This prospective, repeated measures study utilized a convergent parallel mixed methods approach to assess sleep experiences among individuals who were alcohol-dependent undergoing inpatient detoxification and treatment at a clinical research facility across the transition periods associated with the rehabilitation process: the initial adjustment to becoming an inpatient and the transition from inpatient to outpatient status.This study included individual semi-structured interviews and quantitative measures relating to psychological distress, sleep quality, daytime sleepiness, and sleep-related beliefs and behavior . Interviews were conducted and questionnaires were administered within one week of participants’ scheduled discharge date and again four to six weeks post-discharge when they returned for a follow-up visit (or via phone).Participants self-reported significant sleep disturbances at both study time points. Of those participants with valid data at both time points (n = 28), there were no significant changes in mean scores from pre- to post-discharge with the exception of self-efficacy for sleep (SE-S) being significantly higher post-discharge. Preliminary qualitative findings suggested differences between those with ongoing sleep disturbances, those whose sleep disturbances had resolved, and those with no sleep disturbances at either time point.This analysis highlights individual variation in sleep throughout the process of inpatient treatment and transition to outpatient aftercare in individuals with alcohol dependence. Collecting quantitative and qualitative data concurrently and combining emerging themes from qualitative data with quantitative analyses allowed for a more thorough examination of this relatively novel area of research and provided information that can be utilized to inform future behavioral sleep interventions. Alcohography) .Insomnia is defined at the most basic level as difficulty falling or staying asleep and is relatively common in the U.S. . Sleep dSleep disturbances among individuals who are alcohol-dependent may be associated with increased risk of relapse to drinking following detoxification and rehabilitation , 18, 19)For individuals who are alcohol-dependent seeking inpatient treatment, both the initial adjustment to inpatient treatment and the transition from inpatient to outpatient status are time periods accompanied by many changes. The environment and structure of an inpatient facility warrant certain adjustments on the part of the individual. Upon discharge from an inpatient facility, continuity of care with diverse programmatic support structures have been utilized to help individuals maintain healthy lifestyle changes and maximize the likelihood of sustained sobriety ). “Transcombined with deductive quantitative techniques moves beyond traditional approaches and could potentially increase our knowledgebase [Exploring individual perspectives and experiences could provide a better understanding of sleep throughout recovery . In ordeedgebase . CollectThis study was approved by the NIH Addictions Institutional Review Board (IRB) at the National Institutes of Health . All participants enrolled in this study were first admitted to a clinical research facility providing inpatient detoxification and treatment under a screening and assessment protocol, which enrolls adults over 18 years of age seeking treatment for alcohol dependence. All participants received continued physical evaluations, inpatient treatment of alcohol withdrawal, psychosocial management, and an educational treatment program. Participants were eligible to receive up to six or more weeks of inpatient treatment followed by 16 weeks of optional outpatient treatment. Participants were paid for the study portions they completed based on NIH guidelines . All paror complete the follow-up study visit by phone.Participants were eligible for this study if they were 18 years of age or older, enrolled on the screening and treatment protocol (parent study), an inpatient for 21 days or more preceding discharge, not simultaneously enrolled onto a pharmacologic intervention study, able to understand the study and provide informed consent, and willing to return to the Clinical Center four to six weeks after being discharged from inpatient treatment for a follow-up visit Specific measures already collected upon inpatient admission as part of the screening and assessment protocol were used to characterize individuals who participated in this study. Approximately one week prior to participants' scheduled discharge, a study team member approached participants to begin the first segment of data collection for the study. Interviews were conducted and questionnaires were administered within one week of participants’ scheduled discharge date and again four to six weeks post-discharge when they returned for a follow-up visit (or via phone).The qualitative component of this study was based on individual semi-structured interviews. The interview questions were reviewed and pilot-tested by clinicians and investigators with extensive experience working with alcohol-dependent individuals. A second interviewer (MK or GW) was present at all interviews and introduced to the participants with an explanation that he or she would observe, take notes, and probe additional questions based on the participant’s responses. This strategy was employed to decrease the potential bias of only having one interviewer. Questions were focused on sleep patterns prior to becoming an inpatient, during the inpatient stay, and in anticipation of becoming an outpatient and were designed to complement quantitative data. The first interview covered perceptions and descriptions of sleep in the clinic to the home environment, while the second interview focused on the participants’ support system as well as barriers and facilitators to both sleep and sobriety. All interviews were conducted by the first author (AB) for consistency, with the exception of one follow-up interview conducted by the second author (MK). The qualitative phase of data collection was always conducted first to ensure that participants’ responses would not be unduly influenced by their having read the sleep-related surveys prior to being interviewed.Specific measures collected as part of the screening protocol were used to provide descriptive data on participants. The Comprehensive Psychopathological Rating Scale (CPRS) consists of 19 items that correspond to two CPRS-based subscales for affective and anxiety syndromes : 1) the Structured Clinical Interview for Diagnostics and Statistics Manual-IV (DSM-IV) (SCID-I) is the standard interview to evaluate criteria for a psychiatric diagnosis, including that of alcohol dependence and disorders that are frequently co-morbid with alcohol dependence [CIWA-AR: Clinical Institute Withdrawal Assessment-Alcohol Revised is a validated tool is used to determine the severity of alcohol withdrawal based on symptoms and physical signs [The pendence . It is aal signs .The Pittsburgh Sleep Quality Index (PSQI) is a 19-item, self-rated questionnaire used to measure sleep quality and disturbances over a one-month (30 days) time interval. A global summation score higher than five is indicative of poor sleep quality or “disturbed” sleep . The PSQThe Epworth Sleepiness Scale (ESS) is an eight-item self-administered questionnaire that provides a measure of an individual’s general level of excessive daytime sleepiness over a one week time period . IndividThe Dysfunctional Beliefs and Attitudes about Sleep Scale (brief version: DBAS-16) is a 16-item questionnaire that assesses sleep-related cognitions including faulty beliefs and appraisals, unrealistic expectations, and perceptual and attention bias . Higher The Penn Alcohol Craving Scale (PACS) is a clinical tool for practitioners to measure alcohol craving. It is a five-item self-administered instrument that measures frequency, intensity, and duration of thoughts about drinking along with ability to resist drinking (possible range: 0–30) with demonstrably excellent internal consistency, predictive validity, construct validity, and discriminant validity . The TimEach audio-recorded interview was transcribed and quality checked prior to analysis. A codebook was developed based on emergent themes related to transitions and changes in sleep over time from the interviews. A team of two coders independently reviewed a sub-set of transcripts. Discordant coding was discussed until consensus among the coding team was achieved. NVivo (version 10.0) was utilized for further qualitative analyses and to calculate inter-rater reliability percentages.Once the iterative process of consensus building was complete, a representative from the clinical team and a mixed methods expert from the NIH Clinical Center validated the themes and codes presented herein. To ensure that the trustworthiness of qualitative data was preserved, three criteria assessing rigor were considered: creditability, auditability, and fittingness of the data .Statistical analyses of quantitative results were conducted with the Statistical Package for Social Sciences (SPSS) software, version 22.0. All quantitative data were double-data entered, cross-checked, and reconciled where necessary. Sleep quality (PSQI) and relapse status (TLFB and other sources) were the main outcomes of interest. Paired t-tests and McNemar tests were used to compare pre- and post-discharge differences in these main outcomes. Mixed model repeated measure analyses were used to assess the sleep quality (PSQI) changes over three study time points. A p value < 0.05 was considered significant for all analyses. Missing data was assumed to be missing at random.convergent parallel design, wherein both quantitative and qualitative data were collected simultaneously and each method of examination was given equal priority [The format for the use of mixed methods was a priority . Quantitpriority .General demographics and clinical variables are presented in Of the 28 participants who returned for the follow-up visit, 14 (50%) had data on relapse . Of the eight participants who had valid Timeline Follow-Back (TLFB) data at follow-up (4–6 weeks post-discharge), only one had relapsed within the 4–6 week post-discharge time frame, reporting drinking four of the 34 days with an average of 7.13 drinks per drinking day. The nine participants who did not mention drinking during their follow-up interview were treated as “missing” since verification of sobriety was not possible  discussed the actual barriers and facilitators they had experienced during the follow-up interviews. Participants discussed sleep-related behaviors  at both time points (81.8% at pre-discharge and 78.6% at post-discharge). A considerable number of participants 39.4% discussed “racing thoughts” while reflecting on their sleep or drinking patterns during the first interview.A majority of participants (72.7%) discussed some type of fear or uncertainty surrounding either the adjustment to becoming an inpatient and/or returning back home during the pre-discharge interview. Similarly, a large majority of participants (82.1%) discussed the level of difficulty or ease of their transition back home during their follow-up interviews. While only 18.2% of participants discussed a healthy lifestyle in the context of their recovery process during their inpatient admission, almost half of those who returned for the follow-up interview endorsed healthy lifestyle changes since returning home. Most participants (60.6%) identified We examined differences in sub-scales of the PSQI by time point in The mean PSQI scores approximately one week pre-discharge and 4–6 weeks post-discharge remained above the cut-off for “disturbed sleep”  and 4–6 weeks post-discharge  PSQI scores (p < .001 for both comparisons). No significant difference was found between one week pre- and 4–6 weeks post-discharge.In addition to the McNemar test, a repeated measures linear mixed model using 88 time points from all 33 cases found that the estimated marginal mean for baseline sleep disturbances as measured by the PSQI on day 2 of inpatient treatment  was significantly higher than statistically significant differences in demographic or sleep-related variables between those who relapsed, those who were sober, and those whose relapse data were missing, likely due to the small