Motivation: With the advent of relatively affordable high-throughput technologies, DNA sequencing of cancers is now common practice in cancer research projects and will be increasingly used in clinical practice to inform diagnosis and treatment. Somatic (cancer-only) single nucleotide variants (SNVs) are the simplest class of mutation, yet their identification in DNA sequencing data is confounded by germline polymorphisms, tumour heterogeneity and sequencing and analysis errors. Four recently published algorithms for the detection of somatic SNV sites in matched cancer–normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer–normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterized and compared to investigate the strengths and weaknesses of each SNV calling algorithm.Results: Comparing the candidate SNV sets returned by VarScan, SomaticSniper, JointSNVMix2 and Strelka revealed substantial differences with respect to the number and character of sites returned; the somatic probability scores assigned to the same sites; their susceptibility to various sources of noise; and their sensitivities to low-allelic-fraction candidates.Availability: Data accession number SRA081939, code at http://code.google.com/p/snv-caller-review/Contact:david.adelson@adelaide.edu.auSupplementary information:Supplementary data are available at Bioinformatics online. Cancer genome projects are currently working to catalogue the diversity of DNA mutations present in different cancers via high-throughput DNA sequencing of matched cancer–normal samples. These projects seek to find correlations between mutation profiles and clinical outcomes, identify mutations driving cancer progression and identify targets for novel therapeutic developments. Somatic single nucleotide variants (SNVs) are the simplest class of mutation, but their detection from matched cancer–normal sequencing data is complicated by both biological and technical noise.Cancers arise from a single ancestral cell that has acquired enough somatic mutations to deregulate its own proliferation and expand into a large cell population with clonal mutations matching the ancestral profile. Loss of function in genes for genome stability and repair establishes a mutator phenotype in which a greater rate of somatic mutation provides the cell population with a vast repository of mutations in low copy. Those mutations conferring a selective advantage preferentially expand in number, forming subpopulations with the same subclonal mutations. Clonal and subclonal mutations include drivers of the cancer phenotype, and passenger mutations that arose in the same clonally expanding cell line as a driver , then the genotype is called as either heterozygous (variant <75%) or homozygous variant (variant >75%). Otherwise, the site is deemed homozygous reference. Then, at positions where these heuristically determined genotypes do not match in cancer and normal, a one-tailed Fisher’s exact test is performed on the read counts. A significant result is called somatic if the normal sample was homozygous reference, or as loss-of-heterozygosity (LOH) if the normal sample was heterozygous, or unknown if the normal sample was called homozygous variant and the cancer sample did not match. VarScan2 can take optional purity estimates for the cancer and/or normal sample, and will adjust its variant frequency thresholds accordingly.SomaticSniper uses a Bayesian probability calculation to estimate the posterior probability of each possible joint genotype across the normal and cancer samples given the data observed and prior genotype likelihoods based on the reference sequence, sequencing error rate, population mutation rate and somatic mutation rate. Each site is given a ‘somatic score’ (S), a phred-scaled posterior probability that the cancer and normal genotypes are the same.JointSNVMix is based on a different Bayesian approach using a mixed binomial model. The model considers each site across the two samples to have one of nine joint genotypes possible after reducing the bases to ‘A’ for a reference and ‘B’ for a variant base. The set of joint genotypes across all sites is considered to have a multinomial distribution whose parameters have a Dirichlet prior with trained hyper-parameters. At each site, the number of reads supporting the reference base in cancer and normal is considered to have a binomial distribution. The binomial probability parameter is modelled from a beta prior with trained hyper-parameters, conditional on the joint genotype.First, the hyper-parameters of the multinomial and binomial distributions are trained by expectation maximization over a subset of the data, using set default values as priors. Then, the posterior probability of each joint genotype is calculated at each site. The basic model, JointSNVMix1, assumes the data have perfect base calls and alignment, whereas the extended model, JointSNVMix2 (JSM2), weighs each read by base and mapping quality.Strelka performs an initial realignment around indels in the normal and cancer BAM files, then uses a complex set of calculations, again based on a Bayesian probability model, to report the most likely genotype at candidate sites along with the phred-scaled joint probability of the most likely normal sample genotype and the event of any somatic mutation in the cancer sample. The normal sample allele frequencies are modelled as diploid genotypes with a noise term to factor in sequencing and mapping errors, whereas the cancer sample allele frequencies are modelled as a mixture of the normal sample and somatic variation at any frequency. The exact details of the model, which are too numerous to describe here, take into account base and mapping qualities, strand bias, the prior probability of any site being a somatic mutation and the expected rate of heterozygosity in the normal sample.These somatic SNV calling algorithms use a variety of information to calculate a somatic probability score for each candidate site returned. However, the full complexity of noise present in any DNA sequencing dataset is not typically considered during SNV calling, so raw output sets of candidate SNV sites typically require filtering to remove likely false positives.Supplementary Information.VarScan2, SomaticSniper, JSM2 and Strelka were used to return candidate SNV sites from matched cancer–normal exomes from a chronic myeloid leukaemia (CML) patient, sequenced with the Illumina HiSeq platform in paired 100 bp reads (SRA081939). The algorithms were also applied to similar exome sequencing data from non-cancerous patient samples  to assess the output returned in the absence of any real somatic variation between samples. Details of the data and methods used are available in the The output from each of the four algorithms includes both gain-of-variation somatic SNV candidates and sites of apparent LOH in the cancer sample. Using low probability score thresholds for inclusion to generate large candidate sets, the raw output consisted of 2667 somatic and 1720 LOH VarScan candidates; 2663 somatic and 175 LOH SomaticSniper candidates; 2178 somatic and 2040 LOH JSM2 candidates; and 438 somatic and 29 LOH Strelka candidates. Only 50 of the somatic candidates were returned by all four callers, and the vast majority of sites were uniquely returned by one caller.In keeping with the primary purpose of these algorithms, we chose to focus this review on the somatic candidates rather than LOH. A short discussion on the LOH candidates returned by these algorithms is included in Section 4.1.As expected, given the low probability stringency used to define candidate inclusion, the number of sites returned exceeded the number of expected true positives by orders of magnitude. Two simple approaches for reducing the number of candidates would be to remove sites returned with a low probability score, or to remove candidates uniquely identified by one caller.The distribution of somatic probability scores for sites unique to each caller and returned by multiple callers, as shown in Observable in both Supplementary Information.Rather than reducing the number of candidates by increasing the probability score threshold for inclusion, we applied filters designed to remove sequencing and mapping errors. Sites were removed if any of the following criteria were met : variant bases emanate exclusively from one strand; mean variant base quality is less than 15; no variant has base quality over 30; mean variant mapping quality is less than 15; no variant has mapping quality over 40; more than two candidate SNVs  are within 50 bp either side; spanning deletions contribute >20% to the overall depth in either sample; or candidates are immediately adjacent to indels in >20% of reads in either sample. A detailed breakdown of filtering results is available in the v variant reads, the chance that all of those reads occur on one strand is By far the most significant filtering metric was the requirement to have at least one relevant variant base on each strand, with 5437 out of 10 438 candidates removed for having 100% strand bias. Although this filter was designed to remove systematic sequencing errors, complete strand bias can occur solely as a result of random sampling between the two strands, especially at low depths. For a site with a total of There were significant differences between the filter pass rates of the four output sets, as presented in After filtering, 2920 candidate sites remained, including 812 somatic and 475 LOH VarScan candidates; 862 somatic and 85 LOH SomaticSniper candidates; 470 somatic and 455 LOH JSM2 candidates; and 268 somatic and 28 LOH Strelka candidates, with overlaps between the four sets of somatic candidates illustrated in The characteristics of somatic candidates uniquely returned by each caller are illustrated by VarScan’s default algorithm design returns somatic candidates if, for variant bases above 15 in quality, the cancer variant proportion is between 20 and 75% and the normal variant proportion is outside this range. Although obscured to some extent in SomaticSniper shows a distinctive discretized quality in its cancer variant proportions, explained by the low depth at most sites uniquely found by SomaticSniper. Unlike the other callers, SomaticSniper had no lower bound for the depth of its candidate sites, and 70% of the candidates unique to SomaticSniper had depths in the cancer sample below 12. At low depths, variant allele frequencies can only occur at certain discrete levels, largely explaining the pattern in statistically significant difference between variant proportions in the two samples is more likely, regardless of the biological significance.JSM2 uniquely returned low-allelic-fraction candidates with variant proportions in the cancer ∼5–20%, but variant signals in the normal sample were also present at 75% of these sites. Half of the candidates unique to JSM2 had depths in the cancer sample above 90. This suggests a possible weakness of JSM2: that at high depths of sequencing, a Strelka appears tuned to detect even lower allelic fractions, as its unique calls have variant proportion in the cancer around 5%. In contrast to JSM2, 72% of Strelka’s unique output had no variant base in the normal sample.For each of two exomes sequenced to high depth from non-cancerous samples, we twice randomly split the BAM file in half and applied the somatic calling algorithms to these matched normal–normal samples to return purely false-positive candidate sets. After applying the previously described post-calling filters, the number of false-positive sites output by all four algorithms in the four cases were 5, 7, 10 and 11. On inspection, these 33 false positives were seemingly indistinguishable from some of the somatic candidates identified in the cancer samples, with depths ranging from 10 to 73 and most having somatic probability scores above 0.90.Comparing the candidate SNV sets returned by VarScan, SomaticSniper, JSM2 and Strelka revealed substantial differences as to the number and character of sites returned; the somatic probability scores assigned to the same sites; their susceptibility to various sources of noise; and in their differing sensitivities to candidate mutations at a low allelic fraction.All four algorithms return candidate LOH events implying loss of variation in the cancer sample. The term typically implies a deletion event, but duplication events also register as LOH candidates when a previously 1:1 heterozygous signal shifts to a 2:1 signal in the duplicated region. LOH candidates may also arise from somatic mutations present in the ‘normal’ cell sample that were never present as germline polymorphisms in the general cell population of the individual.Given these confounding factors, the LOH candidates returned by these tools are not, by themselves, a strong indication of actual LOH. These SNV calling algorithms have not been optimized to detect LOH regions, and merely give the output as a by-product of their main purpose. Regions with a relatively high frequency of LOH candidates may indicate real copy number variation, but these should be investigated by alternative means like aCGH.After filtering, the proportion of LOH candidates in the output from each algorithm was ∼50% for JSM2, 40% for VarScan and 10% for SomaticSniper and Strelka. As regions of interest with relatively high frequency of LOH candidates are still identifiable in smaller output sets, and as the LOH candidates assigned the highest probability scores by VarScan also tend to be returned by SomaticSniper and, to a slightly lesser extent, by Strelka as well, no obvious benefit is gained in using VarScan or JointSNVMix to return greater numbers of LOH candidates.The main purpose of the four algorithms analysed here is the detection of candidate somatic SNV sites purporting gain of variation in the cancer sample. A core group of sites was identified by all algorithms at high probabilities, though given the identification of a few similar sites within the non-cancerous exomes, false positives are likely to be included even in this common set. Beyond this core group, there were marked differences in the probability scores assigned to the same sites and in the characteristics of sites returned by one algorithm only.VarScan  has the SomaticSniper , some other filters recommended in the literature include within-read position and the presence of particular surrounding sequence motifs .Conflict of Interest: none declared.


