The human body is capable of reacting to multiple aggressors by developing an inflammatory response with the secretion of inflammatory cytokines. The worrisome clinical manifestations occur when this inflammatory response is disproportionate. Hemophagocytic lymphohistiocytosis (HLH) is a rare and severe condition characterized by an overwhelming inflammatory response that may result in end-organ damage and might be fatal. Correspondingly, immune reconstitution inflammatory syndrome (IRIS) is another well-known disorder, seen commonly in human immunodeficiency virus (HIV)-infected patients after the commencement of highly active antiretroviral therapy (HAART). Both entities share a similar clinical presentation and a dismal prognosis. Due to widespread clinical manifestations and laboratory abnormalities, diagnosis is often missed at the time of presentation. There is little consensus on the treatment of secondary HLH, which is usually handled on a case-by-case basis. Rapid curbing of the widespread inflammatory response is the main goal of treatment. To the best of our knowledge, there is scarce literature available on the coexistence of HLH and IRIS; therefore, medical management in the co-occurrence of these two conditions needs to be further investigated. Hemophagocytic lymphohistiocytosis (HLH) represents a life-threatening condition that results from a schematized process ensuing in hyperproduction of cytokines, that leads to fatal end-organ damage. HLH has been linked with multiple conditions, such as infectious diseases, malignancies, and autoimmune diseases. The clinical picture is vague, including fever, hepatomegaly, splenomegaly, and pancytopenia. The lack of specific manifestations poses a challenge in establishing a definitive diagnosis. However, encompassing a mortality of about 95%, launching a timely diagnosis is a critical challenge for physicians ,2. InterPathophysiologyHLH is usually a disproportionate response to an inflammatory signal that results in hypercytokinemia. This excessive response is thought to be due to some form of impairment in the function of cytotoxic T-lymphocytes (CTLs) and natural killer (NK)/T-cell function. Histopathologically, HLH is characterized by a prominent and diffuse accumulation of lymphocytes and mature macrophages, which occasionally exhibit hemophagocytosis . Two distinct forms of HLH have described in the existing literature. The primary or genetic HLH is a fatal disorder found in infants and young children, predominantly due to mutations in genes responsible for the cytotoxic function of NK cells and T-lymphocytes ,2. The sAfter the initiation of HAART, HIV infected patients start a process of replenishment of the immune cells. This process, especially in very immunodeficient patients, may result in a disproportionate and exaggerated host inflammatory response, similar to the one observed in HLH . Risk faDiagnosisDiagnostic guidelines for HLH were revised by the HLH Study Group of the Histiocyte Society, suggesting that the diagnosis of HLH can be made on two bases-either a molecular diagnosis consistent with HLH or if the patient meets five of the following eight criteria: fever, splenomegaly, at least two lineages of cytopenia, hypertriglyceridemia ≥265 mg/dL) or hypofibrinogenemia (≤1.5 g/L), hemophagocytosis on histology, low/absent NK-cell activity, hyperferritinemia (≥500 μg/L) and increased levels of soluble interleukin-2 receptor (sCD25), a marker of macrophage activity) . Diagnos65 mg/dL HLH occurs more frequently in the HIV/AIDS population and has a septic-shock like presentation . It has To the best of our knowledge, there are only a handful of cases of HHV-8-related HLH. They included both HIV-positive and HIV-negative patients as well as post-renal transplant patients. In some of the instances, HHV-8 related HLH occurred in the setting of underlying MCD, Kaposi sarcoma (KS) or primary effusion lymphoma (PEL), while in others, HHV-8 infection resulted in HLH in the absence of any underlying malignancy -20. It iThe treatment strategy of HLH involves treating the underlying cause to halt the overactivation of the immune system. Infectious causes and underlying malignancies must be investigated to direct disease-specific treatment. Rituximab can be initiated if the EBV infection is suspected. Intravenous immunoglobulin (IVIG) is considered an appropriate addition therapy for most viral infections . If the According to the HLH-2004 protocol, an 8-week course consisting of three drugs-etoposide, dexamethasone, and cyclosporine-is recommended as a part of the “initial therapy.” The supportive therapy includes prophylactic cotrimoxazole, consideration of antiviral therapy in patients with ongoing viral infections, and IVIG. Allogenic bone marrow transplantation is recommended for patients with a familial disease/molecular diagnosis and those refractory to first-line therapy . HoweverThe acquired or secondary form of HLH has multiple underlying etiologies like infections, malignancies, autoimmune diseases, and acquired immunodeficiency states like AIDS. The clinical picture is vague, including fever, hepatomegaly, splenomegaly, and pancytopenia. Lack of specific manifestations poses a challenge in establishing a definitive diagnosis. Existing literature is deficient when it comes to unique scenarios like the co-occurrence of HLH and IRIS. Since HLH carries a worse prognosis than IRIS, it might be beneficial to discontinue HAART temporarily in such cases.


Excessive metal femoral head wear has been described only as revision surgery complication after primary ceramic-on-ceramic total hip arthroplasty (THA). Here, we present the first case of metal femoral head wear after primary metal-on-polyethylene THA. A 56-year-old woman was referred to our outpatient clinic 17 years after primary right-sided THA, experiencing pain and decreased right hip range of motion. Radiographic examination revealed acetabular cup dislocation, eccentric femoral head wear, damaged titanium porous coating of femoral stem, metallosis, and pseudotumor formation. Endoprosthetic components were extracted, but further reconstruction was impossible due to presence of large acetabular bone defect. Macro- and micro-structure of extracted components were analyzed. Acetabular liner surface was damaged, with scratches, indentations, and embedded metal debris particles present on the entire inner surface. Analysis of metal debris by energy-dispersive spectroscopy showed that it consisted of titanium and stainless-steel particles. Femoral head was gravely worn and elliptically shaped, with abrasive wear visible under scanning electron microscope. No signs of trunnionosis at head/neck junction were observed. Microstructure of femoral head material was homogeneous austenitic, with microhardness of 145 HV 0.2, which is lower than previously described titanium hardness. In conclusion, detached titanium porous coating of femoral stem can cause stainless-steel femoral head wear in primary metal-on-polyethylene THA. As soon as such detachment becomes evident, revision surgery should be considered to prevent devastating complications. The complications of total hip arthroplasty (THA), such as adverse reaction to metal debris, corrosion, and pseudotumor formation, are no longer reserved exclusively for metal-on-metal but can also occur in metal-on-polyethylene implants . These cA 56-year-old woman was referred to our outpatient clinic in 2018 because of pain and right hip decreased range of motion. She underwent a right-sided THA in 2001, when a modular neck implant and femoral stem with proximal titanium porous coating were used . Early postoperative period was uneventful. In 2012, the patient sustained right-sided trans-acetabular and inferior pubic ramus fractures, which were successfully treated conservatively. Since 2016 she complained about increasing pain in the right groin region and had severely reduced right hip range of motion. Examination in our outpatient clinic showed that her right leg was 2 cm shorter.in situ and damage to the porous stem coating. A revision surgery was indicated, and the patient agreed to the procedure.The initial x-ray examination in 2018 showed acetabular cup dislocation, eccentric femoral head wear, “cloudy bubbles” characteristic of metallosis, and pseudotumor formation . It alsoDuring surgery, performed using direct lateral approach, extensive metallosis was observed . After tMacro- and micro-structure of all extracted components were analyzed in detail at the Faculty of Mechanical Engineering and Naval Architecture of the University of Zagreb. The analysis revealed macroscopic damage to the titanium porous coating of the femoral stem  and a deFemoral head component (AISI 316L stainless-steel) was removed from the femoral neck, and no signs of trunnionosis were observed at the head/neck junction . To deteThe patient signed the informed consent for publishing the medical data and visual materials.The main factor limiting long-term THA survival is wear debris production from bearing surfaces . FemoralTribocorrosion has been described at the head/neck junction and, more often, at the neck/stem junction . In our The main concern of this study was to determine the origin of the metal particles on the polyethylene surface and the type of femoral head wear. The SEM and EDS analysis showed the presence of titanium and austenitic stainless-steel particles , suggestThe only limitation of this study is that microhardness of the porous titanium coating microparticles was not measured due to the method’s unavailability in our setting. Nevertheless, we believe that the comparison with the literature values is justified and that our conclusion is valid.Our study showed that detached titanium porous coating of the femoral stem can cause the stainless-steel femoral head wear in primary metal-on-polyethylene THA. As soon as such detachment becomes evident on routine follow-up radiographs, revision surgery should be considered to prevent devastating complications described in this report.


