in combination. They complement more traditional methods of examining diet–health relationships, which use individual foods or nutrients. Studies of dietary patterns and a particular disease outcome such as obesity have been largely limited to adults. The cross-sectional studies in adults often report conflicting relationships with disease.,Most studies have used data-driven methods, such as principal components analysis (PCA) or cluster analysis, to derive dietary patterns.,Another method of deriving dietary patterns is reduced rank regression (RRR), which uses existing knowledge about disease etiology in combination with exploratory statistics to extract dietary patterns that are likely to be related to a specific disease.All 3 methods of obtaining dietary patterns described here were used in the Avon Longitudinal Study of Parents and Children (ALSPAC); the purpose of this narrative review is to summarize the findings of these analyses and compare and contrast the 3 methods within one cohort.All articles published online by the end of 2013 that derived dietary patterns based on ALSPAC data in children (from age 2 y) and their parents were reviewed. The 24 included articles are summarized in ,The ALSPAC is a birth cohort study that recruited pregnant women resident in 3 health districts of the county of Avon, around Bristol, in southwest England with an expected delivery date between April 1991 and December 1992 (n = 14 541 pregnancies).P < 0.001).The cohort was population based and broadly representative, at recruitment, of the population of women with children aged <1 year in Avon.Maternal diet was assessed by an unquantified FFQ sent to the mothers at 32 weeks gestation.For the majority of foods/drinks, the person was asked to indicate how often the food was consumed currently using the following options: 1) never or rarely; 2) once in 2 weeks; 3) 1–3 times a week; 4) 4–7 times a week; and 5) more than once a day. For foods/drinks normally consumed daily, there were more detailed questions. These included recording how many cups of tea or coffee and the number of slices of bread consumed each day; the usual type of milk (full fat or other) consumed; the usual type of bread  consumed; and the usual type of spread (butter or type of margarine or other) used. To apply quantitative meaning to the frequency categories, the data were numerically transformed into times consumed per week as follows: 1) 0; 2) 0.5; 3) 2; 4) 5.5; and 5) 10 times per week. Consumption of tea, coffee, bread, milk, and fat spreads were recorded on a daily rather than a weekly basis. Excluded from the dietary patterns analysis were participants whose FFQ had more than 10 dietary items unanswered. If 10 or fewer items were missing, the assumption was made that the person did not consume the missing items, and each was given a value of 0. No questions were asked about portion sizes; therefore, standard portion sizes,Prior to attending the research clinics, the parents (of 7-year-old children) or the child with parental help (at ages 10 and 13 y) was invited, by post, to record in a structured diary all foods and drinks consumed by the child over 3 individual days: preferably 1 weekend day and 2 weekdays.For the food record data, misreporting of energy intake (EI) was assessed at each age by an individualized methodEnergy adjustment is necessary because energy is highly correlated with most other nutrients and related to body sizeIn the PCA and cluster dietary patterns analysis using food record data, all foods and drinks were grouped based on the questions asked in the FFQ.,To perform PCA, all variables were standardized by subtracting the mean and dividing by the standard deviation for each variable. For the FFQ, the variables were the standardized average frequencies at which each food/drink was consumed per week; for food records, several input variables were tested. PCA forms linear combinations of the original observed variables by grouping together correlated variables, thus reducing the size of the dataset by identifying underlying components or patterns within the data.Cluster analysis groups individuals into nonoverlapping clusters.,RRR derives patterns that maximize the variation explained in a set of response variables, which are believed to be related to the outcome of interest. In this work, dietary energy density, fiber density, and percentage of EI from fat were selected as intermediate response variables based on evidence of a relationship with obesity, primarily in adults.At 12 weeks gestation, women were asked whether they had ever had any psychiatric problems, including eating disorders such as anorexia nervosa or bulimia nervosa.Intelligence quotient (IQ) was measured using a validated, age-adjusted, shortened version of the Wechsler Intelligence scale for children at age 8 years.Childhood behavioral problems were measured using the strengths and difficulties questionnaire (SDQ).Parents were asked annually by questionnaire about any difficulty they were experiencing feeding their child. The questions covered refusal of food, not eating enough, being choosy about food, and general difficulties with feeding. The answers were the parent’s subjective opinion and were not validated. There were also questions about whether the child was vegetarian or on a special diet of any type.x) to adjust for body size.,At each research clinic, height was measured to an accuracy of 0.1 cm using a Harpenden stadiometer , and weight was measured to 0.1 kg using the Tanita Body Fat Analyser weighing scale . At ages 9, 11, 13, and 15 years, the children underwent a whole-body DXA  scan . The scan provided estimates of total fat mass, lean body mass, and bone mass. Fat mass index (FMI) was calculated by dividing fat mass (in kg) by height , and being overweight before pregnancy was associated with a lower average score (P < 0.0001).P < 0.0001). The “traditional” pattern showed very little association with SEB. The mother reporting herself to be a vegetarian was associated with a high average score on the “vegetarian” pattern (P < 0.0001).Dietary patterns using PCA were obtained in the women at 32 weeks gestation during the study pregnancy and again when the study child was 4 years of age. During pregnancy, 5 patterns were obtained, explaining 31.3% of the variation in the data (n = 12 053).P < 0.0001), suggesting that women were moving toward a more processed dietary pattern. An applied analysis was performed that used the factor loadings obtained from the PCA during pregnancy to calculate the PCA scores on the data obtained 4 years later .When the FFQ was repeated 4 years later, some minor changes to the questions (see Methods section) had been made, which changed the foods associated with the patterns slightly see .11 Four P < 0.001) and vegetarian/semi-vegetarian patterns  and a strong negative correlation between the men’s scores on the health-conscious pattern and the women’s on the processed pattern ; other correlations were weaker.At the same time that the women completed the