The in silico performance was then compared against its performance in an in vitro model to capture the full environmental constraints such as sensing during stimulation at the tissue electrode interface. In vitro modeling demonstrated comparable results to the in silico model, providing verification of the software tool and model. This study provides validation evidence of the suitability of the proposed system for tracking longitudinal seizure activity. Given its flexibility, the event monitor can be adapted to track other disorders with episodic and rhythmic symptoms represented by bioelectrical behavior.Providing clinicians with objective outcomes of neuromodulation therapy is a key unmet need, especially in emerging areas such as epilepsy and mood disorders. These diseases have episodic behavior and circadian/multidien rhythm characteristics that are difficult to capture in short clinical follow-ups. This work presents preliminary validation evidence for an implantable neuromodulation system with integrated physiological event monitoring, with an initial focus on seizure tracking for epilepsy. The system was developed to address currently unmet requirements for patients undergoing neuromodulation therapy for neurological disorders, specifically the ability to sense physiological data during stimulation and track events with seconds-level granularity. The system incorporates an interactive software tool to enable optimal configuration of the signal processing chain on an embedded implantable device (the Picostim–DyNeuMo Mk-2) including data ingestion from the device loop recorder, event labeling, generation of filter and classification parameters, as well as summary statistics. When the monitor parameters are optimized, the user can wirelessly update the system for chronic event tracking. The simulated performance of the device was assessed using an  IEpilepsy is a neurological disorder characterized by a predisposition to have epileptic seizures – the symptoms of abnormal excessive or synchronous neuronal activity in the brain . EpilepsDeep brain stimulation (DBS) is an intracranial neuromodulation therapy that is emerging as an alternative option for the treatment of patients with drug-resistant epilepsy . DBS delThe clinical benefits of simultaneous sensing and stimulation are twofold. Firstly, real-time seizure-onset detection allows for adaptive stimulation to be delivered to abort breakthrough seizure activity. Secondly, the ability to longitudinally detect and record a patient’s seizure activity offers clinicians objective data with regard to seizure frequency, seizure rhythms, and, critically, the impact of interventions such as stimulation regime alterations.Current clinical trials evaluating the efficacy of DBS therapies for epilepsy are dependent on patient/carer manual diaries, which are notoriously inaccurate due to noncompliance and unawareness of seizure activity . There iin silico prediction of the seizure monitor performance prior to real-time investigation of the detector embedded on the neuromodulation device in an in vitro test-bench.In this study we build on the work of the Picostim–DyNeuMo research system, presented in , 12], t, t12], tIIANext-generation neuromodulation devices must enable the objective assessment of neuromodulation therapies. To this end, capabilities required include 1) maintenance of physiological data recording capabilities during stimulation, 2) recording of longitudinal data with sufficient granularity to observe typical events  and 3) enable flexible algorithm design for long-term deployment in a patient-specific or disease-specific manner.BThe Picostim–DyNeuMo research system is a cranially-mounted, rechargeable neuromodulation device that enables dynamic variation of delivered stimulation programs in response to movement (Mk-1) , time (MCThe Oxford Configurable Algorithm Tool (OxCAT) is a software workflow that was developed to facilitate flexible configuration of the embedded signal processing chain and classifier on the DyNeuMo Mk-2 device. The OxCAT workflow was developed as a Jupyter Notebook using Python 3.8. The workflow enables 1) ingestion of pre-recorded data as an input to the workflow, 2) annotation of the input data, 3) a power spectral density viewer for annotated data segments, 4) a filter design tool for dynamic configuration of the device signal processing chain and 5) an interactive receiver-operating characteristic (ROC) curve viewer for dynamic selection of the embedded classifier threshold. In addition, the OxCAT simulates operation of the device signal processing chain and classifier to provide a preliminary prediction of the system performance with the specified configuration. If suitable performance is predicted, the workflow provides the ability to export the specified device configuration as a YAML file for upload onto the DyNeuMo Mk-2 device for real-time operation. An overview of the DyNeuMo Mk-2 device signal chain and OxCAT workflow for device configuration are visualized in DIn this study, seizure data from two patients with genetic generalized epilepsy previously recorded by King’s College Hospital was utilized. Both patients were implanted with externalized DBS electrodes at the centromedian thalamus (CMT). The dataset for patient 1 was recorded in 2011, while patient 2’s dataset was recorded in 2014. The original datasets included both synchronized scalp electroencephalogram (EEG) and CMT LFP recordings; however, only the recorded EEG was utilized by a trained clinician to annotate the data for periods of electrographic seizure activity. Electrographic seizures were identified as epileptiform discharges which lasted greater than three seconds in duration. Discharge or spike activity less than three seconds was considered to be interictal epileptiform activity and was subsequently not included as annotated seizure events. Eight hours of data was analyzed from patient 1 and 69 seizure events were identified. For patient 2, 11 seizure events were identified from