Individuals with substance use disorders (SUDs) have to cope with drug-related cues and contexts which can affect instrumental drug seeking, as shown with Pavlovian-to-instrumental transfer (PIT) tasks among humans and animals. Our review addresses two potential mechanisms that may contribute to habitual or even compulsive drug seeking and taking. One mechanism is represented by Pavlovian and PIT effects on drug intake. The other is a shift from goal-directed to habitual drug intake, which can be accessed via model-based versus model-free decision-making in respective learning tasks. We discuss the impact of these learning mechanisms on drug consumption. First, we describe how Pavlovian and instrumental learning mechanisms interact in drug addiction. Secondly, we address the effects of acute and chronic stress exposure on behavioral and neural PIT effects in alcohol use disorder (AUD). Thirdly, we discuss how these learning mechanisms and their respective neurobiological correlates can contribute to losing versus regaining control over drug intake. Utilizing mobile technology , computational models, and real-world data may help to better identify patients with a high relapse risk and to offer targeted behavioral and pharmacotherapeutic interventions for vulnerable patients. Drugs of abuse stimulate dopamine release and thus reinforce drug intake . Wise orDrug-associated cues can elicit drug craving and promote drug seeking ,13. FromSo how can alcohol cues trigger not only drug craving and functional activation in the ventral striatum, amygdala, and medial prefrontal cortex ,22, but In outcome-specific PIT, presenting a particular reward-predicting cue can selectively elevate instrumental responses that are associated with the same unique reward, while in general PIT, a reward- or loss-predicting cue can generally modify instrumental responses toward any outcome . So-callPIT effects may be specifically strong in stressful situations, when decisions have to be fast, and profit from an overall “atmospheric” evaluation of the dangerousness or safety of the current situation . VariousWith respect to neurobiological correlates, animal experiments and human studies suggest that activation of the basolateral amygdala, the nucleus accumbens shell, and the ventrolateral putamen contribute to an outcome-specific form of PIT ,39,40. TIn line with this, stronger general PIT effects elicited by positive non-drug cues and functional PIT-related brain activation in the nucleus accumbens were observed in prospective AUD relapsers ,41. ThisIn smokers, tobacco-related PIT effects have been demonstrated in several studies in satiated and deprived smokers ,43, but The PIT effects of drug-related cues were also studied in subjects with AUD. Regarding alcohol versus water cues, we expected that alcohol cues would promote approach behaviors and predict poor treatment outcomes, as was the case with general PIT effects. The appetitive and aversive Pavlovian cues were passively conditioned with monetary reward or loss. Surprisingly, however, patients with poor treatment outcomes behaved similar to the healthy controls. Patients with good treatment outcomes who did not relapse in the follow-up period of three months showed a significant difference both in behavior and in functional brain responses to alcohol cues in a general PIT task . They shPatients may learn to use environmental cues as warning-signs and thus train to avoid rather than approach situations in which drugs are available. One training program targeting such drug-approach tendencies is the so-called Zooming Joystick Task. Patients with addictive disorders learn to push pictures of alcohol beverages away instead of pulling them toward themselves. Four training sessions appear to be sufficient to successfully reduce the relapse-risk during an one year follow-up period, with the number needed to treat (NNT) being around 10, suggesting that 10% of all patients would benefit from this intervention . From a In line with the key role of the amygdala and nucleus accumbens, behavioral PIT effects are understood as driven by bottom-up processes. Nevertheless, a conflict—like in a Stroop task—should be elicited in situations in which Pavlovian and instrumental cues are incongruent  and this conflict should trigger the allocation of top-down control. Indeed, the results of Sommer and co-workers  revealedDual-process theories of learning and addiction propose that the development of drug addiction involves a shift from goal-directed to habitual control of action ,7. AnimaModel-based versus model-free behavior and goal-directed versus habitual behavior are assessed by different tasks. Model-based versus model-free behavior is assessed via taking complex decision-making processes into account, while goal-directed versus habitual behavior is operationalized via the impact of reward devaluation. Nevertheless, both tasks are intercorrelated in the sense that individuals who tend to behave in a model-based way also show stronger goal-directed behaviors, while individuals who tend to respond in a habitual way rely more strongly on model-free decision-making . TherefoHuman behavior is more flexible and dependent on context than previously assumed in straight-forward models . Researchers should consider contextual cues, such as expectancies and availabilities, mood states, individual stress-levels, and cognitive control processes. Modern technology allows ambulatory assessments, including reports of mood-states, recordings of geolocation, and psychomotor activity in real life . An impo


Whole-body magnetic resonance imaging (WB-MRI) could be an alternative to multi-modality staging of non-small-cell lung cancer (NSCLC), but its diagnostic accuracy, effect on staging times, number of tests needed, cost, and effect on treatment decisions are unknown. We aimed to prospectively compare the diagnostic accuracy and efficiency of WB-MRI-based staging pathways with standard pathways in NSCLC.The Streamline L trial was a prospective, multicentre trial done in 16 hospitals in England. Eligible patients were 18 years or older, with newly diagnosed NSCLC that was potentially radically treatable on diagnostic chest CT (defined as stage IIIb or less). Exclusion criteria were severe systemic disease, pregnancy, contraindications to MRI, or histologies other than NSCLC. Patients underwent WB-MRI, the result of which was withheld until standard staging investigations were complete and the first treatment decision made. The multidisciplinary team recorded its treatment decision based on standard investigations, then on the WB-MRI staging pathway , and finally on all tests. The primary outcome was difference in per-patient sensitivity for metastases between standard and WB-MRI staging pathways against a consensus reference standard at 12 months, in the per-protocol population. Secondary outcomes were difference in per-patient specificity for metastatic disease detection between standard and WB-MRI staging pathways, differences in treatment decisions, staging efficiency  and per-organ sensitivity and specificity for metastases and per-patient agreement for local T and N stage. This trial is registered with the International Standard Randomised Controlled Trial registry, number ISRCTN50436483, and is complete.Between Feb 26, 2013, and Sept 5, 2016, 976 patients were screened for eligibility. 353 patients were recruited, 187 of whom completed the trial; 52 (28%) had metastasis at baseline. Pathway sensitivity was 50% (95% CI 37–63) for WB-MRI and 54% (41–67) for standard pathways, a difference of 4% . No adverse events related to imaging were reported. Specificity did not differ between WB-MRI (93% [88–96]) and standard pathways . Agreement with the multidisciplinary team's final treatment decision was 98% for WB-MRI and 99% for the standard pathway. Time to complete staging was shorter for WB-MRI (13 days [12–14]) than for the standard pathway (19 days [17–21]); a 6-day (4–8) difference. The number of tests required was similar WB-MRI (one [1–1]) and standard pathways (one [1–2]). Mean per-patient costs were £317 (273–361) for WBI-MRI and £620 (574–666) for standard pathways.WB-MRI staging pathways have similar accuracy to standard pathways, and reduce the staging time and costs.UK National Institute for Health Research. Non-small-cell lung cancer (NSCLC) is the leading cause of cancer related death in the UK, with more than 35 000 deaths annually.Evidence before this studyThe detection of metastatic disease during non-small-cell lung cancer (NSCLC) staging underpins treatment strategy and is fundamental to optimisation of patient outcomes. Staging pathways rely on high technology imaging platforms such as CT, PET-CT, and MRI, which differ in their diagnostic accuracies across individual organs. Such multimodality staging pathways are complex, resource and time intensive, involve irradiation, and increase patient anxiety. Modern MRI platforms can image the whole body within 1 h, and whole-body MRI (WB-MRI) is advocated as a more accurate, efficient, and safer alternative to multimodality staging pathways. We searched PubMed and Embase (without language restriction) for articles published between Jan 1, 1990, and Sept 30, 2018, using MeSH and full-text search-strings for “cancer”, “neoplasm”, “staging”, “diagnostic accuracy”, “magnetic resonance imaging”, “whole body imaging”, “diffusion magnetic resonance imaging”, “metastasis”, and “lung”. We found several meta-analyses reporting WB-MRI accuracy for lung cancer staging, most suggesting accuracy for metastatic disease is equivalent to, or might exceed standard technologies. All such meta-analyses, however, were limited to metastasis detection in specific end organs, notably bone. Various comparators have been selected but the majority compare WB-MRI with PET-CT, and scintigraphy (in the case of bone metastasis). Most primary studies were small, single site, and explanatory, with WB-MRI interpreted by a few specialised radiologists. They focused on single modality comparisons rather than evaluating real-world, multimodality staging pathways. We found no data regarding how WB-MRI influences the first major treatment decision or staging efficiency.Added value of this studyTo our knowledge, this is the largest prospective multicentre trial to date comparing the diagnostic accuracy of WB-MRI staging pathways to standard staging in patients newly diagnosed with NSCLC. We used a pragmatic trial