FFQ at 4 years postpartum, they were asked to pass an identical FFQ to their partner to complete; this was used in a PCA to determine dietary patterns in men.P < 0.0001), although not with scores on the other 3 patterns. Men’s age was positively associated with scores on the health-conscious pattern but negatively associated with scores on the processed/confectionery pattern. Higher frequency of smoking in men was strongly associated with a lower average scores on the health-conscious pattern. Men who identified themselves as vegetarian had a high average score on the semi-vegetarian pattern, a slightly lower average score on the health-conscious pattern, and low average scores on the other 2 patterns. These results suggest that men in this study who are mostly living within families have slightly different patterns of diet from their female partners.The men’s educational attainment was strongly positively associated with scores on the health-conscious pattern (P < 0.0001).P < 0.0001); presence of older siblings was associated with higher average scores on the junk and snacks patterns and lower average scores on the traditional pattern ; living in public rented housing was strongly positively associated with the junk pattern and negatively with the snacks pattern (both P < 0.0001); having financial difficulty was also strongly positively associated with the junk pattern and negatively with the snacks pattern (both P < 0.0001). All of these associations were independent of each other. These findings suggest that the types of food preschool children eat are influenced by the social environment of the family.The first analysis performed in childhood was at age 3 years (n = 10 139)th percentile of BMI from the 1990 UK reference data.The dietary patterns determined at age 3 years were used in analysis that looked at obesity at age 7 years defined by the 95P < 0.0001 at both ages), as was having younger siblings at age 7 years (P < 0.0001). Some childhood eating behaviors were assessed in this analysis: if the child was a vegetarian, they were likely to have lower average scores on the processed and traditional patterns and higher scores on the health-conscious pattern at both ages ; if the child was considered to be a difficult eater, they had higher average scores on the processed pattern and lower average scores on the traditional and health-conscious patterns at both ages ; boys had slightly lower average scores than girls on the traditional pattern (P < 0.0001 at both ages). These analyses suggest that the characteristics of the child as well as the SEB of the family are important in determining the type of diet eaten by the child.PCA was performed on the FFQ data collected when the children were aged 4 years (n = 9550) and 7 years (n = 8286).When PCA was performed at age 9 years (n = 8010)P < 0.0001) than when the youngest age was compared with the oldest age . The snacks pattern only appeared at age 3 years and was associated with the processed but not traditional or health-conscious patterns at later ages. Comparing the average scores for each pattern at each age, only the processed pattern score increased over time (P < 0.0001). When the data were categorized into quintiles, the highest amount of agreement was between the ages of 4 years and 7 years . In general, the amount of agreement was lower for the longer time gaps. Taking these results together shows a gradual evolution of the pattern of eating over childhood, suggesting that assessing diet at only one age during childhood may not be sufficient to characterize the diet.In light of the similarity between dietary patterns obtained at these 4 ages between 3 years and 9 years, the stability of the patterns over time was assessed.This is further illustrated by the PCA that was performed on the FFQ collected when the children were adolescents (aged 13 y).Pattern scores were higher, on average, for the traditional/health-conscious and vegetarian patterns for females and as maternal educational attainment increased.To complete the series of dietary patterns from FFQs in childhood, a PCA was performed on the data collected when the children were aged 2 years.P < 0.0001).P = 0.007). Children who were “very choosy” about foods had lower average scores on all 3 patterns compared with those who “ate anything.” This was particularly true for the health-conscious pattern . These data covering the whole of childhood show that the relationship between dietary patterns and child and family characteristics are similar at each age.The relationships between SEB and the family foods and health-conscious dietary patterns were very similar to those for the equivalent patterns at later ages. High scores on the sweet and easy pattern were evident with lower maternal educational attainment, living in public rented housing, and presence of older siblings . The highest quintile on the confectionery pattern score compared with the lowest was also associated with increased energy  but with decreased protein  and increased total sugars intake , again combined with decreased intakes of most micronutrients . In contrast, the health-conscious and traditional patterns showed much smaller correlations with energy. There were lower fat  and higher protein intakes  in the highest compared with the lowest quintiles of both pattern scores, along with higher intakes of almost all micronutrients (P < 0.0001). The vegetarian pattern score did not show consistent correlations with the micronutrients, but protein intake was lower in the highest than the lowest quintile of pattern score .The first published article from the ALSPAC relating dietary patterns to estimated nutrient intakes used the pregnancy diet and broke new ground in this area of research.,,In the male partners of the ALSPAC mothers and in the study children at each age , only linear correlations were calculated; there were many similarities with the associations shown in the women during pregnancy despite slight variations in the patterns found.,,,Before energy adjustment, at least 50% of the variance of many nutrients was explained by the dietary patterns at each age; this was, for the most part, reduced after adjustment for EI.In the analyses relating dietary patterns to nutrient intakes, the energy adjustment had been carried out after the dietary patterns had been extracted. There remained the question as to whether adjusting for EI prior to entering the foods into the PCA would change the results.The effect of the 2 methods of adjustment on associations between dietary patterns during pregnancy and birth weight were assessed: in both cases, an increase in the health-conscious pattern score was associated with an increase in birth weight . It should be noted that in this analysis many other factors that are known to influence birth weight were not considered.An analysis of the data from the food records collected at age 10 years (n = 7473) explored the methodological issue of whether the patterns obtained using PCA would be affected by the type of input variable