Chronic lymphocytic leukaemia (CLL) is a B-cell malignancy with a highly variable clinical course. Whereas some patients require treatment relatively soon after diagnosis, others may stay free of symptoms for many years with a standard ‘watch and wait' surveillance approach. Genomic analysis of asymptomatic patients and patients with progressive or relapsed refractory disease makes CLL an excellent model to study the course of genetic modifications in relation to the pathobiology of this disease.TP53 in 17p. Sanger sequencing as well as fluorescence in situ hybridisation or genomic arrays have further identified a wide spectrum of genomic modifications emphasising the marked genetic heterogeneity of CLL.The use of karyotype analysis first demonstrated that the deletions of chromosomes 13q, 17p, and 11q as well as trisomy 12 were recurrent aberrations in CLL. Mutations in several cancer genes were subsequently identified in these regions: ATM and BIRC3 in 11q or Nature, which describe the whole exome/genome sequencing of 990 CLL patients.2 Both studies confirmed the considerable genetic heterogeneity of CLL as well as its evolution during disease progression.Considerable progress has been made in the field of CLL genetics over last 3 years, with the publication of multiple studies using next generation sequencing (NGS) culminating with two recent reports in Tumour genome sequencing shatters genetic information into small pieces, which must be then reconstructed like a giant jigsaw puzzle without a picture on the box. Assembling genetic alterations, based on previous knowledge about biological processes, allows investigation of entire sets of mutations in a tumour and determination of the targeted pathways. The fundamental goal is to decrease the data set concerning countless altered genes and proteins to a smaller and more meaningful set of altered pathways. This strategy will generate testable hypotheses, identify tumour subtypes with clinically distinct outcomes, characterise the cancer-specific and cross-cancer pathways and help to identify drug targets. Furthermore, analysis of large cohorts of patients has revealed that the driver mutations targeting multiple components of a single pathway are mutually exclusive on tumour samples. Identification of this type of exclusive pattern is important for the understanding of cancer progression, leading to a stimulating feedback between the patient and the lab, as this analysis may lead to the proposal of genes for targeted therapy.TP53 network is a paradigm for this type of analysis, as it is impaired in most human cancers.3 The backbone of this pathway is the TP53 autoregulatory feedback loop and its negative regulator MDM2  mutations.Inactivation of several members of this network in CLL has already been clearly established with an apparent focus on the DNA-damage pathway with ATM and POT1 mutations . AlthougTP53 pathway  have been shown to bind and inactivate MDM2, leading to a strong TP53 response and cell death.7 It has been hypothesised that RPS15  could act as a ‘detector' of impaired ribosomal biogenesis, explaining why RPS15 mutations can contribute to tumourigenicity. Although only a small number of patients harbour RPS15 mutations, these mutations tend to be exclusive of TP53 alterations and are associated with shorter progression-free survival (PFS).RPS15 mutations shed light on another aspect of the  pathway . Accuratet al.8 demonstrated BIRC3 inactivation in a subset of patients who were refractory to fludarabine therapy. This observation was confirmed by the work of Landau et al. and Puente et al., who both showed that BIRC3 mutations are associated with shorter survival, a feature shared by patients with ATM or TP53 alterations. A remarkable feature of BIRC3 mutations is their occurrence in tumours not presenting any TP53 mutations, suggesting that they are associated with a common pathway. BIRC3, also known as cIAP2 (cellular inhibitor of apoptosis proteins), is a regulator of canonical NF-kB signalling downstream from the TNF-R1 receptor, and also functions as a negative regulator of the non-canonical NF-kB pathway via RING finger domain-dependent ubiquitination of NIK. In a cellular model, downregulation of BIRC3/cIAP2 led to TP53 degradation via NF-KB-dependent phosphorylation and activation of mdm2.9 On the other hand, most BIRC3 mutations are localised in the carboxy terminus, resulting in proteins that are deficient for their ubiquitination activity, suggesting a possible gain of function.In a seminal paper, Rossi TP53 and NF-kB pathways, the mutually exclusive nature of BIRC3 and TP53 mutations cannot be easily explained, but should be explored in more detail to gain insight into the mechanisms, leading to resistance to therapy.Despite the multiple links between the MicroRNAs are an important component of the BCR (B-cell receptor) signalling pathway. The signature profile of microRNAs can distinguish normal B cells from malignant CLL. Several microRNAs regulated by TP53, such as miR-15a, miR-161 localised on chromosome 13 or mi-R34A/b localised on chromosome 11, are frequently deregulated in CLL. Whether or not, these defects impair the TP53 pathway currently remains unknown, but should be investigated to gain more insight into the role of microRNA defects.TP53 mutations. Although seemingly infrequent in the early phase of the disease, TP53 mutations are often found in patients with relapse/refractory disease and poor survival.10 Nonetheless, deep NGS has demonstrated the presence of very small subclones in upto 9% of cases at diagnosis, and retrospectively in early samples of patients who exhibited larger clones at later stages of progression.11 It is noteworthy that approximately one half of these patients did not harbour a 17p deletion, and therefore, retained the wild-type TP53 allele. It is currently unknown whether TP53 mutations observed in patients with and without 17p deletion have different biochemical properties. The importance of TP53 during disease progression is also emphasised by the identification of multiple subclones harbouring different TP53 mutations in leukaemic cells. The presence of TP53 mutation has been linked to chemorefractoriness, and expansion of TP53-mutated subclones has been clearly demonstrated in patients relapsing after initial chemotherapy.Finally, a few words on Defining the origin of these clones, how they evolve and perhaps compete during tumour progression, are among the several questions that NGS will be able to resolve in the near future.TP53 mutations represent an adverse prognostic parameter at all time points of CLL history: at diagnosis, at the time of initial therapy and at relapse. New agents such as BCR inhibitors have provided very promising results, and have been approved by both FDA and EMA for use as first-line therapy in the presence of TP53 alteration. It is therefore highly recommended to test patients for the presence of 17p deletion and TP53 mutation before treatment decisions, even beyond the context of clinical trials.The presence of TP53 are impaired in CLL, as well as alteration of the TP53 gene itself. Whether or not this can be considered as a single clinical entity, has to be resolved yet. The observation that ATM, RPS15, TP53 or BIRC3 alterations are associated with shorter overall survival and PFS is strong argument in favour of this hypothesis, which is reinforced by the observation that TP53 mutations are strongly exclusive with BIRC3, ATM and RPS15 mutations in the series of 990 cases of CLL published by Landau et al. and Puente et al. Although the exclusive nature with ATM mutations is not always observed, the discovery that CLL, and more particularly cases of CLL in progression or relapse, display high levels of subclones that could harbour different genotypes could explain this apparent discrepancy. Analysis of clonal evolution as well as single-cell sequencing will be able to refine our knowledge on the genetics of CLL.Clearly, several upstream pathways converging to


Purpose. The goal of this study was to investigate the effects of arm weight support training using the ArmeoSpring for subacute patients after stroke with different levels of hemiplegic arm impairments. Methods. 48 inpatients with subacute stroke, stratified into 3 groups from mild to severe upper extremity impairment, were engaged in ArmeoSpring training for 45 minutes daily, 5 days per week for 3 weeks, in addition to conventional rehabilitation. Evaluations were conducted at three measurement occasions: immediately before training (T1); immediately after training (T2); and at a 3-week follow-up (T3) by a blind rater. Results. Shoulder flexion active range of motion, Upper Extremity Scores in the Fugl-Meyer Assessment (FMA), and Vertical Catch had the greatest differences in gain scores for patients between severe and moderate impairments, whereas FMA Hand Scores had significant differences in gain scores between moderate and mild impairments. There was no significant change in muscle tone or hand-path ratios between T1, T2, and T3 within the groups. Conclusion. Arm weight support training is beneficial for subacute stroke patients with moderate to severe arm impairments, especially to improve vertical control such as shoulder flexion, and there were no adverse effects in muscle tone. Robots are one of the major technological revolutions in the past decade in rehabilitation training approaches for arm recovery. Robotic therapy stimulates active, assistive paretic limb movement in a reliable, controllable, repeatable, quantifiable, and flexible way that makes it an ideal tool to evaluate kinematic and kinetic measurements, implement rehabilitation paradigms, and facilitate motor recovery from stroke and other neurological diseases . One of The ArmeoSpring is a passive instrumented arm orthosis with a spring mechanism for adjustable arm weight support in a large 3D workspace, and it can be used as a real-time input device with its ancillary software Armeocontrol. It originated from T-WREX, which was developed by Reinkensmeyer et al. (2002) . PositioTwo randomized control trials (RCT) were conducted on the T-WREX system , 6. In tA single-blind RCT found that additional ArmeoSpring training led to significant improvements in shoulder adduction-abduction and normalized jerk compared with conventional training in acute stroke patients . A singlA total of 48 inpatients admitted consecutively to a regional rehabilitation hospital were recruited by convenience sampling. The principal inclusion criteria were (i) being diagnosed with cerebral vascular disease either by a CT scan or MRI in a medical report and compatible with unilateral hemispherical involvement; (ii) being within 1 week to 6 months after stroke; (iii) being able to understand verbal instructions and follow two-step commands according to the Mini-Mental State Examination (MMSE) ; (iv) exParticipants were excluded if they (i) had significant impairment in visual acuity, visual perception, and unilateral neglect  ; (ii) haPatients were categorized into three groups according to the functional levels of the FTHUE . Group 1ArmeoSpring facilitates the patient's own active movements as directed through specific virtual reality computer tasks or games that allow for self-training with immediate performance feedback . It is aThe goal of the ArmeoSpring training modules is to teach patients to move through a smooth path with a minimum jerk trajectory with immediate feedback. All training modules were designed according to the minimum motion the participants achieved according to the