analyzing five hours and twelve minutes from their dataset.Only the synchronized LFP recordings were utilized as input to the OxCAT workflow and saline tank test-bench. The LFP recordings were preprocessed by resampling the recorded signals to a 625 Hz sampling frequency. The data was then segmented into sections to extract each annotated seizure event, including the 30 seconds before and after. Finally, the segmented seizure data was concatenated together to create the final dataset, which was used as an input to the OxCAT workflow and saline tank test-bench.During annotated seizure periods, patient 1 displayed a broadband increase in power between 0 – 22 Hz, where a ‘bump’ between 9 – 14 Hz was also observed. For this reason the bandpass filter in the DyNeuMo Mk-2 signal processing chain was centered on 11.5 Hz with low and high cutoff frequencies of 9 Hz and 14 Hz, respectively. Similarly, patient 2 displayed a broadband power increase in frequencies between 0 – 24 Hz, in addition to a ‘bump’ between 9 – 23 Hz. The bandpass filter for patient 2 was subsequently centered on 16.5 Hz with 14 Hz and 19 Hz bandpass cutoff frequencies. For both patient datasets, the highpass and lowpass (smoothing) filters in the signal processing chain were set to 6.8 Hz and 1 Hz, respectively.E1 score.The performance of the classifier was simulated by filtering the input signal with the specified signal processing chain configured in the OxCAT workflow. To generate the classifier ROC curve, the true and false positive rates for the classifier were calculated by comparing the clinician-annotated data labels with the classifier-predicted labels on a sample-by-sample basis. When determining the overall classifier performance for detecting annotated seizure events, the true positives were defined as positive classifications that occurred within 3 seconds following a clinician-annotated label. False positives were similarly defined as positive classifications that were not associated with a clinician-annotated label in the 3 seconds prior to classification. The metrics calculated for determining overall classifier performance were precision, recall and FFor each dataset the classifier threshold for the device was selected from examination of the corresponding ROC curve in the OxCAT workflow. This was done in a patient-specific manner due to signal levels between patients varying as a result of interpatient variability. To meet the need for accurate seizure counting when implementing the system as a seizure burden monitor, we biased selection of an appropriate threshold to maximize classifier true positives, while minimizing classifier false positives. To this end, patient 1 was selected to have a threshold of 26.7 μV, while patient 2 was selected to have a threshold of 4.2 μV. For both classifier implementations the debounce period for stimulation state transitions on the device was fixed at 2 seconds, i.e. the minimum duration between successive classifications.Fin vitro test setup, designed to evaluate the performance of an implantable aDBS device in an environment that is representative of in vivo use cases. The test-bench is made from two main elements: 1) The saline tank: which is made using an electrophoresis system filled with a 0.9% saline solution that the investigated device was submerged in during testing. Using the saline solution allowed the test-bench to emulate the charge distribution of stimulation artifacts. Furthermore, this setup allows testing of the saline-electrode interface, which is similar to the tissue-electrode interface in vivo, and its effects on the sensing and stimulation performance of aDBS devices. 2) The NeuroTest board: a custom made hardware designed to test the performance of aDBS devices. The NeuroTest board has two main functions. a) NeuroTest-DAC: a two channel arbitrary voltage signal generator that can generate signals with a large dynamic range between 1 μV–1V (RMS). This allows the NeuroTest-DAC to replay prerecorded biopotential signals with amplitudes representative of real signals recorded in vivo. b) NeuroTest-DAQ: a two channel data acquisition system with a 24-bit resolution, with a noise floor of 1 μV RMS at 1 kHz bandwidth, and a configurable sampling frequency from 1 kHz to 16 kHz. During testing, an aDBS–configured device can be placed in the center of the saline tank with the DBS electrodes placed on either side of the device case. Reference DBS electrodes connected to the NeuroTest-DAQ are placed in parallel and in close proximity with the aDBS device electrodes under test. These reference electrodes are used to record the activity in the saline tank to evaluate the performance of the aDBS device. Finally, the NeuroTest-DAC is used to inject prerecorded biopotential signals across the saline tank for in vitro device testing. The NeuroTest has the ability to run a test and record the performance over 24 hours. This allows researchers and engineers to test their aDBS systems and algorithms for a duration that mimics real world use-cases. in vitro test bench setup.The adaptive DBS (aDBS) test-bench is a configurable Gin vitro. During the in vitro test only the patient 1 dataset was selected as it contained the highest number of seizure events. After selecting the required classifier settings for patient 1 using the OxCAT workflow, the DyNeuMo Mk-2 was setup to act in seizure monitoring mode. To enable the seizure monitoring mode the DyNeuMo Mk-2 adaptive DBS mode was required. This was set as follows: 1) by uploading the classifier configuration YAML file to the DyNeuMo Mk-2 and 2) setting the stimulation programs; one for event and a second for non-events. For seizure diary mode both event and non-event stimulation programs should be set to the same settings. The DyNeuMo Mk-2 then logs each time there is a transition between event and non-event stimulation programs within a few seconds resolution. This ensures that the device is not changing the therapy for patients at this stage and only acting as an embedded seizure