used to describe the food groups.The results showed very little difference between the patterns derived from the absolute weights and the energy-adjusted weights of the food groups.The use of binary variables in the PCA gave slightly different patterns, which might represent dietary choices and may provide insight into where dietary change could be influenced. Four patterns explaining 17% of the variation were extracted.The associations between body composition at ages 9 years and 11 years and the PCA dietary patterns obtained at age 10 years using the food group weights (g/d) were examined. The analyses explored the differences between boys and girls and between those who were under-reporters of EI and those who were plausible reporters.There were differences in average standardized pattern scores between boys and girls and between plausible reporters and under-reporters.Cluster analysis was used to obtain dietary patterns, and the results were compared with those from PCA in the children at age 7 years using the FFQ.The age and educational attainment of the mother were strongly independently associated with the child’s cluster membership.Further cluster analysis was performed to assess whether dietary patterns were stable in children longitudinally between the ages of 7 and 13 years.Exactly the same foods were associated with the processed cluster at ages 7 , 10, andThe traditional cluster showed some differences between the age groups in relative amounts of foods consumed. At age 7 years , the amoThe fourth cluster extracted at each age from these data  was assoThe stability of the clusters over the 3 food records kept for the same children at ages 7, 10, and 13 years was examined (n = 4405–5287).st century, particularly in contrast to a processed diet.The cluster patterns provide some useful insights into what a healthy diet might look like in the context of children growing up in the United Kingdom in the early 21r = 0.81) and fiber density (r = −0.73) and moderately correlated with percentage of energy from fat (r = 0.49) at age 7 years, with very similar correlations at age 5 years. The foods with the highest factor loadings were similar at each age. The pattern scores tracked strongly between ages 5 years and 7 years  suggesting that, for the most part, children with high scores at age 5 years were likely to have high scores at age 7 years. Children whose mothers were in the lowest education group and those who watched television for >2 hours/day (from a questionnaire when the child was 4.5 y old) were more likely to have high scores on the energy-dense, high-fat, low-fiber diet at ages 5 years and 7 years.An analysis using RRR was carried out in the Children in Focus subsample of ALSPAC children using food records collected at ages 5 years and 7 years (n = 521 at 5 y and n = 682 at 7 y) and fat mass measured by DXA at age 9 years.P = 0.04), and excess adiposity increased from 13% to 23% (P = 0.01) between these quintiles. In the multivariate model  a 1 standard deviation increase in pattern score was associated with an increase in fat mass of 0.28 kg . This was only slightly attenuated by controlling for EI. There was a positive linear trend between the adjusted odds of excess adiposity at age 9 years and quintiles of dietary pattern score at age 5 years (P = 0.03) and age 7 years (P < 0.0001). A child in quintile 5 compared with quintile 1 of the dietary pattern score at age 5 years was 2.52  times more likely to have excess adiposity at age 9 years, and a child in quintile 5 compared with quintile 1 of the dietary pattern score at age 7 years was 4.18  times more likely to have excess adiposity at age 9 years.There were no associations between quintiles of pattern score at age 5 years or age 7 years and mean BMI or overweight  at ages 5, 7, or 9 years.z-score representing the degree to which their reported dietary intake reflected this dietary pattern at each age. Linear regression analysis between dietary pattern z-score and FMI z-score was performed. Fully adjusted dietary pattern z-scores at ages 7 years and 10 years were positively associated with later fat mass; however, at age 13 years, full adjustment attenuated the association to the null  was assessed.null see . Most ofThe degree of tracking of this energy-dense, high-fat, low-fiber dietary pattern over the 3 ages was assessed using applied dietary pattern scores based on the pattern scores at age 7 years.z-score and increasing energy-adjusted food intake z-score of some food groups, such as chocolate/confectionery, crisps, and processed meat. There were associations with decreasing intake of other foods, such as fresh fruit, vegetables, high-fiber breakfast cereals, brown/wholemeal bread, and cakes/biscuits. The relationship of the dietary pattern scores and food intakes with increasing maternal prepregnancy BMI showed fairly similar associations, i.e., positive with dietary pattern z-score, white bread, and processed meat and negative with cakes/biscuits, fresh fruit, and vegetables. These finding suggest that these maternal characteristics are associated with higher scores on a dietary pattern that is related to increased adiposity in children and adolescents.Maternal factors were investigated in analyses adjusted for misreporting status.P < 0.05) compared with that with prior attainment scores , suggesting a small but independent role for preschool diet. These results were adjusted for child and maternal factors, including breastfeeding and maternal educational attainment.The educational attainment of ALSPAC children was assessed nationally at school entry (4–5 y), at key stage 1 (6–7 y) and key stage 2 (10–11 y). Associations with PCA-generated dietary patterns from the FFQs at ages 3, 4, and 7 years were examined (n = 4244).P < 0.0001) and positively associated with the health-conscious/vegetarian pattern score at age 9 years, close to the age of IQ assessment . There were no adjusted associations with dietary pattern scores at age 4 years or age 7 years. These results are consistent with the child’s educational attainment data (above), which used entirely different methods of assessment applied nationally to all children in state schools. Taken together, the results suggest early diet (preschool) is more important in relation to cognitive development than later diet. This may be linked to the lower intake of micronutrients associated with higher scores on the processed types of dietary patterns.IQ was measured in the children at age 8 years and assessed in relation to the PCA dietary pattern scores from ages 3 years to 9 years (n = 3966 with complete data).In the children, behavioral problems had been assessed by the SDQ at ages 4 years and 7 years, and scores for hyperactivity, conduct problems, emotional problems, peer problems, and prosocial behavior were obtained.Box 1 Key findings in briefSimilar dietary patterns were found in a cohort of children at various ages between 3 years and 13 years and in their mothers and fathers using principal components analysisThe