design to better test pathway performance in routine clinical practice and investigated staging pathway efficiency in terms of test number, time to completion, and costs. We also contemporaneously tested the effect of alternative staging pathways on the nature and timing of the first major treatment decisions. Patient outcomes were followed-up after 12 months to better evaluate pathway accuracy at the time of initial staging. We found both pathways had similar accuracies for identifying patients with metastatic disease and the nature of the first major treatment decision was similar. WB-MRI was more efficient and reduced the time to staging completion and costs.Implications of all the available evidenceWB-MRI staging pathways have similar accuracy to current standard staging pathways, resulting in the same treatment decisions. However, they are more efficient and reduce time to complete staging and costs. WB-MRI is, therefore, more suitable for staging in routine clinical practice. Future research should investigate the utility of WB-MRI treatment response assessment and cancer surveillance after curative treatments.vs PET-CT) instead of the multiple staging tests encountered in daily practice.Modern MRI scanners can image the entire body within 1 h, and whole-body MRI (WB-MRI)—which typically scans from the head to mid-thigh—is a potentially more accurate and safer alternative to standard multimodality staging pathways. WB-MRI could also accelerate staging, thereby increasing efficiency by reducing additional tests, staging time, and costs. Meta-analyses suggest accuracy of WB-MRI in detecting metastatic disease for metastatic disease is equivalent to, or might exceed, standard technologies,We did two parallel prospective multicentre trials to elucidate and directly compare the diagnostic accuracy and efficiency of WB-MRI-based staging pathways with standard staging in NSCLC (Streamline L) and colon cancer (Streamline C).Streamline L is a multicentre, prospective trial comparing diagnostic accuracy for metastatic disease of staging pathways based on initial WB-MRI, with standard staging in NSCLC. Ethics committee approval was granted on Oct 3, 2012, and the trial was coordinated by Cancer Research UK and University College London Cancer Trials Centre, with oversight from an independent data monitoring committee and a trial steering committee. All patients gave written informed consent.Patients were recruited from 16 general and teaching UK National Health Service (NHS) hospitals. Because 11 of the 16 sites did not have the infrastructure to do WB-MRI, these sites sent patients to a nearby hospital for scanning . EligiblParticipants were identified from outpatient clinics, multidisciplinary team meetings, and inpatient wards by local research team, who took informed consent from consecutive, unselected, eligible patients. A screening log detailed all patients approached and reasons for non-participation, where applicable. Age, performance status, sex, and request date for the first staging investigation were collected from recruited patients. Staging completion date was also recorded, defined as the date of the final test in the standard staging pathway.online.The protocol has been publishedParticipants had contemporaneous WB-MRI plus all standard staging investigations done as part of usual clinical care. Standard investigations were generally undertaken at the recruitment site, or a secondary hospital by referral in the case of specialised tests (such as PET-CT), and were interpreted by local consultant radiologists as per usual clinical practice. Interpretation of standard investigations was masked to WB-MRI images and findings. Case report forms included the nature and date of all standard investigations actually done before the first major treatment decision, and their findings regarding presence and location of metastatic disease.The platform used for WB-MRI was in line with usual practice. A minimum dataset of sequences was acquired, including diffusion, T2-weighted, and T1-weighted (pre-intravenous and post-intravenous gadolinium contrast medium) imaging . WB-MRI Across all recruitment sites and imaging hubs, 16 radiologists interpreted WB-MRI and were unaware of all other standard staging investigations and clinical information (other than the suspected cancer diagnosis and its lobar location). All radiologists were fellows of the Royal College of Radiologists and had interpreted at least 20 validated staging WB-MRIs. Radiologists with experience of fewer than 100 WB-MRI datasets initially had their reports validated by more experienced colleagues  and reported alone only once deemed competent by their colleague. This procedure was designed specifically to mirror how WB-MRI would be reported in NHS practice if more widely disseminated. Radiologists completed case report forms documenting the T and N stage of the local tumour,Patients were discussed in the multi-disciplinary team meeting at their local hospital as per usual care pathways. WB-MRI images and reports were withheld until patients had completed all standard staging investigations so that the multidisciplinary team made its first major treatment decision based only on standard staging.In the same meeting, the WB-MRI report and images were then shown to the multidisciplinary team via 3Dnet. The team considered the report and images and stated whether additional tests would have been requested before the first major treatment decision could be reached, had WB-MRI been the initial staging investigation . Any such tests were then done if they or an equivalent test had not already been done as part of the standard pathway and the multidisciplinary team considered them essential to patient care. If done already, their results were noted. The multidisciplinary team recorded the TNM stage based on the WB-MRI staging pathway  and stated what the first major treatment decision would have been on the basis of this pathway. The final multidisciplinary team treatment decision was then made based on all available tests  to assess the effect of lesion size on diagnostic accuracy, per-organ sensitivity, and for WB-MRI as a stand-alone investigation based on the original radiologist report.Secondary outcomes were difference in per-patient specificity for metastatic disease detection between standard and WB-MRI staging pathways, agreement between treatment decisions based on alternate pathways and the multidisciplinary team and consensus panel treatment decisions, staging efficiency , per-organ sensitivity and specificity for metastasis, and per-patient agreement for local T and N stage. Additional secondary outcomes related to the effect of differing combinations of MRI sequences on accuracy, interobserver variability in WB-MRI interpretation, and the effect of adding WB-MRI to standard pathways will be reported elsewhere. The comparative patient experience of staging pathways and the findings of a discrete choice experiment have already been reported.26Using methods for comparative studies,We report our prespecified primary and secondary outcomes, and additional sensitivity analyses. Binary comparisons  were calculated using paired proportions  in STATA 14.2 . For the primary outcome, equivocal disease was considered positive for metastasis. Sensitivity analysis treated equivocal results as negative.There were no missing data for the primary outcome. Statistical significance was determined on the basis of 95% CIs from Newcombe paired proportion method;We compared the costs of WB-MRI versus standard pathways . The cosStreamline L is registered with the International Standard Randomised Controlled Trial registry, number ISRCTN50436483.The funder of the study stipulated that the study design should be a diagnostic accuracy trial using a cohort design, but was not involved in data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.Between Feb 26, 2013, and Sept 5, 2016, 976 patients were screened for eligibility . 353 patSensitivity of staging for patients with metastatic disease was 50% (95% CI 37–63) for WB-MRI and 54% (41–67) for standard pathways, a difference of 4%  and standard pathway . The number of equivocal results per pathway is shown in the The WB-MRI pathway had 65% agreement for N stage compared with 75% for the standard pathway, a significant difference of 10% 3–18; . Of the Agreement with the final treatment decision of the multidisciplinary team was 98% for WB-MRI and 99% for the standard pathway . TreatmeAcross the cohort, standard staging pathways involved 302 individual investigations and WB-MRI involved 232 individual investigations; WB-MRI pathways generated an additional 45 tests . The medvs 19 days [17–21]); a difference of 6 days (4–8) (Time to staging was shorter for WB-MRI pathways than for standard pathways (13 days [12–14] ys (4–8) . Mean peys (4–8) .Figure 3To date, Streamline L is the largest prospective multicentre trial to compare the diagnostic accuracy of WB-MRI and standard staging pathways for metastatic disease in patients with newly diagnosed NSCLC. Both pathways showed similar accuracy, but the WB-MRI pathway was more time-efficient and cost-efficient. Treatment decisions were similar. Our data suggest WB-MRI is a viable replacement for standard pathways.WB-MRI pathways had no advantage over standard pathways in terms of diagnostic accuracy. The overall sensitivity of both pathways for metastatic disease was lower than published studiesWe found that the WB-MRI pathway had 82% sensitivity for patients with metastatic disease of at least 1 cm, compared with only 9% for smaller metastasis. Our WB-MRI protocol complied with accepted international standards,We found WB-MRI pathways had similar accuracy for T staging compared with standard pathways, suggesting the anatomical information given by WB-MRI matched that of standard imaging. Sensitivities for N stage were comparable to that previously reported,Generally, efficiency receives less attention than diagnostic accuracy.A strength of our trial is its pragmatic design. We recruited from a representative range of general and teaching hospitals, with all imaging done and interpreted according to usual local protocols, to increase generalisability of our results. The 16 radiologists interpreting WB-MRI were representative of those who would do so in daily NHS practice. We avoided using a smaller number of highly experienced radiologists; although we acknowledge that such individuals might achieve