Stem Cells International focuses on the potential applications of amniotic cells in regenerative therapies to repair tissues and organs that have been damaged by trauma, disease, or aging. Amniotic cell populations have historically included cells in amniotic fluid that have been sloughed from external and internal surfaces of the developing fetus and potentially from the amnion, the innermost extraembryonic membrane of the amniotic sac. Amniotic fluid is recovered by amniocentesis, a technique that was initially used to assess fetal health in cases of Rh blood group incompatibility [ex vivo culture of amniotic cells as a source of normal, rather than transformed cancer cells for biomedical research. Fauza and colleagues [in utero. Ovine amniotic fluid and later human amniotic fluid proved to contain populations of rapidly proliferating mesenchymal, also known as stromal, cells that have since dominated research efforts. Similar to multipotential stromal cells (MSCs) derived from bone marrow [http://www.ClinicalTrials.gov/).This special issue of tibility  and to dtibility , 3. Thestibility  providedlleagues  were amoe marrow , 7 and ae marrow , 9, amnie marrow –13. Trophttp://www.isscr.org/). A unifying feature of amniotic and placental cell sources is ex vivo culture from some of the earliest stages of fetal development, ranging from 15 weeks to 17 weeks of gestation with amniocentesis sampling to near birth at 9 months with delivery of full term placenta. Another unique feature reflects signaling cascades during gestation; amniotic and placental cells are exposed to paracrine signaling among the mother, the fetus, and the placenta. These transient conditions may confer distinctive properties to amniotic cells that are not shared by other cell sources. The consensus of the diverse papers offered here is that continued research and development may prove amniotic cells to be superior cell sources for selected applications. Unique features of amniotic cells present opportunities for regenerative medicine and biomedical research that are not shared by other cell sources, including pluripotent stem cells as defined by the International Society for Stem Cell Research  as amniotic membrane markers. Comparative gene expression analyses combined with While the first two papers in this special issue have focused on biomarkers, a review article by R. J. Hodges et al. in Australia presents “Amnion epithelial cells as a candidate therapy for acute and chronic lung injury”. The authors discuss the plasticity and immunomodulation properties of amnion epithelial cells in repair lung injury. In addition, they address the therapeutic potential of these cells with references to purity of cell population and the transcription factors they express. Key features of amnionepithelial cells and their role as exogenous stem cells compared to resident endogenous lung stem cells have been presented.The authors provide a list of factors that are potentially involved in the repair mechanisms elicited by amnion. In a paper focused on mesenchymal stem cells, C. M. Raynaud et al. in Qatar and USA. present a “Comprehensive characterization of these cells from human placenta and fetal membrane and their response to osteoactivin stimulation.” The authors have employed transcriptomics, immunocytochemistry, cytokine array analysis, and other complementary methods to evaluate the similarities and differences between placenta- and membrane-derived mesenchymal stem cells before and after differentiation. Using established protocols to isolate these cells from both sources, the authors show that placenta- and membrane-derived mesenchymal stem cells respond differently to osteoactivin during osteogenic differentiation. A concise review of “Amniotic fluid stem cells: future perspectives.” By M. Rosner et al. in Austria discusses the progress made by this group as well as others, since their first report on connection between amniotic fluid cells and stem cell research. The comparison among AFS cells, ES cells, adult stem cells, and iPS cells has been followed by an emphasis on the importance of monoclonal genomically stable human AFS cell lines and their capacity to form embryoid bodies. As a novel approach, this paper has regarded AFS cells as a source for cell-based therapies for kidney disorders such as acute and chronic renal failures and acute tubular necrosis. While promising, the authors have emphasized that standardized protocols are required to isolate monoclonal populations of AFS cells. The challenge inherent to population complexity in amniocentesis samples as well as the potential effects of paracrine signaling prompted P. G. Wilson et al. in the USA, “Clonal populations of amniotic cells by dilution and direct plating: evidence of hidden diversity,” to first establish an efficient method to generate amniotic cell cultures, avoiding the need for refrigeration and centrifugation of samples. Application of this method allowed isolation of a large number of clonal lines from independent amniocentesis samples. As proof of concept for clonal identity, clonal populations of stromal and epithelial cells were compared with each other and with control cell populations. The results of flow cytometry, immunocytochemistry, differentiation tests, and transcript analysis revealed clear differences not only among stromal cell clones and epithelial cell clones from the same donor, but also between mixed cell populations from different donors. Functional communication between the grafted and host cells plays a pivotal role in delivering therapeutic agents to the damaged tissues. In a research paper by A. Jezierski and colleagues in Canada “Human amniotic fluid cells form functional gap junctions with cortical cells,” the authors show that amniotic fluid cells express high levels of connexin 43, a gap junction protein known for its role in brain development and function. Furthermore, AF cells establish intercellular communication with astrocytes, suggesting a novel role for AF cells to deliver therapeutic factors, including specific microRNAs and small molecules, to the damaged tissues. In particular, this approach may facilitate neuroprotection in the early stages of graft-host interaction during which intercellular coupling via gap junctions precedes the integration of transplanted cells into the neuronal circuit.Stem Cells International is to provide an overview of the recent progress in the field of amniotic stem cells by independent research groups from different continents. In an article by K. Rennie et al., authors from Canada, Austria, China, and Japan discuss applications of amniotic membrane and fluid in stem cell biology and regenerative medicine. While amniotic membrane is widely used as a natural scaffold for clinical applications, using standardized protocols to establish homogeneous clones from amniotic membrane or fluid cells has been described as a critical step towards development of desired phenotypes for cell transplantation. The paper has also recapitulated the use of amniotic fluid cells in several disease models, hoping that more progress will be made towards effective regenerative therapies in the near future.A key feature of this special issue of The editors hope that the original and review articles integrated in this special issue provide more insights into the advancement and challenges associated with the use of amniotic cells in regenerative medicine.Mahmud Bani-YaghoubMahmud Bani-YaghoubPatricia WilsonPatricia WilsonMarkus HengstschlMarkus HengstschlToshio NikaidoToshio NikaidoDuanqing PeiDuanqing Pei


Aortic coarctation represents a distinct anatomic obstruction as blood moves from the ascending to the descending aorta and can present in a range of ages from infancy to adulthood. While it is often an isolated and discrete narrowing, it can also be seen in the more extreme scenario of severe arch hypoplasia as seen in the hypoplastic left heart syndrome or in conjunction with numerous other congenital heart defects. Since the first description of an anatomic surgical repair over sixty years ago, an evolution of both surgical and transcatheter therapies has occurred allowing clinicians to manage and treat this disease with excellent results and low morbidity and mortality. This review focuses on the current state of both transcatheter and surgical therapies, paying special attention to recent data on long-term follow-up of both approaches. Further, current thoughts will be explored about future therapeutic options that attempt to improve upon historical long-term outcomes. Coarctation of the aorta has previously been defined as a congenital stenosis of the aorta, often occurring in the juxtaductal position. It can be associated with other lesions including a patent ductus arteriosus , ventric1). Infrequently, it can also exist in the transverse aortic arch and abdominal aorta, or be a part of a long-segment arch hypoplasia as seen in various left-sided obstructive lesions such as hypoplastic left heart syndrome [Coarctation of the aorta is often a discrete obstruction commonly located in the descending thoracic aorta. More specifically, it is usually located in the juxtaductal position immediately distal to the left-subclavian artery in a left-sided arch  and lower extremity central pulses , or the presence of a supine arm-leg blood pressure gradient. In patients with an aberrant right subclavian artery, all four extremities may be supplied by vessels distal to the obstruction, thus making diagnosis difficult. In neonates, a patent ductus arteriosus may help by limiting the degree of physiologic obstruction around a juxtaductal coarctation, but at the expense of possibly obscuring the diagnosis. Therefore, a neonatal coarctation may not manifest itself until the ductal tissue fully constricts .2). In older patients where acoustic windows may be suboptimal, it can be difficult to visualize the descending aortic segment of concern. In these patients, magnetic resonance imaging  and less often computed tomography scanning has become the modality of choice in the evaluation and management of both native and recurrent coarctations [Transthoracic echocardiographic techniques have become the standard in confirming clinical suspicion of coarctation , 13. Thictations -19. Thisctations . The indications for therapeutic intervention for coarctation are clear for the neonate struggling with or at risk for hemodynamic collapse from significant obstruction or with evidence of multiple left-sided obstructive lesions. However, indications for intervention are less clear for asymptomatic patients with mild hypertension and a documented blood pressure gradient between their upper and lower extremities. Campbell’s natural history study on coarctation suggests an increase in mortality and median lifespan of just 31 years