sample size. Additionally, there were no differences in baseline average number of drinks per day in the 90 days prior to admission between the same groups . However, demographic and clinical variables are presented by relapse status (if known) and “trajectory” of sleep quality based on PSQI scores pre- and post-discharge in developing sleep disturbances post-discharge based on PSQI scores, although some participants outlined negative changes in sleep from pre- to post-discharge qualitatively. Those who relapsed had higher craving scores  and those with no sleep disturbances at either time point had the lowest craving scores of any group, but the differences were not statistically significant. All of the participants whose sleep disturbances resolved were non-White.There were no Preliminary qualitative findings suggested differences between those with ongoing sleep disturbances (n = 11), those whose sleep disturbances had resolved (n = 8), and those with no sleep disturbances at either time point (n = 6). Only one of the eight individuals whose sleep disturbances resolved and two of the 11 individuals with ongoing sleep disturbances mentioned healthy lifestyles during their pre-discharge interviews. Only one of the eight individuals whose sleep disturbances had resolved mentioned “racing thoughts” during their pre-discharge interview. Lastly, to complement the quantitative results and summarize the overarching emergent themes from the interviews, we present key qualitative findings by theme, specifically those related to the transition from inpatient to outpatient, in This analysis highlights individual variation in sleep throughout the process of inpatient treatment and transition to outpatient aftercare in individuals with alcohol dependence. Collecting quantitative and qualitative data concurrently and combining emerging themes from qualitative data with quantitative analyses through triangulation (simultaneously) allowed for a more thorough examination of this relatively novel area of research and provided information that can be utilized to inform future behavioral sleep interventions. As previously discussed, the rehabilitation process represents a time of transformation. Inpatient facilities may represent an environment conducive to initiating lifestyle changes, including those which could improve sleep.As with previous studies , 47, theSimilar to our previous work establishing the prevalence of sleep disturbances throughout the inpatient stay, there was low variability in daytime sleepiness levels (ESS) and average scores on the measure were not indicative of “excessive” daytime sleepiness. Measures of sleep-related safety behaviors (SRBQ) and dysfunctional beliefs about sleep (DBAS-16) remained relatively stable at both time points, despite participants discussing many changes occurring throughout the transition from inpatient to outpatient during their interviews. Self-efficacy for sleep (SE-S) improved significantly with inpatient standard of care which did not include specific interventions focused on sleep hygiene. However, study participants discussed bedtime routines and strategies for sleep they initiated as inpatients. In the inpatient program, it is possible that staff members could have provided suggestions for non-pharmacologic interventions. Additionally, there is a “schedule” for the unit when activities end each night and begin the next morning–and patients typically adjust accordingly. Despite these potential confounding factors, self-efficacy will be explored as an important variable in sleep behavior change in a larger sample, given its sensitivity in this small sample.no sleep disturbances at either time point and 2) those whose sleep disturbances resolved by the post-discharge time point were less likely to endorse “racing thoughts” while inpatients. These findings offer preliminary support to the idea that “stabilizing” sleep during the inpatient phase may be especially important.The demographic and clinical variables presented in The mixed methods nature of this study allowed for the collection of rich and diverse information. In particular, the wealth of qualitative data accrued and the rigorous process through which they were analyzed was useful in describing the complex phenomenon of sleep throughout recovery. However, this study is not without limitations. Given a small sample size and subsequently low power levels, the quantitative analyses were strictly exploratory in nature and were meant to complement qualitative findings. The sample was non-representative; findings should not be generalized to all individuals who are alcohol-dependent, seeking treatment, and willing to return for a follow-up visit. Finally, at discharge, all but three participants were prescribed at least one medication that could have potentially altered their sleep. It is unclear how this use of sleep medications affected the nature of the qualitative narratives provided by the participants.Future efforts should include following individuals for a longer period of time post-discharge when possible to capture participants’ experiences longitudinally and explore whether lasting changes to sleep parameters occur. The quotes reflected in this paper coalesce around the overarching theme of structure; the appreciation of re-developing routines during inpatient treatment may be conducive to changing sleep habits through a tailored behavioral sleep intervention. At a minimum, sleep should be monitored in alcohol treatment programs in order to understand it both as a potential relapse trigger and an important component of a healthy lifestyle post-discharge. The most effective mechanism for assessing sleep in this particular population  still needs to be explored.transition periods throughout the process of recovery highlights the important role they may play in sleep quality and eventually relapse. Of particular importance may be learning how to capitalize on positive lifestyle changes post-discharge from inpatient rehabilitation facilities that emerged qualitatively in this study, particularly those changes introduced during the inpatient phase of recovery and sustained. This study fills a gap in the literature by characterizing sleep throughout the rehabilitation process and ongoing maintenance of abstinence (or relapse).This research confirms a high prevalence of sleep disturbances in a sample of treatment seeking individuals who are alcohol-dependent throughout various stages of recovery that had not yet been explored in detail using a mixed methods approach. Patient-reported outcomes and in-depth interviews provided a clearer picture of individual experiences throughout recovery and the complexity of alcoholism and associated co-morbid conditions, compared to either data source individually. Capturing the essence of S1 TableDescription of interviewer prompts for both the pre-and post-discharge interviews.(DOCX)Click here for additional data file.S2 TableDescription of themes relevant to transition from pre- to post-discharge and corresponding frequency of endorsements.(DOCX)Click here for additional data file.


Human functional magnetic resonance imaging (fMRI) brain networks have a complex topology comprising integrative components, e.g. long-distance inter-modular edges, that are theoretically associated with higher biological cost. Here, we estimated intra-modular degree, inter-modular degree and connection distance for each of 285 cortical nodes in multi-echo fMRI data from 38 healthy adults. We used the multivariate technique of partial least squares (PLS) to reduce the dimensionality of the relationships between these three nodal network parameters and prior microarray data on regional expression of 20 737 genes. The first PLS component defined a transcriptional profile associated with high intra-modular degree and short connection distance, whereas the second PLS component was associated with high inter-modular degree and long connection distance. Nodes in superior and lateral cortex with high inter-modular degree and long connection distance had local transcriptional profiles enriched for oxidative metabolism and mitochondria, and for genes specific to supragranular layers of human cortex. In contrast, primary and secondary sensory cortical nodes in posterior cortex with high intra-modular degree and short connection distance had transcriptional profiles enriched for RNA translation and nuclear components. We conclude that, as predicted, topologically integrative hubs, mediating long-distance connections between modules, are more costly in terms of mitochondrial glucose metabolism.This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. The neuron is the anatomical unit of nervous systems and the action potential is the physiological unit of communication between neurons. Functional MRI is incapable of resolving cellular structures and processes on these microscopic scales of space and time in humans. A single fMRI voxel (around 1 cubic millimetre) represents approximately 1–2 million neurons and other cells. The sampling rate of fMRI (approx. 1/60 = 0.02 Hz) is too slow to resolve rapid transients like action potentials, or the full spectrum of electrophysiological oscillations (0.1–1000 Hz). An fMRI time series will typically only resolve very low-frequency oscillations (approx. 0.1 Hz) and these ‘resting-state’ dynamics will represent local blood oxygenation changes coupled to neuronal activity rather than a direct measure of neuronal electrophysiology.The mechanistic links between the blood oxygen-level dependent (BOLD) contrast measured by fMRI and underlying neuronal states of excitation and inhibition have been extensively investigated . There iTo set against this list of arguments against fMRI, there are also two important advantages to consider. First and foremost, fMRI is remarkably safe and accessible for human participants including patients. Second, despite the caveats about its physiological origins, fMRI has turned out to be a highly reliable and plausible marker of local or regional brain (de-)activation by diverse cognitive tasks , as wellIn this context, it has been exciting to see new opportunities recently emerging to link fMRI phenomena to the genomic substrates of human brain organization. A pivotal role has been played by the Allen Institute for Brain Science (AIBS), which has measured expression of all approximately 20 000 genes in the human genome at each of approximately 500 locations in six post-mortem adult human brains, and publically released these data . On thisHuman fMRI research is arguably negotiating a shift from an interventional paradigm, focused on local signal changes estimated in response to experimentally controlled changes of cognitive state, to a more naturalistic paradigm focused on estimating very low-frequency oscillations and their correlation or functional connectivity between pairs of brain regions or voxels . FunctioThe complex topology of human fMRI networks—comprising small-worldness, hubs and modules among other non-random and non-regular features—has been accounted for theoretically by an economical model of competition between selection pressures for both low biological cost and high topological integration ,19. Low On this basis, we predicted that human fMRI network nodes with high inter-modular degree, mediating many long-distance connections between modules, would be associated with a distinctive gene expression profile compared to the transcriptional profile of nodes with high intra-modular degree, mediating many short-distance connections within the same module. To test this, we measured inter-modular degree, intra-modular degree and connection distance, for each of 285 regional nodes, by graph theoretical analysis of resting-state, multi-echo echoplanar imaging data on 38 healthy young adults. We anatomically matched the fMRI network parameters at each node to detailed human brain maps of whole-genome expression provided by the AIBS . Then, we used the multivariate technique of partial least squares (PLS) to identify combinations of approximately 20 000 genes whose regional expression profiles best predicted the fMRI network parameters . Finally2.