sensitivities greater than we report, they do not represent the national workforce. We used multidisciplinary team meetings to mirror patient care in the NHS. In doing so, we captured the entirety of standard pathways, including contemporaneous treatment decisions. We used a novel cloud-based image repository to maintain blinding and control multidisciplinary team access to WB-MRI until the appropriate time in the decision-making process. We were able to model the content and timing of WB-MRI staging pathways, and the potential effect on decision making. Conversely, previous research usually reports head-to-head comparisons between single imaging platforms, failing to capture pathway complexity. To our knowledge, our trial design is unique.Streamline L does have limitations. Our withdrawal rate was superficially high, but most excluded participants were excluded because of a final diagnosis other than NSCLC. We masked radiologists reporting WB-MRI to patient history and contemporaneous imaging. This was masked to isolate diagnostic test accuracy within a pragmatic setting. Participants were representative of those undergoing staging in daily practice, although we did exclude pregnant women, patients not wanting to undergo WB-MRI, and patients with contraindications to MRI. We modelled timing of WB-MRI staging pathways on the basis of real waiting times collated from recruitment sites during the trial, although sites had capacity to do WB-MRI. Waiting times might not be representative of those at other hospitals, and in other countries. Some of the benefits of reduced staging time by WB-MRI pathways could be negated if time to commencing treatment  are not reduced in parallel. Treatment decisions based on WB-MRI pathways were made after the multidisciplinary team was unmasked to all standard imaging tests, which could introduce bias. However, this situation was unavoidable if the full complexity of standard staging pathways was to be captured without interference from WB-MRI findings and if treatment decisions were to be recorded contemporaneously. Furthermore, alternate pathway agreement with a retrospective optimal treatment at 12 months remained very similar. Our cost analyses reflect an English NHS perspective and could differ in other settings, which might negate some of the cost advantages of WB-MRI pathways. Although WB-MRI is advocated as being safer than current standard staging investigations, new technologies are reducing radiation dose,In summary, WB-MRI staging pathways have similar diagnostic accuracy to standard pathways for identifying patients with metastatic disease in newly diagnosed NSCLC, and lead to similar treatment decisions. However, they reduce staging time and costs. In a real-world NHS setting, WB-MRI-based pathways are a viable replacement for standard pathways.ctc.enquiries@ucl.ac.ukIndividual participant data that underlie the results reported in this article, after deidentification , will be available for individual participant data meta-analysis beginning 9 months and ending 36 months after article publication. Data will be available to investigators whose proposed use of the data has been approved by an independent review committee (learned intermediary) identified for this purpose. Data access requires proof of relevant ethical committee approval for the specified analysis only. Data will be limited to those required for a specific analysis to protect deanonymisation. Where proposals that would compete with ongoing or planned research from the investigators within the trials team, data access will only be granted once investigator team publications are submitted. Proposals should be directed to the corresponding author; to gain access, data requestors will need to sign a data access agreement. After 36 months, there is no funded technical support. Information regarding submitting proposals and accessing data can be obtained by emailing


Ankylosing spondylitis (AS) is an important factor to not only cause employment obstacle, but also result in serious social economic load. Several randomized controlled trials investigated the efficacy of group- versus home-based exercise programs in patients with AS. This systematic review will collect and summarize the available evidence to realize the effectiveness of group- and home-based programs in patients with AS.A search in PubMed, Web of Science, EMBASE, and the Cochrane Library will be electronically performed by 2 independent investigators to capture all potential studies comparing group- and home-based in patients with AS. The time limit of search will be from their inception to April 2018. Two independent investigators provide their agreement in presencial meeting for a final selection, and at a later stage, the articles will be reviewed in full-text by the all authors. Quantitative analysis will be performed with Review Manager (RevMan) software (version 5.3.0).This meta-analysis will provide a high-quality synthesis of current evidence of group- versus home-based exercise programs in patients with AS.The conclusion of our meta-analysis will provide the evidence which program is an effective intervention for patient with AS. To date, the etiology of AS is still not fully known, however, published evidences suggested that several aspects such as heredity, drugs and accident may be the contributor to this condition. With the progression of the AS, the patients often suffered from limited motion and deformity of the spine, dysfunction, and poor quality of life (QoL). At the same time, published evidences also reported that patients with inflammatory arthritis in primary care also affected by increased cardiovascular morbidity and mortality. Therefore, AS has been regarded as an important factor to not only cause employment obstacle, but also result in serious social economic burden. And thus, AS patients will also be instructed to receive treatment to reduce pain and morning stiffness, and then to further prevent deformity and maintain correct posture, to also keep physical condition and psychosocial health as well.Ankylosing spondylitis (AS) is a chronic and progressive rheumatic disease, which will make patients to suffer from pain, fatigue, joint destruction, deformity, even disability, loss of joint function, and so on.,7 It is noted that exercise, which is one of the nonpharmacological treatments, positively interferes in all kinds of physical and psychological sides. Several studies suggested that even low intensity physical exercise also obtained considerable reductions in mortality and improved health outcomes among patients when compared with subjects receiving controls.,9 For patients with AS, 2 exercise programs including home-based and group-based exercise has been applied in practice, however published evidences found that home-based exercise can effectively improve the health-related QoL and reduce fatigue in patients with AS. More importantly, home-based exercises program is cheaper, easier and more efficient, and thus it has been advised to be as for the promising nonpharmacological option for the treatment of AS.–12 It is noted that, however, several studies have been recently performed to examine the effect of group-based exercise program, and found beneficial effects on pain, mobility, function, and disease activity in patients with AS.,14 It is difficult to make decision in clinical practice due to home-based exercise program and group-based exercise program all obtained promising results in AS patients. Therefore, we designed the present meta-analysis to investigate whether group-based exercise program is superior to home-based exercise program in terms of disease activity and functional status in patients with AS. We designed this systematic review and meta-analysis on April 6, 2018 and we expected to complete this study by August 30, 2018.At the present, various therapeutic modalities  can be used to relieve uncomfortable symptoms and put off disease progression for AS. Despite several promising options has been developed in pharmacological therapy, the lasted recommendations released by the Assessments of SpondyloArthritis International Society and the European League Against Rheumatism (ASAS/EULAR) emphasize that combination of pharmacological including nonsteroidal antiinflammatory drugs (NSAIDs), disease-modified antirheumatic drugs (DMARDs) and tumor necrosis factor (TNF) inhibitor and nonpharmacological treatments including exercise should be the optimal management for AS.2 The systematic review and meta-analysis has been registered in the International Prospective Register of Systematic Reviews (PROSPERO) platform with the number of CRD42018097046. We will perform all statistical analyses in accordance with the recommendations proposed by Cochrane Collaboration (CC).We designed this protocol for a systematic review and meta-analysis according to the framework constructed in preferred reporting items for systematic reviews and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation.2.1Papers, which population inclusion criteria gathered adult patients with AS diagnosed by a rheumatologist will be chosen. Randomized controlled trials (RCTs) or clinical trials, in which at least one of the groups received the group-based exercises or home-based exercises, will be included. The outcome measures of interest were the Bath Ankylosing Spondylitis Metrology Index (BASMI), the Bath Ankylosing Spondylitis Functional Index (BASFI), the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and depression. Participants aged less than 18 years old or with juvenile-onset of AS will be excluded. Review articles, observational studies without controls, case reports, cross-sectional studies, self-controlled studies, and commentaries will also be excluded.2.2The aim of this meta-analysis is to investigate the comparative effects of home-based exercise related to group-based exercise programs in AS patients. The research team will search 4 electronic databases including PubMed, Web of Science, EMBASE, and the Cochrane Library using combinations of the terms home-based exercise, supervis∗ exercise, group-based exercise, and ankylosing spondylitis. Search terms will be adapted for use with each database. Common keywords and medical subject headings (MeSH) consisted of 2 components: the condition (AS), the intervention . The time limit of search will be designed from their inception to April 2018. In the present meta-analysis, we will only consider the