upper limb functional level in the FTHUE . The tesThe training module for Group 1 was for patients who had just started to exhibit voluntary movement of the shoulder and elbow, and the training tasks involved only one- and two-dimensional tasks at a lower level of difficulty. Training modules for Group 2 involved activities with a greater range of shoulder and elbow movement such as one- and two-dimensional activities at a higher level of difficulty and consisted of more two-dimensional tasks. The one- and two-dimensional tasks can be divided into either horizontal or vertical catching tasks . An examThis was a prospective single-group cohort study. This study was approved by the human subjects' ethics committee of the hospital. All participants signed informed consent forms. All participants received daily 45-minute sessions for the arm weight support training, 5 days per week for 3 weeks in addition to conventional rehabilitation training in the hospital, which included 60-minute activities of daily living training and affected arm horizontal and vertical reaching activities in occupational therapy, 60-minute biomechanical training in upper and lower limbs as well as gait training in physiotherapy, 30-minute speech therapy by appointment, and occasional patient and family discussions with healthcare workers at the rehabilitation hospitals.Two ArmeoSpring devices were set up in the occupational therapy department in the hospital. Each device was designated for either left or right arms. Four occupational therapists were trained on the procedures for setting up the device on patients. After setting up the ArmeoSpring training tasks, participants were instructed to engage in training without a therapist present. To put the patient in the ArmeoSpring, the therapist has to adjust the arm orthosis to fit the patient's dimensions according to the setup procedures. Before setting up training activities, the patient has to be calibrated on the range of active movement on the computer's working plane. Once the workplace setup is complete, the therapist can select the appropriate preset training modules of activities from a wide range of functional activities in the form of virtual reality practice for the patient.To ensure the patient's safety, an additional safety belt was designed to prevent patient falls and compensatory trunk movements during training. The device and system were checked regularly for any defects. Defects were reported to the company agent immediately. Trainings were also stopped if there was an increase in spasticity to Grade 3 or above on the Modified Ashworth Scale (MAS) .Evaluations were conducted, and data was collected at three measurement occasions: immediately before training (T1); immediately after completion of the three-week training (T2); and at a three-week follow-up after completion of the three-week intervention (T3), by a rater blind to participants who had received ArmeoSpring training. The primary outcome measures were (i) the Fugl-Meyer Assessment (FMA) Upper Extremity Score and Hand Score to measure arm impairments ; (ii) acx- and y-axes during horizontal and vertical catching ; y values are in the vertical direction (up to down), and z values correspond to the horizontal direction (far to close). All values are reported relative to the first joint  where the arm orthosis is attached. A perfect linear movement has a hand-path ratio of 1. A hand-path ratio of 2 indicates that the length of the patient's hand trajectory was twice as long as the shortest line connecting the points.Armeocontrol, an ancillary software program, captured secondary kinetic outcomes. They included (i) the hand-path ratio , which indicates the extent to which the user deviates from the ideal straight line between two objects when moving from one to the next ; (ii) thcatching . x valuep = 0.01 for within-group comparisons  and p = 0.007 for between-group comparisons .After removing dropout cases, all available data were analyzed in an intention-to-treat analysis. The “last observation carried forward” (LOCF) method was used; that is, if a subject dropped out, missing values were replaced by the last assessment score of that variable. We used Pearson chi-square and one-way ANOVAs to compare baselines of categorical and continuous data, respectively. We used univariate ANOVAs to compare within-group differences in each group three measurement occasions, T1, T2, and T3, and one-way ANOVAs to compare the between-group differences in the gain scores: Gain 1 between initial assessment (T1) and assessment at the end of ArmeoSpring training (T2) and Gain 2 between T1 and assessment at 3-week follow-up (T3). We used Tukey's honestly significant difference method (HSD) for post hoc comparison to find significant differences for pairs of groups. Because seven instruments were used in measuring outcomes, a conservative level of statistical significance by the Bonferroni correction was set at p = 0.068–0.764). The only significant difference was arm impairment levels as stratified by the FTHUE for group allocation and 2 main brain lesion sites (p < 0.05). There were no significant differences in Vertical Catch (level 1) or Horizontal Catch (level 1) of hand-path ratio between any groups (p = 0.013–0.998).p = 0.000–0.009). Interestingly, Group 2 had significant differences across all three measurement occasions except for percentage scores of Horizontal Catch (p = 0.124). Group 1 had significant improvements in all kinetic and kinematic parameters (p = 0.000 to 0.007) except for hand-path ratios (p = 0.023–0.035).p < 0.001) and Gain 2 (p < 0.001) between the three groups. Post hoc analysis indicated that differences were between Groups 1 and 2 and Groups 1 and 3. This is consistent with the results of the catching tasks, in which there were only significant differences in Gain 1 and Gain 2 of Vertical Catch in both percentage and time scores among the three groups (p = 0.000-0.001), Gain 1 in the Vertical Catch of hand-path ratio only (p < 0.001), and Gain 2 in the FMA Upper Extremity Scores (p < 0.001). Regarding control of the hand, the differences in FMA Hand Scores were significant in Gain 1 (p = 0.006) and Gain 2 (p = 0.006), and post hoc analysis indicated that the differences in Hand Scores were between Groups 2 and 3 for Gain 1 and Gain 2. However, differences were found only for Gain 2 for Groups 1 and 3. Most of the differences in AROM shoulder flexion, FMA Upper Extremity Scores, and hand-path ratio  were in gain scores between Groups 1 and 2 and Groups 1 and 3, whereas significant differences in gain scores of Groups 2 and 3 were mostly found in FMA Hand Scores.Results of between-group comparisons found that there were no significant differences in change of tone at the three measurement occasions in all groups. There were significant differences in AROM shoulder flexion in both Gain 1 . This study differs from previous studies because it pioneers the triage of patients to the use of ArmeoSpring that is most effective for them. Groups 1 and 2  showed more proximal improvement than Group 3 . This is important to help therapists decide which treatment is right for the patient. Moreover, we found that there was no difference in change of muscle tone among the three groups, which indicates that ArmeoSpring training does not lead to any increase in spasticity in patients with different levels of upper extremity impairment, regardless of the group the participants belong to.Within-group comparison results indicated that Group 3 did not benefit from ArmeoSpring training except for an increase in Horizontal Catch time and percentage scores. It should be noted that most of the significant differences in gain scores of outcome measures of shoulder range and proximal control were between Groups 1 and 2 and Groups 1 and 3, and there was no significant change in elbow or forearm gain scores. Across the three groups, there were more improvements in shoulder flexion than in the elbow and forearm. Group 1 showed the most improvement. These patients were mostly in functional level 2  and only able to activate their shoulder movement to activate the device. Group 1 patients—those who had just started to show voluntary movement of their elbow and shoulder—demonstrated the most improvements in proximal control. Meanwhile, Group 2 patients—those with a more active range of motion in their elbow and shoulder—had the most improvements in hand control. This is because, prior to using the ArmeoSpring, Group 1 patients had significant difficulty lifting the affected arm against gravity but were able to move with the nonweight support provided by the ArmeoSpring. Another option for those patients who are not sufficient to properly use the device is training by using the ArmeoPower, a powered exoskeleton with an intelligent arm supported in a 3D space. A recent study showed that it is useful to improve upper limb motor function recovery according to the results of both ArmeoPower kinematic parameters and cortical excitability of primary motor areas in response to transcranial magnetic stimulation .Moreover, in our study, Vertical Catch movement improved significantly compared to Horizontal Catch movement in terms of both percentage and time scores of Vertical/Horizontal Catch in groups of severe and moderate impairments, respectively. The results were consistent with that of the T-WREX study, which showed a trend toward larger improvements at the shoulder and elbow compared to the forearm and wrist after T-WREX training, whereas the control group had larger but no significant improvement in the forearm . Other sIt is surprising to find that there were no within-groups changes in hand-path ratios between the three measurement occasions in all groups. This is particularly interesting because hand-path ratios are commonly used to measure kinematic outcomes to evaluate the movement efficiency of robotic devices performing a smooth movement trajectory in virtual rehabilitation, with the shortest trajectory to the target as measure of efficient movement . Our resAlthough there were obvious changes in shoulder control, hand coordination, and power grip, there were no significant differences in gain scores in overall functions as measured by the FIM among the three groups of different arm impairment levels despite different improvements in their arms. The overall improvement in arm functionality may be due to effects of conventional training or spontaneous recovery. This implies a common phenomenon of robotic therapy in which the training is able to reduce arm impairments but cannot improve overall functions. Reviews by both Kwakkel et al.  and PranAlthough Huang and Krakauer  concludeThis study is subject to several limitations. First, the FIM scores were retrieved from the hospital centralized case management system and the data at T3 were not known. There was also no control group in this study and that the results were not compared with parallel studies highlighting effects on arm control and muscle tone of other robotic-based protocols. Different training protocols including frequency and duration of training regimens should be considered to maximize treatment effects. In the training modules, there were fewer games with forearm tasks, which might have placed Group 1 at a disadvantage because they may be physically unable to participate.The ArmeoSpring is beneficial for subacute stroke patients with moderate to severe arm impairments particularly in improving vertical control (such as shoulder flexion). Using ArmeoSpring will not induce any adverse effects in muscle tone.