health-conscious and traditional patterns of diet extracted at all ages were associated with better nutrient profiles than the processed patterns, which tended to be energy-dense and nutrient-poorDietary patterns from cluster analysis grouped the children by foods recorded at ages 7, 10, and 13 years; many of the children continued with the same dietary pattern at each age, with the health-conscious and processed patterns being the most stableAn “energy-dense, high-fat, low-fiber” dietary pattern was extracted from food recordings at ages 7, 10, and 13 years using reduced rank regression analysis. High scores on this pattern were associated with increasing adiposity between 11 and 15 years in these childrenA major determinant of the dietary patterns extracted from all 3 methods was the amount of fruits and vegetables consumed; the healthier diet patterns contained more fruits and vegetables, whole-grain cereal products, and plain potatoes; the less healthy patterns contained more chocolates/confectionery, white bread, cakes/biscuits, and crispsMother’s educational attainment was a strong determinant of the dietary patterns extracted using all 3 methods; higher educational attainment was associated with healthier, more nutrient-dense dietary patternsP < 0.001) and to have higher average scores on a vegetarian dietary pattern  than women without such disorders.Dietary patterns from PCA using the FFQs in childhood (ages 3–9 y) were investigated in relation to the presence of eating disorders in the mothers to assess whether children of those with eating disorders have a different type of diet from children whose mothers are not affected.,,,,,,,,,Similar patterns of eating emerge both in children at each age and in their parents; these have some common features regardless of which method of obtaining dietary patterns is used. Higher consumption of fruit and vegetables, wholegrain bread and breakfast cereal, plain potatoes, and low-fat milk are always associated with better scores on the healthier types of patterns,,The different sources of data (FFQ or food record) provide some different insights into diets consumed during childhood. The food records covered in detail all foods that were consumed over a short period of time, so new patterns, such as the packed lunch pattern, which did not occur in the FFQ analyses,,,There was evidence of tracking of the dietary patterns using all 3 methods of deriving dietary patterns and using both FFQs,,The development of obesity was assessed using the patterns derived from both PCAThese data suggest that action to increase young children’s intake and liking of fruits and vegetables, as well as whole-grain products, is likely to provide progress in tackling the obesity epidemic and that this action should start before the age of 7 years to be most effective.,Insight into obesity development in children participating in the ALSPAC benefited from the fact that fat and lean mass had been measured using DXA at several ages. This is a much more sensitive method for identifying problematic body composition than the use of BMI definitions of obesity alone.,,,,,,,,,,Using all 3 methods, the patterns obtained were highly influenced by the characteristics of the child’s mother, particularly her educational attainment, age at the birth of the child, and prepregnancy BMI. Higher maternal educational attainment is associated with high scores on the healthier patterns,,,Dietary patterns are associated with the nutrient content of the diet. Higher scores on both the healthy and traditional types of patterns are associated with higher micronutrient content of the diet in both adults and children.,,The PCA using the FFQ derived a vegetarian or semi-vegetarian type of pattern in the adults (both women and men),,,,,,Although often living in the same family home, male and female partners had slightly different dietary patterns,,,From the analyses relating dietary patterns in the children to behavioral and cognitive outcomes, the association of high scores on the junk/processed pattern in preschool children with lower educational attainmentSome methodological issues associated with dietary patterns analysis have been explored, and these articles have added to the sparse literature in this field. In particular, the investigation into the best stage at which to apply energy adjustment in PCA analyses showed that there is no benefit from adjusting the food group intakes prior to performing the PCA.,The main strength of the ALSPAC is the derivation of dietary patterns at many ages during the childhood of a cohort of children and in their parents, as well as the use of 3 different methods to derive the patterns. Additional strengths are the relatively large sample size, adjustment for confounders, and, in some analyses, physical activity measurement,,PCA and cluster analysis have faced criticism because they are data dependent and the patterns obtained can, therefore, not be directly compared across studies, countries, and cultures. Furthermore, in PCA a number of subjective decisions have to be made during the analytical process,Uniquely in the ALSPAC, dietary patterns were derived using 3 different methods to evaluate the data collected at different ages throughout childhood and in parents in the same cohort. This has led to many insights into how foods are consumed together in a highly developed country in which food stuffs are readily available and relatively cheap. All 3 methods used to derive dietary patterns confirm that fruit, vegetable, and whole-grain intakes define whether a person is likely to be consuming a healthy diet or not. This suggests that public health initiatives that aim to improve fruit, vegetable, and whole-grain intake as part of a balanced diet are important. It is also clear that the differences in dietary patterns are strongly related to social inequality, particularly with regard to the educational attainment of the mother. These differences may well be contributing to the large inequalities in health outcomes seen in the United Kingdom.