burden monitor. However, to assess the performance of the device in vitro, the DyNeuMo Mk-2 was set to perform in full adaptive mode, by setting two different stimulation programs with different current amplitudes. This makes testing the system performance easier by detecting the different stimulation levels in the test-bench, using the reference electrodes connected to NeuroTest board. The stimulation programs used during the test were 1) non-event program (P0): 1mA, 125 Hz, 90 μs, active recharge; 2) event program (P1): 3mA, 125 Hz, 90 μs active recharge.The DyNeuMo Mk-2 was configured to prototype the embedded seizure burden monitor proof-of-concept IIIA1 score of 86.1% and 88.0% for patients 1 and 2, respectively. Additional classifier performance summary statistics are included in Classifiers configured by the OxCAT workflow demonstrated good predicted performance at tracking annotated seizure events. For each patient the classifier threshold was conservatively selected from the respective ROC curve to minimize the false positive rate, B1)in vitro test-bench setup was calibrated to replay the patient 1 data with signal levels within ±5% of original data signal levels when sensed by the DyNeuMo Mk-2 in saline. This was a crucial part of the test as a higher error in the replayed patient signal levels compared to the original dataset will result in a different amount of detected seizure events. The results of the achieved signal levels sensed by the DyNeuMo Mk-2 in the in vitro test-bench setup were comparable to the original signal levels recorded in the band of interest (7 – 15 Hz) for patient 1. These results are summarized in The NeuroTest board and 2)in vitro test of the DyNeuMo Mk-2 achieved a 7.5% higher trigger rate than that estimated by the OxCAT workflow. Also, when compared to the clinician annotated events  power recorded from the subthalamic nucleus has been identified as a biomarker for motor impairment symptoms of the disease [In this paper, we present the DyNeuMo Mk-2 and OxCAT workflow as a configurable system to enable patient-specific seizure detection. The OxCAT algorithm workflow enables flexible configuration of the DyNeuMo device for tracking power-in-band variations in recorded LFP data associated with seizures. The predicted behavior of the device classifier by the OxCAT workflow well-matched that of its  disease . The relAlthough this work provides preliminary evidence that the DyNeuMo device may function well for seizure detection, there are technical limitations of this work that should be highlighted. In relation to the device hardware, the classifier on the device is limited to a two second debounce period. This is to ensure that the device guarantees that patients will receive this minimum duration of clinical stimulation when stimulation on the device is varying. Second, although the DyNeuMo Mk-2 device enables deterministic, time-based feed-forward adjustments to the stimulation and classifier the data presented herein focuses primarily on the implementation of the system for daytime seizure monitoring. Additional data recorded over the entire 24-hour day-night cycle is required to enable classifier implementation for true diurnal configurations of the DyNeuMo Mk-2 device as a seizure monitor, where variations in frequency bands associated with sleep may lead to variation in classifier performance at night-time .In addition to the technical limitations highlighted above there are several outstanding research questions that can affect implementation of the proposed seizure burden monitor. Firstly, the correlation between device-recorded electrographic seizure activity and the occurrence of clinical (patient-experienced) seizures needs to be further investigated. There are a variety of different seizure types and further investigation of how these seizure types relate to the data recorded from deep brain targets should be further assessed to ensure accurate tracking of specified seizure types when the monitor is deployed longitudinally. Furthermore, additional considerations should be taken when the proposed seizure monitor is deployed as part of stimulation therapy. For the presented datasets selection of the classifier threshold was biased to prioritize maximizing true positives for accurate seizure monitoring. In practice, the therapeutic trade-off between true and false positives should be carefully considered when implemented for stimulation therapy. For epilepsy, failure to deliver stimulation during seizure events may lead to worse therapeutic outcomes than falsely providing stimulation during non-seizure periods. In fact, there is increasing evidence that the therapeutic benefits of responsive neurostimulation are provided when stimulation is applied during non-seizure states, rather than seizure states . SimilarThe DyNeuMo Mk-2 has a rolling memory to store up to 1200 events, which is sufficient to record seizures over at least 24 hours for most patients. The DyNeuMo Mk-2 prioritizes critical operations, such as delivering stimulation first, and running the real-time classifier second. Therefore, the system only has a resolution of 1 – 2 second while recording event changes in the user logs (as illustrated in the bottom panel of Finally, the data presented in this first proof of concept is limited. Datasets used for classifier training were historically recorded using externalized DBS leads. For each patient, recordings were limited solely to the hospital period between implantation of the DBS leads and pulse generator. Longitudinal data collection from these patients for further analysis and device testing was thus not possible. The aim of this paper is to demonstrate that the DyNeuMo Mk-2 system is able to detect seizures in the presence of stimulation accurately, and as predicted by the OxCAT workflow, so that it can be deployed as a seizure burden monitor. In the future, the performance of the DyNeuMo Mk-2 classifier must be tested with additional data captured by the device embedded loop recorder.