study published in English language. Moreover, we will check the bibliographies of eligible studies and topic-related review to capture any potential study. If disagreement on citation search was identified, a third senior investigator will be consulted to solve it.2.3Two authors independently will be assigned to screen titles and abstracts in order to identify those studies that meet the inclusion criteria. And then, we will retrieve the full-text of potential studies, and 2 independent investigators will check the eligibility of each study. Any divergency about study selection will be addressed through consulting a third senior investigator.2.4All captured citations will be imported into EndNote literature management software V.X7. We will then assign 2 reviewers to abstract the basic information and data for the specific outcomes from the eligible studies, such as first author, publication year, age of participants, sample size, details of interventions, and outcomes of interest using this standard data extraction form. We will contact the corresponding author if sufficient data of an eligible study cannot be abstracted from the full text.2.5,18 A study will be assigned a risk level of “high risk of bias,” “unclear risk of bias,” or “low risk of bias” according to the match level between the actual information and the evaluation criteria.We will assign 2 independent reviewers to appraise the risk of bias from seven domains, including randomization sequence generation, allocation concealment, blinding of participants, blinding of study personnel, blinding of outcome assessors, incomplete outcome data, selective reporting and other bias with the Cochrane risk of bias assessment tool.2.6P-value, and we used the fixed-effects model if there was no evidence of heterogeneity (I2 < 50%), otherwise a random-effects model was used. Pooled differences in means were calculated and a 2-tailed P-value < .05 was considered to indicate statistical significance. All analyses were performed using Review Manger (RevMan) statistical software, version 5.3.0 .Outcome measures were compared between participants treated with group-based or supervised exercises group and home-based group with each study. The homogeneity among trials was evaluated using 2.7 Moreover, we will also perform the Egger linear regression test to quantitatively detect the symmetric or a symmetric of funnel plot.For single outcome, we will draw the funnel plot to identify publication bias if the number of studies analyzed is more than 10.3 Because the etiology of AS has not yet been fully clarified, and thus treatment was performed to only reduce symptoms. Despite several pharmacological options have been developed, some adverse events limit the use of pharmacological therapy. Considered these limits of pharmacological therapy, the ASAS/EULAR recommends combination of pharmacological and non-pharmacological treatments to be the optimal management for AS.,7 To date, 2 exercise programs including home-based and group-based exercise can be selected to treat AS patients, however the comparative efficacy of these 2 interventions is not known. Just because of this, it is difficult to make decision in clinical practice due to home-based exercise program and group-based exercise program all obtained promising results in AS patients. Therefore, it is essential to investigate the comparative of group-based exercise program compared to home-based exercise program in patients with AS.AS is a debilitating condition for patients because it will cause several morbid consequences such as joint destruction, deformity, and loss of joint function.This systematic review and meta-analysis will be one of the first to investigate the comparative efficacy and safety of home-based exercise and group-based exercises programs for patients with AS. The results of the systematic review and meta-analysis will influence evidence based decision making for management of AS patients as it will be fundamental in providing reliable recommendations for AS patients management.Hui Liang, Xu Tian, Xiao-Ling Liu, and Li-Fen Jin conceived the study, developed the study criteria. Shu-Ya Wang and Yi Dai searched the literature. Li Kang and Li-Sai Chen analyzed the data. Hui Liang, Xu Tian, Xiao-Ling Liu, and Li-Fen Jin wrote the protocol. Hui Liang and Xu Tian conducted the preliminary search. Xu Tian and Xiao-Ling Liu extracted data. Hui Liang and Li-Fen Jin revised the manuscript. All authors have read, and approved the final manuscript.Conceptualization: Hui Liang, Xu Tian, Xiao-Ling Liu, Li-Fen Jin.Data curation: Xiao-Ling Liu, Shu-Ya Wang, Yi Dai.Formal analysis: Xu Tian, Li-Sai Chen.Investigation: Li Kang, Li-Fen Jin.Methodology: Xu Tian, Li Kang, Li-Sai Chen, Li-Fen Jin.Resources: Xiao-Ling Liu, Shu-Ya Wang, Yi Dai.Supervision: Hui Liang, Xu Tian, Li-Fen Jin.Writing – original draft: Hui Liang, Xu Tian, Xiao-Ling Liu, Li-Fen Jin.Writing – review & editing: Hui Liang, Xu Tian, Li-Fen Jin.


DNA sequencing technology has revolutionized the field of biology, shifting biology from a data-limited to data-rich state. Central to the interpretation of sequencing data are the computational tools and approaches that convert raw data into biologically meaningful information. Both the tools and the generation of data are actively evolving, yet the practice of re-analysis of previously generated data with new tools is not commonplace. Re-analysis of existing data provides an affordable means of generating new information and will likely become more routine within biology, yet necessitates a new set of considerations for best practices and resource development. Here, we discuss several practices that we believe to be broadly applicable when re-analyzing data, especially when done by small research groups. Advances in high-throughput, next-generation sequencing technologies have catapulted biology into a new computational era. In fields of biology that leverage sequencing data, the primary limiting step in the earlier stages of biological inquiry has increasingly shifted away from data generation to data analysis. Concomitant with the increasing emphasis on the computational processing of these data is the advancement of the computational tools available for such analyses; new computational approaches for the analysis of these data are constantly being created, tested, and proven worthy of use. Yet, outside of computational lab groups, the practice of re-analysis of previously generated data with new tools and approaches is not commonplace. Such re-analysis has great utility and will become more routine within the life sciences, yet re-analysis necessitates a new set of considerations for best practices and resource development.Our interest in the issues surrounding re-analysis was spurred by a large-scale sequencing project: the Marine Microbial Transcriptome Sequencing Project (MMETSP), which generated 678 transcriptomes, spanning 396 different strains of eukaryotic microbial eukaryotes isolated from marine settings . This dade novo transcriptomes from RNA sequencing data have been described, and preexisting tools have been improved upon [Since the original MMETSP analysis, new tools and techniques for the assembly of ved upon . Moreoveved upon  was desiThese secondary data products of sequencing, such as annotated assemblies, should be viewed as hypotheses generated from the underlying biology, rather than some immutable “truth.” As such, these secondary data products can continue to be improved as new tools are developed. For example, we note that  describeUltimately, such iterations on the original raw data have the potential to improve upon the secondary data products, that is, the assembled transcriptomes and associated annotations that are relied upon by the broader community for biological inquiry. Through this process, we developed several practices that we believe to be broadly applicable when re-analyzing data, especially when done by small research groups.Funding agencies and academic journals now mandate the deposition of raw data into digital repositories  and Gene Expression Omnibus, European Nucleotide Archive). Thus, to date, the majority of the sequence data that have been generated and published is openly available online for reference and use in other studies. The sharing and availability of raw data from high-throughput sequencing studies has been largely managed through the development of archival services such as the SRA, which was established as part of the International Nucleotide Sequence Database Collaboration . The SRAhttps://www.ncbi.nlm.nih.gov/genbank.tsa/).In fact, a substantial proportion of these data products might be aptly categorized as “dark data,” as they are largely undiscoverable and often archived independently in association with a publication or on private servers. Even more limiting, however, is that the guidelines for public databases such as the TSA specifically state that “assemblies from sequences not directly sequenced by the submitter” should not be uploaded to the TSA, thereby excluding the potential for reassembled datasets to be made available and directly linked to preexisting BioProjects, BioSamples, TSAs, and SRA entries . Moreover, such an archival platform would ideally document the full provenance of the secondary data product. Movement toward this kind of data archival system is being made both with the development of alternative scientific data publication models  as wellhttps://zenodo.org), a scientific data repository founded by CERN, which provided a DOI for the assemblies (https://doi.org/10.5281/zenodo.740440). The header information for each assembly was modified to contain the DOI. We then created a GitHub repository containing the scripts used to generate the assemblies. The repository was then archived with Zenodo, which generated a single DOI for the project (https://doi.org/10.5281/zenodo.594854).In the absence of a community database specifically for the type of secondary product that was produced in this analysis, we opted to upload the assemblies, annotations, and counts to Zenodo  to host and link both the code and results from large-scale re-analysis projects in a publicly accessible way. The direct linking of protocols and metadata to output data products is paramount in the data-heavy future of scientific advancement. We also identified several lingering issues surrounding large-scale re-analysis.Actual computation on these large datasets is a non-trivial