secondary to congestive heart failure, aortic rupture and an increased risk of endocarditis for those who remain unrepaired . Most auThe first surgical therapy documented for coarctation was performed separately by Crafoord and Gross in 1945 through a lateral thoracotomy and involved resection of the coarcted segment followed by a direct suture anastomosis of the transected ends , 8. HighConcerns about high recoarctation rates following end-to-end anastomosis led to attempts to augment the coarcted segment with prosthetic material . SimilarPatch aortoplasty is still being used, however, in the setting of more complex aortic arch reconstructions. This is especially evident in severe arch hypoplasia, as seen in infants with hypoplastic left heart syndrome, where the transverse arch is augmented with cryopreserved pulmonary artery allograft . RecoarcThis technique, which utilizes one’s own tissue, was first described by Waldhausen  in 1966 4). Recent long-term studies have demonstrated similar rates of recoarctation from neonatal repair, but also have shown much lower recurrence rates when the operation was performed on older children (0-3%) [5). While severe left arm ischemia is rare, long-term arm length discrepancy and claudication with exercise due to compromised arterial supply has clearly been described [Initial proponents of this technique touted lower recoarctation rates in infants because of the use of one’s native tissue to perform the repair , 40. Medn (0-3%) , 43 . The main disadvantage of this technique is that it requires a longer cross-clamp time for two surgical anastomoses to be sewn, and the tube graft will not grow with the patient. Yet, for adult-sized patients presenting with long-segment coarctation, this technique may be preferable at many centers.This technique, while initially used by Gross , has bee7). Initially described by Singer in 1982  and LockWhile procedural success and safety in infants with native coarctation is quite good , recurreThese results suggest that for native discrete coarctation it is reasonable to initially pursue balloon angioplasty for older children and adults. In infants, however, transcatheter procedures should be considered only a temporizing step prior to eventual surgical repair in select high-risk patients who would benefit from more time before surgery. For recurrent coarctation, however, balloon angioplasty is generally felt to be superior to surgical reintervention due to its high procedural success compared to a greater incidence of surgical complications , 73.8). Acute and intermediate results in older children and adults for both native and recurrent coarctation have shown this technique to be both safe and effective with similar reintervention rates to surgery and fewer complications [9). For discrete coarctations, balloon angioplasty appears to work quite well, but elastic recoil makes angioplasty for longer hypoplastic segments less successful. Interventional cardiologists have thus begun placing balloon expandable stents across thoracic and abdominal coarctations to improve procedural outcomes , 75  stent -87 are tRegardless of the specific intervention, the aorta in patients with coarctation is truly abnormal post-procedure and may be at risk for to specific complications long-term. Chronic hypertension remains present in a significant number of individuals despite improvement in anatomic obstruction , 88, 89.Individuals with long-segment arch hypoplasia such as those with hypoplastic left heart syndrome warrant even closer monitoring for recurrent coarctation since ventricular function can deteriorate with persistent obstruction . These fAs described earlier, aneurysm development has been noted after transcatheter balloon valvuloplasty, endovascular stenting , 79 and Endocarditis has been described in the past for patients with native coarctation , after sThere have been significant advances in transcatheter techniques for aortic coarctation in the last thirty years and future innovations are continuing to be developed. Surgical approaches, as well, have evolved to the point of extremely low mortality and infrequent morbidity on even the smallest of infants. With both approaches, there are definitive issues of recoarctation, aneurysm formation and persistent hypertension that require life-long monitoring. Still, aspects of individual patient’s anatomy will continue to drive decision-making for all therapeutic interventions. Continued assessment of long-term data surrounding the most recent transcatheter therapies and the current surgical approaches is necessary to further validate each option.


Mobility impairments due to injury or disease have a significant impact on quality of life. Consequently, development of effective treatments to restore or replace lost function is an important societal challenge. In current clinical practice, a treatment plan is often selected from a standard menu of options rather than customized to the unique characteristics of the patient. Furthermore, the treatment selection process is normally based on subjective clinical experience rather than objective prediction of post-treatment function. The net result is treatment methods that are less effective than desired at restoring lost function. This paper discusses the possible use of personalized neuromusculoskeletal computer models to improve customization, objectivity, and ultimately effectiveness of treatments for mobility impairments. The discussion is based on information gathered from academic and industrial research sites throughout Europe, and both clinical and technical aspects of personalized neuromusculoskeletal modeling are explored. On the clinical front, we discuss the purpose and process of personalized neuromusculoskeletal modeling, the application of personalized models to clinical problems, and gaps in clinical application. On the technical front, we discuss current capabilities of personalized neuromusculoskeletal models along with technical gaps that limit future clinical application. We conclude by summarizing recommendations for future research efforts that would allow personalized neuromusculoskeletal models to make the greatest impact possible on treatment design for mobility impairments. Mobility involves walking, stair climbing, posture, balance, manipulation, transfers, and other locomotion tasks and is therefore central to qualify of life. When an individual incurs a mobility impairment, quality of life is diminished in proportion to the extent of the impairment. For example, mild knee osteoarthritis can limit participation in desired recreational or athletic activities without significantly affecting normal daily activities and productivity. In contrast, a stroke can make it nearly impossible to walk or manipulate objects, significantly diminishing an individual's ability to be self sufficient and function in society. Spinal cord injury can leave a person with normal upper extremity function but no remaining lower extremity function, significantly impacting only certain aspects of mobility.Treatments for different mobility impairments are typically stereotypical, with a standard menu of treatment options existing for any particular mobility impairment. For example, severe medial compartment knee osteoarthritis may be treated surgically using high tibial osteotomy, unicondylar knee replacement, or total knee replacement. Once a patient seeks surgical treatment for debilitating pain and significant loss of function, the clinician must choose between these treatment options based on clinical assessment of the patient. Furthermore, the clinician must determine the optimal values of the parameters associated with the selected treatment . A similar situation exists for rehabilitation and surgical treatments of neurological disorders such as stroke, Parkinson's disease, and cerebral palsy. In clinical practice, the final treatment plan is usually selected based on subjective clinical experience rather than on objective prediction of post-treatment function developed from patient data.Personalized computational models of the neuromusculoskeletal system could facilitate objective prediction of patient-specific functional outcome for different treatment designs being considered by the clinician. Depending on the intended clinical application, a personalized neuromusculoskeletal model could account for patient-specific anatomical , physiological , and/or neurological  characteristics, all within the context of a multibody dynamic model. Personalized models for treatment design are motivated by the fact that for many treatments, "one size fits none." Every patient is different and possesses unique anatomical, neurological, and functional characteristics that may significantly impact optimal treatment of the patient. Personalized models provide one possible avenue for increased objectivity in treatment planning, reducing the likelihood that different clinicians will plan different treatments given the same patient data. Ideally, virtual treatments performed on a patient's personalized model would allow objective and reliable prediction of post-treatment function and thus identification of an optimal treatment plan. Such predictions would identify not only the best type of treatment (including previously unknown treatments) but also treatment parameters to which functional outcome is highly sensitive .This paper explores how personalized neuromusculoskeletal models could be used to improve treatment design for mobility impairments. The exploration is based on a survey of personalized modeling research being performed in Europe and thus is limited in its scope. The survey was funded by the National Science Foundation (NSF) in the United States with the goal of synthesizing research recommendations and informing research funding in the area of technology to improve mobility. In October of 2010, two teams of four panelists recruited by NSF visited a number of academic and industrial sites throughout Europe over a one week time period. Since time and financial constraints limited the number of labs that could be visited, it was not possible to gather information from all labs in Europe performing valuable work in this area. Given that the goal of the tour was to survey the state-of-the-art in Europe, we also omit discussion of valuable work being performed by labs outside of Europe. The remainder of this paper summarizes the panel's findings related to the potential clinical use and benefit of personalized neuromusculoskeletal modeling.In this section, we discuss current and future clinical uses of personalized neuromusculoskeletal models to design improved treatments for mobility impairments. To set the stage, we begin by discussing common reasons why human movement data are collected, followed by a proposal for a general process to follow when