Dentate neural stem cells produce neurons throughout life in mammals. Sonic hedgehog (Shh) is critical for maintenance of these cells; however, the perinatal source of Shh is enigmatic. In the present study, we examined the role of Shh expressed by hair follicles (HFs) that expand perinatally in temporal concordance with the proliferation of Shh-responding dentate stem cells. Specific inhibition of Shh from HFs or from epithelial sources in general hindered development of Shh-responding dentate stem cells. We also found that the blood–brain barrier (BBB) of the perinatal dentate gyrus (DG) is leaky with stem cells in the dentate exposed to blood-born factors. In attempting to identify how Shh might be transported in blood, we found that platelets contain epithelial Shh, provide Shh to the perinatal DG and that inhibition of platelet generation reduced hedgehog-responsive dentate stem cells.DOI:http://dx.doi.org/10.7554/eLife.07834.001 Although most of the neurons in the brain have been made by the time we are born, new neurons develop throughout life in part of the brain called the hippocampus. These neurons are thought to help with learning and forming memories. Conditions such as depression and Alzheimer's disease have been linked to not being able to produce enough new neurons.The neurons develop from a pool of stem cells in part of the hippocampus. A protein called Sonic Hedgehog (Shh) helps to ensure there are enough stem cells and control when they develop into new neurons. The brain cells that produce Shh in adult mice do not appear until a week after birth, by which point the stem cells are already present and generating neurons. This has led scientists to question where these cells get Shh from around the time of birth.One idea is that cells outside of the brain contribute the Shh such as hair follicles—the structures that hairs grow out of—in the scalp. Hair follicles produce Shh, develop at around the same time as the brain stem cells, and are known to regulate the development of other nearby stem cells. So, Choe et al. conducted a series of experiments in genetically engineered newborn mice and found that the brain stem cells multiply at around the same time that the hair follicles start to produce Shh. Furthermore, reducing the amount of Shh produced by the hair follicles hampered the growth of these stem cells and caused fewer neurons to develop from the stem cell pool.These results raised the question of how Shh gets from the hair follicles to the stem cell pool in the developing brain. In adult animals, a barrier exists between the brain and the blood supply to protect the brain from infection. However, parts of this barrier are still leaky before birth, which might allow blood cells to carry Shh to the brain. Cloe et al. found that platelets—the blood cells responsible for clotting—are able to carry Shh to the brain stem cell pool. Further experiments showed that preventing platelets from forming caused fewer stem cells to develop.The suggestion that Shh from the epithelium—the tissue layer that hair follicles are found in—is able to signal to the brain during a specific window of time raises several questions that require further study. Does epithelial Shh also signal to other organs during embryonic or postnatal development? Does injury to the nervous system that increases the permeability of the blood–brain barrier lead to the delivery of Shh to the brain via the circulation in adult animals?DOI:http://dx.doi.org/10.7554/eLife.07834.002 Neural stem cells in the dentate gyrus (DG) consistently provide new excitatory neurons to modulate hippocampal circuitry and disrupted neurogenesis is linked to multiple neurological and psychiatric diseases . Stem ceSkin morphogenesis and homeostasis are regulated by hair follicles (HFs), each of which is a small structure stocked with cells producing factors such as platelet-derived growth factors (Pdgfs) and Shh . The perGata1 and Nfe2 knockout mice have abnormal bone mass  matures as early as embryonic day (E) 15.5 in most forebrain areas  except fGli1-GFP transgenic mice expressing GFP in hedgehog-responding cells. The GFP + hedgehog-responding cells of a Gli1-GFP GENSAT transgenic mouse line were obvious in the forming HFs   . At P10 s (TACs)  (Li et as (TACs) . At P50,s (TACs) . This imPtch1-LacZ mice. At P3, Ptch1-LacZ + cells were enriched in the cranial suture, a front of bone growth . Inhibition of dermal mesenchymal hedgehog signaling dramatically reduced the size of the skull at P3, which was not observed in either Krt14-Cre;Shhflx/flx and Msx2-Cre;Shhflx/flx mutants platelets  and Gli1-GFP mice were obtained from GENSAT . Rosa-Ym GENSAT . To obtaEmbryos were collected at noon of embryonic days. Collected brains were fixed in 4% paraformaldehyde (PFA)/phosphate-buffered saline (PBS) overnight and cryo-protected in 20% sucrose/PBS for 4–8 hr. OCT-embedded tissues were processed in a cryostat at 12-µm sections for immunostaining and 20-µm sections for in situ hybridization. A single experiment was done by comparing control and mutant sections stained on the same slide to minimize variation between slides. Primary antibodies used for the immunostaining are chicken anti-GFP , 1:1000), rabbit anti- Pdgfrβ , 1:200), rabbit anti-Ki67 , 1:200), rat anti-Pdgfrα , 1:400), mouse anti-fibrinogen-FITC , 1:1000), mouse anti-Reelin , 1:1000), rabbit anti-Shh , 1:100), rabbit anti-Laminin , 1:1000), rat anti-CD34 , 1:300), rat anti-CD45 , Armenian hamster anti-CD42d , rat anti-CD41 , Armenian hamster anti-CD61 , rabbit anti-Lef1 , rabbit anti-Sp7 , 1:100), rat anti-PECAM , rabbit anti-Prox1 , mouse aROSA-LacZ reporter line as stated in the previous publication (Fixable dyes (Invitrogen) such as 70 KDa biotinylated dextrans and biotin-conjugated cadaverine were dissolved in 1× ice-cold PBS at 1 mg/ml and 2 mg/ml, respectively, and used 0.2 ml to perfuse an embryo followed by 2 ml of 4% PFA solution. We performed X-gal staining of a lication  and usedTamoxifen  stock was prepared by dissolving the powder in corn oil (Sigma) at 20 mg/ml. Pregnant female mice were single dosed subcutaneously with 4 mg of TM at the specified embryonic day. Timed pregnant mice were subcutaneously injected with BrdU  dissolved in saline (10 mg/ml) at the dose of 50 mg/kg animal to label cells in S-phase cell cycle. Materials used in the t-test using a SigmaPlot program  and a Graph Pad program .Values are presented as SEM in graphs. For the statistical analysis of samples, we used Student's  review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent , a Reviewing Editor, and three reviewers.Thank you for submitting your work entitled “Epithelial cells supply Sonic Hedgehog to the perinatal dentate gyrus via transport by platelets” for peer review at The reviewers have discussed the reviews with one another and the Reviewing editor has drafted this decision to help you prepare a revised submission.This manuscript explores the perinatal source of Hh ligand, focusing on the first postnatal week of murine life prior to Hh secretion by dentate hilar cells. The authors demonstrate that Hh ligand is secreted by hair follicle cells of the scalp and transported to the hippocampus via platelets and through a focally leaky BBB. Without this extra-axial source of Hh ligand, the hippocampal stem cell population is diminished and dentate gyrus neurogenesis is impaired into later postnatal life.The work utilizes elegant mouse modeling to demonstrate a previously unrecognized mechanism of Hh ligand delivery to the hippocampal stem cell population and elucidates a fascinating extension of the hippocampal “stem cell niche” outside of the brain. It is an important set of findings that furthers our understanding of Hh-mediated stem cell maintenance and highlights platelets as an under recognized source of growth factor transport to the brain.However, two of the three referees raised some major concerns and point out that your conclusion is not yet convincing because you have not ruled out that some of the mouse lines are not inadvertently affecting Shh directly in the brain. Elucidating the mechanisms of SHH packaging into platelets goes beyond the scope of the paper, but providing data on the recombination patterns of the Cre alleles used would go a long way toward addressing the concerns of the reviewers. We would encourage you to undertake these major revisions and submit for further consideration.Major revisions:Msx2-Cre, both decrease Shh expression in the skin that covers the brain and decrease dentate granule cell proliferation. The data presented regarding the specificity of the two promoters that were used is limited. For example, K14 is also expressed in thymic tissues, raising the question of microglial changes in Shh expression in the mutant, and is also expressed in ovaries. Moreover, the Msx2-Cre is usually used to tag cells derived from the AER. When crossed through females, it is expressed ubiquitously. Thus more data on the specificity would help. It would be important to show that neither of these Cres alter the expression of Shh mRNA in the periventricular area.1) How well do the authors show that Shh is made in skin and conveyed to the hippocampus? The authors show that two Cre drivers, Keratin14 and It would also be important to show that using these Cre's affects the level of Shh protein present in the Dentate granule zone, to confirm that the Shh present there is gone.gli1 expression perhaps?), in addition to the changes in proliferation shown for both, and changes in Ptc-LacZ shown for Msx2-cre.Please provide some additional data that there is loss of Shh signaling per se in the Dentate granule cells in these mutants (2) The blot of E17.5 blood samples immunoprecipitated with CD41 are used to show that Shh is associated with platelets '. Our unNfe2 knockout experiments in Nfe2-dependent platelets play an important role in expanding the Ptch1+ DG stem/progenitor cells, but this might not be through their role as a Shh carrier. Rather, some other platelet-derived factors or indirect effects downstream of platelet differentiation might be responsible for this Nfe2-dependent effect.3) Regarding the conclusion that Shh from HFs passes through the leaky BBB to dentate neural stem cells and platelets act as the Shh carrier: the Furthermore, how is follicular Shh incorporated into platelets? And how do platelets release Shh at the DG? Revealing these mechanisms and inhibiting them would address the above issue and greatly improve the study, but this may be too much to ask. The authors should revise the text instead in order to avoid overinterpretation.4) The authors should be more careful about identification of the DG neural stem cells and use more markers to define them. Counting the numbers of Ki67+ cells and LEF1+ cells is not enough.Suggestions for improvement:Msx2-cre; Shhfl/fl mouse would strengthen the conclusions.The authors examine cell proliferation in the postnatal hippocampus and find it to be decreased when SHh ligand is conditionally ablated from hair follicle cells of the head, but postnatal neurogenesis is not examined in this model. Demonstrating postnatal decrease in Dcx+ cells of the dentate at P40 in the  Major revisions:1) How well do the authors show that Shh is made in skin and conveyed to the hippocampus? The authors show that two Cre drivers, Keratin14 and Msx2-cre, both decrease Shh expression in the skin that covers the brain and decrease dentate granule cell proliferation. The data presented regarding the specificity of the two promoters that were used is limited. For example, K14 is also