issue, as it requires access to facilities with sufficiently large, high-memory machines. Amazon Web Service instances and other “cloud” platforms, including XSEDE, provide flexible computing options and are broadly accessible. Cloud-based systems, however, tend to be more expensive per computation hour than local resources. High-performance computing (HPC) resources at local institutions represent another potential site of compute ability. However, HPC resources can be temperamental and potentially balk at larger, more node-consuming procedures; moreover, bioinformatics tools may be poorly optimized for HPC resourcess. Trinity, used in our pipeline, creates many small files for each run, and this repeatedly caused disk slowdowns on our HPC. The re-analysis by  attempteBeyond the optimization of computational resources, we feel that there is a significant opportunity for scientific advancement with high-throughput sequencing projects in making data products “forward discoverable,” because this makes it possible to improve downstream work without significant upstream investment. In an ideal future, a researcher might be automatically notified when a dataset that she is actively working on is updated or changes. This presents many social and technical challenges that will need to be solved if we are to take full advantage of public datasets.DOI: Digital Object Identifier; HPC: high-performance computing; MMETSP: Marine Microbial Transcriptome Sequencing Project; SRA: Sequence Read Archive; TSA: Transcriptome Shotgun Assembly.The authors declare that they have no competing interests.Funding was provided by the Gordon and Betty Moore Foundation (award GBMF4551 to C.T.B.).Conceptualized by H.A., L.K.J., and C.T.B. Written by H.A. and C.T.B. Edited and revised by H.A., C.T.B., and L.K.J. All authors read and approved the final manuscript.GIGA-D-18-00196_Original-Submission.pdfClick here for additional data file.GIGA-D-18-00196_Revision-1.pdfClick here for additional data file.GIGA-D-18-00196_Revision-2.pdfClick here for additional data file.Response-to-Reviewer-Comments_Original-Submission.pdfClick here for additional data file.Response-to-Reviewer-Comments_Revision-1.pdfClick here for additional data file.Reviewer-1-Report- -- Konrad Foerstner2/7/2018 ReviewedClick here for additional data file.Reviewer-2-Report- -- Konrad Foerstner7/2/2018 ReviewedClick here for additional data file.


Research in human action recognition has accelerated significantly since the introduction of powerful machine learning tools such as Convolutional Neural Networks (CNNs). However, effective and efficient methods for incorporation of temporal information into CNNs are still being actively explored in the recent literature. Motivated by the popular recurrent attention models in the research area of natural language processing, we propose the Attention-aware Temporal Weighted CNN (ATW CNN) for action recognition in videos, which embeds a visual attention model into a temporal weighted multi-stream CNN. This attention model is simply implemented as temporal weighting yet it effectively boosts the recognition performance of video representations. Besides, each stream in the proposed ATW CNN framework is capable of end-to-end training, with both network parameters and temporal weights optimized by stochastic gradient descent (SGD) with back-propagation. Our experimental results on the UCF-101 and HMDB-51 datasets showed that the proposed attention mechanism contributes substantially to the performance gains with the more discriminative snippets by focusing on more relevant video segments. Action recognition and activity understanding in videos are imperative elements of computer vision research. Over the last few years, deep learning techniques dramatically revolutionized research areas such as image classification ,2, objecUnlike image classification, the most distinctive property of video data is the variable-length. While images can be readily resized to the same spatial resolution, it is difficult to subsample videos temporally. Therefore, it is difficult for the early 3D convolution neural networks (3D CNNs)  to achieIn addition, some of the legacy action recognition datasets  only coPrevious multi-stream architecture, such as the two-stream CNN , suffersInspired by the success of the attention model widely used in natural language processing  and imagThe major contributions of this paper can be summarized as follows.An effective long-range attention mechanism simply implemented by temporal weighting;Each stream of the proposed ATW CNN can be optimized end-to-end, without requiring additional labeling;State-of-the-art recognition performance is achieved on two public datasets, i.e., the HMDB-51  and UCF-This paper is an extension to its conference version  with reoThe remainder of the paper is organized as follows. In Human action recognition has been studied for decades, which is challenging partially due to large intraclass variations in appearance of motions and camera settings, etc. Before the emergence of deep learning, handcrafted action representations were in the prime position along during the progress of action recognition. There were usually two major steps, including the action representation extraction and the classifier training. Among them, many methods are based on spatio-temporal interest point detection. For instance, Laptev et al.  extendedIn the past few years, CNN-based techniques have revolutionized the image/video understanding ,30,31,32RGBD camera-based action recognition offers 3D information, which is a valuable addition to the conventional RGB channels. Such datasets are usually captured by the Microsoft Xbox One Kinect Cameras, such as the Kinetics dataset . DespiteInspired by the success of computer vision with still RGB images, many researchers have proposed numerous methods for the conventional RGB video camera-based action recognition. Deep learning-based action recognition methods can be divided into four major categories.3D CNNs-based methods. Ji et al.  extendedTwo-stream CNN-based methods. Simonyan et al.  proposedRNN-based methods. Donahue et al.  proposedHybrid model-based methods. Hybrid methods incorporate both conventional wisdom and deep learning for action recognition ,43,44. SIn this section, the temporally structured video representation model is introduced first, followed by the formulation of the attention-aware temporal weighted convolutional neural network (ATW CNN). After these formulations, the implementation details of the proposed ATW CNN is presented.dense sampling in the time domain, the inputs of the network are consecutive video frames covering the entire video;spare sampling one frame out of N segments , non-overlapping segments are obtained by evenly partition the video into N such chunks, as illustrated in with a target number of How do various CNN-based architectures incorporate the capacity to extract semantic information in the time domain? According to the previous two-stream CNN  literatuN is reasonably chosen.As noted by ,10,13, tV is equally partitioned into N segments, i.e., k-th segment. Inspired by [Suppose a video pired by ,8,53, mupired by , warped In the traditional two-stream structure , the denOne RGB video frame, five optical flow images and five warped optical flow images are randomly sampled from each segment V is uniformly partitioned into N segments, i.e., i-i-th snippet, with y being the corresponding training label. We aggregate the sampled RGB frame and its corresponding optical flows and warped optical flows into a snippet. A series of such snippets are fed to the proposed ATW CNN for training.The architecture of the proposed ATW CNN for action recognition is presented in ATW CNN aims at the automatic selection of the semantically dominant snippets and the designation of large attention weights to them via the temporal visual attention module. For each modality, it comprises a base CNN stream and a temporal attention model. We choose the ResNet-101  as our bi-th snippet, i.e., the temporal attention weight for the i-Subsequently, they are normalized by a softmax function to guarantee positiveness and unit sum  are cropped to training . Firstlytraining . SubsequDuring the testing phase, a fixed number of snippets (80 in our experiments) are uniformly sampled from each video. We use weighted average fusion  in 51 categories. The videos are collected from various sources, mostly from movies, and the other from websites such as the Prelinger archive, YouTube and Google. The action categories include “general facial actions”, “facial actions with object manipulation”, “general body movements”, “body movements with object interaction” and “body movements for human interaction”. Compared with UCF-101, video clips in HMDB-51 are more challenging because they are generally more representative of the complexity of real-world actions. Evaluation on these two trimmed datasets is performed with average accuracy as the criterion.dense sampling in time domain;interval sampling  are empN is fixed at 4 for the proposed ATW CNN for the remainder of the paper.With small segment numbers  for both Different initialization strategies also contribute to performance differences. Three common initialization strategies for the weights in the proposed attention layer are empirically tested on the first split of the UCF-101 dataset, includingAs shown in To fully evaluate the performance of the proposed ATW CNN, we compare it with 14 existing state-of-the-art action recognition methods ,49,51,52The action recognition accuracies of the proposed ATW CNN and 14 competing methods ,49,51,52To validate the effects of the attention model in the proposed ATW CNN, we visualize the learned temporal visual attention in terms of most relevant and irrelevant video frames, to cast light on how the attention weighting operation interprets the target activity. We present the highest ranking and lowest ranking four video frames in attention weights  are fed to three individual CNN streams, respectively, with respective attention models and a late fusion procedure to induce attention weighting in predictions. We evaluated the proposed ATW CNN on two benchmark action recognition datasets, i.e., the HMDB-51  and UCF-For potential future work, we are planning to further extend the proposed attention model to account for spatial  attention and possibly long-term temporal attention in untrimmed videos based on RNNs and LSTMs.