using personalized models in the treatment design process. We then discuss mobility-related clinical problems currently being addressed with personalized neuromusculoskeletal models, and we conclude this section by highlighting gaps in clinical application where personalized models could add significant value.Pre-treatment human movement , strength , and imaging , computed tomography (CT), x-ray, fluoroscopic) data provide the experimental measurements necessary to develop objective model-based predictions of post-treatment function. As described by Dr. Maria Grazia Benedetti at the Rizzoli Orthopedic Institute in Bologna, Italy, there are three primary reasons for collecting human movement data in a clinical setting:Assessment - Assess after treatment how the treatment worked for an individual patient or a group of patients. An example would be using gait data to assess changes in walking speed and knee flexion angle following tendon transfer or lengthening surgery in a specific child or group of children with cerebral palsy. This use of human movement data is relatively common.1) Identification - Identify on an individual patient basis which patients should be treated (but not how they should be treated). An example would be using gait data to determine whether tendon transfer or tendon lengthening surgery should be performed for a specific child with cerebral palsy. This use of human movement data remains uncommon but is becoming more common.2) Prediction - Predict on an individual patient basis which treatment should be performed and how it should be performed. An example would be using gait data to determine whether tendon transfer or tendon lengthening surgery should be performed, which tendon to transfer or lengthen, and where to transfer it or how much to lengthen it, to improve walking ability for a specific child with cerebral palsy. This use of human movement data does not yet happen in clinical practice.3) prediction rather than assessment or identification, though identification has significant clinical value as well. While prediction is the most challenging use, it is also the use with the greatest potential to improve functional outcome on an individual patient basis.The focus of this paper is on how personalized neuromusculoskeletal models could be used for How should personalized neuromusculoskeletal models be used to predict functional outcome for various treatment plans under consideration? Expanded from ideas presented by researchers at the Rizzoli Orthopedic Institute in Bologna, Italy, and Dr. Bart Koopman at the University of Twente in Enschede, the Netherlands, we propose a three-step process for treatment design using personalized models:Model preparation steps:1) Identify model outputs to be used as indicators of clinical/functional outcome.• Define model complexity required to predict these outputs with sufficient accuracy for the intended clinical application.• Collect pre-treatment movement, strength, and imaging data (as required) to construct the personalized model and predict the outputs of interest.• Model construction steps:2) Calibrate model geometry and parameter values to which the outputs of interest are sensitive using pre-treatment movement, strength, and/or imaging data.• Estimate model parameter values to which the outputs of interest are insensitive using data reported in the literature.• Incorporate surgical or rehabilitation treatment plans under consideration into the personalized model.• Model utilization steps:3) Predict post-treatment patient function for each proposed treatment plan.• Select treatment plan and associated parameter values that maximize functional outcome, possibly using numerical optimization methods.• Validate personalized model predictions using post-treatment function measured from patients whose treatment was not planned with a model.• Implement optimal surgical or rehabilitation treatment plan designed with the personalized model.• Collect post-treatment movement, strength, and/or imaging data from the patient to assess clinical/functional outcome.• In this process, only the steps relevant to the mobility-related clinical application at hand need be performed. For example, clinical applications that do not require modeling of individual muscle forces may not require any imaging and strength data from the patient, and thus steps related to calibration of patient-specific muscle and bone geometry can be omitted. Model parameter values that require calibration to patient data may necessitate collection of additional experimental data solely for calibration purposes .Calibrate and Validate. Unless the model is calibrated to relevant data collected from the patient prior to treatment, the model will not be sufficiently personalized to predict the patient's post-treatment function. Similarly, unless calibrated model predictions are validated using post-treatment data collected from patients whose treatments were not planned with the model, clinicians will not have confidence in the model predictions, and personalized models will never advance toward widespread clinical utility. Validation of treatment planning using personalized models will ultimately require randomized controlled trials, where outcomes are compared between patients whose treatments were planned with a personalized model and those whose treatments were not.Two critical tasks to highlight in this process are During our tour of European research labs, we sought to identify clinical applications where a personalized modeling process similar to the one outlined above was already being followed. By the end of the tour, we made three valuable observations related to clinical application of personalized neuromusculoskeletal models. First, few labs have reached the point of being able to apply this process to specific clinical problems. Second, some of the best existing clinical applications involved generic rather than personalized models. Third, most clinical applications we observed involved orthopedic surgery, with few applications involving neurorehabilitation. Below we comment further on these observations.Three large projects funded by the European Commission (EC) are making significant strides in developing and applying personalized neuromusculoskeletal models to orthopedic clinical problems. The first is the "Osteoporotic Virtual Physiological Human" (VPHOP) project , which iIn a related project, Viceconti's team at the Rizzoli Orthopedic Institute has developed personalized neuromusculoskeleal models of pediatric patients who received a surgical limb salvage procedure for bone cancer ,6. For tThe second large EC-funded project is called "NMS Physiome" , which iThe third large EC-funded project is entitled "Improving Safety and Predictability of Complex Musculo-skeletal Surgery using a Patient-Specific Navigation System" (TLEMsafe) , which iOther research we observed involved the use of generic rather than personalized neuromusculoskeletal models. While personalized models have the greatest potential to impact clinic practice, generic models can still provide significant clinical benefits. Two clinical applications of generic models were particularly well developed. The first was the design of a total ankle replacement by Dr. Alberto Leardini and colleagues at the Rizzoli Orthopedic Institute in Italy ,11. The The other example was evaluation of tendon transfer surgery for massive rotator cuff tears by Dr. Frans van der Helm and colleagues at Delft University of Technology in the Netherlands ,15. The The primary rehabilitation applications we observed utilized a personalized modeling method called Complementary Limb Motion Estimation (CLME) ,19. The Mobility-related clinical problems are typically treated by either surgery or rehabilitation and either do or do not possess a significant neurological component. Thus, use of personalized neuromuscular models to improve treatment of mobility impairments can be grouped into four categories: 1) surgical treatment without a significant neurological component, 2) surgical treatment with a significant neurological component, 3) rehabilitation treatment without a significant neurological component, and 4) rehabilitation treatment with a significant neurological component. Of these four categories, the first is the most developed and the fourth the least developed in terms of personalized neuromusculoskeletal modeling. This situation is not surprising given that technology is a more recent addition to rehabilitation treatments  than to surgical treatments and that neurological factors are more difficult to model than are mechanical factors. Below we present clinical gaps in personalized modeling for each of these four categories.Osteoarthritis is a prevalent disabling disease that is commonly treated by surgical intervention. Though it clearly possesses a neurological component , that coIn contrast, cerebral palsy and Charcot-Marie-Tooth disease are neurological disorders that are commonly treated by surgery, since no treatment exists for the underlying neurological problem. Though Charcot-Marie-Tooth disease is not well known, it is the most commonly inherited neurological disorder and limits mobility in approximately 1 in 2,500 individuals . SurgicaStroke, spinal cord injury, and traumatic brain injury significantly affect mobility, possess a major neurological component, and are often treated by rehabilitation methods. Personalized neuromusculoskeletal models have yet to be applied to traditional or robot-assisted rehabilitation treatments for these disorders. Given this large gap, even personalized models that omit neural control models have the potential to make a significant clinical impact. For example, a number of clinical and research labs in Europe are utilizing robot-assisted therapy for neurorehabilitation ,29. ManyPersonalized musculoskeletal models that include personalized neural control models would be even more beneficial for improving rehabilitation of neurological disorders. Models that account for patient-specific neural control limitations and neuroplasticity could be used to identify the maximum expected improvement and how best to get there. As suggested by Dr. Herman van der Kooij of the University of Twente in the Netherlands, such models could be useful for predicting how people interact with and adapt to their environments, which could improve the effectiveness of robotic therapy systems. Furthermore, such models could be valuable for the design of neuroprostheses that use functional electrical stimulation to restore lost function ,31. For One of the primary reasons for these clinical gaps is lack of effective collaboration between clinical researchers and personalized modeling researchers. An excellent counterexample is the Rizzoli Orthopedic Institute in Italy, where clinicians and engineers