Tetraspanins are four-span membrane proteins that are widely distributed in multi-cellular organisms and involved in several infectious diseases. They have the unique property to form a network of protein-protein interaction within the plasma membrane, due to the lateral associations with one another and with other membrane proteins. Tracking tetraspanins at the single molecule level using fluorescence microscopy has revealed the membrane behavior of the tetraspanins CD9 and CD81 in epithelial cell lines, providing a first dynamic view of this network. Single molecule tracking highlighted that these 2 proteins can freely diffuse within the plasma membrane but can also be trapped, permanently or transiently, in tetraspanin-enriched areas. More recently, a similar strategy has been used to investigate tetraspanin membrane behavior in the context of human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) infection. In this review we summarize the main results emphasizing the relationship in terms of membrane partitioning between tetraspanins, some of their partners such as Claudin-1 and EWI-2, and viral proteins during infection. These results will be analyzed in the context of other membrane microdomains, stressing the difference between raft and tetraspanin-enriched microdomains, but also in comparison with virus diffusion at the cell surface. New advanced single molecule techniques that could help to further explore tetraspanin assemblies will be also discussed. Lateral segregation of membrane components within the plasma membrane of eukaryotic cells is an essential phenomenon for the optimal function of most of biological processes. This includes the diffusion of lipids and proteins within the plasma membrane, as well as their organization into microdomains. It is now well established that plasma membranes of eukaryotic cells are organized as a mosaic of micro or nanodomains that contain specific sets of lipids and proteins . ImportMembrane microdomains have been associated early on with virus infection (first reviewed in ). CharacThe initial evidence of the existence of membrane microdomains came from biochemical approaches involving membrane solubilization with detergents and from fixed cells images obtained with both conventional fluorescence and electron microscopy. However, none of these approaches can probe the dynamics of membrane components, a crucial parameter to decipher the molecular mechanisms associated to these microdomains. Thanks to the development of advanced microscopy techniques that break the diffraction barrier, others and we have investigated the dynamics of membrane microdomains at the single molecule level. In this paper, we briefly present single molecule techniques and review the main results concerning tetraspanin and TEMs, especially in the context of virus infection.i.e., ensemble labeling or single molecule techniques  and single molecule tracking (SMT). FFS is a single-molecule sensitive technique that analyzes fluctuations in the fluorescence emission of small molecular ensembles in a sub-femtoliter volume and thus provides information about a multitude of parameters such as stoichiometry, concentration and molecular diffusion of fluorescently labeled molecules with a very high temporal resolution . In iewed in ). Howeveiewed in ). Singleiewed in . Varyingiewed in . More reiewed in ) and theiewed in . Howeveri.e., proteins undergoing Brownian motion can be transiently confined, through mechanisms involving interactions with lipids, actin cytoskeleton and/or other proteins. SMT has been used to reveal the lateral organization of membrane proteins such as G Protein-coupled receptors [The advantage of SMT as compared to FRAP and FCS is that individual molecules can be analyzed with high spatial and temporal resolution providing a detailed description of their motion within the plasma membrane . SMT is eceptors ,25, GPI-eceptors ,27, tetreceptors ,28 and tetc.) can be tracked in real time, called single particle tracking (SPT) , iewed in ). After iewed in ,31,32.3ß1 or α6ß1), CD9 or CD81 with EWI-2 or EWI-F/CD9P-1, or Tspan5, Tspan14, Tspan15 with ADAM10 [Tetraspanins are transmembrane proteins involved in many key physiological functions such as immunity ,34, gameh ADAM10 ,46. As th ADAM10 , a technh ADAM10 .6 integrin diffusion [6 integrin whereas directed diffusion was observed in the absence of the tetraspanin. It was proposed that CD151 promoted recruitment of its partners into TEAs. A similar role was proposed for the tetraspanin CD82 that can restrict the diffusion of EGF receptor [Biochemical experiments described above have been and are still necessary to dissect the network of protein-protein interactions but only provide a snapshot of its membrane organization. In this context, SMT was applied to tetraspanins and has first provided a dynamic view of the tetraspanin web . Using Tiffusion . This pareceptor . Altogetreceptor .The role of tetraspanins during infection has been described early on and these proteins are implicated in various aspects of virus life cycle, e.g., many viruses use TEMs to enter host cells and to infect other cells after their assembly and budding . Human immunodeficiency virus (HIV) is a major cause of morbidity and mortality around the world. There are two types of HIV (HIV-1 and HIV-2) but, worldwide, the predominant virus is HIV-1 and it is probably one of the most studied pathogens. One of the critical steps of HIV-1 life and reproduction cycle is its assembly and the release of new virions from infected cells . It is k2/s for CD9, values comparable with diffusion coefficients measured by FRAP). The decrease in CD9 dynamics was attributed to a confinement of tetraspanins during Gag assembly, the percentage of CD9 molecules exhibiting confined motion increasing significantly from 14% to 34% of the total number of trajectories, at the expense of Brownian trajectories (from 48% to 27%). Similarly, confinement of CD81 molecules strongly increased from 20% to 42% of the total number of trajectories. Surprisingly, CD81 dynamics in HeLa cells was completely different from that of CD9 (CD81 is much more confined than CD9), even if the two molecules are often co-localized and share membrane partners. This difference can be in part explained by CD81 interaction with the cytoskeleton (manuscript in preparation). In the set of experiments described above, the complexity of membrane organization required control proteins to validate our observations. CD46, a protein that is not localized in lipid rafts and minimally associates with TEMs but which has been identified in HIV-1 particles, was used as a control and its membrane behavior was mostly unaffected upon Gag expression. The stochasticity of the recorded events also requires getting a high number of trajectories to confidently describe the behavior of each protein. Typically, using our experimental conditions, we calculated that a minimum of 300 trajectories was necessary to be statistically significant.All these publications emphasized the importance of tetraspanins in HIV-1 budding but the influence of Gag assembly on tetraspanin organization were still unexplored. We therefore investigated the dynamics of CD9 and CD81 by combining both SMT and FRAP in HeLa cells expressing GFP-tagged Gag proteins . We initAs raft microdomains had been associated to HIV-1 budding  and becaPlasmodium [While several tetraspanins are involved in HIV-1 infection, CD81 plays a specific and essential role in the entry in hepatocytes of two major human pathogens, the malaria parasite asmodium  and the asmodium . In the et al. in this special issue). HCV first interacts with attachment factors such as glycosaminoglycans and the Low Density Lipoproteins Receptor (LDL-R). After this first attachment step, viral particles interact with a series of entry factors including the scavenger receptor SR-BI, CD81 and two tight junction proteins, Claudin1 (CLDN1) and Occludin. Importantly, CD81 and CLDN1 associate to form functional complexes, which are