JAK2V617F being the most prevalent. (2) Methods: using mechanism-based mathematical modeling (MM) of hematopoietic stem cells, mutated hematopoietic stem cells, differentiated blood cells, and immune response along with longitudinal data from the randomized Danish DALIAH trial, we investigate the effect of the treatment of MPNs with interferon-α2 on disease progression. (3) Results: At the population level, the JAK2V617F allele burden is halved every 25 months. At the individual level, MM describes and predicts the JAK2V617F kinetics and leukocyte- and thrombocyte counts over time. The model estimates the patient-specific treatment duration, relapse time, and threshold dose for achieving a good response to treatment. (4) Conclusions: MM in concert with clinical data is an important supplement to understand and predict the disease progression and impact of interventions at the individual level.(1) Background: myeloproliferative neoplasms (MPNs) are slowly developing hematological cancers characterized by few driver mutations, with  DormJAK2V617F allele burden to estimate both treatment duration and outcome for the benefit of the patients. In combination with unique data from a randomized trial, the mechanistic Cancitis model performs well. To our knowledge, such comprehensive data material of MPN patients with frequent serial measurements of cell counts and JAK2V617F allele burden over several years is rare. Earlier, the focus has typically been on population responses rather than individual trajectories that may show significant variations [In the present paper, we show that the Cancitis model may be used in combination with a few initial measurements of the riations ,27,28,29In this section, the data and model predictions are compared. The model predictions are obtained using the validated mechanism-based Cancitis model outlined in JAK2V617F response over time for IFN-treated patients from the DALIAH trial normalized with their respective baseline value. Thus, the effect of treatment will conservatively be compared to the baseline level. Due to drop-out from the study, the number of patients eligible for the analysis is decreasing over time. The longitudinal median values closely follow an exponential decay pattern, with a half-life of 25 months. Stratification by age and treatment dependence is also shown. Boxplots for each study visit in the protocol, scheduled at months 4, 8, 12, 18, 24, and 36, are shown in the figure. Similar investigation for patients staying in the trial until month 36 yields a half-life of 24 months. Likewise, the boxplots for each study visit for patients with ET, PV, and PMF receiving Pegasys or PegIntron and with an age below 60 or above 60 are shown. These figures show a statistically significant reduction in the JAK2V617F allele burden over time during treatment with IFN, despite great inter-variance, especially for patients treated with interferon-α-2b (PegIntron), except for those above 60 year of age receiving PegIntron. Untreated disease development cause exponential increase, which is dampened but not significantly reversed for those above 60 of age receiving PegIntron. The reduction in the JAK2V617F allele burden in response to interferon-α-2a (Pegasys) seems more pronounced than that of PegIntron .First, we investigated the separate effect of varying the parameters in the model, such as death rate, differentiation rate, self-renewal rate, etc. The far most sensitive parameter was the stem cell death rates. The death rate of the malignant stem cells was the single parameter which described the JAK2V617F allele burden data well. JAK2V617F as well as leukocyte and platelet counts over time—using the malignant stem cell death rate as a fitting parameter. The model can account for good responders (top row), defined as decreasing JAK2V617F response during treatment as well as poor responders (bottom row), where an increase in JAK2V617F response occurs during treatment. The response is patient-specific and dose-dependent, thus whether the actual dose is above or below an individual threshold value plays a crucial role. All the patient data and model calibrations are shown in the JAK2V617F data, the model may be used as an individual predictive tool. Including the three first data points during treatment  for calibration gives predictions for the remaining five-year period, as illustrated in At the individual level, the Cancitis model is calibrated to clinical data, as illustrated in The Cancitis model also predicts the overall outcome of the effect of IFN treatment, as illustrated by the inverse Kaplan–Meier plot in The true positive PMR cases increase with time as more data are collected (from 20% to 63%) as the true negative cases decrease (from 59% to 21%). Likewise, the model-derived sensitivity, specificity, and accuracy increase over time as more data are included, see JAK2V617F allele burden and model predictions as more data are included over time. Notice that the difference in medians between the measured and model predictions is negligible and the difference in the percentiles deviates less than 5%, while the medians of the model deviate less than 2.5% from the trial data.Finally, The mechanism-based model is used for estimating the patient-specific threshold value for dosing, separating a good responder from a poor responder as shown in JAK2V617F value is reached after 1.6 years. In contrast, prolonged treatment in the model even with a continued lower dose eliminates the cancer over time.Using the mathematical model to investigate different hypothetical treatment scenarios, such as treatment disruption and prolonged treatment, as illustrated in the two scenarios in JAK2V617F allele burden if treatment is discontinued at any point of visit to the clinic. A prolonged treatment period implies a prolonged relapse time.In the model, the number of malignant stem cell vanishes at year 12 for the patient shown in JAK2V617F allele burden data better than the empirical model presented in [The mechanism-based Cancitis model reproduces and predicts the ented in , and in ented in ,32.JAK2V617F allele burden and leukocyte and platelets counts with previous data—may be sensitive to many unknown factors, causing random