expressed in thymic tissues, raising the question of microglial changes in Shh expression in the mutant, and is also expressed in ovaries. Moreover, the Msx2-Cre is usually used to tag cells derived from the AER. When crossed through females, it is expressed ubiquitously. Thus more data on the specificity would help. It would be important to show that neither of these Cres alter the expression of Shh mRNA in the periventricular area.K14-Cre mice were selected according to the specific expression of K14-Cre in the skin. The K14-Cre line in the experiment was obtained from one of two lines originally generated from mice that expressed the highest levels of Cre RNA in the skin . As noted in the Methods section, we only derived Cre expression from the male side to avoid non-specific expression of Cre or germ-line expression of the Cre. Msx2-Cre mice have been used for the expression of Cre in the AER and skin , in addition to the changes in proliferation shown for both, and changes in Ptc-LacZ shown for Msx2-cre.Gli1-GFP in Gli1-GFP mice with the Msx2-Cre along with Shhflox allele took too long time we bred Nfe2 mutant mice to the Gli1-GFP reporter line. As shown in Gli1-GFP expression was drastically reduced in Nfe2 mutant mice supporting the idea that platelet mutants have reduced dentate cells produced from Shh activation.We also added another Shh reporter line i.e., 2) The blot of E17.5 blood samples immunoprecipitated with CD41 are used to show that Shh is associated with platelets . Our understanding of the model is that megakaryocytes and platelets do not synthesize Shh, but that it is associated with the platelets at a later time point. The size of the Shh band shown is the size of uncleaved, immature Shh, rather than the mature, N-terminal protein that is a ligand. This really brings into question the model that “shh could be packaged into platelets similar to other factors that are packaged into platelets without being expressed by megakaryocytes”.Shh-Cre with Ai14 reporter which has a strong red fluorescence in the Shh expressing cells. We did not see any platelets or MK cells are co-localized with Ai14 reporter which reconfirm that MK cell lineages do not express Shh (We checked whether the lineage of megakaryocytes do express mRNA by using ress Shh . The ratress Shh . Cells fress Shh . Further3) Regarding the conclusion that Shh from HFs passes through the leaky BBB to dentate neural stem cells and platelets act as the Shh carrier: the Nfe2 knockout experiments insuggest that Nfe2-dependent platelets play an important role in expanding the Ptch1+ DG stem/progenitor cells, but this might not be through their role as a Shh carrier. Rather, some other platelet-derived factors or indirect effects downstream of platelet differentiation might be responsible for this Nfe2-dependent effect.Nfe2-mediated platelet formation could also possibly affect the dentate at the age. We toned down our conclusion drawn from Nfe2 mutants and focused on describing the result that Ptch1-LacZ positive dentate cells were also decreased in the Nfe2 mutants and that the possible down-regulation of Shh responsiveness could be involved in the mutant.It is totally possible that the other contents of platelets such as PdgfA and VEGF could be released to the DG stem cells. Other signaling pathways involved in the Furthermore, how is follicular Shh incorporated into platelets? And how do platelets release Shh at the DG? Revealing these mechanisms and inhibiting them would address the above issue and greatly improve the study, but this may be too much to ask. The authors should revise the text instead in order to avoid overinterpretation.We totally agree with the reviewers point here and tried to get further supporting data about the same question. Unfortunately we can’t provide solid results except the preliminary results  at the m4) The authors should be more careful about identification of the DG neural stem cells and use more markers to define them. Counting the numbers of Ki67+ cells and LEF1+ cells is not enough.We previously showed that Lef1 is a strong dentate stem cell marker and that at perinatal ages the stem cells are rapidly proliferating mode  so we re


In addition, we observe a striking pattern of mutual exclusive integration. This is an indication that insertions in these loci target the same gene, either in their linear genomic vicinity or in their 3D spatial vicinity. Our findings shed new light on the repertoire of targets obtained from insertional mutagenesis screening and underline the importance of considering the genome as a 3D structure when studying effects of genomic perturbations.Genomically distal mutations can contribute to the deregulation of cancer genes by engaging in chromatin interactions. To study this, we overlay viral cancer-causing insertions obtained in a murine retroviral insertional mutagenesis screen with genome-wide chromatin conformation capture data. Here we find that insertions tend to cluster in 3D hotspots within the nucleus. The identified hotspots are significantly enriched for known cancer genes, and bear the expected characteristics of  Retroviral insertional mutagenesis is used for identifying genes involved in the development of cancer. Here, the authors overlay cancer-causing insertions with genome-wide Hi-C data and find that retroviral elements tend to cluster in 3D hotspots. The three-dimensional 3D) organization of the genome appears to play an important role in carrying out the instructions encoded in its linear sequence. For instance, ample evidence suggests that the 3D conformation of chromosomes in the cell nucleus is an important factor in gene expression regulation12D organiz245689These observations are enabled by a technique called chromosome conformation capture or one of its variants, that is, 4C, 5C, Hi-C and ChIA-PET1112et al.,et al.Chromatin interaction studies also help to unravel the influence of 3D genome organization on complex genetic diseases such as cancer151617et al.et al.The variability of chromatin interactions between cell types is mostly confined to local interactions20Here we study the effect of long-range chromatin interactions on co-localization of viral integrations in mouse cancer genomes. This is achieved by overlaying Hi-C data obtained in mouse embryonic stem (ES) cells and cortex cells, with cancer-causing insertional mutations obtained in murine lymphoma and leukaemia. Rather than investigating the landscape of translocations and copy number variations we aim to delineate the repertoire of target genes affected by insertional mutations, while taking into account the 3D conformation of the genome.Retroviral insertional mutagenesis (IM) is a forward genetic screening technique for identifying genes involved in the development of cancer, and is based on the ability of retroviruses to insert their DNA in the genome of a host cell. Since the viral long-terminal repeats (LTRs), located at either end of the provirus, contain strong enhancer sequences, these insertions can lead to the deregulation of nearby genes2526CISs are defined as clusters of insertions along the linear genome without consideration of genome organization. However, long-range chromatin interactions might allow insertions to contribute to deregulation of genomically distal genes. As a result, insertions that deregulate the same gene may be found dispersed across multiple linearly distal but spatially proximal loci . TherefoImportantly, if this hypothesis is correct, the current practice of CIS calling and searching for nearby putative cancer genes based only on the linear genome is inadequate. More specifically, it has two important limitations. First, the insertion signal is diluted, since a cluster of insertions that affect the same gene is split across multiple distal loci. Consequently, many truly causal ICs may not reach the required significance threshold to be called a CIS. This is especially problematic in small sample sizes. Second, the genes in the genomic vicinity of the ICs are not necessarily the actual target genes. As a result, CISs that exert their effect by chromatin looping can be left without a clear target or even associated to wrong target genes.To investigate this phenomenon, we assess whether ICs are in spatial proximity more frequently than expected by chance. In the following, we demonstrate that, in addition to the well-characterized clustering of insertions along the linear genome, insertions also co-localize according to the 3D conformation of the genome. This is important for determining the putative targets of insertions. Consequently, our spatial clustering approach identifies additional loci with putative cancer genes and improves the identification of putative target genes of many other ICs in retroviral IM screens. In addition, it provides new clues as to how long-range chromatin interactions are involved in  enhancer activity.http://mutapedia.nki.nl). In total, this data set contains 19,997 viral insertion sites across 933 murine tumours of various genetic backgrounds. These tumours developed in a range of tissues, predominantly in the thymus, spleen and lymph node, and contained a mixture of B and T cellsRetroviral IM data were acquired from Mutapedia  between open chromatin and the presence of insertions. Such strong correlation is observed for all chromosomes . This implies that inserted regions in the mouse genome tend to be co-located in 3D hotspots.The most significant differences, however, are observed when comparing co-localization of bin pairs of which both bins are recurrently inserted with bin pairs of which at least one bin does not harbour any insertions In an orthogonal analysis , we consWe next established which pairs of inserted loci in the mouse genome are co-localized in 3D hotspots. To this end, we first defined ICs by selecting peaks in the kernel-smoothed insertion count  along thTo determine chromatin interactions between ICs, we compared the distribution of Hi-C values between the high-scoring ICs with the distribution of Hi-C values between all bins at a comparable genomic distance. In spirit, this is similar to the normalization used before and described in the Methods section. Note that, as in this analysis the insertion data is not binned, we can use the Hi-C data at its original resolution of 40 kb. A Wilcoxon rank-sum test was used to determine whether two ICs are more frequently spatially co-localized than expected by chance (see Methods for details). Only the 17,102 possible intra-chromosomal combinations of high-scoring ICs were considered. A pair of ICs with significant chromatin interactions is called a co-localized IC (CLIC). The two loci that constitute a CLIC will henceforth be referred to as CLIC loci. Note that each CLIC locus corresponds to an IC, but that an IC is only a CLIC locus in case they engage in one or more significant chromatin interactions, that is, when they are part of one or more CLICs.P value=1.4 × 10−5) than the overlap observed for ICs that did not form CLICs . This supports our previous observation that the 3D co-localization arises more frequently between recurrently inserted loci and is, at least to some extent, driven by selective pressure. We found 874 CLICs, encompassing a total of 479 unique CLIC loci. An overview of the CLICs is given in rm CLICs . MoreoveNotch1, Ikzf1, Jdp2 and Ccnd3, all of which are top CIS genes. Typically, mutually exclusive mutations provide evidence that the mutated loci are functionally linked in a common biological pathway as alteration of a second locus within the same pathway offers no further