(a)n = 300) was sub-sampled from the primary cohort for structural and functional MRI assessments and more detailed cognitive testing. Here, we used fMRI data from 40 participants sampled from the top two age strata of the secondary cohort (20–24 years), with 10 men and 10 women in each of the two strata. Participants were excluded if they were currently being treated for a psychiatric disorder or for drug or alcohol dependence; had a current or past history of neurological disorders including epilepsy or head injury causing loss of consciousness; had a learning disability requiring specialist educational support and/or medical treatment; or had a safety contraindication prohibiting MRI.In total, 2500 healthy young people in the age range 14–24 years were recruited in north London and Cambridgeshire and provided details by postal questionnaire on socio-demographics and mental health. This primary cohort was stratified into five contiguous age-related strata: 14–15 years inclusive, 16–17 years, 18–19 years, 20–21 years and 22–24 years. Recruitment within each stratum was evenly balanced for sex and ethnicity. A demographically balanced cohort (MRI scanning was conducted at the following three sites: (i) the Wellcome Trust Centre for Neuroimaging, London, (ii) the Wolfson Brain Imaging Centre, Cambridge, and (iii) the Medical Research Council Cognition and Brain Sciences Unit, Cambridge. All sites were identically operating 3 T whole-body MRI systems  with standard 32-channel radio-frequency (RF) receive head coil and RF body coil for transmission.Resting-state fMRI data were acquired using a multi-echo echoplanar imaging sequence with online reconstruction : repetitdoi://10.5281/zenodo.50505). Wavelet decompositions were implemented using an open source, R-based software library: brainwaver v. 1.6, which is freely downloadable at: https://cran.r-project.org/web/packages/brainwaver/index.htmlPre-processing and ME-ICA was performed with the AFNI tool meica.py  which we(b)2 on the surface). This parcellation template image in standard space was transformed to the native space of each individual's fMRI dataset and regional BOLD time series were estimated by averaging the time series over all voxels in each of the 308 parcels. Some regions  were excluded because of low regional mean signal in at least one subject, and two participants were excluded because of poor co-registration between functional and anatomical data. Two further regions were later excluded from the analysis due to outlier values of the corresponding gene expression data . The fMRI dataset available for analysis thus consisted of 38 individual matrices of regional mean BOLD oscillations at each of 285 cortical regions.To define regional nodes or parcels of cortex for network analysis, we used a backtracking algorithm  to parceFunctional connectivity was estimated by the pairwise wavelet correlations between each possible pair of regional mean fMRI time series. The resulting functional connectivity or association matrices were thresholded to construct binary (undirected and unweighted) adjacency matrices or graphs . We usedQ(G), of a graph is proportional to the number of intra-modular edges compared to the number of intra-modular edges expected in a random graph [γ defining the coarseness of the modular partition was set at γ = 2, yielding eight modules. We demonstrate in the electronic supplementary material that our key results are robust to this parameter setting.We used standard network metrics to characterize the topology of the fMRI network . To estimate the inter- and intra-modular degree of each node, we first had to define the modular community structure of each network. The modularity, om graph . The proom graph  over 100k(i), i = 1,2,3 … 285, was calculated as the total number of edges connecting it to the rest of the network. Total degree was subdivided into the intra-modular degree kintra(i), i.e. the number of edges connecting the ith node to other nodes within the same module, and the inter-modular degree kinter(i), i.e. the number of edges connecting the ith node to nodes in other modules. For each node, we also estimated the participation coefficient, PC(i), which has been widely used as a measure of nodal role in a modular community structure [ik(m) is the number of edges between node i and all nodes in module m, and the sum is over all M modules [kintra(i), kinter(i) and PC(i) were estimated for each subject with respect to the prototypical modular structure estimated for the sample as a whole. For each edge, we also estimated its connection distance (in millimetres) as the Euclidean distance between the linked pair of regional nodes in standard anatomical space. Topological metrics were calculated using the Brain Connectivity Toolbox, v. 2014-04-05 [For each subject's binary graph, the degree centrality of each node, tructure ,41:2.1wh modules . The PC 14-04-05 .(c)http://human.brain-map.org/static/download; [Microarray data for six donors  were available from the AIBS . Five oZ-transformation to normalize mean expression of each gene for variance in its expression . The final output was a (20 737 × 285) matrix, T, of Z-scored expression values for each of 20 737 genes estimated in 285 fMRI regions. Gene expression data for individual genes or subsets, such as the 19 genes selectively over-expressed in human supragranular cortex [T).We used the Maybrain package  to match the centroids of the regions of the fMRI parcellation template to the closest regional gene expression profile. Microarray data were averaged across all samples from all donors in homologous regions in both hemispheres. The data were also averaged across probes corresponding to the same gene, excluding probes that were not matched to gene symbols in the AIBS database. We used the r cortex , and ther cortex , were av(d)Each of the 308 regions in the cortical parcellation scheme was assigned to a cytoarchitectural type according to the classification scheme of von Economo & Koskinas  (figure (e)To explore the associations between topological centrality and distance metrics at each node of the fMRI networks, and transcription across the whole genome, we used the multivariate technique of PLS.T comprised the predictor variables; the (285 × 3) matrix C comprised the response variables of intra-modular degree, inter-modular degree and mean connection distance for each regional node of the fMRI networks.PLS is an established and widely used multivariate method for identifying associations between a set of response variables and a set of predictor variables, especially when the number of predictor variables exceeds the number of observations, and when the predictor variables are highly interdependent or multi-collinear ,47. In tT, PLS finds components from T (gene expression) that have maximum covariance with the response variables in C (fMRI network measures). The total number of components needed to exactly fit the response C is limited by the number of observations (in this case the number of brain regions). The PLS components are ranked by covariance between predictor and response variables, so the first few PLS components  will provide the optimal low-dimensional representation of the covariance between the higher dimensional data matrices .PLS is related to principal component analysis (PCA) and combines a PCA-style dimensionality reduction with linear regression. While PCA identifies the so-called principal components in the data that best explain the variance in the predictor variables We used non-parametric data resampling techniques for inferential analysis of PLS results. We tested the goodness of fit of low-dimensional PLS components by repeating the analysis 1000 times after shuffling the regional labels assigned to each set of three response variables. We note that the dependency between spatially neighbouring regions that exists in both fMRI and transcriptomic datasets may lead to an over-estimation of significance by this simple, spatially naive null model. In the electronic supplementary material, figure S4, we confirm that the PLS results were robust to the use of more sophisticated null models that account for spatial correlations expected due to homogeneous tissue type within anatomical regions. We used bootstrapping  to estimate the error on the PLS weights estimated for each gene. The ratio of the weight of each gene to its bootstrap standard error was used to rank the genes according to their contribution to each PLS component. The list of ranked genes for the first three PLS components can be found in the electronic supplementary material: Vertes_PLS_GOenrichment.xlsx(f)http://cbl-gorilla.cs.technion.ac.il, version 30 January 2016) [p-value for significance of each term so that the false discovery rate (FDR) over all GO terms was PFDR < 0.001 and (ii) for visualization purposes we also discarded enriched GO terms for biological processes associated with over 2500 genes, which typically correspond to general ontological terms near the top of the hierarchy, such as ‘cellular process’ or ‘organelle organization’. All excluded terms are still listed and highlighted in grey in the electronic supplementary material: Vertes_PLS_GOenrichment.xlsx.We used gene ontology (GO) tools for enrichment analysis of the ranked gene lists defined by the first three PLS components (Gorilla: ry 2016) ,28. The ry 2016) . Enrichmhttp://revigo.irb.hr) to summarize the list of significant GO terms by selecting representative subsets of the terms using a simple clustering algorithm that relies on measures of semantic similarity between terms [10 of the p-value for the significance of each term. Clusters in these plots therefore represent families of related GO terms, and the GO term associated with the largest marker in each cluster can be annotated to label the whole cluster in a representative manner.To visualize the results of whole-genome enrichment analysis, we used the online tool REViGO (en terms . For exaa priori with (i) supragranular layers of human cortex  [For the more hypothetically driven enrichment analysis of gene lists associated ed, HSE)  or (ii) ed, HSE)  we also 3.(a)n = 38 healthy volunteers aged 20–24 years. We focus most attention on the characteristics of the graph with 10% connection density. This fMRI network had complex topological properties consistent with many prior studies [figure 1a–d and electronic supplementary material for definitions of these widely used network metrics).We constructed graphs of the human brain functional network by binary thresholding of the pairwise inter-regional wavelet correlation  matrices estimated for  studies , includik), inter-modular degree (kinter), intra-modular degree (kintra) and PC. We note that definition of kinter, kintra and PC will depend on both the network connection density and the resolution parameter, γ, defining the coarseness of the modular partition. In coarser decompositions with fewer modules, for example, fewer edges will be classed as inter-modular and the inter-modular degree distribution will shift to the left. We show in the electronic supplementary material that similar results were obtained with a coarser decomposition defining only four modules, as well as with a range of thresholds on the functional connectivity matrix, yielding networks with connection densities in the range 10–30%. For each node, we also estimated four spatial parameters: the connection distance  and the three-dimensional  coordinates of each node's location in anatomical space .At each node in the fMRI network, we estimated four topological parameters: total degree .The topological parameters were correlated with each other by construction: total degree, y location, meaning that intra-modular hubs were concentrated in posterior cortical regions; whereas inter-modular degree and PC were positively correlated with z location, meaning that inter-modular hubs were concentrated in superior cortical regions. The spatial patterning of these parameters can also be represented by anatomical maps of nodal topology and connection distance (a). Hubs defined by high intra-modular degree were concentrated in occipital and somatosensorimotor cortex, or spatially patterned on the rostro-caudal axis; whereas hubs defined by high inter-modular degree and PC were concentrated in somatosensorimotor and superior parietal cortex, or spatially patterned on the dorsoventral axis. Nodes with greater connection distance were concentrated in lateral cortex, reflecting the existence of long-distance, inter-hemispheric