share the same office space and interact during clinical decision making. These interactions create an atmosphere where clinicians routinely enter into the technical world and engineers routinely enter into the clinical world. Such an environment of shared intellectual investment in solving clinical problems is critical if personalized neuromusculoskeletal modeling is to make a broad impact in the clinic.Clinical Process of Personalized Modeling, the primary challenges faced by these efforts are the Calibrate step within Model construction and the Validate step within Model utilization. In this section, we discuss current technical capabilities of personalized modeling related to model calibration and validation, followed by a discussion of technical gaps that need to be filled if personalized neuromusculoskeletal models are to become clinically useful.Significant research efforts are currently underway in labs throughout Europe to develop personalized neuromusculoskeletal modeling tools and methods. Recalling the section above on the Despite significant computational advances over the past ten years, model personalization remains a major challenge, as does the ability to use a personalized model to predict the outcome of a clinical intervention. Personalized neuromusculoskeletal models can be applied to mobility-related clinical problems only to the extent to which key model features can be calibrated to data collected from a patient. Thus, the ability to calibrate models to patient data is a prerequisite to clinical use of personalized models, with the proposed clinical application determining the extent of model personalization required.Since most neuromusculoskeletal models are generic, being constructed from detailed anatomic measurements performed on cadaver specimens ,33, a moGeometric calibration - Use of imaging data  to calibrate bone geometry, muscle lines of action, and muscle moment arms in a musculoskeletal model.1) Kinematic calibration - Use of motion data  to calibrate constraint-based joint positions and orientations in the body segments of a skeletal model.2) Kinetic calibration - Use of load data  to calibrate body segment mass and inertia, foot stiffness, muscle strength, and other muscle-tendon properties in a neuromusculoskeletal model.3) Neurologic calibration - Use of motion, load, and muscle activity data  to calibrate feedforward, intrinsic feedback, reflexive feedback, and/or synergy properties of the neural control system in a neuromusculoskeletal model.4) The challenge is how to construct a personalized model that is consistent with all available data from these different modalities .Current methods for geometric calibration involve uniform scaling, non-uniform scaling, deformation, or direct creation of bone models and muscle lines of action from patient MR or CT data. Uniform scaling based on external measurements is inaccurate when calculating muscle moment arms, muscle-tendon lengths, muscle forces, and joint contact forces , especiaKinematic calibration involves determining fixed joint positions and orientations in the body segments of a skeletal model with a pre-defined kinematic structure. The calibration process is usually performed using surface marker data, with joint angles in the model being calculated as a byproduct. European labs have used optimization methods  and exteKinetic calibration typically involves calibration of segment mass properties or muscle force-generating properties. Though segment mass properties can be calibrated to force plate and motion data , they arA promising development to address geometric, kinematic, and kinetic calibration simultaneously is research being performed by Dr. Wafi Skalli at Arts et Métiers ParisTech in Paris, France using the EOS bi-plane x-ray system . With the EOS system, a subject stands upright while a low-dose x-ray system scans the entire body from head to toe collecting one continuous distortion-free image in each of two orthogonal planes. The resulting bi-plane images are then processed and morphed using template anatomy for personalization and visualization. Geometric calibration of bone and muscle geometry via deformation of template bone and muscle models can be performed rapidly and accurately relative to geometry constructed directly from CT data -47. KineThe remaining area, neurologic calibration, has seen the least progress due to the significant challenges involved in understanding how the human neural control system functions. This calibration step can be pursued using a range of approaches, from a physiological approach that seeks to model the detailed anatomy and physiology involved in neural control, to an emergent approach that seeks to model the neural control computations implemented by the anatomy but without modeling anatomic detail. An example of a physiological approach is detailed modeling of feedforward, intrinsic  feedback, and reflexive  feedback mechanisms utilized by the neural control system -54. To dValidation of clinical predictions is the other major challenge faced by personalized models. This challenge can be surmounted when clinical outcome variables are external quantities that can be easily measured . Frequently, however, established clinical databases use coarse ordinal scales to rank movement ability, and mapping these scores to neuromechanical models is difficult. In addition, significant challenges remain when the outcome variables are either internal to the body  or dependent on quantities that are internal to the body. Since such quantities cannot be measured directly by non-invasive means, alternate methods are needed for personalized model validation. For example, predicted muscle forces have been evaluated indirectly using in vivo joint contact force measurements  or novelAs suggested by this review of current technical capabilities in Europe, at least four critical technical gaps currently exist that limit the potential clinical applicability of personalized neuromusculoskeletal models:How can we make the personalized model calibration and prediction process fast and easy?1) Though several excellent musculoskeletal modeling programs exist, none of them contain functionality that automates the model calibration process and simplifies the model prediction process. Personalized model calibration and prediction currently require significant expertise and programming ability possessed by only a small number of researchers in a limited number of research labs. Making these capabilities available to the larger neuromusculoskeletal modeling community via fast, automated algorithms will be essential for the growth of personalized modeling efforts. Ultimately, personalized modeling will be adopted for routine clinical use only when it is extremely easy to use.How can we calibrate "unobservable" parameters to which model predictions are sensitive?2) For some clinical problems, personalized model predictions of functional outcome will be sensitive to model parameter values that cannot be calibrated to available data. The first step in addressing this problem is identifying when it occurs, which requires performing sensitivity analyses that in some cases will be limited by existing computational capabilities. The next step is development of new experimental methods or hardware that provide sufficiently rich information to calibrate the parameter values needed to develop the predictions.How can we create personalized neural control models?3) Few neuromusculoskeletal models published to date account for any level of personalized neural control modeling. Such modeling would ideally account for limitations in a patient's neural control capabilities as well as the extent of possible plasticity. Emergent approaches for modeling neural control could be incorporated into personalized musculoskeletal models as a starting point, while physiological models could be refined to the point where essential model parameters become well defined and methods for calibrating them are developed. The ability to incorporate complex personalized neural control models into personalized musculoskeletal models would greatly expand model applicability to clinical situations, especially those involving neurorehabilitation.How can we validate model-based predictions, especially for internal quantities such as muscle, joint, and bone loads?4) Validation of internal quantities that influence treatment design remains a major challenge. While researchers continue to refine optimization and EMG-driven methods for predicting muscle forces and related joint and bone loads, the ability to validate these predictions has lagged behind. Direct measurement of internal quantities under special conditions , and the opportunity to test model-based predictions against these internal measurements, provides a valuable avenue for model validation efforts . IdentifNeuromusculoskeletal modeling has yet to make a significant difference in routine clinical practice. For this situation to change, the key gaps identified above need to be addressed by modeling researchers in close collaboration with clinical investigators. While the biggest clinical gap for personalized neuromusculoskeletal modeling is in neurorehabilitation, the gap for other mobility-related clinical problems is almost as large. The biggest technical gap is in personalized neural control and recovery models, though issues like automation of the model personalization process and development of personalized foot-ground contact models are critical as well for advancement. For clinical problems that involve highly unique patient characteristics, stereotypical treatment design is likely to yield variable functional outcomes. These types of clinical problems are where personalized neuromusculoskeletal models have the greatest potential to create a positive paradigm shift in the treatment design process.The authors declare that they have no competing interests.BF organized and drafted the manuscript based on information gathered during the European tour. ML provided clinical perspective on information gathered. DR organized the tour and the selection of European sites. All authors made significant contributions to gathering, critically evaluating, organizing, and revising the content of the manuscript. All authors read and approved the final manuscript.


Ongoing quality control of the gluconate assay has uncovered problems with assay performance and data processing. Significant, and unpredictable, matrix-interference discovered in an independent re-validation have led the authors to conclude that gluconate is not a reliable analyte for measuring cervicovaginal fluid dilution. As a result, gluconate adjusted cervicovaginal fluid volumes reported in the manuscript are incorrect and are not correctible. Other findings and conclusions of the study remain unaffected.