selective advantageWe observed that insertions in CLICs exhibit a distinct pattern of mutual exclusion, that is, insertions are unlikely to co-occur in the two loci in the same sample. This is exemplified in P value=10−66) pattern of mutual exclusion, supporting the hypothesis that insertions in both loci target the same gene.Mutual exclusion is apparent for many more CLICs. To characterize this, we scored mutual exclusion for two loci by the Mean-Manhattan distance, defined as the fraction of samples with one of two loci inserted. The distribution of distances for CLICs and all non-significant combinations of high-scoring ICs are compared in P value=1.8 × 10−5) than the overlap observed for high-scoring ICs that do not form CLICs. Thus, insertions in regions engaged in 3D interactions are more likely to deregulate genes causing cancer.We determined the occurrence of known cancer genes within CLIC loci. We used the list obtained from Cancer Gene Census (accessed: Jan 2014) for this purposeOf the known cancer genes within a CLIC locus, 31 (in 27 CLIC loci) were not among the list of CIS genes . This shBrca2, Fancc, Apc and Jak1. For all of these genes, the literature provides evidence that suggests a role in the haematopoietic neoplasms under study. For instance, while germline mutations in human BRCA2 are known to predispose for breast and ovarian cancer, recently, evidence was presented suggesting that mutations in the BRCA pathway also significantly increase the risk for certain leukaemias and lymphomasFANCC, was also among the list of CLIC genes. Furthermore, APC, a gene with a role in a plethora of cancers has also been implicated in promoting leukaemiabona fide putative cancer genes. These cancer genes can only be discovered by aggregating evidence across multiple loci co-localized by 3D conformation.Among these genes are P value=4 × 10−8). Taken together, this suggests that insertions in these CLIC loci may be involved in deregulation of a known cancer gene by long-range chromatin interactions.The majority of CLIC loci  do not overlap a known cancer gene. However, 54% of these CLIC loci form a CLIC with a CLIC locus that does harbour a known cancer gene. This leaves only 166 (35%) CLIC loci without a known cancer gene (corresponding to 463 (53%) CLICs for which none of the CLIC loci overlap to any known cancer genes). This number is significantly lower when compared with a control set of high-scoring IC pairs that do not participate in a CLIC  regulating gene expression in the nucleus. Notch signalling plays an important role in haematopoietic neoplasms, including leukaemia and lymphomaNotch1 across a large genomic distance by long-range chromatin interactions. This is supported by the observation that insertions across the six CLIC loci exhibit a distinct pattern of mutual exclusion , we searched for enrichment of TF-binding sites (TFBSs) in the locus without the known cancer gene (locus B). Finding such TFBSs may be an indication that locus B contains regulatory elements that are involved in the regulation of the cancer gene in locus A and that insertion of a viral LTR in that locus can boost this regulatory interaction activating the cancer gene at locus A.P value cutoff of 10−5 was employed to determine the TFBSs. A CLIC locus is called a TFBS carrier if it contains more TFBS peaks than the median number of peaks across all ICs. Note that the number of peaks in an IC was normalized by the size of the ICs.To this end, we used previously published chromatin immunoprecipitation-sequencing data for 50 TFs in mouse ES cells . This implies that known cancer genes frequently co-localize with distal loci that are enriched for regulatory elements that aid viral insertions at those distal loci to influence the activity of cancer genes.We found that among the 337 CLICs that overlapped a cancer gene in locus A, 230 are TF carriers in locus B. This is significantly more than in a control set of high-scoring IC pairs that do not participate in a CLIC  for all genes in CLICs with genes in a control set of high-scoring IC pairs that do not participate in a CLIC. This comparison is statistically significant (TAB−TA)>0). These include prominent insertional target genes such as Myb, Gfi1 and Ccnd2  of genes located in the 28 CLIC loci that harbour insertions in more than five samples displayed increased spatial association scores www.ingenuity.com) revealed that of the 83 genes in these loci, 42 can be linked to cancer . Among these are Stat1, Stat2, Il23r and Il12rb2, all of which are members of the JAK–STAT signalling pathway. This pathway is known to be deregulated in haematopoietic malignanciesCpt1a, which recently has been identified as member of a 24 gene prognostic signature for acute myeloid leukaemiaConsidering the 3D organization of the genome in the analysis of IM, data can also reveal novel target genes. For instance, based on our CLICs, we retrieve 31 known cancer genes that were not identified by a traditional CIS analysis. Moreover, we identified 16 CLIC loci that did not overlap nor co-localize with any previously identified CIS genes or known cancer genes. Ingenuity Pathway Analysis , obtained by Gaussian kernel convolution (GKC): σ and depends on the local density of insertion sites. In our analysis, we set 2σ to 80 kb. To deal with the fact that the Hi-C data is binned, the IC boundaries are aligned to the nearest bin boundary. This results in clusters spanning between 40 and 800 kb, which is within the range of minimum and maximum size of CISsf(x), retaining only those ICs for which some evidence for selection is observed. Note that this threshold is lower than the threshold required for statistical significance ICs are determined as the local extrema (peaks) in the kernel-smoothed insertion count Two regions with a small genomic distance have higher numbers of chromatin interactions, independent of the actual 3D organization of the genome. Therefore, several studies have defined normalized Hi-C contact maps by accounting for the spatial bias in the Hi-C signal14hij, the Hi-C contacts between bin i and j with genomic distance of d. The normalized score Hd, where Hd is the kth superdiagonal of H  to the distribution of bins with approximately the same genomic distance (negative distribution), using a one-tailed Wilcoxon rank-sum test. To guarantee that there is a sufficient number of values in the positive distribution, we set the minimum size of an IC to three bins so that each positive distribution consists of at least 3 × 3=9 points. To this end, ICs with size of less than three bins are expanded to cover one more bin on both sides.We tested co-localization for all combinations of ICs within the same chromosome . The co-localization of two ICs, δ=, where dmin and dmax are defined as the minimum and maximum genomic distance between ICi and ICj, respectively .Supplementary Figures 1-17List of Co-localized Insertion Clusters (CLICs)List of CLIC-lociList of genes with increased spatial association scores for two thresholds


The performance achieved here with small numbers of electrodes and computationally simple decoding algorithms suggests that it may be possible to control a BMI using ECoG recorded from damaged sensorimotor brain systems.In patients with unilateral upper limb paralysis from strokes and other brain lesions, strategies for functional recovery may eventually include brain-machine interfaces (BMIs) using control signals from residual sensorimotor systems in the damaged hemisphere. When voluntary movements of the contralateral limb are not possible due to brain pathology, initial training of such a BMI may require use of the unaffected ipsilateral limb. We conducted an offline investigation of the feasibility of decoding ipsilateral upper limb movements from electrocorticographic (ECoG) recordings in three patients with different lesions of sensorimotor systems associated with upper limb control. We found that the first principal component (PC) of unconstrained, naturalistic reaching movements of the upper limb could be decoded from ipsilateral ECoG using a linear model. ECoG signal features yielding the best decoding accuracy were different across subjects. Performance saturated with very few input features. Decoding performances of 0.77, 0.73, and 0.66 (median Pearson's  The brain-machine interface (BMI) is a tool to replace areas of human functionality lost due to trauma or degenerative disease. To date, BMIs have been used with humans to control cursors In most efforts to develop a brain-machine interface (BMI) to restore upper limb function, the design has assumed a normally functioning brain as the source of neural control signals, with the BMI serving to bypass lesions of neural pathways connecting the brain to its muscle effectors. However, a large patient population with hemiplegia from strokes and other cerebral lesions may also benefit from BMIs The descending corticospinal tract is not solely comprised of axons that cross the midline. A minority of the fibers also arise from ipsilateral cortex Reach trajectories have been decoded extensively in nonhuman primates performing center-out reaches with microelectrode arrays Three subjects, two male and one female aged 24–36 years, were implanted with ECoG arrays prior to surgical resection of their seizure foci. Additional subject information can be found in the supporting materials. Grid placement was determined solely on the basis of their clinical need without any influence from this study. Only subjects with motor cortex coverage were considered for this study. 2  for subject 1 and 2; ECoG signals from subject 3 were also referenced to an inactive intracranial electrode, but were recorded by a 128-channel NeuroPort system . Signals were digitized by the Neuroscan system at 1 kHz after being band-pass filtered between 0.15 and 200 Hz (subject 1 and 2). Signals recorded by the BlackRock system were band-pass filtered in analog with a low-pass cutoff of 7,500 Hz and a high-pass cutoff of 0.3 Hz, digitized at 30 kHz, then downsampled to 1 kHz. Anatomical reconstructions of each subject's electrode placement were generated by volumetrically co-registering post-implantation brain CT with high-resolution pre-implantation brain MRI images using BioImage  or NeuroPort (subject 3) amplifier's external trigger inputs and the Optotrak Data Acquisition Unit (ODAU).Subjects were instructed to make reaches to the tip of a long wooden dowel being moved by the experimenter in three-dimensional space. Subjects used the arm ipsilateral to the ECoG electrode implantation. Each reach was either terminated by touching the dowel with the subject's pointing index finger  or with an index-thumb pinch . The subject returned his or her hand to a comfortable resting position following completion of each reach to the target. The subject rested his or her hand in the home position for a variable amount of time (0–16.7 seconds), after which the target was moved to another point in three-dimensional space. The position of the target in three-dimensional space was determined by the experimenter in an attempt to probe the natural workspace of the subject's upper limb as thoroughly as possible. The target tended to be placed in front of and above the subject's rest position, but varied in the lateral  directions. The durations of the reaches performed by subjects 1, 2, and 3 were 3.2–6.2, 2.0–5.0, and 1.2–5.3 seconds, respectively, with median durations of 4.7, 3.0, and 2.7 seconds. The volume encompassed by the subject's workspace is detailed in Recorded ECoG signals were imported into MATLAB  and analyzed