fluctuations in data and thus making the comparison uncertain. In our approach, based on a time-series data analysis, the effects of noise are minimized for statistical reasons. Thus, the model gives good estimates for how long time a patient should expect to receive IFN treatment in order to decrease the JAK2V617F allele burden to a specific level, and the accuracy of those estimates increases when going from a prediction based on three observations to one based on four, five, or six. The clinicians could update their estimate at each visit to the clinic, thus improving the treatment strategy as well as informing the patients about the updated estimate. For the patient in We emphasize that clinical practice which relies on comparing the recent data—e.g., the JAK2V617F mutated cells. This may suppress the malignant cells to go below the detection limit.The study shows that IFN normalizes blood cell levels and has a marked effect on the competition of wild-type and JAK2V617F value is reached after 1.6 years. In contrast, prolonged treatment in the model even with a lower dose may eliminate the cancer over time. From JAK2V617F for the group of good responders versus that of the poor responders, we get 16.5 and 18.2, respectively, and the means become 29.7 and 65.2 with standard deviations of 38 and 56, respectively, due to a single outlier (P089). Thus, despite potential differences in the quality of the model fits, there are no statistically significant differences between the two groups. The observed difference in efficacy between PegIntron and Pegasys in favor of PegIntron is of interest. Several mechanisms might be operative. Differences in pharmacokinetics, drug dose, and toxicity profiles may account for the observed differences in the ability of the drugs to decrease the JAK2V617F allele burden. PegIntron is more likely to hydrolyze due to an unstable urethane bond between the pegylated portion and the recombinant IFN molecule compared to Pegasys, which has a more stable amide bond [The mathematical modeling approach allows for the investigation of different hypothetical treatment scenarios—e.g., treatment disruption or prolonged treatment. These two scenarios are illustrated in ide bond . Therefoide bond . WhetherThe unique longitudinal data provided by the randomized DALIAH data are necessary for calibrating reliable mathematical models in relation to blood cancers. In turn, mathematical models (1) provide the means to test whether the IFN treatment mainly affects the malignant stem cell death rate; (2) offer “a microscope” for obtaining continuous measurements over time for the stem cell population, which is currently experimentally inaccessible from mature blood cell counts; (3) offer an efficient methodology for connecting data points over time and predicting the further time course; (4) deliver estimates of patient-specific threshold values for dosing and timing; (5) serve as an additional expert decision tool in the clinic for predicting the treatment outcome; and (6) provide estimates for the duration of the treatment period and dose to obtain a desired molecular residual disease and the relapse time that may follow.JAK2V617F kinetics and response to treatment.Our results are more comprehensive than the previously presented results in ,18, mainJAK2V617F allele burden and to a minor degree in the leukocyte and platelet counts whenever the treatment dose is abruptly changed. In the present case, no other single parameter is able of calibrating the model to the data, thus the malignant stem cell death rate is the single dominating factor. IFN may affect HSC by the loss of quiescence, leading to exhaustion in the long run and hence the loss of self-renewal potential. Neglecting the IFN effect on quiescence in the model may lead to an overestimate of the actual estimated values of the malignant stem cell death rate.It is a limiting factor of our study that the effect of IFN in the Cancitis model is implemented through the increased death rate of malignant stem cells. However, including stem cell differentiation rate also as being affected by the IFN treatment provided similar results, except for small humps in the JAK2V617F) are considered, ignoring the possibility of additional mutations, resistance, and comorbidities, which may be important especially in the long time horizon. The flexible framework of mathematical modelling allows for extensions of the Cancitis model to include additional mutations and drug resistance, which will be addressed in future work. Such extensions of the model are in principle straight forward, but the challenging part is that these extensions introduce additional parameters which have to be estimated, and therefore additional measurements are needed to support that. It is another limitation of the study that only side effects related to the JAK2V617F allele burden or leukocyte and thrombocyte counts are considered—i.e., we only discuss normal and elevated levels of these in our modeling attempt and do not include indirect or derived consequences, nor do we include other possible side effects.Furthermore, in the Cancitis model only single malignant clones , as described in  and encoThe Cancitis model has previously been published in , and an In the context of IFN treatment, certain PD parameters need adjustment, as described in the next section. Here, we briefly address how IFN PK is added to the model. IFN is generally administrated weekly by self-injection subcutaneously over a period of years. Thus, we ignore the variation in IFN concentration in blood on a weekly scale and only include changes in doses according to the patient journals. Inspired by , we adop for IFN . The PD The IFN therapy affects the death rate of stem cells but also the differentiation rate. In addition, IFN may activate dormant stem cells and put them in cycle  and may JAK2V617F allele burden of the model agreed with the growth found in [fminsearch function. All the data points during treatment are used to calibrate the treatment effects, and secondly we solely use the first three data points  for the calibration of the treatment effects; based on this, we estimate the development to follow and compare this development with the actual