connections between bilaterally homologous cortical areas (a–c).The three-dimensional location of nodes was correlated with their topological properties : intra-mdistance a. Hubs dal areas a–c.Figuf, §2d) [kintra: F6,278 = 22.7, p < 0.001; kinter: F6,278 = 11.1, p < 0.001). Intra-modular degree was highest in primary and secondary sensory cortex and lowest in association cortex and limbic regions. Inter-modular degree was highest in primary motor cortex and lowest in secondary sensory cortex. Because both total degree and PC were constructed from intra- and inter-degree, they also showed significant differences between cytoarchitectonic classes , with similar patterning to kintra and kinter, respectively. The average nodal connection distance was also significantly different between cytoarchitectonic classes . The longest connection distances were in association cortex, whereas the shortest distances were in secondary sensory cortex and limbic regions  . Both in(b)kintra and kinter) and distance parameters was related to local expression of approximately 20 000 genes, we co-registered the fMRI regional nodes in the same anatomical space as the AIBS dataset of human brain gene expression. For each fMRI node, we then estimated the mean regional expression of each of 20 737 genes (§2e). To explore a low-dimensional representation of the multivariate relationships between the matrix of response variables  and the matrix of predictor variables (gene expression profiles) we used PLS (§2e).To investigate how this spatially patterned set of fMRI network nodal topology (p < 0.001) for a spatially naive permutation test .The first three PLS components accounted for about 37% of the total variance in nodal metrics and this measure of the goodness of fit was statistically significant  that were not explicitly included in the PLS model but were known to be significantly correlated with intra-modular degree , with positive PLS1 scores located in posterior cortical nodes . Nodal PLS1 scores were also significantly different between cytoarchitectonic classes  with positive PLS1 scores located in primary and secondary sensory cortical areas.The first PLS component (PLS1) was positively correlated with intra-modular degree and not significantly predictive of inter-modular degree . This mer degree . Thus, Pal nodes a,c. Nodax, y, z) that were not explicitly included in the PLS model but were known to be significantly correlated with inter-modular degree  and x  axes, with high PLS2 scores located in superior and lateral cortex . Nodal PLS2 scores were also significantly different between cytoarchitectonic classes  with the highest PLS2 scores located in primary motor and primary sensory cortical areas and the lowest scores located in secondary sensory cortex. We note that the association between PLS2 and cytoarchitecture depended on the coarseness of the modular partition because coarser partitions by definition lead to longer inter-modular connections .By contrast, the second PLS component PLS2) was predictive of inter-modular degree and not significantly predictive of intra-modular degree . This me was predr degree . Thus, Pl cortex b,d. NodaIn short, the first two PLS components defined independent gene expression profiles that were specifically associated with (high) intra-modular degree and (short) connection distance (PLS1) or with (high) inter-modular degree and (long) connection distance (PLS2). The third PLS component defined an independent gene expression profile that was not significantly predictive of inter- or intra-modular degree (or PC), but was significantly predictive of connection distance, and was spatially patterned in all three dimensions . Since we were hypothetically motivated to explore the relationships between fMRI network topology and gene expression, PLS3 was not as relevant as PLS1 or PLS2. The fourth and subsequent PLS components inevitably explained progressively smaller proportions of covariance between network metrics and gene expression, and will be less robust to noise. We therefore focus further attention only on the first two components of the PLS solution.(c)Given the statistical independence of PLS components, these results indicate that there are specific or distinct gene expression profiles associated with different nodal roles in fMRI networks. We used enrichment analysis to resolve the differences in transcriptional predictors of nodal topology and connection distance in more detail. We found that PLS1 and PLS2 components were significantly enriched for distinct biological functions.PFDR < 0.001) for GO terms related to transcriptional regulation in the nucleus. By contrast, genes significantly over-expressed in association with high inter-modular degree and longer connection distance (positively weighted on PLS2) were significantly enriched (PFDR < 0.001) for GO terms related to oxidative metabolism and mitochondria (Genes significantly over-expressed in association with high intra-modular degree (positively weighted on PLS1) were significantly enriched  to test each PLS component for over-expression of a set of genes anatomically specific to supragranular layers of human cortex  and (iip < 0.001); but HSE genes were not significantly enriched among the over-expressed genes positively weighted on PLS1.It has been shown  that thep > 0.05). We note, however, that this result depended on the coarseness of the modular partition in a predictable manner, with coarser partitions by definition constraining inter-modular links to span longer distances. As connection distance was weighted more strongly on PLS2, AG genes were correspondingly more enriched in PLS2 in the analysis of the coarser four-module community structure .Separately, it has been shown  that a s4.The biological validation of human fMRI networks has been challenging, not least because there are fundamental questions outstanding about the biological sources of the BOLD signal itself. We cannot yet securely reduce the basic fMRI observation of inter-regional correlation between pairs of functionally connected BOLD time series to a mechanistic explanation in terms of cellular processes, neuronal physiology, neurovascular coupling or anatomical connectivity. This has made it difficult to test  economical models of human fMRI networks by the classical reductionist logic of explanatory mechanistic coupling between cellular processes, at a micro scale, and network topology metrics, at a macro scale .Caenorhabditis elegans [Most of the previous evidence for biological validity of human MRI connectomes has therefore rested on analogical rather than reductionist logic. Informative analogies make comparisons between a poorly understood system and a more certainly or completely understood system of the same type. There have been several studies recently supporting the value of this approach for comparative connectomics—comparing the topology of human neuroimaging networks to the topology of more biologically specified nervous systems . For exa elegans  includes elegans . Indeed, elegans –58. It s elegans .Here, we have provided further evidence in support of this economical model of brain network organization by a more reductionist approach. We spatially co-registered fMRI network parameters with whole-genome expression data on anatomically corresponding brain regions. We used the multivariate method of PLS to define the gene expression profiles that were optimally predictive of fMRI network parameters. We found that the first two PLS components were specifically predictive of distinct nodal network phenotypes: PLS1 was predictive of high intra-modular degree and short connection distance; whereas PLS2 was predictive of high inter-modular degree and long connection distance  and that individual differences in gene expression can have a marked effect on group statistics .It was also notable that the genes associated with inter-modular degree and long distance (positively weighted on PLS2 in these data) were enriched for a set of 19 genes, expressed specifically in human supragranular cortex, that may have been necessary for the characteristically human evolution of cortico-cortical connectivity and associative cognitive processes . The HSEInterpreting the relationship between gene expression and network topology is potentially complicated by the spatial patterning of both transcriptional and topological phenotypes. Regional co-expression, or sharing of the same gene expression profile between a pair of brain regions, is related to the spatial distance between them: regions that are closer to each other will have greater genomic co-expression. Functional connectivity between regions is also conditional on distance: regions that are closer to each other are more likely to have correlated fMRI time series and so to form clusters and modules of locally inter-connected nodes in fMRI brain graphs. The question arises: does an association between gene co-expression and fMRI connectivity trivially reflect the confounding effect of distance? Previous studies have been concerned that topological clusters and modules of nodes may have transcriptional profiles in common simply because they are spatial neighbours, or members of the same cytoarchitectonic class . For exay-axis, whereas inter-modular degree was correlated with nodal location on the z-axis and connection distance was correlated with nodal location on the x-axis. PLS analysis enabled us simultaneously to explore the relationships between all three network parameters and the whole genome. We found two distinct components of gene expression that were specifically related to different aspects of nodal topology and connection distance, and had different spatial patterning as well as differential enrichment for biological processes. This pattern of results is not obviously attributable to a homogeneous and spatially isotropic effect of distance as a confounding factor of both genomic co-expression and functional connectivity [Our analysis of network topology has focused on nodes rather than edges and we have shown that different nodal properties have different spatial patterning, e.g. intra-modular degree was correlated with nodal location on the ectivity ,64,68. IThere are a number of theoretical and methodological limitations to this work. First, the results reported here are correlational, not causative. More generally, there remains an explanatory gap in determining whether and how these specific gene profiles support short-range intra-modular connectivity (PLS1) or long-range inter-modular connectivity (PLS2). Second, the matching between fMRI and transcriptional data is imperfect as the transcriptional data are based on six human brains (mean age = 42.5 years) sampled at approximately 500 locations in each hemisphere, whereas the fMRI data are recorded from 38 healthy young adults (mean age = 22 years) sampled at 308 locations across the cerebral cortex. Third, the interpretability of enrichment analyses based on these microarray data is hampered by the fact that expression was not measured separately in different cell types. Up- or down-regulation of a gene may therefore equally represent variations in the density of certain cell types enriched for that gene or variation of expression levels of the gene within a cell type. Fourth, we approximated the distance between connected nodes by the Euclidean (straight line) distance, which is anatomically unrealistic, especially for inter-hemispheric connections between posterior parietal and anterior prefrontal cortex which follow a nonlinear trajectory constrained by the contours of the corpus callosum. In addition, our nodal measure of connection distance averaged the distance of all edges, whereas it would be informative in future studies to distinguish between the nodal distance of intra-hemispheric and inter-hemispheric or trans-callosal connections.Nonetheless, it is encouraging to see that reductionist strategies, linking macro network properties measured in human fMRI to the underlying micro organization of cortical cytoarchitectonics and gene expression, are increasingly tractable and informative. The fMRI/mRNA results reported here have provided mechanistic support for the economic model that highly integrative network nodes, mediating many long-distance connections between modules, are metabolically expensive.