essential to HCV entry [HCV entry is a complex phenomenon requiring virus binding to several transmembrane proteins . HCVCV entry . In addiCV entry . Lipids CV entry . Indeed,CV entry  and thatCV entry .2/s). The latter observation can be explained by a decrease of membrane fluidity since a similar decrease was observed with a lipid marker (from 0.45 to 0.17 µm2/s). A lower percentage of cholesterol in the basolateral membrane following polarization could explain this result, taken into account that this lipid is implicated in the apical targeting of GPI-anchored proteins [In order to elucidate the protein/protein/lipid orchestration during HCV entry, we have used SMT to analyze CD81 membrane behavior in hepatocytes, in combination with biochemical approaches, and demonstrated that restricting CD81 diffusion impaired the infectivity of the virus ,85. In aproteins . Similarproteins  and modiproteins  and data−2 µm2/s as compared to control cells). Even if we cannot completely exclude that the lipid composition is modified upon EWI-2wint expression, the obvious explanation is that CD81 molecules diffused in larger nanoclusters  of these proteins is indeed altered but so far we have not been able to properly identify the molecular mechanisms behind this alteration because of the complexity of the membrane landscape. Further experiments to better understand how the different partners interact with each other are clearly needed, from the membrane behavior of each partner to their dynamic interaction. In the latter case, two-colors SMT should be very helpful, as well as FCCS (Fluorescence Cross Correlation Spectroscopy) that allow dynamic probing of protein-protein interaction at different time scales. Even if several papers have stressed on the differences between TEMs and rafts, comparing tetraspanins with raft markers such as GPI-anchored proteins is mandatory to understand structure-function relationship within plasma membranes. The importance of the lipids such as cholesterol should also be deeply investigated in regards to their key role in the formation of microdomains.Besides the dynamics of tetraspanin assemblies or microdomains, their composition and stoichiometry are still poorly documented and we believe that recently developed super resolution techniques, that improve 10 fold the resolution of optical microscopy, should be very helpful. For example, single molecule localization microscopies like Stochastic Optical Reconstruction Microscopy (STORM)  or Photo


Coughing plays an important role in influenza transmission; however, there is insufficient information regarding the viral load in cough because of the lack of convenient and reliable collection methods. We developed a portable airborne particle-collection system to measure the viral load; it is equipped with an air sampler to draw air and pass it through a gelatin membrane filter connected to a cone-shaped, megaphone-like device to guide the cough airflow to the membrane. The membrane was dissolved in a medium, and the viral load was measured using quantitative real-time reverse transcriptase-polymerase chain reaction and a plaque assay. The approximate viral recovery rate of this system was 10% in simulation experiments to collect and quantify the viral particles aerosolized by a nebulizer. Using this system, cough samples were collected from 56 influenza A patients. The total viral detection rate was 41% (23/56), and the viral loads varied significantly . Viable viruses were detected from 3 samples with ≤18 plaque forming units per cough sample. The virus detection rates were similar among different groups of patients infected with different viral subtypes and during different influenza seasons. Among patients who did not receive antiviral treatment, viruses were detected in one of six cases in the vaccinated group and four of six cases in the unvaccinated group. We found cases with high viral titers in throat swabs or oral secretions but very low or undetectable in coughs and vice versa suggesting other possible anatomical sites where the viruses might be mixed into the cough. Our system is easy to operate, appropriate for bedside use, and is useful for comparing the viral load in cough samples from influenza patients under various conditions and settings. However, further large-scale studies are warranted to validate our results. Coughing plays an important role in the rapid spread of influenza infections among humans. Influenza virus-borne bio-particles are discharged from an infected person through coughing and transmitted to uninfected person(s). However, whether influenza virus particles are directly transmitted to the target host as large droplets or through inhalation by the host as small airborne particles remains controversial.For example, Brankston et al. and Tellier reviewed many clinical and epidemiological studies, as well as experimental transmission studies using animal models and volunteers, and drew strikingly different conclusions: Brankston et al. did not support the airborne route Recently, viral RNA was detected in voluntary cough samples of influenza patients by many researchers using their own methods. For example, Stelzer-Braid et al. In the present study, we developed a portable system to easily collect bio-particles released by coughing at bedside within a short time without burdening the patients , and quaThis study was approved by the ethical committee of Sendai Medical Center , and written informed consent was obtained from all patients.Airborne particles in coughs and mists, generated in laboratory experiments to simulate coughs, were collected using an airborne particle-sampling unit composed of portable air sampler  connected by a flexible polyvinyl chloride hose with reinforced ends   to a gelCough, throat swab and oral samples were collected, in this order, from individuals exhibiting symptoms of influenza who visited one of three medical facilities in Sendai City, Japan. Among them, those who received final diagnosis of influenza by viral isolation from throat swab samples were enrolled in this study. Samples from 16 patients from Sendai Medical Center , 39 from Japan Self-Defense Force Sendai Hospital , and 1 from Shoji Clinic  were collected from January 2008 to February 2011 and included for analysis.3/h, which is the maximum pumping rate according to the manufacturer and was previously adopted in a swine influenza study For sample collection, patients were asked to cough voluntarily approximately 20 times at their own pace and without great effort into the cone entrance toward the gelatin membrane filter, which was at the opposing tip of the cone. The connected sampler was set at a constant airflow rate of 8.0 mInfluenza virus A/Aichi/2/68 (H3N2) was propagated in the allantoic cavities of fertilized chicken eggs. The allantoic fluid containing the viruses was harvested and atomized in simulation experiments using an electric compressor nebulizer .The gelatin membrane was dissolved in 10 mL of MEM and treated with 10 µg/mL of collagenase  at 37°C