using the Signal Analysis Toolbox. These signals were re-referenced to a common average reference (CAR) to avoid spatial biases from varying distances between active and reference electrodes In addition to frequency domain features, previous work indicated that smoothed time domain features contained information related to movement kth dimension of the kinematic output, The kinematics were modeled as a linear combination of the input features with a constant offset and a Gaussian noise term: r) between observed and predicted kinematics was used to quantify model accuracy. Feature selection and model training were performed on 80% of each block of trials, and the remaining 20% was used only for evaluation. Each training session contained at least 18 movements, and each testing session contained at least 4 movements. Chance decoding performance was calculated for each session by randomly shuffling the extracted and smoothed neural features 1024 times, similar to the random shuffle procedure done in All models were tested under fivefold cross-validation. Pearson's correlation  and the kinematic data were normalized by subtracting the means and dividing by the standard deviations. The means and standard deviations were recomputed during every fold of cross-validation using only the training data. This normalization was done to ensure the magnitude of the features did not impact how heavily they were weighted in the decoding models.remaining variance, etc.While Cartesian coordinates for arm position  are orthogonal, constraints on the positioning and capabilities of the subjects resulted in an inability to fully probe these axes of the workspace independently. The kinematics of the resulting movements in this space were correlated to the extent that presenting decoding results in Cartesian axes would be somewhat misleading. We therefore used principal component analysis (PCA) to decorrelate the kinematic dimensions by projecting the 3D arm position onto another set of orthogonal axes. These decorrelated kinematics, or principal components (PCs), accounted for decreasing proportions of the variance in the original signals. The first PC was therefore oriented in the direction of largest variance , while the second PC was oriented in the direction of the most p<0.05, ANOVA with Dunn-Sidak post-hoc). All but one of the models built on the second and third PCs across all subjects were indistinguishable from chance. We therefore focus on the decoding accuracies of the first PC in this study.The coefficients used for the PCA transform were recalculated for each fold of cross-validation using only the normalized training data. In all three subjects, decoding accuracy of the first PC was greater than the second and third PCs . Performance of these restricted models is also reported below in comparison to the full model performance for model orders one of up to 40. An analysis of the performance saturation of these models with increasing numbers of inputs was performed with a Kruskal-Wallis non-parametric one-way analysis of variance. The least significant difference post-hoc test was used to determine the first number of inputs at which additional inputs did not statistically increase performance.The large smoothing window applied to the extracted features meant it was possible that changes in the neural features could occur substantially before or after their associated movements but still yield a high correlation with the movements. To investigate whether the feature changes preceded or followed the associated movements, we calculated correlations every 50 ms between the extracted features and the first principal component of movement offset by at most 1000 ms relative to one another.The extracted signal features had substantial correlations with the first PC of the ipsilateral hand position, and the maximally correlated feature types varied across subjects. The three-dimensional kinematics and their contributions to the first PC are shown in The large smoothing window applied to the extracted features meant it was possible that changes in the neural features could occur substantially before or after their associated movements but still yield a high correlation with the movements. To investigate whether the feature changes preceded or followed the associated movements, we plotted the magnitudes of the correlations between the neural features and the hand kinematics at different time offsets relative to one another . Subjectp<0.05, ANOVA with Dunn-Sidak post-hoc) than models with the best performing number of inputs.p<0.05). Smaller ranges of time lags  resulted only in small reductions in performance. The low frequency features  and LMP performed significantly better than the high frequency features (low gamma through high gamma 2) for subject 1 (p<0.05). In subject 2, there was no significant difference between models trained with high gamma 1 or high gamma 2, and these sets of models outperformed all other single signal feature models (p<0.05). In subject 3, models trained with delta, low gamma, and high gamma 2 performed statistically worse than all other single signal feature models, which had no significant difference between each other (p<0.05). All p-values reported between feature types were obtained as a part of the two-way ANOVA with Dunn-Sidak post-hoc test described in the The input features in p<0.05, one-way ANOVA with least significant difference correction) if more signal features and/or recording sites were added to the one best model input for subject 1 or 3, or to the two best model inputs for subject 2. Models trained with nine inputs were chosen a posteriori as a proxy for the peak decoding accuracy across sessions and subjects, as it gave consistently high results. Decoding accuracy was found to be significantly higher than chance . The decoding performance of the first PC of movement for each session is shown in r) between actual and predicted reach kinematics of 0.77, 0.73, and 0.66 for subjects 1–3. This accuracy was accomplished using as little as 133 seconds, and no more than eight minutes, of training data in each session. Furthermore, two of the subjects in this study (subject 1 and 3) had severe upper limb weakness contralateral to ECoG recording grids, arising from lesions of brain structures critical for motor control. Although subject 2 did not have contralateral limb weakness, he had a lesion of parietal lobe structures that participate in visually guided reaching and grasping movements of the upper limb Our findings in three different subjects show that it is possible to decode a low-dimensional representation of natural reaches from ipsilateral ECoG electrodes in the presence of damaged cortical motor systems. This decoding attained a median Pearson's correlation  and the performance of different spectral features. For example, more intact motor and premotor cortices in subjects 2 and 3 may have allowed for better decoding with high gamma power.It is also possible that compensatory movements with the contralateral hemibody presented a confound The results depicted in We found that decoding performance saturated with a small number of model inputs. That is, a few signal features at a few recording sites yielded the best performance, and the addition of more signal features and/or recording sites did not significantly improve performance. This finding could reflect a very coarse neural representation for ipsilateral limb movement that is widely distributed across sensorimotor systems typically specialized for contralateral limb movement. Alternatively, it could reflect transcallosal activation of these systems by homologous systems in the contralateral hemisphere. In this way, activity in sensorimotor cortex contralateral to movement (e.g. left hemisphere controlling right hand in subject 1 and 2) could modulate the activity of sensorimotor cortex ipsilateral to movement (e.g. in right hemisphere in subject 1 and 2). The encoding of this modulation during reaching movements might also be coarse, serving primarily to coordinate the movements of the two arms during reaching. Such explanations are necessarily highly speculative. The spatial resolution and anatomical distribution of our ECoG recordings were not sufficient to test these hypotheses. Nevertheless, our findings indicate that only a few electrodes are needed to achieve reach decoding from ECoG features, and that these electrodes qualitatively correspond to sensorimotor cortex as identified by ESM .p<0.05, ANOVA with Dunn-Sidak post-hoc), and that all but one of the models built for the second and third PCs were indistinguishable from chance. One possible explanation is that the second PC captured bi-directional movements in the lateral dimension, i.e. to the left or to the right  for a wider population of patients with upper limb paralysis from brain lesions such as stroke, trauma, or surgical resection of a tumor. For example, upper limb function could be partially restored by low dimensional control of a neuroprosthetic device in which ECoG electrodes are implanted over healthy ipsilateral cortex. Alternatively, electrodes could be implanted in and around cortical sensorimotor areas that have been damaged, in order to control the affected, contralateral upper limb. An important advantage of this approach is that it avoids the risks of surgically implanting chronic indwelling electrodes in healthy cortical areas controlling the patient's only functioning upper limb. In addition, implantation of ECoG electrodes in the lesioned hemisphere can be done in conjunction with other invasive interventions, such as infusions of stem cells and growth factors encouraging neurogenesis and neuroplasticity, thereby sharing the risk with other experimental therapies.Our results suggest that it may also be possible to bootstrap a BMI system controlling contralateral arm movements by first using it to control ipsilateral arm movements. For example, the movements of the ipsilateral limb under BMI control could be mirrored in the contralateral arm using robotic assistance or functional electrical stimulation. This could provide an opportunity for development of contralateral arm control through functional reorganization and even neurogenesis. The neural activity generated while training the BMI could potentially facilitate neurobiological interventions through activity-dependent neuroplasticity, allowing the patient to eventually wean off ipsilateral arm control as control of the contralateral arm is restored. This might expedite the training process for BMIs by exploiting the more intact movements of the patient's unaffected limb.S1 TableExtrema of hand position relative to the shoulder in each dimension. Units are in cm, e.g. S1's hand position moved between 21.6 cm below their shoulder and 15.2 cm above it.(DOCX)Click here for additional data file.S2 TableExperimental session details.(DOCX)Click here for additional data file.S1 VideoActual (solid) and predicted (transparent) 3d hand position for subject 1. Any time delays that would be induced by our offline methods have not been included. The sphere denotes the position of the target.(MP4)Click here for additional data file.S2 VideoActual (solid) and predicted (transparent) 3d hand position for subject 2. Any time delays that would be induced by our offline methods have not been included.(MP4)Click here for additional data file.S3 VideoActual (solid) and predicted (transparent) 3d hand position for subject 3. Any time delays that would be induced by our offline methods have not been included.(MP4)Click here for additional data file.