To investigate the effects of functional strengthening  and analytical strengthening (using repetitive movements) on level of activity and muscular strength gain in patients with chronic hemiparesis after stroke.A randomized, assessor-blinded trial was conducted in a therapist-supervised home rehabilitation program. Twenty-seven patients with chronic stroke were randomly allocated one of two groups: functional strengthening (FS) (n=13) and analytical strengthening (AS) (n=14). Each group received a five-week muscle strengthening protocol  including functional movements or analytical movements, respectively. Pre-, post-, and ten-month follow-up outcomes included the Upper-Extremity Performance Test (primary outcome), Shoulder and Grip Strength, Active Shoulder Range of Motion (ROM), the Fugl-Meyer Assessment, and the Modified Ashworth Scale (MAS) (secondary outcomes).There was significant improvement in the Upper-Extremity Performance Test for the combined unilateral and bilateral task scores in the FS Group  in the 10-month follow-up. No significant difference was observed between groups in the other outcomes (p>0.05).A five-week home-based functional muscle strengthening induced positive results for the upper-extremity level of activity of patients with moderate impairment after chronic stroke. However, it can accompany other motor problems and is recognized as a limiting factor for rehabilitation-,-,,Several studies have reported that activity-dependent brain plasticity is proportional to the complexity of motor learning and correlates with functional recovery after strokeTherefore, the aim of this study was to determine whether a five-week home-based program of functional strengthening was more effective than analytical strengthening for improving UE activity levels in subjects with chronic hemiparesis.,This prospective, single-blinded randomized clinical trial was registered and allocated by the Brazilian Clinical Trials Registry (identifier number RBR 22Y7P9). It included concealed randomization and blinded assessments according to the CONSORT guidelines for randomized clinical trialsParticipants were recruited from Mãe de Deus Hospital and Grupo Hospitalar Conceição in Porto Alegre, Brazil, by reviewing medical records of patients admitted in the previous 5 years. The inclusion criteria consisted of: (1) six months to five years since the onset of a unilateral stroke; (2) ability to understand simple instructions Patients were matched based on muscle strength since it is an important factor in determining outcomes,All participants have received a 30-minute therapist-supervised home rehabilitation program three times per week for five weeks The load was set according to the ability to generate maximal force during shoulder flexion, as mentioned before. The weight used during exercises remained at 60% of maximum strength measured during the baseline evaluationFS Group: Participants assigned to the FS group performed reaching-to-grasp movements against resistance. This intervention was designed to incorporate the repetitive nature of functional tasks and encouraged different grasping configurations by using objects that varied in size and shape. The previously established weight for each participant was placed within the object and remained throughout the intervention. Movements involving shoulder abduction, flexion, and adduction were performed to reach and grasp objects (plastic containers) at different heights. Participants were instructed to extend and flex their fingers to pick up a pot that was on a lower surface, place it on a higher surface, drop it, then pick up another pot with different diameter and place it on a lower surface, and so forth. During the first eight sessions of the protocol, a shoulder range of motion of 60 degrees was used, and in the remaining seven sessions, the shoulder range of motion was increased to 90 degrees. This range of motion was selected in order to avoid secondary pain as result of possible scapular dyskinesia. Even though the size of the pots could vary, the weight was kept constant.AS Group: Participants assigned to the AS group performed UE strengthening using repetitive movements without a functional goal. Repetitive exercises were performed with a dumbbell (which was placed in the patient’s hand by the therapist) in shoulder abduction, flexion, and adduction with range of motion similar to the FS group (60 and 90 degrees progressively).Both groups were instructed to perform at the same level of intensity and the same number of sessions. The final range of motion (60 or 90 degrees) was visually controlled by the therapists. The programs consisted of three sets of 12 repetitions Measurements were performed at baseline, immediately after treatment (outcome), and 10 months after randomization. All measures were taken at the patient’s home by a research assistant who was blinded to group allocation. The primary clinical outcome was activity level  and was assessed by The Upper-Extremity Performance Test Secondary outcome measures included shoulder and grip strength, active shoulder range of motion (ROM), motor recovery of the UE, and muscle tone. Three grip strength measures were recorded in a standardized position and instruction using the Jamar® dynamometer . Three shoulder strength measures were also recorded in a standardized position and instruction with a load cell . The highest score was used for the analysis. Standard goniometry was used to measure active shoulder flexion ROM. The improvement in motor impairment of the UE was evaluated with the UE section of the Fugl-Meyer (UE-FM) assessment scaleThe primary clinical outcome  was chosen for the sample size calculation. Based on our previous dataResults are presented as median (min-max) or mean and standard deviation (SD). Data normality was tested using the Shapiro-Wilk test, and the homogeneity of variance was tested by Levene’s test. Only grip force and active shoulder ROM showed normality. To determine differences in those evaluations, a two-way analysis of variance (ANOVA) test was used (group and time as factors). For non-parametric data, the Mann-Whitney U-test was used to compare the scores between groups. In the case of missing follow-up values, the last-observation-carried-forward (LOCF) method was used. This method inputs the outcome measures as follow-up determination. SPSS® 16.0  was used for data analysis. Significance was set at p<0.05.A total of 141 patients were screened, of whom 28 (20%) met the study criteria. One subject from the FS group dropped out before the baseline measure due to a second stroke. Consequently, the 27 participants were randomized as follows: 13 to FS and 14 to AS. After completion of the intervention, all patients performed the outcome measures. In the 10-month follow-up, six participants could not be reassessed due to death (3), unwillingness to participate (2), or relocation (1) .The biographical characteristics of the 27 patients are shown in The TEMPA scores significantly improved in both groups throughout the intervention period (outcome measures) and in the follow-up. A statistically significant difference was observed between the FS group and the AS group for the unilateral task analysis  immediately after treatment and the combined unilateral and bilateral task scores  in the 10-month follow-up  and 3.No statistically significant differences were observed for handgrip strength and for shoulder flexion strength between groups immediately after treatment or in the 10-month follow-up. For active shoulder ROM and for the motor assessment (UE-FM), no difference between group effects was observed.Muscle tone evaluation  demonstrated no difference between groups immediately after treatment or in the 10-month follow-up .This study was performed to determine the effect of functional and analytical strength training on UE activity levels in patients with chronic stroke. Observations made in this randomized trial partially confirmed our preliminary hypothesis. Functional strength training was able to induce greater improvements in the combined unilateral and bilateral activity of the paretic UE, as evaluated by means of the TEMPA scale immediately after the treatment and in the 10-month follow-up.,,,,Although morphological and physiological changes in motor units have been observed in patients with chronic stroke,,Another relevant factor for the improvement in activities of daily living is the active shoulder ROM. The loss of elbow-shoulder coordination and the decreased active ROM partly explain differences in movement patterns between stroke patients and healthy subjects,,,Muscle weakness is a significant motor impairment that mainly hinders voluntary movements,,-Current neurorehabilitation approaches advocate the use of functional tasks compared to performing systematic strength training with isolated exercises,One important point is that both strengthening protocols used in this trial induced no increase in muscle tone, agreeing with recent studies that have demonstrated the benefits of muscle strengthening without detrimental effects to patients after stroke, such as pain or exacerbation of spasticityThis study had some limitations. One limitation was the relatively small sample size. This sample did not reach the calculated sample size due to the specific inclusion and exclusion criteria. After intervention, we analyzed more than 90% of the sample, but the sample loss at follow-up was more than 20% of sample loss because of death, relocation, or unwillingness to participate. Our results are extended specifically to patients with chronic stroke and moderate paresis. Another limitation is the absence of a control group that received neither functional strength training nor analytical strength training. For this reason, our findings cannot be generalized to the broader community based on this study alone.In the present study, we reported positive results for muscle strength training during UE rehabilitation in patients with chronic stroke. Immediately after functional strengthening, patients improved their activity level for the paretic UE and this improvement was maintained in the follow-up. Therefore, a 5-week home-based functional muscle strengthening induced positive results for the UE activity levels of patients with chronic hemiparesis and moderate motor deficits. These findings have important implications for the rehabilitation of patients with chronic stroke and moderate hemiparesis.