Mosquito coils, vaporizer mats and emanators confer protection against mosquito bites through the spatial action of emanated vapor or airborne pyrethroid particles. These products dominate the pest control market; therefore, it is vital to characterize mosquito responses elicited by the chemical actives and their potential for disease prevention. The aim of this review was to determine effects of mosquito coils and emanators on mosquito responses that reduce human-vector contact and to propose scientific consensus on terminologies and methodologies used for evaluation of product formats that could contain spatial chemical actives, including indoor residual spraying (IRS), long lasting insecticide treated nets (LLINs) and insecticide treated materials (ITMs). PubMed, , U.S. National Library of Medicine, NIH), MEDLINE, LILAC, Cochrane library, IBECS and Armed Forces Pest Management Board Literature Retrieval System search engines were used to identify studies of pyrethroid based coils and emanators with key-words “Mosquito coils” “Mosquito emanators” and “Spatial repellents”. It was concluded that there is need to improve statistical reporting of studies, and reach consensus in the methodologies and terminologies used through standardized testing guidelines. Despite differing evaluation methodologies, data showed that coils and emanators induce mortality, deterrence, repellency as well as reduce the ability of mosquitoes to feed on humans. Available data on efficacy outdoors, dose–response relationships and effective distance of coils and emanators is inadequate for developing a target product profile (TPP), which will be required for such chemicals before optimized implementation can occur for maximum benefits in disease control. Currently, control of malaria vectors relies almost entirely on indoor residual-spraying (IRS) and long-lasting insecticide-treated nets (LLINs) . These vLiterature shows that much of the success of DDT is due to excito-repellency ,5. An exRepellents either activate or inhibit action of ORs interfering with the host-seeking behaviour of mosquitoes, resulting in repellency or anti-feeding . A repelIn addition, due to increased need for effective vector control tools, to combat residual outdoor-biting and resting mosquitoes , it is tThe main active ingredients recommended by the World Health Organization (WHO) for use in the vapour phase all belong to the pyrethroid chemical class. The most commonly used format; mosquito coils are cheap and effective but produce smoke  which isRecently, other delivery formats that do not require heating or combustion have been developed. These are commonly known as emanators and are composed of insecticides impregnated on substrates such as paper, plastic or agarose-based gels ,25. UnliThe aim of this review was to determine effects of mosquito coils and emanators on mosquito responses that reduce human-vector contact and to propose scientific consensus on terminologies and methodologies used for evaluation of product formats that could contain spatial repellents including IRS, LLINs and insecticide treated materials (ITMs).st September 2012. We were confident that the search engines we used provided almost all relevant studies of interest. Data were extracted from selected articles that met all study criteria using a standardized spreadsheet. The information collected included first author, year of publication, methods and design, active ingredient, dose, mosquito species, sample size, description of the control, testing conditions  and the outcome measures reported with any available statistical information.This review was conducted in accordance with PRISMA  guidelines . PubMed,All publications evaluating coils and/or emanators were reviewed. However, to facilitate comparison of bioefficacy of different active ingredients across studies, the following selection scheme was employed Figure : (i) labSeveral investigators report a number of mosquito responses to airborne insecticide particles. These responses are classified into measurable indicators namely: deterrence, repellency and irritancy, biting/feeding inhibition, knock-down and mortality. Scientific discussions differentiate between mechanisms in mosquitoes leading to responses elicited in the presence of chemical actives and the outcomes quantified ,7,8,11, All studies identified and included in the review evaluated formulated/optimized emanators and coils. It should be noted that comparison of pyrethrins to metofluthrin emanators is only appropriate if both actives were formulated or both were neat material (unoptimized) as effects on volatization and longevity  will be different and bias analyses. This holds true even for comparing results of the same active ingredient.Airborne insecticide particles present inside and around houses create a chemical barrier that prevents mosquitoes from entering . DeterreRepellency was originally defined to refer to the distribution of insects/mosquitoes on chemically treated surfaces compared to untreated surfaces . This de“Non-contact irritancy” was measured in the field using local houses or experimental huts fitted with exit- and entry-traps ,33-35 byFeeding or biting inhibition is where mosquitoes are prevented from biting or feeding on humans. Coils reduce the biting rate of mosquitoes Table . Small aThe most accurate and representative method to measure feeding inhibition is through human landing catch (HLC) . Some stKnocked-down (KD) is the incapacitation of mosquitoes after contact with a sub-lethal dose of insecticide  resultinHigh concentrations of pyrethrins induce faster KD50 (within 3–5 minutes of exposure) followed by high mortality rate while low concentrations induce slower KD50 (more than 10 minutes after exposure) indicating a dose–response relationship Table . It is aet al. reported that caged mosquitoes placed immediately near metofluthrin-treated paper strips showed 100% KD within 30 minutes and 100% mortality 24-hours post-exposure, while mosquitoes placed 1.5m away from the strip had slower KD and 70% mortality and mosquitoes placed 5m away were unaffected [Optimized metofluthrin emanators induce 100% KD of mosquitoes within 30 minutes of exposure followed by 100% mortality within 24 hours in the laboratory . We did affected . This coThe intensity of KD and mortality of mosquitoes is largely dependent on release and degradation rates of actives, initial loading dose on substrate and environmental conditions.To characterize behavioural endpoints of mosquitoes exposed to chemical emanations of coils and emanators through rigorous independent and repeatable tests, it is essential to harmonize methodologies used.Stegomyia (Aedes) aegypti and Culex quinquefasciatus for testing household-insecticides [The mosquito species selected for bioefficacy studies is dependent on the objective and medical importance of a particular species in a given study area. The World Health Organization (WHO) recommends use of cticides . Evaluat3) [Field and laboratory studies are conducted in chambers, cylinders, rooms or huts of different sizes Table . Mosquit3) . This is3)  are good3) . Tests c3) . DespiteThe spatial activity of airborne insecticide is dependent on airflow , wind speed, temperature and humidity within the treated space . The greOther factors affecting experimental outcomes include sample size, which may refer to the number of people used in the trial or number of mosquitoes used and the number of replicates performed during evaluations. It is necessary to determine the number of mosquitoes required for a representative sample. This also applies to the number of human subjects required to account for differences in individual attractiveness to mosquitoes -51. WherSpatial repellents is the general term used to describe delivery formats such as coils, mats and passive emanators which release vaporised chemical actives capable of affecting mosquito behaviour at a distance. Most vapour chemical actives also knock down, kill or inhibit feeding of mosquitoes. General use of this term causes confusion especially where oriented movement away from the chemical source is not demonstrated. For purposes of clarity we propose that spatial repellency should be used as a general term to refer to sum of mosquito behaviours induced by airborne chemicals that cause mosquitoes to sit apart from a source of stimulation. Despite differences in evaluation methodologies, coils and emanators clearly reduce human-mosquito contact. They induce mortality, deterrence, repellency and reduce feeding of mosquitoes on humans. Mortality was the least observed effect where tests were conducted in experimental huts. This shows that these products do not kill mosquitoes in natural settings with free air movements and therefore may not affect overall mosquito densities or contribute to “community effect” as other toxic insecticides would.Mosquito coils increased the proportion of mosquitoes exiting huts. It is not clear whether mosquitoes leave treated houses because they are unable to locate hosts for blood meals and therefore continue searching for other blood sources or whether they leave because they are irritated by chemicals in the smoke/vapour and are forced to escape. This needs more investigation.Reduction in human-vector contact through feeding inhibition is likely to have an epidemiologically significant effect because of reduced risk of getting infectious mosquito bites. Any reduction in human-biting rate of mosquitoes is likely to lower vectorial competence of vectors and affect the lifetime fecundity of vectors which will in turn influence the basic reproductive rate of any parasites that they transmit. In addition to the measure of chemically induced feeding inhibition, it is necessary to conduct studies that quantify fecundity in order to see whether reduced blood feeding consequently reduces fertility of mosquitoes and leads to an overall reduction of mosquito population.There is minimal data available on dose–response relationships, effective distance and residual efficacy of treated materials. However, the data reviewed here indicate that feeding inhibition, knockdown and mortality are positively influenced by high doses of active ingredient while deterrence does not change with change in dose. However, other studies indicate that deterrence resulting from DDT residues inside huts diminishes with time as the active ingredient degrades , indicatIt is hypothesized that since spatial repellents do not kill mosquitoes, there is increased risk of unprotected people being infected with pathogens transmitted by mosquitoes diverted from repellent users . TherefoA meta-analysis could not be conducted as a result of the differences in evaluation methodologies as well as minimal statistical parameters reported by various studies. Hence, we strongly underline the need to reach consensus in spatial repellent testing methodologies and data reporting facilitated through the development of standardized assay guidelines. It is important to note that it is highly likely that additional data on spatial repellents has been gathered but not made available to the scientific community. Publication bias due to industry-associated research may contribute to missing data sets, which if shared could greatly contribute to better characterization of spatial repellents. This information is vital for the development of standardized testing methodologies as well as target product profiles. Therefore scientists in industry are encouraged to share their data which will aid this process.Spatial repellents have the potential to become an important component of vector control since outdoor biting vectors are gaining importance as malaria vectors . In ordeThe authors declare that they have no competing interest.SBO conducted the review and drafted the manuscript. SBO, SJM and MFM wrote the final version of the manuscript. All authors read and approved the final manuscript.