data for JAK2V617F. Information about whether PMR appears in the patient-specific data are compared to the model predictions. A partial molecular response is defined according to the 2013 ELN and IWG-MRT criteria [The Cancitis model described in found in  for the criteria ,41, but JAK2V617F-positive MPN patients from the randomized DALIAH trial, and the model captures MPN patients treated with IFN very well. We demonstrate that the Cancitis model provides novel scientific insights into the underlying hematopoietic dynamics with and without treatment. The Cancitis model captures the pronounced effect of IFN treatment on the JAK2V617F allele burden, as well as on elevated leukocyte and thrombocyte counts. In relation to this, we note the true positive—i.e., the model’s ability to predict the PMR - increase over time. A (inverse) survival plot illustrates the PMR to IFN, which strongly supports the superiority of the Cancitis model to predict the treatment outcome on the population level.The Cancitis model has been validated further on a cohort of The Cancitis model has proven to be potentially helpful in the clinical setting, as it may predict how long treatment has to be continued for good responders. It is important to have as short IFN treatment periods as possible while suppressing the disease or sufficiently limiting the disease burden due to side effects related to IFN therapy. This will not only reduce the discomfort for the patients but also will be more cost-effective. The model may be used to plan how long time a good responder needs treatment to obtain a complete molecular response. It is at least equally important to obtain information as early as possible on whether patients respond favorably or poorly to the IFN therapy both for economical and medical reasons, including the quality of life for patients.


Medical imaging plays an important role in determining the progression of joint damage in rheumatoid arthritis (RA). High resolution peripheral quantitative computed tomography (HR-pQCT) is a sensitive tool capable of evaluating bone microarchitecture and erosions, and 3D rigid image registration can be used to visualize and quantify bone remodeling over time. However, patient motion during image acquisition can cause a “stack shift” artifact resulting in loss of information and reducing the number of erosions that can be analyzed using HR-pQCT. The purpose of this study was to use image registration to improve the number of useable HR-pQCT scans and to apply image-based bone remodeling assessment to the metacarpophalangeal (MCP) joints of RA patients.Ten participants with RA completed HR-pQCT scans of the 2nd and 3rd MCP joints at enrolment to the study and at a 6-month follow-up interval. At 6-months, an additional repeat scan was acquired to evaluate reliability. HR-pQCT images were acquired in three individual 1 cm acquisitions (stacks) with a 25% overlap. We completed analysis first using standard evaluation methods, and second with multi-stack registration. We assessed whether additional erosions could be evaluated after multi-stack registration. Bone remodeling analysis was completed using registration and transformation of baseline and follow-up images. We calculated the bone formation and resorption volume fractions with 6-month follow-up, and same-day repositioning as a negative control.13/57 (23%) of erosions could not be analyzed from raw images due to a stack shift artifact. All erosions could be volumetrically assessed after multi-stack registration. We observed that there was a median bone formation fraction of 2.1% and resorption fraction of 3.8% in RA patients over the course of 6 months. In contrast to the same-day rescan negative control, we observed median bone formation and resorption fractions of 0%.Multi-stack image registration is a useful tool to improve the number of useable scans when analyzing erosions using HR-pQCT. Further, image registration can be used to longitudinally assess bone remodeling. These methods could be implemented in future studies to provide important pathophysiological information on the progression of bone damage. Rheumatoid arthritis (RA) is a chronic, inflammatory, autoimmune disease that affects peripheral joints, such as the metacarpophalangeal (MCP) joints of the hands. In RA, pro-inflammatory cytokines and disease-specific autoantibodies stimulate an increase in osteoclast activity, resulting in local bone resorption and an imbalance in local bone remodeling –3. This While other imaging modalities such as ultrasound, magnetic resonance imaging, and conventional radiography are more common for imaging hand RA, they are unable to detect small erosions due to their low spatial resolution. High-resolution peripheral quantitative computed tomography (HR-pQCT) is a sensitive tool capable of imaging bone microarchitecture, bone density, and erosion size and number with high precision –7. The hThe standardized scan acquisition protocol for MCP joints of the hand using HR-pQCT to evaluate and quantify joint changes in RA was designed with the primary purpose of quantifying joint space . While tAs well as measuring erosion presence and volume in a single scan, rigid 3D image registration is a technique that can be used to visualize and quantify longitudinal changes in erosion size and shape by monitoring changes in cortical and trabecular bone . TrackinThe purpose of this study was to use 3D rigid image registration to reduce the impact of stack artifact on visualization and quantification of bone changes in the HR-pQCT images of the MCP joints of patients with RA. We propose a new HR-pQCT scanning protocol for the 2nd and 3rd MCP joints and a semi-automated image registration method to align the stacks and reduce the impact of stack shift artifact. This in turn allows for a more robust method to longitudinally assess bone erosions and bone remodeling. Further, we applied a 3D longitudinal image registration and bone remodeling analysis technique and adapted it to the higher resolution second generation HR-pQCT scanner. The sensitivity of these analyses to motion and interpolation method were evaluated. These image registration techniques could be important tools in analyzing bone changes