The assembly of synthetic membranes provides a powerful tool to reconstruct the structure and function of living cells. de novo formation and growth of biomimetic membranes. These studies give us a deeper understanding of the nature of living systems and bring new insights into the origin of cellular life.The assembly of artificial cells provides a novel strategy to reconstruct life's functions and shed light on how life emerged on Earth and possibly elsewhere. A major challenge to the development of artificial cells is the establishment of simple methodologies to mimic native membrane generation. An ambitious strategy is the bottom-up approach, which aims to systematically control the assembly of highly ordered membrane architectures with defined functionality. This perspective will cover recent advances and the current state-of-the-art of minimal lipid architectures that can faithfully reconstruct the structure and function of living cells. Specifically, we will overview work related to the  Inspiration for this strategy was drawn from the Land's Cycle – a process which takes place in biological membranes for phospholipid remodeling.de novo membrane assembly.In nature, membrane-forming lipids are synthesized in multiple enzyme-catalyzed steps and involves several cofactors .14 Over 2.2.de novo formation of synthetic lipid membranes from reactive precursors. The first example based on a bioorthogonal approachi) catalyzed azide–alkyne cycloaddition (CuAAC)In situ membrane formation occurs spontaneously and does not require pre-existing membranes to house catalysts or precursors. Bioorthogonal click chemistry reactions take place at the interface of insoluble alkyl azide emulsion droplets and the monolayers of alkyne lysolipid that presumably coat the droplets. Steady-state fluorescence anisotropy measurements showed that the triazole phospholipid membranes closely resemble their natural counterparts in fluidity properties. Overall, the strategy is biomimetic in that it proceeds in aqueous medium with high specificity and a lack of background reactions in the absence of a catalyst.Given the relevance of mimicking biological systems, several groups have recently explored methodologies for the et al. demonstrated that the CuAAC reaction can be light-triggered by ruthenium tris-bipyridine [Ru(bpy)32+] complex under mild aqueous conditions.in situ formation of phospholipids in a high yielding manner, which subsequently self-assemble into synthetic membrane vesicles. Konetski et al. further demonstrated that the incorporation of a photoinitiator complex into the CuAAC reaction can be used to achieve spatiotemporal control over vesicle assembly.Follow-up work by Hardy et al. showed that a photo-initiated thiol-yne click chemistry reaction could be used to rapidly synthesize dithioether analogs of phospholipids in aqueous solution.In a separate work, Zhou 2.3.et al. utilized native chemical ligation (NCL)Based on a similar strategy, Brea et al. further showed that histidine ligation (HL)de novo generate amide-linked phospholipids  has been used to construct complex supramolecular assemblies from discrete molecular building blocks using chemical reactions carried out reversibly under conditions of equilibrium control.g the pH .34 The iMore recently, the Yi group used a similar approach to develop a novel class of pH-responsive vesicular structures from an equimolar mixture containing octyl amine and the supra-amphiphiles 1-[10-(4-formyl-phenoxy) decyl] pyridinium (FDP) or 1-methyl-3-[10-(4-formyl-phenoxy) decyl] imidazolium (FDI).3.in situ generation of membrane-forming material is required for their growth.38Growth of vesicle membranes composed of single-chain amphiphiles like fatty acids has been demonstrated simply by addition of fresh monomers.et al. reported the self-reproduction of giant vesicles (GV) driven by an imine hydrolysis reaction taking place in a membrane environment.et al. also showed that the growth and division of giant vesicles composed of various phospholipids and a cationic amphiphile can be coupled with the polymerase chain reaction (PCR) taking place inside the GVs  complex, which uses lauryl (dodecyl) azide for its own generation, as well as for the generation of triazole-containing phospholipids. Phospholipid formation led to growth of the membrane and occasional division events. In principle, such a system should be able to sustain efficient membrane reproduction if the precursors are continuously replenished.Simple autocatalytic reactions have been utilized in the past to drive the growth of membrane-bound vesicles. Wick de novo membrane formation with finely tuned physicochemical triggers or genetic circuits. Additionally, it would be desirable to employ non-amphiphilic water-soluble precursors to rule out non-specific interactions arising from incorporation of amphiphiles into the membranes.The current methods of artificial vesicle growth and division lack the sophistication or spatiotemporal control found in living cells.4.et al. have shown that reversible chemoselective reactions can be harnessed to achieve nonenzymatic spontaneous exchange and remodeling of both lipid tails and head groups in synthetic membranes.in situ membrane remodeling by lipid tail exchange also lead to subsequent micrometer scale changes in membrane morphology and the formation of distinct lipid microdomains  pathway of phospholipid synthesis.Linking gene expression with phospholipid membrane formation is one of the highly sought after goals of bottom-up synthetic biology.et al. showed that phosphatidylcholine synthesis can be effected by using four purified membrane proteins bound to a liposome membrane.et al. demonstrated that vesicles encapsulating a cell-free transcription/translation (TX-TL) system (PURE® system) can express two membrane proteins (GPAAT and LPAAT), that can catalyze the formation of new phosphatidic acid , thus limiting their scope of application towards vesicle growth and division.6.For the bottom-up construction of an artificial cell, a major goal will be the functionalization of the membranes with suitable proteins. In this section, we will discuss various methods of specific localization of both soluble proteins and integral membrane proteins to artificial membranes.6.1.e.g. palmitoylation, prenylation)e.g. glycerophosphoinositol (GPI) anchor].et al. described a methodology of covalent protein localization to giant unilamellar vesicle (GUV) membranes based on the chemoselective reaction between benzylguanine (BG)-functionalized phospholipid anchors and a SNAP-tagged GFP  lysophospholipid was imparted a dual role. In the first step, the lysolipid functioned as a detergent in solubilizing the protein in micelles. In the next step, the lysolipid reacted with a suitable partner  in a bioorthogonal manner to generate a phospholipid which assembled to form membranes along with spontaneous reconstitution of the protein. CuAAC reaction was utilized to reconstitute commercially available cytochrome c oxidase (CcO)in situ formed liposomal membranes. Lastly, NCL reaction was used to accomplish the reconstitution of a mammalian plasma membrane calcium ATPase fusion protein called PMCA2-EGFPCole and co-workers tackled this problem by coupling bioorthogonal methods of titution .64 In th2A receptor (A2AR) – a G-Protein Coupled Receptor (GPCR)in situ (In situ lipid synthesis for protein reconstitution technology), uses a thioester analog of the commonly used non-ionic detergent n-dodecyl-β-d-maltoside (DDM).2AR is treated with equimolar amount of the cysteine-functionalized lysolipid to form the corresponding phospholipid by NCL, which subsequently leads to stable liposome generation and concurrent embedding of A2AR in the membrane. INSYRT proceeds in approximately 20 min without the need for additional post workups or purifications. The reconstituted GPCR was shown to be capable of interacting with known orthosteric ligands, such as the antagonist [3H]-ZM241385 Kd) and inhibitory constant (Ki) (Brea and co-workers more recently showed that the scope of the NCL-based method could be expanded to incorporate adenosine A)in situ  and 11.7ZM241385 . Additioant (Ki) . The INS7.e.g. ribozymes or enzymes). Such efforts will help bridging important gaps in the understanding of the evolution of membrane synthesis machinery. Furthermore, such biochemical functionalities can be incorporated into genetic circuits to trigger membrane synthesis and growth in response to a stimulus. In the grand scheme of construction of synthetic life, it is highly desirable to develop a system capable of undergoing Darwinian evolution. It has been shown that simple physical effects can lead to the origin of competition among model protocells.de novo membrane formation can potentially be applied to novel applications in living cells. Lipids remain among the less understood and explored classes of biomolecules. There are multiple disease conditions where aberrations in membrane fluidity, lipid metabolism and signaling pathways are implicated.de novo vesicle formation will be useful as tools for understanding how membranes can be assembled from basic building blocks and similar ideas could be implemented for studying other self-assembly processes. These strategies serve to demonstrate how synthetic pathways – parallel or even radically different from their biological counterparts – could be incorporated in the approach to bottom-up construction of an artificial cell.The pursuit of developing synthetic cells from the bottom-up could be rewarding in several ways. First, it may help us answer some of the most fundamental questions pertaining to the very definition of life. For instance, what is the minimum biochemical requirement for life or what were the key steps leading to the origin of life on Earth and possibly elsewhere. In this perspective, we discussed that model systems based on simple coupling reactions between amphiphilic precursors can provide us hints at how complexity arose in early protocell membranes. However, it is still not clear how such activated amphiphiles might have been generated under prebiotic conditions. It has been suggested that ribozymes had once occupied the biochemical niche of fatty acid activating enzymes and acyltransferases;There are no conflicts to declare.