The tool allows the user to directly read RNA-Seq data files deposited in the Gene Expression Omnibus or GEO database. Operated using any web browser application, ABioTrans provides easy options for multiple statistical distribution fitting, Pearson and Spearman rank correlations, PCA,  FPKM, RUpon submitting data files and all supporting files , the user can filter the lowly expressed genes by indicating the minimum expression value and the minimum number of samples that are required to exceed the threshold for each gene. If input data contain raw read counts, user can choose one of the normalization options  listed upon availability of supporting files. FPKM, RPKM, and TPM option perform normalization for sequencing depth and gene length, whereas RUV and upper quartile eliminate unwanted variation between samples. To check for sample variation, Relative Log Expression (RLE) plots  of inputThe scatter plot displays all gene expressions between any two columns selected from the datafile. This is intended to show, transcriptome-wide, how each gene expression varies between any two samples. The lower the scatter, the more similar the global responses and vice-versa . That isAfter knowing this information, the next process is to make a distribution (cumulative distribution function) plot and compare with the common statistical distributions. As gene expressions are known to follow certain statistical distributions such as power-law or lognormal , we inclABioTrans allows the comparison with (i) log-normal, (ii) Pareto or power-law, (iii) log-logistic (iv) gamma, (v) Weibull, and (vi) Burr distributions. To compare the quality of statistical distribution fit, the Akaike information criterion (AIC) can also be evaluated on this screen.This mode allows the user to compute linear (Pearson) and monotonic non-linear (Spearman) correlations, (i) in actual values in a table or (ii) as a density gradient plot between the samples.k-means clusters.The PCA button plots the variance of all principal components and allows 2-D and 3-D plots of any PC-axis combination. There is also a slide bar selector for testing the number of These functions measure the disorder or variability between samples using Shannon entropy and expressions scatter . Entropy2) of expression divided by the square mean expression (μ2), for all genes between all possible pairs of samples  distinguishing the significant and insignificant, DE and non-DE genes, is displayed. Plot of dispersion estimation, which correlates to gene variation, is also available in accordance to the selected analysis method.To better visualize DE analysis result by edgeR and DESeq, volcano plot  first undergo scaling defined by eviation . SubsequABioTrans also lists the name of genes for each cluster.This function is used to define the biological processes or enrichment of differentially regulated genes in a chosen sample or cluster. User can select among 3 gene ontology enrichment test: enrichR, clusterProfiler and GOstats .The user needs to create a new csv file providing the name of genes (for each cluster) in 1 column (foreground genes). Background genes (or reference genes), if available, should be prepared in the same format. Next, the sample species, gene ID type (following NCBI database ) and oneThe loading time of ABioTrans for a first time R user is about 30 min on a typical Windows notebook or Macbook. This is due to the installation of the various R-packages that are prerequisite to run ABioTrans. For regular R users, who have installed most packages, the initial loading can take between a few to several minutes depending on whether package updates are required. Once loaded, the subsequent re-load will take only a few seconds.zfGenes, Biofilm-Yeast, and Yeast-biofilm2).The typical time taken from pre- to post-processing using all features in ABioTrans is between 10–20 min. ABioTrans has also been compared with other similar freely available RNA-Seq GUI tools, and itdemonstrates better functionalities and capabilities .ABioTrans is a user-friendly, easy-to-use, point-and-click statistical tool tailored to analyse RNA-Seq data files. It can also be used to analyse any high throughput data as long as they follow the format listed in this technology report. The complete user manual to operate ABioTrans is available as https://github.com/buithuytien/ABioTrans, Operating system(s): Platform independent (web browser), Programming language: R (RStudio), Other requirements: Bioconductor genome wide annotation databases, R-packages . These packages will automatically be installed when the ABioTrans.R is executed in RStudio. No restriction of usage for non-academic.ABioTrans is available at: YZ and TTB developed the software tool. KS planned, designed the tool and wrote the manuscript. 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.


We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone. The significance of BIDS is timely: there is increasing availability of open neuroimaging data resources, and strong interest in aggregating large, heterogeneous datasets to harness a new range of scientific questions, and augment statistical power. This also poses new challenges in terms of data organisation, harmonisation, (re)processing and sharing, especially without a standard format for digital neuroscience data between or within data modalities .The Brain Imaging Data Structure (BIDS) is an emerging standard for the organisation of neuroimaging data , infrastructure (data storage space) and financial  resources. Poor or lacking data management strategies also negatively affects the reproducibility of results, even within the lab where the data were collected.BIDS was initiated with magnetic resonance imaging (MRI) data. It provides a simple, hierarchical folder structure, with key study parameters documented in text-based metadata files. MRI-BIDS can manage multiple MRI modalities, with minimal curation overheads. This reduces the likelihood of data-handling errors. Another key benefit is the augmented interoperability between BIDS-compatible software tools for data analytics.2. MEG-BIDS can therefore readily be generalised to electroencephalography (EEG), multiunit recordings, and local field potentials. Further to strengthening and rationalising data management in MEG labs, MEG-BIDS provides a common structure for present and future large MEG open-data repositories3–5. The new standard handles files collected from all types of MEG instruments, regardless of their raw data file format  The absence of a unique data file format in MEG is indeed compensated by MEG-BIDS’s standard data organisation and metadata principled reporting: the sharing and processing of large and complex data hierarchies is simplified, and made compatible and reproducible across tools for data analytics.Here we introduce a significant extension of BIDS to electrophysiology data. The technical sophistication of magnetoencephalography (MEG) makes it the most challenging electrophysiology data type for standardisation6, with direct inputs from MEG investigators, technical support staff and data managers. The teams of leading academic data-analysis software were also directly involved7: Brainstorm8, FieldTrip9, MNE10, and SPM11, which all have adopted MEG-BIDS. The design process was initiated at the 2016 International Conference on Biomagnetism , where the first incarnation of MEG-BIDS was introduced, and open group discussions ensued.The MEG-BIDS specifications were defined in accord with best-practice guidelines for conducting MEG research12, and received comments and suggestions from the community to refine the MEG-BIDS specifications. In July 2017, we published an open poll survey for the MEG community to express their potential interest in MEG-BIDS. The poll received 78 international entries, with most salient results indicating i) strong interest in a common standard for MEG data organisation (98.7%), ii) affirmed willingness to try a MEG-BIDS solution (97.4%).A first version of the present manuscript was shared as a preprintSubject, Session, Technique, and Run. In MEG terminology, Subject refers to a scanned participant. We acknowledge that MEG is not strictly a scanning technique. Yet, this is for convenience, affinity with other neuroimaging modalities, and to reflect the language used in most MEG labs. ‘Session’ defines a non-intermittent period of time during which the subject is in the scanner. ‘Run’ is a period of time during which brain activity or empty-room (for noise characterisation) is recorded continuously, with no interruptions. It is typical with MEG that a Session consists of multiple Runs: task instructions can change and/or participants can take a break between runs. The notion of Task refers to the instructions  that are performed by the participant. Responses is a feature for continuous recording of behaviour. Note that BIDS also supports storage of stimuli files (such as videos), and annotations of events via a hierarchical event descriptor extension. MEG-specific metadata elements can be reported with the widely used JavaScript Object Notation (JSON) and Tab Separated Value (TSV) text file formats, both human- and machine-readable, which contributed to the versatility and practicality of MRI-BIDS.MEG-BIDS shares common data descriptors with BIDS, such as 13, and include links to main BIDS specifications and JSON schemas. Note that there are no JSON LD context files, but with attention to backward compatibility with present BIDS specifications, they could be added in future versions. There is also ongoing work in the BIDS community to reach