Inhibin B has been identified as a potential marker of Sertoli cell function in males. The aim of this study is to produce a normative model of serum inhibin B in males from birth to seventeen years. We used a well-defined search strategy to identify studies containing data that can contribute to a larger approximation of the healthy population. We combined data from four published studies (n = 709) and derived an internally validated model with high goodness-of-fit and normally distributed residuals. Our results show that inhibin B increases following birth to a post-natal peak of 270 pg/mL (IQR 210–335 pg/mL) and then decreases during childhood followed by a rise at around 8 years, peaking at a mean 305 pg/mL (IQR 240–445 pg/mL) at around age 17. Following this peak there is a slow decline to the standard mature adult normal range of 170 pg/mL (IQR 125–215 pg/mL). This normative model suggests that 35% of the variation in Inhibin B levels in young males is due to age alone, provides an age-specific reference range for inhibin B in the young healthy male population, and will be a powerful tool in evaluating the potential of inhibin B as a marker of Sertoli cell function in pre-pubertal boys. Inhibin B is a member of the transforming growth factor beta family of growth factors, and in males is secreted by the Sertoli cells of the testis that are located on the basement membrane of the seminiferous tubules, and nurture and support spermatogenesis. There is a well described negative feedback relationship, which becomes established around puberty , 2, withIn a retrospective longitudinal study we have previously shown a potential role for inhibin B to predict fertility outcome in young males . In adulWe searched two databases, Pubmed and Medline, for the search term inhibin B. The last search was performed in August 2015. Abstracts were studied, duplicates removed, and initial exclusion criteria applied. The exclusion criteria included, papers that were not written in English, those not containing humans and those not containing serum inhibin B levels. Full-text papers were then studied and further exclusion criteria applied to rule out studies not involving healthy male subjects, containing data that was not in an extractable form, not containing the correct age range, and using pubertal (i.e. Tanner) stage rather than age. The reference lists of selected studies were checked to identify further relevant studies. Data was mined from charts in the 4 identified studies  using WeApproval was not required from an ethics committee or institutional review board since our research was limited to use of previously collected, non-identifiable data that has been published in peer reviewed journals which is specifically excluded from Research Ethics Committee review by the National Research Ethics Service guidelines of the UK Health Research Agency . Patient2 coefficient of determination) and normality of residuals . The Akaike information criterion (the other common measure of goodness of fit for predictive models) was not calculated, since is equivalent to the r2 coefficient of determination for the linear least square regression models under consideration, with both measures being directly related to the residual sum of squares for a candidate model. We assessed candidate models for underfit (i.e low r2 due to insufficient complexity of the model in terms of number of model parameters) and overfit . To guard against models being selected by chance configuration of the data two forms of internal validation were implemented. 5-fold cross-validation was performed with residual mean training error for five randomly-chosen 80% subsets of the data compared to residual mean test error for the 20% subsets not used to fit the model. Bootstrap validation was performed on each candidate model by 2000 iterations of selecting with replacement ages and root-transformed pairs at random from the data, calculating the mean square error for each sample, and estimating the extra-sample prediction error by the mean of the bootstrap mean square errors.We used an established methodology –23 to coThe search for the term Inhibin B in Pubmed and Medline generated 1568 results, yielding 871 unique sources after removal of duplicates. The initial exclusion criteria were applied to the abstracts, resulting in 51 full-text studies being analysed and further exclusion criteria applied. Four papers were selected for quantitative synthesis in this study .2 and residual normality were rational polynomials. Models having fewer than 8 parameters displayed considerable underfit to the data, with r2 values over 10% lower than for the 8-parameter model. An 11-parameter model had higher r2 and lower residual mean error than the 8-parameter model, but this increase in model performance involved negative inhibin B values between conception and birth  and less normally-distributed residuals (94% agreement with a perfect Gaussian distribution as against 97%). Estimates of generalisation error obtained from 5-fold cross validation and 2000 bootstrap samples were within 1% of each other for all models. We therefore report the 8-parameter model2 = 0.35, indicating that 35% of the variation in inhibin B levels for these ages is due to age alone, with the remaining 65% due to other factors such as genetics, lifestyle and Tanner stage. The repeated imputation of adult inhibin B values had no appreciable effect on the derivation of the model for ages 0–17 years, since the model parameters obtained for each instance were similar  at birth in males and reaches a post-natal peak of 270 pg/mL (IQR 210–335 pg/mL) at around 3 months old ; Table 4We have derived a normative model of inhibin B for a healthy human population of males from birth to the age of seventeen. We have shown that, in males, levels of inhibin B rise from birth to a post-natal peak, only to decrease to low, but still measurable, levels during childhood, and increase again from approximately 8 years of age to reach a peak around 17 years old. Our internal validation results suggest that (a) the optimal model is not obtained by a chance selection of suitable data, (b) the reported model is neither over- nor underfitting the data, and (c) the generalisation error when using the model to predict new values is likely to be low.The finding of a post-natal peak is in keeping with a number of studies. Chada et al, (2003) reported that inhibin B showed a significant increase to a peak at 3–4 months of age and a decrease at 5–11 months . This trThese data also show that there is a rise in inhibin B from age 8. Although this analysis does not include pubertal staging, this rise in inhibin B would seem to be earlier than the clinical onset of puberty, likely reflecting prepubertal proliferation of Sertoli cells , 29. TheWe have also shown that there is a pubertal peak, as the level at about 17 years old exceeds that of the adult . This isIt is interesting that, in males, inhibin B peaks at a younger age (17 years in our model) than testosterone, which peaks at 19 years . We knowThis study has a number of limitations, including its relative small size and different storage procedures for the samples. Crofton et al (2002) reported storing samples for up to eight years at -80°C before analysis . This vaIn summary we have described a normative model of inhibin B for young males from birth to aged 17 years. We believe this will be an invaluable tool as a reference model for evaluating the role of inhibin B as a marker of Sertoli cell function in the younger male.S1 DatasetThe combined worksheet has the 709 extracted age-inhibin B pairs, together with imputed values at age 30 and fixed zero values at conception. Raw values in pm/mL are square root adjusted. The Xi columns are the 10-fold imputation variants. The Kj worksheets contain the 80% of the data used for training at each validation fold, together with the 20% remainder used as test data.(XLS)Click here for additional data file.


To describe functional outcomes, care needs and cost-efficiency of hospital rehabilitation for a UK cohort of inpatients with complex rehabilitation needs arising from inflammatory polyneuropathies.186 patients consecutively admitted to specialist neurorehabilitation centres in England with Guillain-Barré Syndrome (n = 118 (63.4%)) or other inflammatory polyneuropathies, including chronic inflammatory demyelinating polyneuropathy (n = 15 (8.1%) or critical illness neuropathy (n = 32 (17.2%)).Cohort analysis of data from the UK Rehabilitation Outcomes Collaborative national clinical dataset. Outcome measures include the UK Functional Assessment Measure, Northwick Park Dependency Score (NPDS) and Care Needs Assessment (NPCNA). Patients were analysed in three groups of dependency based on their admission NPDS score: ‘low’ (NPDS<10), ‘medium’ (NPDS 10–24) and ‘high’ (NPDS ≥25). Cost-efficiency was measured as the time taken to offset the cost of rehabilitation by savings in NPCNA-estimated costs of on-going care in the community.The mean rehabilitation length of stay was 72.2 (sd = 66.6) days. Significant differences were seen between the diagnostic groups on admission, but all showed significant improvements between admission and discharge, in both motor and cognitive function (p<0.0001). Patients who were highly dependent on admission had the longest lengths of stay (mean 97.0 (SD 79.0) days), but also showed the greatest reduction in on-going care costs (£1049 per week (SD £994)), so that overall they were the most cost-efficient to treat.Patients with polyneuropathies have both physical and cognitive disabilities that are amenable to change with rehabilitation, resulting in significant reduction in on-going care-costs, especially for highly dependent patients. Guillain-Barré Syndrome (GBS) and other inflammatory polyneuropathies are a group of disorders that are often associated with significant long-term disability Inflammatory polyneuropathies are a clinically and pathophysiologically heterogeneous group. GBS is an acute, autoimmune condition, with a natural course fast with high disability and usually episodic immune treatment; Chronic inflammatory demyelinating polyneuropathy (CIDP) has a chronic, autoimmune, natural course, slow with ongoing disability, usually maintenance immune treatment; Critical Illness Neuropathy (CIN) is more a myopathy than a neuropathy; it is an acute, ischemic/degenerative/inflammatory disorder, associated with a prolonged period of critical illness – usually in intensive care settings. It has no immune treatment option. Its natural course natural course represents resting disability with slow recovery and cognitive deficits due to the systemic inflammatory/infectious etiology. Given this heterogeneity, differences in outcome are expected between these groups.The existing literature tends to focus on GBS, where a number of studies have explored outcomes relating to predominantly physical disability ) or quality of life measures One of the key challenges of healthcare services across the world is to identify those services that are not only effective, but also represent value for money. Porter and Teisberg In England, the UK Rehabilitation Outcomes Collaborative (UKROC) database collates episode data for inpatients admitted to specialist rehabilitation services. In addition to providing the commissioning dataset, it also routinely provides national benchmarking on quality, outcomes and cost efficiency of rehabilitation. Within the dataset, functional gain is evaluated using the UK Functional Assessment Measure (UK FIM+FAM) The aim of this paper was to validate the factor structure of the UK FIM+FAM within the study population and to describe functional outcomes, including change care needs and cost-efficiency following specialist rehabilitation for patients with complex disability arising from inflammatory polyneuropathies. We also examined care needs and outcome across the different diagnostic groups and compared outcomes and co-efficiency of rehabilitation for patients with different levels of dependency.Rehabilitation Services in England are classified into three different levels. Level 1  and Level 2 (district or supra-district) specialist rehabilitation services take a selected population of patients with complex needs for rehabilitation that are beyond the scope of their local (level 3) general rehabilitation services http://www.csi.kcl.ac.uk/ukroc.html. Data collection is now a mandatory requirement for commissioning of specialist rehabilitation services in England, but between 2010 and 2013 it was voluntary and contributing centres could report one of three measures, the Barthel Index, the FIM or UK FIM+FAM. Between 1.1.10 and 30.4.13, a total of 319 inpatient episodes were recorded for patients admitted