Hantavirus disease belongs to the emerging infections. The clinical picture and severity of infections differ between hantavirus species and may even vary between hantavirus genotypes. The mechanisms that lead to the broad variance of severity in infected patients are not completely understood. Host- and virus-specific factors are considered.We analyzed severe cases of hantavirus disease in two young women. The first case was caused by Puumala virus (PUUV) infection in Germany; the second case describes the infection with Dobrava-Belgrade virus (DOBV) in Russia. Symptoms, laboratory parameters and cytokine levels were analyzed and compared between the two patients. Serological and sequence analysis revealed that PUUV was the infecting agent for the German patient and the infection of the Russian patient was caused by Dobrava-Belgrade virus genotype Sochi (DOBV-Sochi). The symptoms in the initial phase of the diseases did not differ noticeably between both patients. However, deterioration of laboratory parameter values was prolonged and stronger in DOBV-Sochi than in PUUV infection. Circulating endothelial progenitor cells (cEPCs), known to be responsible for endothelial repair, were mobilized in both infections. Striking differences were observed in the temporal course and level of cytokine upregulation. Levels of angiopoietin-2 (Ang-2), vascular endothelial growth factor (VEGF), and stromal derived factor-1 (SDF-1α) were increased in both infections; but, sustained and more pronounced elevation was observed in DOBV-Sochi infection.Severe hantavirus disease caused by different hantavirus species did not differ in the general symptoms and clinical characteristics. However, we observed a prolonged clinical course and a late and enhanced mobilization of cytokines in DOBV-Sochi infection. The differences in cytokine deregulation may contribute to the observed variation in the clinical course. Diseases caused by hantaviruses differ enormously in severity and clinical course. Host- and virus-specific determinants are discussed as reasons for the broad range of clinical pictures –5. The mThe reasons for the variation of severity between virus species/genotypes and in individual patients are not yet known. Diverse determinants concerning virus- and patient-specific characteristics may play a role in the pathogenesis. Differences in the use of entry receptors, in the regulation of cytokine response and in viral replication were described to be associated with pathogenicity –11. StudThe comparison of the clinical picture and course of severe disease caused by different hantavirus species may provide useful insights into their pathogenicity. Therefore, we analyzed the course of two severe hantavirus cases caused by infection with PUUV and DOBV-Sochi.recomLine HantaPlus assay, Mikrogen Diagnostik). Admission was on day four and on day six after onset of symptoms for the patient with PUUV and DOBV infection, respectively. To analyze the genotype of DOBV and to obtain partial nucleotide sequences of genomic segments, RT-PCR of serum and urine samples with subsequent sequencing was performed as described previously [Apodemus ponticus) and from a fatal case of hantavirus disease reported in a 47-year-old woman in the district of Krasnodar in southern European Russia  and leukocytes (6 cells/μl versus 34 cells/μl) in the patient with DOBV-Sochi. Apart from these characteristic urine pathologies, both patients developed uremia and oliguria. Glucosuria, pollakiuria, nycturia or dysuria were not observed. Lastly, they suffered from anuria in the further clinical course. As a consequence, renal replacement therapies were applied. The reasons for dialysis were uremia and severe fluid overload for DOBV-Sochi patient and uremia for PUUV patient. The patient infected with PUUV infection was dialyzed once on day seven after onset of symptoms, whereas the patient with DOBV-Sochi infection underwent dialysis six times between day nine and day 18 after onset of symptoms Fig. . The pat9/L) indicates a subsequent acute renal failure with a rise in serum creatinine levels in Puumala virus infection [9/L for the patient with PUUV infection. For the DOBV-Sochi patient the level (53 × 109/L) was also below 60 × 109/L on admission.The analysis of the course of laboratory parameters in DOBV-Sochi infection demonstrated a prolonged phase with elevated levels of leukocytes and serum creatinine and decreased levels of thrombocytes and serum albumin compared to infection with PUUV Fig. . Severalnfection , 29. CorThe hospitalization of the patient with PUUV infection lasted nine days, whereas the patient with DOBV-Sochi infection was hospitalized for 18 days. The outcome of the hantavirus infection of both patients was complete recovery of renal function.Our previous studies revealed the role of circulating endothelial progenitor cells (cEPCs) and cEPCs-mobilizing cytokines in the clinical course of patients infected with PUUV . As the Both patients demonstrated an increase in levels of cEPCs, Ang-2, VEGF, and SDF-1α compared to levels observed in healthy controls. Erythropoietin (EPO) levels were decreased during the disease indicating damage to the EPO-producing renal cells. All four samples of the PUUV patient and the samples of day 16 and 21 of the DOBV-Sochi patient were below detection limit of the EPO assay (<2.5 mIU/ml). Besides the varying extent of cytokine level elevation, differences existed in the course of cEPC and cytokine level changes between both infections. A prolonged elevation of cEPC levels with a slow normalization in the patient with DOBV-Sochi infection was observed. The duration of the increase of Ang-2 and SDF-1α levels was also extended and much higher in DOBV-Sochi infection than in infection with PUUV. Furthermore, levels of VEGF in DOBV-Sochi infection increased later than in PUUV infection. The same delay was observed for the decrease of EPO levels. Taken together, both infections are characterized by mobilization of cEPCs and cytokine level elevation, but the temporal course and the extent of increase of cytokine levels differ enormously between infection with PUUV and DOBV-Sochi.Among Old World hantaviruses, DOBV genotype Sochi is characterized by severe clinical course and a high CFR of 14.5% . In contDifferent cytokines were discussed to be responsible for hantavirus pathogenesis , 38–41. A reason for the altered clinical course and cytokine deregulation of DOBV-Sochi infection may be the enhanced replication of the virus. Viral load and antibody response influence the severity and the clinical course of hantavirus infection –49. UnfoThe comparison of hantavirus disease caused by infection with PUUV and DOBV-Sochi revealed a more severe course for DOBV-Sochi. Initial symptoms and organ involvement did not vary noticeably. The two infections differed especially in the course and levels of cytokine upregulation. These results may indicate that temporal control and high level upregulation of certain cytokines contribute to the severity of the clinical course of hantavirus disease.


The focus of multiple sclerosis research has recently turned to the relatively rare and clearly more challenging condition of primary progressive multiple sclerosis (PPMS). Many risk factors such as genetic susceptibility, age, and Epstein–Barr virus (EBV) infection may interdepend on various levels, causing a complex pathophysiological cascade. Variable pathological mechanisms drive disease progression, including inflammation-associated axonal loss, continuous activation of central nervous system resident cells, such as astrocytes and microglia as well as mitochondrial dysfunction and iron accumulation. Histological studies revealed diffuse infiltration of the gray and white matter as well as of the meninges with inflammatory cells such as B-, T-, natural killer, and plasma cells. While numerous anti-inflammatory agents effective in relapsing remitting multiple sclerosis basically failed in treatment of PPMS, the B-cell-depleting monoclonal antibody ocrelizumab recently broke the dogma that PPMS cannot be treated by an anti-inflammatory approach by demonstrating efficacy in a phase 3 PPMS trial. Other treatments aiming at enhancing remyelination (MD1003) as well as EBV-directed treatment strategies may be promising agents on the horizon. In this article, we aim to summarize new advances in the understanding of risk factors, pathophysiology, and treatment of PPMS. Moreover, we introduce a novel concept to understand the nature of the disease and possible treatment strategies in the near future. Since first described by Charcot almost two centuries ago , the fieNevertheless, the recent focus on progressive MS forms [primary and secondary progressive multiple sclerosis (PP and SPMS)] leads to a deep insight in the different pathological aspects driving the disease. In this article, we summarize the recent developments and integrate the different aspects to provide a framework explaining the sequence of events leading to the unique clinical picture.The genetic predisposition for MS is based on observations highlighting the role of maternal genes and epigenetic factors . Half siThe most important environmental factor is the sun exposure and its subsequent effect on vitamin D deficiency . The rolAuto) through cross reactivity with some myelin, bystander damage during the immune reaction against EBV infection, immune reaction against αβ crystallin expressed by oligodendrocytes, and at last infection of some naturally present autoreactive B cells leading to their maturation and initiating the immune cascade in CNS  is characterized by secretion of IFN-γ and IL-6 leading to a chronic inflammatory state with progressive activation of tissue-resident macrophages and monocytes , an immuProgressive phase of MS (PP and SPMS) is the result of long-lasting degenerative changes, which appears only when an age threshold is reached and progresses in similar rates . GeneralGut flora can provoke autoreactive CD4+ formation through antigenic mimicry, mostly with myelin oligodendrocytes glycoprotein or through innate immune signaling . Germ-frFH and Th17 activation in serum of PPMS patients was reported and correlated with the progression rate  gained more interest as one of the key mechanisms for neurodegeneration and axonal demise in MS . In PPMSSimilarly, the astrocytes are considered of particular importance in MS. Besides there well-known role in “scar formation,” recently the astrocytes have been identified as a potent secretor of different pro-inflammatory cytokines making them a possible target for therapeutic interventions .Radiologically the white matter pathology in PPMS is divided into three categories as follows.The well-defined hyperintense T2 WMLs indicate local demyelination of the WM. Histopathologically, the WMLs are either active with hypercellular infiltrate, chronic active or inactive. Both active and chronic active lesions are characterized by relative preservation of the axons but the cellular infiltrate differs; in the former, the lymphocytes are the main cells whereas in the latter the myelin-laden microphages form the mainstay of the lesions. On the other hand, the inactive lesions are characterized by extensive astrogliosis .Diffusely abnormal white matter (DAWM) refers to the diffuse and subtle signal hyperintensities in the WM. The DAWM in PMS exhibits no acute changes like