to the NIDM (Neuroimaging Data Model) efforts to expose experiment metadata as linked data. In the same vein, with MEG-BIDS extending from original MRI-BIDS, it does not support Resources Description Format (RDF) representations. The original decision for BIDS to not rely on RDF was driven by the complexity of that format and relatively low familiarity among scientists and software developers outside of the semantic web circles. Yet, current investigations of BIDS to NIDM conversions may lead to RDF views of BIDS datasets.The comprehensive MEG-BIDS specifications are openly available elsewhereThe MEG-BIDS file organisation also extends, with full compatibility, that of MRI-BIDS: file names are constituted by a series of key-value pairs, with multiple possible file types, while retaining a few typological aspects. MEG-BIDS can therefore register data of any kind, including but not limited to task-based, resting-state, and empty-room data collection. We emphasise that all of the above notions apply also to EEG and all other modalities of electrophysiology, for which MEG-BIDS serves as template for standardisation.13.Such flexibility was crucial to retain for MEG, as we already mentioned there is no common, open or standard file format in the field. MEG-BIDS stores unprocessed (raw) data in the native vendor file format. This means that users can still rely on their preferred data review application, possibly provided by the system’s vendor, for files stored in the MEG-BIDS folder structure. Free, open-source BIDS-compliant software (see below) can also extract most required meta information elements from these raw data files, such as data collection parameters and other study and task descriptors. They are eventually transcribed into sidecar JSON files by these MEG-BIDS compatible applications. One major benefit of metadata extraction is the facilitation of subsequent data searches and indexation, without the handling and repeated parsing of large raw data files. Additional relevant files can be included alongside the MEG raw data: some propositions are detailed in the online specificationsStudy folder. Multiple Subject subfolders contain the data from the participants enrolled. They are arranged by Session, each session subfolder containing Run folders and eventually, data and metadata files , a channel description table (*_channels.tsv), and other general BIDS files, such as task events tables (*_events.tsv) that are likely to be specific of each run. Session specific files include the coordinates of anatomical landmarks and head-localisation coils stored in a JSON document (*_coordsystem.json) together with the fiducials information, optional photographs of the anatomical landmarks and/or head localisation coils (*_photo.jpg), 3-D scalp digitalisation files (*_headshape.<manufacturer_specific_format>) and acquisition times (scans.tsv). The Subject and Study specific files are inherited directly from the general BIDS specifications . Note that in case of conflict between fields of different runs/sessions, the inheritance principle should be applied: the description file closer to the data prevails1.The 2. MEG-BIDS therefore associates all recordings with anatomical fiducial locations stored in a dedicated field of the MRI json file. Again, MEG-BIDS compatible software can read and interpret this information properly.One issue that required special attention was the multiplicity of coordinate systems and units between MEG systems. To impose a unique coordinate system for BIDS based on the subjects’ brain anatomy  was an appealing solution, which however would lack generalizability in the MEG practice. For instance, MEG data can be collected without anatomical information, such as empty-room noise recordings, which are important to optimize source modelinghttps://github.com/INCF/bids-validator and the actual online tool at: https://incf.github.io/bids-validator/). It is available for users to verify the validity of their MEG-BIDS data preparation.The BIDS online validator was updated to accommodate its MEG extension (with open code available at GitHub: https://github.com/INCF/BIDS-examples).We provide four publicly-available data repositories in MEG-BIDS format, for a total of 200GB. They are freely accessible for download in the public domain via OpenNeuro. Note that for educational and demonstration purposes, the International Neuroinformatics Coordinating Facility’s GitHub also hosts a lighter version  of the MEG-BIDS dataset examples (Resting-state14 (https://openneuro.org/datasets/ds000247): Five minutes of eyes-open, resting-state MEG data . This dataset is described in Brainstorm’s specific MEG-BIDS tutorial .Auditory task15 (https://openneuro.org/datasets/ds000246): MEG-BIDS version of an auditory-stimulation study . The data is described in detail in the main online tutorial of Brainstorm .Visual and auditory tasks16 (https://openneuro.org/datasets/ds000248): MNE data sample  from a previously published study10 (includes T1 and FLASH MRI). This dataset is described in detail in MNE’s online tutorial .Visual group study17 (https://openneuro.org/datasets/ds000117): A multi-modal  human neuroimaging dataset of 16 subjects from a previously published study on face processing18 (60.88GB): This dataset is described in detail in the SPM12 manual .Widely-used free and open MEG  software packages have already added functionality to support MEG-BIDS. All feature basic preprocessing tools and advanced solutions for sophisticated data analytics e.g., source imaging, time-frequency decompositions, statistical inference, multivariate decoding, and measures of functional connectivity:Brainstorm8: Matlab and Java application, with rich graphical-user interactions and analytic pipeline designs for MEG, EEG, NIRS, and electrophysiology recordings. BIDS-formatted MEG/EEG datasets can be imported automatically into the Brainstorm database, as described in the above-mentioned MEG-BIDS Resting-state tutorial using the OMEGA sample.FieldTrip9: Matlab toolbox for MEG, EEG, and other electrophysiological data full analysis pipelines. Among others, FieldTrip has been used for the MEG part of the Human Connectome Project.MNE10: a Python software package with MEG analysis tools and workflows. MNE provides code to read and write files in MEG-BIDS-compatible format. Eventually, the MNE team has committed to distribute all its tutorial datasets in MEG-BIDS, along with and the relative analysis scripts. A preliminary version is available at https://mne-tools.github.io/mne-bids/.SPM11: software written in Matlab, where many widely-used methods for the analysis of PET, fMRI and for computational neuroanatomy were originally developed and implemented. SPM has been extended to MEG and EEG analyses and SPM12 includes the spm_BIDS library to parse and query BIDS-formatted datasets, as well as low-level functions to read/write JSON and TSV metadata files. A complete pipeline for the analysis of a group MEG-BIDS dataset is also available.MEG-BIDS JSON file generator: Python scripts to produce the JSON sidecar files and reduce the overhead of adopting MEG-BIDS: publicly-available (https://github.com/INCF/pybids).http://incf.github.io/bids-validator/) :MEG-BIDS validator . A command line version is also provided so that it can be used in scripted analysis. The validator performs several sanity checks on datasets with ensure they are compatible with BIDS. This includes the use of regular expressions to check filenames, and JSON schemas to ensure that the metadata files are standardised by data types.per se. Most present and future tools for MEG data analytics can be readily equipped with the necessary readers for all existing vendor formats: these libraries are available in open source from the above-cited software. We believe the capacity of MEG-BIDS to organise data without requiring a common data format is actually a strength: the standard is flexible enough for any data parameters to be extracted and stored as metadata in sidecar JSON files at the time of creating a new MEG-BIDS data entry, regardless of the original file format of the raw data. Therefore, any new data format for electrophysiology is by design compatible with MEG-BIDS19.MEG-BIDS is a proposal to establish a standard framework for the organisation of electrophysiology data. It does not impose the standardisation of the data file format Along the same lines, MEG-BIDS handles the different coordinate systems defined by MEG vendors, provided that they are documented in the *_coordsystem.json file. This extends to the coordinate systems used for MEG and EEG sensor locations, MRI volumes, anatomical fiducials, landmarks and digitised head points.derivatives folder.Following this seminal contribution, we will extend MEG-BIDS towards the handling of processed data, which for now and akin to MRI-BIDS, are simply stored in a data 4 and OpenNeuro20. It also facilitates multimodal integration , as the data from multiple modalities can follow the same organisation scheme.We anticipate that the systematic data organisation enabled by MEG-BIDS will be supported by an increasing number of neuroimaging tools, and that more publicly-available data repositories will adopt the standard. The straightforward design of MEG-BIDS makes it an interoperable common exchange format for transferring data between investigators and community repositories e.g., OMEGAHow to cite this article: Niso, G. et al. MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Sci. Data 5:180110 doi: 10.1038/sdata.2018.110 (2018).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.