Learning from errors is fundamental to adaptive human behavior. It requires detecting errors, evaluating what went wrong, and adjusting behavior accordingly. These dynamic adjustments are at the heart of behavioral flexibility and accumulating evidence suggests that deficient error processing contributes to maladaptively rigid and repetitive behavior in a range of neuropsychiatric disorders. Neuroimaging and electrophysiological studies reveal highly reliable neural markers of error processing. In this review, we evaluate the evidence that abnormalities in these neural markers can serve as sensitive endophenotypes of neuropsychiatric disorders. We describe the behavioral and neural hallmarks of error processing, their mediation by common genetic polymorphisms, and impairments in schizophrenia, obsessive-compulsive disorder, and autism spectrum disorders. We conclude that neural markers of errors meet several important criteria as endophenotypes including heritability, established neuroanatomical and neurochemical substrates, association with neuropsychiatric disorders, presence in syndromally-unaffected family members, and evidence of genetic mediation. Understanding the mechanisms of error processing deficits in neuropsychiatric disorders may provide novel neural and behavioral targets for treatment and sensitive surrogate markers of treatment response. Treating error processing deficits may improve functional outcome since error signals provide crucial information for flexible adaptation to changing environments. Given the dearth of effective interventions for cognitive deficits in neuropsychiatric disorders, this represents a potentially promising approach. To adapt to the environment, human beings must learn from the consequences of their behavior. Understanding the nature of the brain mechanisms that flexibly modify behavior based on its consequences is a fundamental goal of neuroscience. These mechanisms are also of considerable clinical importance since a number of neuropsychiatric disorders are strongly associated with maladaptively rigid and repetitive behaviors that are not optimally responsive to outcomes. One approach to understanding the neural basis of learning from consequences is to study error processing. Errors provide critical information for adjusting behavior to optimize outcomes. Error processing, which is also referred to as “response monitoring” or “performance monitoring,” involves detecting errors during task performance, evaluating what went wrong, and adjusting behavior accordingly. These dynamic adjustments of responses are at the heart of behavioral flexibility. They enable individuals to optimize function in complex, uncertain, and constantly changing environments. Since learning from errors is impaired in several neuropsychiatric disorders, understanding the neural and genetic mechanisms of error processing has important clinical implications. Identifying specific deficits can illuminate the pathophysiology of these disorders and provide novel targets for treatment. Below, we selectively review the behavioral and neural hallmarks of error processing; impairments in schizophrenia, obsessive-compulsive disorder, and autism spectrum disorders (ASDs); and genetic contributions. The goal is to evaluate the potential of the neural markers of errors to serve as endophenotypes. Endophenotypes are biologically-based heritable dysfunctions that are thought to be a closer reflection of the effects of the genes that predispose to illness than either the diagnosis itself, or the symptoms that define it  in trials that follow an error  Rabbitt, . These tReinforcement learning theory  and functional MRI (fMRI) activation of the dorsal anterior cingulate cortex  is an event-related potential that peaks ~100 ms following an error Figure  and is uThe ERN has been proposed to reflect error detection and reinforcement learning  study of Agam and colleagues, ERN amplitude correlated with fMRI activation in both the PCC and dACC, and these two regions showed coordinated activity based on functional connectivity MRI. This suggests that the dACC and PCC are components of a functional network that mediates error processing. The PCC and ACC have direct anatomical connections through the cingulum bundle  and ASD, accumulating evidence suggests that error processing deficits contribute to rigid, repetitive behavior in a range of disorders. For example, a previous review described ERN abnormalities in anxiety disorders, depression and substance abuse and their relations to symptoms  and repetitive, ritualized behaviors that individuals feel compelled to perform (compulsions). In contrast to the blunted neural responses to errors in schizophrenia, OCD is often associated with exaggerated error responses including increased error-related ACC activation  strategy. The RDoC strategy involves developing, “…for research purposes, new ways of classifying mental disorders based on dimensions of observable behavior and neurobiological measures.” RDoC encourages researchers to base their selection of subjects on dimensions that can be characterized along the causal chain from genes to molecules to circuits to behavior, rather than relying on DSM diagnoses  Axis I psychiatric disorders are highly heritable, their genetic origins remain elusive. A major obstacle to identifying genetic risk factors is the difficulty defining neurobiologically-valid phenotypes for inclusion in studies. Current DSM criteria for disorders such as schizophrenia and autism define phenotypes that are so broad that it is possible for two study samples with the same diagnosis to bear little resemblance to one another. This phenotypic heterogeneity suggests etiological and genetic heterogeneity and reliance on such overly broad diagnostic categories can lead to inconsistent findings. Within studies, relatively large effects may be obscured because they only characterize a subset of the sample. While phenotypic heterogeneity is expected within complex genetic disorders such as schizophrenia and autism, subdivision based on phenotypes has not led to neurobiologically-valid subtyping schemes. In schizophrenia, for example, most subtyping schemes have been based on symptoms , but symptom definitions are broad and imprecise and their assessment is heavily dependent on self-report. In addition, symptoms often lack temporal stability and predictive validity . Moreover, neither diagnosis nor symptoms can identify syndromally-unaffected relatives who carry susceptibility genes. Finally, the substantial shared genetic liability for neuropsychiatric disorders such as schizophrenia, major depressive disorder, ASD, attention deficit-hyperactivity disorder and bipolar disorder , which is associated with schizophrenia  is also a candidate gene for schizophrenia  with the T allele resulting in 40% less transcriptional efficiency , 7 , and 2   and 10  repeats . COMT metabolizes released DA and the Met allele significantly reduces COMT activity, leading to higher DA. The COMTVal158Met polymorphism has been studied extensively in relation to schizophrenia, and several meta-analysis have argued against association  gene leads to a valine-to-methionine substitution  has been associated with increased risk for schizophrenia  has been associated with reduced ERN and post-error slowing  that leads to reduced activity-dependent secretion of BDNF  is a nerve growth factor thought to facilitate synaptic connections in the brain  and increases the efficacy of NPS about tenfold  is a 20 amino-acid peptide that modulates stress and arousal  waveform. It is arguable which method is more valid. Such measurement differences can affect study outcomes as can be illustrated in OCD, which is often characterized by exaggerated neural responses on both correct and error trials. Several studies reporting an increased ERN in OCD, or in non-clinical populations with OCD symptoms, defined it using only the error trial (Gehring et al., a priori assumptions about the shape of the hemodynamic response, may more accurately distinguish preparatory activation from error-related activation, and can also be used to evaluate the temporal characteristics of the hemodynamic response, which may differ between study groups (e.g., Dyckman et al., Methodological differences may also contribute to discrepancies in fMRI results. For example, most standard fMRI analysis techniques assume a shape to the hemodynamic response. While this is a statistically powerful technique when the models are correct, a single assumed model is unlikely to be valid across all brain regions and stimulus types (Duann et al., Conflicting findings of error processing deficits in particular disorders may also arise from a number of other factors such as the use of different tasks and levels of difficulty, the characteristics of the samples studied such as whether certain symptoms are present, treatment with medications, and task performance (e.g., Mathews et al., in vivo to assess the risk of developing symptoms and response to therapy (Klunk, Unlike neurodegenerative disorders such as Alzheimer's Disease, which are associated with specific neuropathologies, neuropsychiatric disorders likely have multiple overlapping etiologies and neuropathologies. Consequently, neuropsychiatric disorders lack sensitive and specific pathophysiological markers such as amyloid beta protein, which is specific to Alzheimer's Disease, is thought to cause the associated dementia, and can be measured y Klunk, . Error pWhile there is clear evidence that deficient error processing is associated with symptoms and functional outcome in neuropsychiatric disorders, further research is required to fully elaborate the bases of these relations both within and across disorders. If, as we and others have proposed, deficient error processing mediates the pathway between genetic predisposition and illness by interfering with adaptive responses to outcomes (e.g., Olvet and Hajcak, The existing literature on error processing allows the generation of biologically plausible hypotheses concerning the effects of genetic variation on well-validated and heritable indices of error processing that are abnormal in neuropsychiatric disorders, show evidence of diagnostic specificity, contribute to disability, and are thought to be mediated by specific neural mechanisms. Understanding the genetic mediation and mechanisms of error processing deficits in neuropsychiatric disorders may eventually lead to the development of specifically targeted interventions and enable the use genetic information to identify individuals most likely to benefit from these treatments. This can substantially reduce outcome variability, thereby increasing power, and reducing the required sample size and cost of treatment trials. The findings of imaging-genetics investigations may also provide novel neural and behavioral targets for treatment and sensitive surrogate markers of treatment response. Treating error processing deficits may significantly affect functional outcome in neuropsychiatric disorders or possibly even prevent onset or relapse since error signals provide crucial information for flexible adaptation to changing environments, and deficits in learning from errors, as indexed by abnormal neural responses and reduced behavioral adaptation, likely substantially contribute to rigid, perseverative, and maladaptive patterns of behavior. Given the dearth of effective interventions for cognitive deficits in neuropsychiatric disorders, this represents a promising approach.