over time as seen on HR-pQCT for patients with RA.Ten participants with RA in physician-classified remission were recruited using the Rheum4U platform  from theHR-pQCT scans of the 2nd and 3rd MCP joints of the participants’ hand were acquired  at baseline and at a 6-month follow-up. Quality control scans were performed daily using a phantom with rods of known density. A same-day repeat scan after repositioning was obtained at the follow-up visit. The hand was secured in a custom positioning device and used an adaptation of an established protocol  to reducThe proximal, middle, and distal stacks of the 2nd and 3rd MCP joints were registered in order to achieve optimal alignment. Each stack was registered using the 25% overlap of the previous stack. The registration was initialized using the mass centers and moment of inertia to give an estimate of the new orientation. Once the registration was initialized, the proximal stack was registered to the middle stack using a simplex optimization to determine rigid transformation parameters by maximizing the correlation coefficient. The proximal stack was then transformed to the middle stack image space using a cubic interpolator. The same procedure was followed to register the distal stack to the middle stack. Masks of the overlapped regions were created and used to remove the common regions with the middle stack from the distal and proximal stacks. Finally, the transformed proximal and distal stacks (excluding the overlapped region) were concatenated to the middle stack (including the overlapped region) creating an image of the three stacks optimally aligned. The final image of the joint includes the proximal and distal stacks registered, transformed, and aligned with the middle stack to give the appearance of contiguous bone, with the stack shift artifact eliminated Fig. .Fig. 1AIn order to investigate bone damage and healing phenomena in RA, longitudinal 3D rigid body image registration was implemented to align and superimpose the follow-up image with the baseline image. The first step in the image registration workflow was to determine a transformation matrix to rotate and translate the follow-up image to the baseline image space. For the purpose of this registration, the periosteal mask of either the metacarpal or phalange bone was dilated and then used to crop the desired bone, with a 5-voxel border of background. From there, the center of mass and moment of inertia was used to initialize the registration. This rigid registration used a simplex optimizer approach and a correlation object function to iteratively find the optimal fit between the follow-up and the baseline image. The transformation matrix was then applied to the follow-up image to create a translated and rotated image that was resampled using cubic interpolation. Finally, the images were masked within the largest common volume (LCV) to exclude any voxels outside the common region.3 so that any voxels above this threshold would represent bone resorption. The baseline image was subtracted from the follow-up image and then segmented so that any voxels greater than the threshold value of 125 mgHA/cm3 would represent bone formation. To eliminate noise from the difference image, a connected components filter was then applied so that clusters of voxels connected by fewer than 5 voxels were removed from the image. These segmented regions of bone loss and bone gain were then overlaid with the segmented baseline scan to create a comprehensive image depicting bone loss and bone gain  image to the baseline (fixed) image, the moving image was transformed to the fixed image space. Following this transformation, cubic interpolation was performed to realign the moving image to the fixed image’s coordinate system. Image interpolation can be seen as a linear convolution with a low-pass filter, and therefore, may have an effect on bone morphometric analysis , 24. To Descriptive statistics were used to observe if there were any improvements in the number of erosions that could be analyzed with multi-stack registration, compared to scans without multi-stack registration. Kruskal-Wallis tests were used as a non-parametric method to compare the differences in bone formation and resorption fraction across different motion grades against an alpha value of 0.05. A Wilcoxon signed rank test was used to compare the difference in bone formation and resorption fraction between registrations with only the moving image interpolated compared to registrations where both scans undergo interpolation against an alpha value of 0.05. Results are reported as median  unless otherwise stated. Analysis was completed using R (v3.4.3) in RStudio (v1.1.423).Fifteen joints from 8 participants were analyzed for erosions both using multi-stack registration and without. Two participants were excluded due to motion or acquisition errors preventing successful multi-stack registration at either baseline or follow-up, and an additional joint was excluded due to inaccurate registration. Of the 57 erosions analyzed from baseline and follow-up combined, 13 erosions (23%) could not be analyzed from raw images due to a stack shift artifact. These erosions crossing stack boundaries were present in 8 of the 15 joints (53%). The erosions could be volumetrically assessed after stack registration .Of the 15 joints that were aligned successfully with multi-stack registration, 9 joints from 5 participants were included in bone remodeling analysis as 6 joints did not meet our motion scoring criteria for quantitative assessment, despite having the stacks successfully aligned. Based on visual inspection, multi-stack registration improved our ability to perform longitudinal registration to assess bone remodeling Fig. . The medp < 0.05). There was no significant difference (p > 0.05) in bone formation fraction with an increasing motion score from 2 to 3 (0.0% (IQR 0.0–0.4%) and 0.0% (IQR 0.0–0.6%) respectively) or bone resorption fraction with an increasing motion score from 2 to 3 (0.0% (IQR 0.0–0.8%) and 0.1% (IQR 0.0–1.2%) , while the mean bone resorption was 0.0% (IQR 0.0–0.9%). The differences between the 6-month longitudinal bone formation and resorption fractions with the negative control fractions