for 1 h and ultra-centrifuged at 125,000 g for 100 min to obtain viral precipitate, which was then dissolved in extraction buffer included with the RNA extraction kit ; the viral RNA was extracted in 80 µL of RNAse-free water according to the manufacturer's instructions. The RNA solution was concentrated using a freeze-drying system composed of a freeze dryer , a centrifugal concentrator , and a vacuum pump . The total amount of extracted RNA was used for complementary DNA (cDNA) synthesis using the reverse transcription kit  with random primers following the manufacturer's protocol. The amount of generated cDNA was measured with quantitative real-time reverse transcriptase-polymerase chain reaction (qRT-PCR) using the MiniOpticon system with CFX Manager software , influenza A matrix protein 1 (M1)-specific primers, and probes designed by Daum et al. Throat swab samples in MEM transport medium were centrifuged at low-speed (1500 g) for 15 min, and then inoculated onto Madin-Darby canine kidney (MDCK) cells for viral culture schlieren  analysis, as per the report by Tang et al. The collection system was equipped with a portable air sampler unit containing a gelatin membrane filter and a large cone-shaped, megaphone-like device to guide the expelled particles to the filter  A, B. ThTo evaluate the efficiency of our system to measure the total viral load in a cough, we attempted to separately estimate the rough recovery rates of the collection and quantification processes.8 plaque forming units (PFU)/mL of influenza virus was atomized by a nebulizer every 0.5 s for 3 s, which was repeated 10 times, and directed toward a gelatin membrane filter set 10 cm from the nebulizer. The generated viral mist was drawn directly into the gelatin filter membrane apparently by robust pumping of the sampler, which was confirmed against a black paper background and was visible by the naked eye. A similar experiment was repeated using a hollow paper tube  to guide the mist to the membrane, of which the outer and inner surfaces were coated with aluminum foil to prevent static charge (4 PFU/mL) was atomized , 88% of the samples were from 18–38-year-old patients, and the male-to-female ratio was 3∶1. None of the patients had significant health problems. Forty-five (80%) cases were infected with influenza A(H1) virus, 5 (9%) with A(H3), and 6 (11%) with A(H1N1)pdm09 .Next, the amount of viable viral particles trapped by the gelatin membrane was quantified using a conventional plaque assay. Viable viruses were detected in 3 (5%) samples with titers of 1.5, 1.5, and 18 PFU per cough of viral subtypes A(H1), A(H3) and A(H1N1)pdm09, respectively. Due to the potential existence of non-viable virions, qRT-PCR targeting a viral gene was simultaneously performed. The detection limit for reliable quantification in our qRT-PCR system was preliminary determined as 10 gene copies per µL cDNA of the influenza virus gene. Calculations with dilution rates by the volume of the membrane solution and the times of coughs, as well as results of our actual cases, determined that the detection limit was about 10 copies per cough. Using this detection limit as a parameter, the cases were deemed as either positive or negative for the presence of influenza virus. Of the 23 (41%) cases determined as positive, and the viral load varied widely from 10 to 2240 copies/cough. Seventeen (30%) samples contained a few to several dozen copies/cough, five (9%) contained 100–200 copies/cough, and one contained an exceptionally high level, i.e., 2240 copies/cough; the remaining samples had an average and median of 63 and 44 copies/cough, respectively, with a standard deviation of 56. The highest viral content was found in a sample obtained at day 3 of illness in a patient with the influenza A(H1N1)pdm09 virus infection, which was one of three cases in this study in whom active virus was detected (the plaque count  =  18/cough).The results were analyzed from different perspectives depending on the characteristics of individual cases and initially graphed with the days of illness along the abscissa. Day 1 was defined as the onset day of any influenza symptom . We did not find any significant differences in the viral detection rates among groups of viral subtypes , influenFor infection control, it is important to determine the presence or absence of vaccination and antiviral treatment effects on viral load. Therefore, we analyzed the obtained data to assess the impact of patient vaccination and antiviral treatment status on the viral load in a cough. Among 56 cases, 11 (20%) received influenza vaccinations before the influenza season and 34 (61%) received antiviral treatments with the neuraminidase (NA) inhibitors oseltamivir or zanamivir at the time of cough collection.First, we graphed the viral loads in individual cases along with the state of antiviral treatment against time from treatment initiation to cough collection . Here weFor cases treated during a supposedly sufficient time for viral replication before cough collection (>24 h) in the host, the detection rate was similar among control untreated cases  as was the viral load . We were also interested in the results of patients with a shorter duration of treatment (1.5–4.5 h) from the perspective of whether viral release from the respiratory tract by coughing could be inhibited by drug administration after the viral budding process concluded. This point of view was based on the mechanisms of the action of NA inhibitor drugs, as the timing of this action is considered important at the moment of viral release at viral budding sites to inhibit release by the inactivation of the viral NA enzyme. Thus, we wished to determine whether there was another mechanism by which the drugs enhanced rebinding of the virus to the cell surface, which had already been released from the cell surface, and thus reduce the viral load of the cough or not. We, therefore, added the results of 10 such cases to the same graph and found that the virus detection rate of these cases  was also similar to those of both untreated and sufficiently treated cases , as was the viral load . However, when the medians were compared, these short-term treated cases showed no significant difference with the untreated cases, but the sufficiently treated cases showed apparently smaller viral loads .On the other hand, we analyzed cases that did not receive antiviral treatment, by the status of receiving vaccination of seasonal vaccines before onset of seasonal influenza epidemic of subtype H1N1 or H3N2. Viruses were detected in one (17%) of six vaccinated cases and in four (67%) of the six control unvaccinated cases. The viral loads of vaccinated cases were lower than those of the unvaccinated cases  A. TheseIn this study, cough samples were collected from patients by voluntary coughing. We thought that it would be important to determine whether the symptom of cough impacted that actual viral loads in a cough; therefore, we considered coughing by non-symptomatic patients, by e.g., due to allergy, physiological