with a diagnosis of Guillain-Barre Syndrome or other inflammatory polyneuropathy to a total of 56 specialist rehabilitation units. Of these, 217 were admitted to services that record the UK FIM+FAM and had complete UK FIM+FAM admission scoring. Of these 186 patients  had complete UK FIM+FAM scores at both admission and discharge and were taken as the study sample extracted for this analysis. This sample included data from 45 specialist rehabilitation units, representing approximately 75% of the total number of specialised inpatient neurorehabilitation centres (level 1 and 2) within England during the study period.The UKROC database collates the national clinical dataset for in-patient specialist (Levels 1 and 2) rehabilitation in England. The dataset comprises socio-demographic and process data  as well as clinical information on rehabilitation needs, inputs and outcomes. Full details may be found on the UKROC website The FIM+FAM is a global measure of disability that includes the 18-item FIM (version 4) and adds a further 12 items, mainly addressing psychosocial function so that the total FIM+FAM comprises 30 items (16 motor items and 14 cognitive items). Each item is scored on a seven-point ordinal scale from 1  to 7 (complete independence). Originally developed in the US in the 1990 s A separate optional 6-item Extended Activities of Daily Living (EADL) module has been developed with the aim to extend the upper range of the tool The Northwick Park Dependency Score (NPDS) is an ordinal scale of dependency on nursing time (number of helpers and time taken to assist with each task) designed to assess needs for care and nursing in clinical rehabilitation settings Basic Care Needs (BCN) Special Nursing Needs (SNN)  or 5 (present)).The NPDS is shown to be a valid and reliable measure of needs for care and nursing in rehabilitation settings Low dependency (NPDS <10): patients are largely independent for basic self care,Medium (NPDS 10–24): patients generally require help from one person for most self-care tasksHigh (NPDS ≥25): patients require help from two or more persons for most care tasks and often also have special nursing needs.The NPDS also translates via a computerised algorithm to Northwick Park Care Needs Assessment (NPCNA) Although there is no formal accreditation process for use of the UK FIM+FAM and NPDS, the attendance of UK FIM+FAM training by at least a core team of staff is requirement for UKROC registration. All units that are registered with UKROC have access to free training and updates in workshops that are run several times a year to keep staff up to date, and telephone support is also provided by the UKROC team.Within the UKROC dataset, the cost efficiency is calculated as the time taken to offset the cost of rehabilitation by the resulting savings in the cost of on-going care in the community. This is calculated from ‘Mean episode cost of rehabilitation’ divided by ‘mean reduction in weekly cost of care’ from admission to discharge, as estimated by the NPCNA. The cost of episode was calculated per patient as bed-day cost multiplied by length of stay in days. In this study, the cost per bed-day was calculated retrospectively based on the same costing methodology as our previously published cost analysis 16, because it was not previously validated specifically in this population, we carried out a preliminary principal component analysis (PCA) to confirm the overall factor structure. We used admission and discharge scores data pooled together, N = 368 to extend across the scoring range and to allow for a minimum sample size of 10 cases per item. To assess internal reliability, we calculated Cronbach’s coefficient-alpha for the whole scale and subscales as determined by the PCA. A coefficient-alpha between 0.70 and 0.95 is considered to reflect good internal consistency. The factor structure was then tested using confirmatory factor analysis in IBM SPSS AMOS 21. Goodness of fit was assessed with four indices: root-mean-square error of approximation RMSEA, comparative fit index/Tucker-Lewis index CFI/TLI and goodness of fit index GFI. Due to the sample size, the chi-square difference test was not considered a relevant fit index.As the dataset was of reasonable size and the data near normally distributed, parametric techniques were used and statistical analysis was carried out using IBM SPSS statistics v21. Although the UK FIM+FAM has been validated using UKROC data for a general neurorehabilitation samplePaired T tests were used to compare differences in scores between admission and discharge. To identify differences between groups, we used one-way ANOVA with Bonferroni correction. For all statistical tests, two-tailed p values of <0.05 were considered to be statistically significant. Chi-squared test was used for categorical data. ‘FIM+FAM splats’ (radar charts) were employed to show item-by-item changes between mean scores at admission and discharge.The UKROC database collates de-identified data as part of routine clinical practice and the programme registered as a Payment by Results Improvement Project. The analysis of this routinely-collected data is classed as service evaluation, which does not require research ethics permission in the UK.Demographics of the UKROC data and study population are shown in The study sample comprised 116 male and 70 female patients with a mean age at admission of 53.6 (sd = 16.2) years, range 18–85 years. The mean rehabilitation length of stay was 72.2 (sd = 66.6) days. There were 118 (63.4%) patients with Guillain-Barré Syndrome (GBS), 15 (8.1%) patients with CIDP and 32 (17.2%) patients with CIN and myopathy. A further 37 (11.1%) had unspecified neuropathies.16 we rotated, using Varimax procedure, two main factors, representing the motor and cognitive dimensions (accounting for 45.9% and respectively 14.5% of the variance). Four items  which loaded significantly (>0.3) onto both factors, were assigned on the basis of best clinical fit . Most of the items loaded strongly on the first principal component (26 out of 30 items above 0.40). Based on the previous researchical fit . The CroThe mean reduction in overall dependency  was 13.7 ((%%CI 11.1–16.2), of which the majority of change was in the Basic Care Needs section ). This translates into a reduction of 37.4 care hours per week with mean cost savings £720.3 (SD £891.3) per week.Comparison of cost efficiency between the diagnostic groups  demonstrThis multi-centre analysis reports the first application of the UK FIM+FAM and Northwick Park Dependency scores to assess the functional outcome and efficiency of rehabilitation in patients with GBS and other polyneuropathies. Our findings show that, across all diagnostic and dependency subgroups, these patients make significant functional gains during rehabilitation.As expected the majority of patients had predominantly physical disability on admission, and made substantial gains in motor function during the course of their rehabilitation programmes. Somewhat less expected was the extent of disability in cognitive/psychosocial items, which was most evident in the CIN patients, but by no means confined to this group. There is been considerable debate in the literature as to whether the FIM+FAM provides added value over the FIM as an outcome measure for complex rehabilitation. In terms of overall statistics, the FIM+FAM appears to add little benefit The EADL module of the UK FIM+FAM is a relative recent addition (published in 2009) that was introduced to extend the ceiling of the FIM+FAM and to address independence in activities that are important for successful community re-integration Cost-efficiency of rehabilitation was evaluated in terms of the length of time taken to offset the costs if the in-patient rehabilitation programme by savings in the cost of on-going care in the community. For the sample as a whole, costs were offset within just 12 months, but the timeframes ranged from 11–22 months across the different levels of dependency. These periods are relative short compared with the figures of 16–39 months in an equivalent population of patients undergoing rehabilitation following complex acquired brain injury (ABI) We also interrogated the dataset for differences within the diagnostic subgroups of patients with inflammatory polyneuropathies. Patients with CIN were the most dependent and also had more severe cognitive/psychosocial disability than the other groups, both on admission and discharge. This may reflect the multiple insults that many patients in this group will have experienced in the course of prolonged stays in intensive care. However, despite their higher levels of dependency, the CIN patients took the least time to offset the cost of rehabilitation (7.4 months), confirming that specialist rehabilitation is highly cost-efficient in this group of patients.Although the UK FIM+FAM was the primary functional outcome for this study, we also report the change in FIM scores for the purposes of comparison with other studies in the literature that have used the FIM to assess outcome form rehabilitation in patients with inflammatory peripheral neurological disorders. A few such studies exist, although most of them are single centre studies focussing patients with GBS Prasad et al reported outcomes from in-patient rehabilitation in 28 GBS patients using the FIM. They showed that activities dependent on the use of the legs  were the most severely affected, following by activities dependent on the use of arms (eg dressing), or use of both arms and legs (eg transfers) Khan et al reported a good functional recovery for GBS survivors residing in the community Novak at al reported outcomes from rehabilitation for patients with CIN The authors recognise a number of limitations to this study:Although the study population represents a national cohort of patients drawn from 45 different rehabilitation units across England, and is larger than the other published studies in the literature, the sample size is still relative small, particularly for the subgroups of CIN and CIDP.As with any cohort design that describes functional gain in rehabilitation, spontaneous improvement during the follow-up period cannot be excluded and it might suggest that part of the functional change is not the direct result of rehabilitationThe data were extracted from the UKROC database during a relatively early stage in its development when data reporting was not mandatory. Therefore, FIM+FAM data were available for only just over half of the total eligible population and NPDS data were available in approximately one-third. This could have led to some selection bias. From April 2013, the dataset was mandated as a requirement for commissioning of specialised rehabilitation services and routine benchmarking data on quality and cost-efficiency should come on stream from 2014, so future analyses of the dataset in 2–3 years’ time should provide a more comprehensive picture.The UKROC method of reporting cost-efficiency in terms of the time to offset the costs of rehabilitation is as yet specific to the UK. As noted in the Our methods for evaluating cost-efficiency are therefore not yet at a stage of development whether they could replace FIM-efficiency, but as this and other studies show, they have the potential to overcome some of the floor and ceiling effects that limit the usefulness of FIM-efficiency as a measure of value-based health care in rehabilitation.In conclusion, this study builds on the existing literature provides further evidence that patients with polyneuropathies have both physical and cognitive disabilities that are amenable to change with rehabilitation. In addition, it demonstrates significant reduction in on-going care-costs, especially for highly dependent patients, and provides new evidence for the cost-efficiency of rehabilitation in this group of patients although controlled study designs are required to identify the extent to which these outcomes reflect the added value of rehabilitation over and above natural recovery. Further research is also needed to explore the underlying reason for the diagnosis-specific differences between the various sub-groups. The study also highlights the need for clinicians to be aware that, even in the absence of overt cognitive impairment, patients with inflammatory polyneuropathies may have significant cognitive, psychosocial and communicative disabilities that need to be addressed in their own right as part of the rehabilitation programme.Patients with polyneuropathies have both physical and cognitive disabilities that are amenable to change with rehabilitation.The significant reduction in on-going care-costs, especially for highly dependent patients, supports new evidence for the cost-efficiency of rehabilitation in this group of patients.