demyelination or blood–brain barrier (BBB) leakage, nonetheless chronic axonal degeneration and gliosis. DAWM most likely represents degenerative changes secondary to remote focal WM pathologies .Normal-appearing white matter exhibits normal signal in the conventional T2 sequences. The NAWM changes include axonal injury without demyelination, low-grade inflammation, microglial, and astrocytic activation without being correlated to the WML load excluding the possibility that they are “pure” secondary retrograde axonal degeneration. The degree of axonal loss in NAWM as well as white matter atrophy measurements correlate with disease severity in SPMS .Gray matter damage emerged over the last years as a major determinant of disability and disease progression . GMD invN-acetylaspartate (NAA) measured using MRI spectroscopy, was reduced in MS patients and correlated to clinical severity of the disease  either through antigen mimicry or through infection of the normally present BAuto-forming apoptosis-resistant active memory BAuto cells (first hit). On the other hand, autoreactive CD4+ T cells (TAuto) are induced by the intestinal microbiome (second hit). Both BAuto and TAuto interact in the peripheral lymphoid tissue. TAuto cells cross the BBB and are further activated by perivascular BAuto sells. B and T cells recognize the neuronal antigens and start an inflammatory reaction leading to migration of CD8+ cells and macrophages through BBB as well as activation of the microglial cells and astrocytes leading to demise of the neurons (first event). The apoptotic neurons and oligodendrocytes release other sequestrated antigens that subsequently will be recognized by B and T cells accentuating the inflammatory reaction (second event) with wide spread low-grade inflammatory process. Other factors like mitochondrial dysfunction, glutamate cytotoxicity, and iron accumulation lead to further demise of neurons  compared with placebo. Timed 25-foot walk improved after 120 weeks (p = 0.04).Ocrelizumab is the first drug ever to show efficacy in slowing the disease progression in a phase 3 clinical trial with PPMS patients . In the Vitamin B7-biotin activates acetylCoA carboxylase, a potentially rate-limiting enzyme in myelin synthesis and subsequently may help inducing remyelination . Indeed,Laquinimod is an orally available carboxamide derivative with multimodal mechanism of action rendering it both anti-inflammatory and neuroprotective ; laquiniIn the MS-STAT study, 80 mg/day simvastatin was reported to cut the annualized brain atrophy rates in patients with SPMS by almost the half in a placebo-controlled randomized clinical trial . Simvastin vitro with AdE1-LMPpoly increased survival in patients with the EBV-associated carcinoma , a superimposed fluctuating high-grade inflammatory process appears in younger age and manifests itself in the form of recurrent exacerbations. Evidences supporting this hypothesis are (1) more than half of MS patients suffer from PMS (either as PPMS from the beginning or SPMS), (2) the striking clinical and pathological similarities between PP and SPMS, (3) the almost universal positive EBV status in MS patients, (4) the presence of EBV-infected B cells in brain and meninges of MS patients, perivascular spaces, and parenchyma, (5) the well-known change in age-dependent host response to latent EBV infection, (6) the success of B cell-depleting agents in RRMS and PPMS, (7) the “preliminary” success of T-cell-based therapy against EBV-infected B cells in SPMS, (8) the presence of vitamin D deficiency in RRMS but not PPMS patients and its well-described effect on the relapse rate but not disease progression, and finally, (9) almost all pathological aspects of the progressive phase like MiA, iron accumulation, mitochondrial dysfunction, involvement of the NAWM and NAGM, cortical and cerebral atrophy, as well as meningeal infiltration can be detected very early in the disease course even in CIS patients , 90–93. The current therapy options for PPMS are promisingly increasing with upcoming possibilities of targeting different aspects of the disease Figure . CombinaPrimary progressive multiple sclerosis is considered a relatively rare, but very challenging phenotype in the care of MS patients. Our current knowledge supports an underlying inflammatory-driven neurodegenerative process. Autoreactive EBV-infected B cells are essential to drive the progressive inflammation. The results of ocrelizumab and biotin announce the beginning of a new era with more therapies are eventually coming to the market in next years.AA formulated the main concept, reviewed the published data, postulated the mentioned hypothesis, and drafted the manuscript. HT supervised and reviewed the article. MW reviewed the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with one of the authors, HT, and states that the process nevertheless met the standards of a fair and objective review.


The ongoing collision between the Indian plate and the Eurasian plate brings up N-S crustal shortening and thickening of the Tibet Plateau, but its dynamic mechanisms remain controversial yet. As one of the most tectonically active regions of the world, South-Eastern Tibet (SET) has been greatly paid attention to by many geoscientists. Here we present the latest three-dimensional GPS velocity field to constrain the present-day tectonic process of SET, which may highlight the complex vertical crustal deformation. Improved data processing strategies are adopted to enhance the strain patterns throughout SET. The crustal uplifting and subsidence are dominated by regional deep tectonic dynamic processes. Results show that the Gongga Shan is uplifting with 1–1.5 mm/yr. Nevertheless, an anomalous crustal uplifting of ~8.7 mm/yr and negative horizontal dilation rates of 40–50 nstrain/yr throughout the Longmenshan structure reveal that this structure is caused by the intracontinental subduction of the Yangtze Craton. The Xianshuihe-Xiaojiang fault is a major active sinistral strike-slip fault which strikes essentially and consistently with the maximum shear strain rates. These observations suggest that the upper crustal deformation is closely related with the regulation and coupling of deep material. India began colliding with Eurasia over 40–50 million years ago, leading to strong North-South crustal shortening and uplifting1463The southeast borderland of Tibet is a seismically active zone and exhibits complex topographic relief, as shown in 911213Global Position System (GPS) measurements have been widely used to constrain the horizontal crustal deformation of Tibet1617182021222324814In this study, we integrated GPS data with an improved data processing strategy to assess the 3D velocity throughout SET. The GPS-derived horizontal velocity field relative to the stable Eurasian plate displays crustal block motion by clockwise rotation around the Eastern Himalayan Syntaxis. Particularly the regional vertical-improved GPS velocity including the Longmen Shan zone, Gongga Shan and Southern Yunnan sub-block shows regional crustal vertical deformation properties of SET. Then, the strain rates are calculated from the GPS-derived horizontal velocity. Finally additional information on the methods is described at the end of the paper.The newly GPS horizontal velocity field relative to the stable Eurasia throughout SET and neighboring regions reveals a continuous crustal clockwise motion around the Eastern Himalayan Syntaxis, as shown in The vertical velocity field is obtained from continuous GPS (CGPS) stations . The camThe western corner of SET where the Indian lithosphere subducts beneath Tibet and BurmaIn order to identify how much a material has been deformed and where it has been deformed, the strain modeling is facilitated throughout SET. Strain rates are sensitive to the length scale of the analysis. To calculate the average strain rates, two methods are adopted, the Grid-Distance Weighted approach and the Grid-Nearest Neighbor approachThe continuous positive extension strain pattern  reveals The crust SSE- SSW extensional strain dominates active deformation of SET ). The SaIt is meaningful to study the tectonic deformation of SET in order to understand the dynamic process of the Indian-Eurasian collision, plateau’s uplift and its mechanism. The NNE-SSW shortening of the plateau interior is accommodated by conjugate strike-slip faulting and orthogonal normal faulting81229318The present-day crustal motion on the basis of the measurements of 409 GPS stations highlights the lithosphere deformation throughout SET and its surroundings. The improved vertical crustal deformation is constrained by removing the surface loadings from CGPS time series, showing a strong correlation with average principal horizontal shortening strain rates. The regional uplifting and sinking of the crust are sensitive to the crustal compression and extension. However, a regional crust pulling-apart induces a sinking of a basin, resulting in multi-periodic activities of its boundary faults and relative uplifting of the mountain, i.e. the Sichuan basin . In contThe strike-slip faults play a key role in reconciling the block motions and crustal uplifting of Tibet. The strain shear rates reveal the crustal strike-slipping and extension on the Chuan-Dian Block which is bounded by the left-lateral Xianshuihe-Anninghe-Xiaojiang Faults. The GPS observations in the Longmen Shan zone present unusual crustal uplifting, which is caused by the remote tectonic effects in the continent interior by the continent to continent collision of the Yangtze plate (Sichuan Basin) and the Tibet Plateau (Songpan-Ganzi Block). The dilatational and max-shear strain fields suggest that there exist double features as thrust and strike-slip fault in Longmen Shan region.We present a model to show a potential motion of the materials that could be inferred from the upper crustal maximum shear patterns and tracing channel-flow throughout SET . The resst and 2nd order effects in correcting the ionosphere effects. We applied International Earth Rotation and Reference Systems (IERS) 2010 conventions to correct the tidal solid Earth and pole tidesWe used 66 Continuous and 343 Campaign GPS stations  in and aIt allows re-estimation of sigma for GPS stations with two optional noise analysis models: white noise model and flicker noise plus white noise model353739http://homepage.mac.com/nfcd/work/programs.html) to compute the strain field from GPS horizontal velocity data. More details including the main capabilities, functions and some example applications of SSPX were illustrated by Cardozo and Allmendingern nearest stations within a maximum radius, where n should be equal or greater than 3. The larger the number of nearest neighbors, the more the smoothing of the deformation field. In this study, we used Grid-Nearest Neighbor routine with 12 neighbors and maximum radius = 300 km for detailed strain modeling computation (α = 100 km. Weighting by distance (Grid-Distance) produces a smoother strain than the nearest neighbor method (Grid-Nearest Neighbor), and is particularly effective for visualizing regional patterns. However, it is likely that using the distance weighted approach some important details might be overlooked. The parameters setting for strain calculation are from Cardozo and AllmendingerWe used the SSPX program .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.