stimulations, or causes other than influenza infection. Viral loads in the cough samples collected by voluntary coughing were compared between influenza cases with and without a symptom of coughing using throat swab samples as control . The virs = 0.355, p = 0.007) and cough samples/oral secretions . Notably, several cases showed almost no correlations: a high viral load in the throat swab or oral secretion while very low or undetectable in the cough sample, and vice versa . The levels of viral genes measured from coughs in many patients by our system were similar to those measured using the methods of Lindsley et al., who perfectly collected cough samples by asking the patients to blow into a spirometer Furthermore, we used universal primers for cDNA synthesis from the viral RNA aimed to quantify the RNA, because we were also preparing to assess influenza B cases during this study period and, therefore, could not use a carrier virus in the ultracentrifuge process. The combined use of specific primers for each viral target and some carrier viruses may improve viral recovery; however, this possibility should be examined in a future study.Our particle collection method may not sufficiently distinguish large droplets that directly hit the membrane from the small particle droplet nuclei floating inside of the cone, probably because the 50-cm distance from the face to the filter may not long enough to exclude collection of large droplets as well. This possibility was already taken into consideration. Our method was aimed to obtain information regarding the approximate total amount of virus released by coughing.Apart from the issue of absolute recovery rate, relative comparisons of viral loads among patients may be possible. The highest viral load was 2240 copies/cough among the 56 samples, which was more than 10-fold greater than the average of the virus-positive samples. A possible factor that may play a role in spread of infection is the existence of the so-called “super spreader,” which has been proposed in epidemics of severe acute respiratory syndrome Here, we measured the viral loads in cough samples collected from influenza patients. However, there were some limitations to our study regarding the study subjects: most were generally healthy young adults or adolescents, and data from young children, elderly persons, or persons with chronic medical conditions were limited. Second, we could not follow the time course of the viral shedding in the cough among individuals.We described applications of our methodology to study the effects of vaccination and antiviral treatment, and found that the former may suppress viral release during coughing, but the latter may not, although the former was not yet supported statistically. Regarding antiviral treatment, care should be taken when interpreting the results of this study because all cases treated with oseltamivir were infected with influenza A(H1) virus during the 2008–2009 influenza season, which was considered as resistant to this drug, reflecting the circulating virus at the time of the study Correlation analyses on the viral loads between the cough and throat swab or oral secretion samples showed that the viral load in a cough may not necessarily reflect those of a throat swab or oral secretion and vice versa, suggesting that the virus in the collected coughs, at least for cases with significant disparities in the viral load level between the two kinds of samples, neither originated from the pharyngeal wall nor the oral cavity, and thus might be mixed with cough air flow at anatomically deeper sites in the respiratory tract than those sites. Regarding the weak correlations between samples, we cannot deny the possibility that in a certain proportion of cases, the virus might have originated from the throat wall or oral cavity as well, or that the virus in the cough may have been trapped in the throat wall and/or oral cavity and we only detected these.In the present study, we measured the viral load mainly by genetic quantification. However, for optimal infection control, information regarding the activity of virus is more important. We detected active viruses in only 5% of cough samples with moderately high viral titers. This is probably because of the inactivation of the viruses while trapped in the gelatin membrane until plaque titration. We observed that the viruses did not become inactivated if the plaque titration was conducted within a short time after being trapped in the membrane, but they may become inactivated after an extended period with varying degrees of inactivation speed depending on the environmental temperature and humidity (data not shown). This result indicates that our methodology might be insufficient for quantification of viable viruses.Altogether, our method can be effectively applied for point-of-care detection of influenza viruses from the cough and their quantification. Nonetheless, further large-scale studies are needed to validate our results, which involve several important epidemiological, clinical, and pathophysiological issues.Figure S1Size distributions of bio-particles in a human cough and mist generated by a nebulizer. Comparison of the size distribution of bio-particles from human coughs and mist generated by a nebulizer. The air inside a closed 2 m3 chamber was set at about 20% RH and cleaned-up using an air fan unit with a high-efficiency particulate air filter unit. Immediately after healthy adult volunteers coughed voluntarily into the chamber via small window with a flap to seal it, or 2 min after the allantoic fluid of the embryonated chicken egg was atomized in the chamber for 3 s, the particle concentrations were measured using a laser particle-counter  for each particle size range. The data of human cough are presented as absolute particle counts and standard error rang per single cough of the average of five subjects, and the data of the nebulizer are presented as the concentration inside the chamber.(TIF)Click here for additional data file.Figure S2Viral loads in coughs of influenza patients in different influenza seasons. The viral load/cough is plotted on the ordinate and the days of illness during sample collection on the abscissa. Epidemic seasons are presented using different symbols: closed circles, open circles, and open triangles represent seasons 2007–2008, 2008–2009, and 2010–2011, respectively.(TIF)Click here for additional data file.Figure S3Viral loads of coughs of influenza patients by body temperature. Data of individual cases are plotted on the graph with the viral load in a cough on the ordinate and body temperature at the time of cough sampling on the abscissa. Data of days 2 and 3 were plotted together in the graph. Viral subtypes are presented using different symbols: open circles, closed circles, and open triangles represent infections with A(H1), A(H3), and A(H1N1)pdm09 virus, respectively.(TIF)Click here for additional data file.Table S1Demographics of virus-detected and undetected cases.(TIF)Click here for additional data file.