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The lipid bilayer of model membranes, liposomes reconstituted from cell lipids, and plasma membrane vesicles and spheres can separate into two distinct liquid phases to yield lipid domains with liquid-ordered and liquid-disordered properties. These observations are the basis of the lipid raft hypothesis that postulates the existence of cholesterol-enriched ordered-phase lipid domains in cell membranes that could regulate protein mobility, localization and interaction. Here we review the evidence that nano-scaled lipid complexes and meso-scaled lipid domains exist in cell membranes and how new fluorescence microscopy techniques that overcome the diffraction limit provide new insights into lipid organization in cell membranes. In the fluid mosaic model , the lipIn 1997, Simons and Ikonen proposed the lipid raft hypothesis in which the phase behavior of different lipid species is exploited to create lateral heterogeneity in the plasma membrane . AccordiIt was then hypothesized that specific membrane proteins would have a high affinity for one phase, thereby partitioning into this phase and being laterally sorted. This would allow lipid rafts to serve as signaling platforms, concentrating some proteins to facilitate their interaction while excluding others . The speWhile the coexistence of micron-scale, resolvable ordered and disordered phase lipid domains was readily observed in model membranes using fluorescence microscopy and phase-partitioning membrane probes , no suchIn some of these definitions, a substantial cohesion length that is a characteristic of a phase in model membranes is no longer included so that no distinction between nano-scaled complexes and meso-scaled domains are made. This lack of distinction may make it difficult to translate findings from pure lipid bilayers to complex cell membranes because the lack of microscopically visible lipid domains in cells is not proof of the absence of lipid rafts. Whether complexes of a few molecules could indeed be called a phase is biophysically controversial and for this reason, we continue to distinguish between multi-molecular complexes and meso-scale domains. Although this limit is arbitrary, meso-scaled domains should be above 20 nm in size and thus contain several thousand lipids .Defining lipid phases is not an issue in model membranes and thus lipid phase have been precisely mapped in such systems resulting in phase diagrams that show the phase behavior at different lipid compositions . It is nex vivo and in vivo in intact zebrafish embryos  and yeast. Progress has also been made in analyzing membrane domains in plant cells. This has included the observation that detergent resistant membranes extracted from plant cell membranes  which weTable 1 for typical biological samples.Much of the controversy surrounding lipid rafts developed as a result of their supposed small size which made them impossible to image using standard fluorescence microscopy approaches. This is because the resolution of a conventional fluorescence microscope is limited by diffraction to above 200 nm. However, in recent years, three families of techniques have emerged which all break the diffraction barrier and allow imaging of cellular structures far below the conventional 200 nm limit. These methodologies are structured illumination microscopy (SIM), stimulated emission depletion microscopy (STED) and photoactivated localization microscopy (PALM). Many of these techniques and now starting to be applied to imaging plant cells . The majIn SIM, the sample is illuminated with a grid pattern, which is then shifted while multiple images are acquired. A super-resolution image is then calculated computationally from the data. SIM can achieve resolutions of around 100 nm in lateral direction, can perform 3D imaging in live cells  and uses conventional fluorophores .Stimulated emission depletion microscopy uses a doughnut-shaped depletion laser beam to de-excite fluorophores at the periphery of a confocal excitation spot. This narrows the size of the spot thereby increasing the resolution. Depending on what laser powers the sample can tolerate from the depletion beam, resolutions of 50–100 nm laterally are typically possible in biological samples. The technique is built on a conventional laser-scanning microscope and has been applied to live cell imaging .Photoactivated localization microscopy and related techniques image and localize individual fluorophores, which typically results in localization precisions of individual molecules of around 20–30 nm. While the technique has long acquisition times and is generally a 2D technique based on total internal reflection fluorescence (TIRF) illumination, progress is being made in establishing 3D PALM as well as higher-speed imaging for live cell analysis .Figure 1) can be used to map the localization of raft and non-raft targeted fluorescent fusion proteins and a quantitative analysis can distinguish protein clusters from random distributions, frequently identifying clusters on scale of 50–100 nm . This allows dynamics to be analyzed on sub-resolution length scales similar to what has been achieved previously with near-field scanning optical microscopy (NSOM) based techniques  – a method for determining molecular diffusion coefficients based on fluorescence fluctuation analysis  very close (much less that the wavelength of light) to the sample, detecting the emitted fluorescence and then raster-scanning to build up an image which can result in lateral resolutions of less than 10 nm. For example, this technique has been used to show that GPI-anchored proteins, commonly used as lipid raft markers, are arranged in nano-scale clusters on the surface of immune cells . These “Although not a super-resolution technique, we recently used fluorescence lifetime imaging microscopy (FLIM) to gain insights into lipid organization in cell membranes below the diffraction limit. This was possible because we used an unbiased unmixing approach, the so-called phasor apporach, to map the spectral signatures of Laurdan in each pixel. We could show that Laurdan in the plasma membrane of HeLa show is not a homogenous phase of intermediate order but a mixture of ordered and disordered domains. By using the pure lipid mixtures of 70:30 sphingomyelin:cholesterol and 100% dioleoylphosphatidylcholine as reference points for liquid-ordered and liquid-disordered phases, we estimated that ~76% of the plasma membrane is covered with ordered phases. This approach could not tell us whether Laurdan with an ordered FLIM signature comes from a continuous phase or from many domains and complexes with a large variation in sizes, simply because the data acquisition was still diffraction limited. One should also take into consideration that the liquid-ordered and liquid-disordered membranes in cells may have significantly different properties than the pure lipid mixtures that we used as reference data. It was for example shown that the difference in membrane order between phase-separated ordered and disordered domains in plasma membrane vesicles was much smaller than the differences observed in model membranes . HoweverOne of the biggest changes to our current understanding of membrane heterogeneity has been an elevation of the role of the cytoskeleton . The corvia short, dynamic actin fibers aligning assembling into aster formations .Firstly, the cytoskeleton can directly influence the diffusion and clustering of membrane proteins. The main theory here is the “picket fence” or “hop diffusion” model first developed by Figure 2). By performing FCS experiments over a range of size scales, it is possible to infer information on the underlying, sub-resolution organization without requiring more complex super-resolution hardware. These so called “FCS diffusion laws” make it possible to determine whether it is transient confinement zones or membrane lipid domains that exert the greatest influence on diffusion within the bilayer  and therefore influences diffusion and distributions indirectly by regulating the bilayer phase behavior. Blocking actin polymerization using latrunculin causes a decrease in membrane order observed with the environmentally sensitive membrane probe di-4-ANEPPDHQ . MembranFigure 4). While we have do direct evidence that phase geometry frequently change in cell membranes, coverage of 30–70% of either phase afford the possibility that protein interactions occur during the meso-scaled remodeling of phase geometries.It has been hypothesized that the cytoskeleton may cause “pinning” of local membranes in an ordered state, which then act as nucleation sites for the development of ordered-phase domains. Using computer modeling, it was demonstrated that if such pinning took place in a membrane that was very close to the critical composition for fluid – fluid phase coexistence, small critical fluctuations could cause many of the properties attributed to rafts, such as their small size and transient nature . MoreoveThe high level of ordered-phase coverage could be the result of the extremely high density of membrane proteins (estimated at 23% protein coverage for the red blood cell membrane; via its effects on membrane lipid order. Further technological advances, particularly the development of functional probes that report on the membrane environment are undoubtedly needed to answer many of the outstanding questions of the organizational hierarchy of cellular membranes. What started as one hypothesis that brought lipids back into the focus has now evolved into a number of competing membrane models that are not mutually exclusive. Excitingly, as we understand more of how cell membranes are organized, we also gain deeper insight into functional processes such as receptor signaling and cargo-driven endocytosis.Newly developed imaging techniques which allow super-resolution are dramatically increasing our understanding of the complexity of cell membrane organization. While the basic principles of the original lipid raft hypothesis – ordered membranes based on cholesterol and saturated lipids – may remain, more details have already emerged that cause the distinction between lipid domains into which certain proteins may partition and lipid complexes that may contain multiple proteins. Other forces at work include direct protein–protein interactions, ordering of shell lipids by protein transmembrane domains, critical transient lipid composition fluctuations and a complex interplay between the bilayer and the underlying actin cytoskeletal meshwork. This structure may influence the distribution of membrane proteins directly or The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.