were statistically significant p < 0.0. There wp > 0.05).Scan-rescan analysis was also performed with a cubic interpolator applied to both the fixed and moving image rather than just the moving image with the intention of analyzing the effects of interpolation on the bone remodeling analysis. There were no significant differences found for either bone formation or bone resorption when comparing this interpolation method with interpolation of the moving image only  of images had to be excluded from erosion analysis due to stack shift artifact that crossed through the middle of an erosion . FurtherWhile multi-stack registration reduces the impact of the stack artifact and improves longitudinal image registration to assess bone remodeling, motion artifact still has an impact on the quantitative analysis of bone remodeling. Although it was not significant, we observed that low quality images of the MCP joints with higher motion grades led to a trend towards higher bone formation and resorption volumes compared with images with a higher quality and lower motion grades. This trend was also observed in a previous study using a similar bone remodeling analysis method on the radius and tibia on the first generation HR-pQCT scanner . This suWe also explored whether applying interpolation to both fixed and moving images decreased the interpolation error to an extent that it impacted bone remodeling volume fraction. The application of a transformation matrix to the moving image results in errors caused by image interpolation which may have an impact on longitudinal bone analysis . HoweverScan-rescan analysis was also completed to act as a negative control. There was a significant difference in the bone formation and resorption fractions between the 6-month longitudinal and negative control, indicating that the changes observed in formation and resorption were due to actual bone changes, rather than image noise and patient repositioning. Part of the challenge for scan-rescan analysis of bone remodeling may be due to the absence of scans with a motion score of 1 . As a result, the scan-rescan bone remodeling volume fractions may have been overestimated when compared to the longitudinal analysis based on the lack of any extremely high-quality scans. While variations in x-ray tube or detector functioning can affect the density values used to perform bone remodelling analysis, the fluctuations recorded on the daily quality control scans were very small relative to the differences detected over the 6-month follow-up period.There are some limitations associated with the multi-stack image registration technique. First, the acquisition of 3 separate stacks can be challenging for the operator and participant. As an overlapping acquisition protocol has not been implemented by the manufacturer, each stack must be acquired individually rather than contiguously. This results in a longer acquisition time, as well as the scanner stopping and starting between stacks, which could potentially lead to even more movement. This may also explain why there was such a large proportion of scans that would have had to be excluded without the registration of stacks as the noticeable breaks between stack acquisition are not present in the standard protocol. Further, this technique does not eliminate motion artifact, as the reconstruction of each stack takes into account the average position of each stack. When there is motion within a stack, this can impact the scan in a way that cannot be corrected by this image registration technique. While the current study improved the number of scans that could be analyzed, only 9 out of 20 joints (45%) met the criteria to be included in the longitudinal analysis. There were 4 joints that could not be analyzed due to acquisition error or motion that prevented successful multi-stack registration, 1 joint that failed stack registration despite appropriate motion scores, and 6 joints that successfully had the stacks aligned, but were excluded since they did not meet our motion criteria. Despite the benefits of the multi-stack registration, motion artifact still presents a major limitation when analyzing HR-pQCT scans of the MCP joints. Future investigations should build upon this work to reduce the impact motion artifact has on these scans.3 presented in previous work [3) after several tests that appeared to give the best depiction of bone change. This may be because the previous work was done on the radius and tibia, on the first-generation HR-pQCT scanner with lower spatial resolution, which may have different thresholds of change than the MCP joints analyzed in the current study. This new threshold should be validated using cadaveric samples to ensure that the change being visualized is due to real bone change and not noise.There are also limitations associated with the bone remodeling analysis method used in this study. First, the threshold value of 225 mgHA/cmous work , 18 was The multi-stack image registration technique proposed in this study could be a valuable tool to improve the utilization of HR-pQCT scans for the research of bone changes in RA. Improving the number of useable scans will be instrumental in furthering the use of HR-pQCT to study bone changes in RA. Further, 3D longitudinal image registration can be applied to second generation HR-pQCT scans to visualize and quantify bone changes at a higher resolution, over a relatively short time period (6-months) without the need for a bone biopsy.Multi-stack imaging can be used to increase coverage of HR-pQCT scans. The multi-stack registration tool presented here is useful to decrease the effects of motion on multi-stacks. This tool can improve the number of useable scans when analyzing erosions and other pathological defects, as well as to longitudinally assess bone remodeling in larger regions of interest. These methods could be implemented in future studies to provide important pathophysiological information on the progression of bone damage.Additional file 1.


Mental disorders in children and adolescents have an impact on educational attainment.To examine the temporal association between attainment in education and subsequent diagnosis of depression or self-harm in the teenage years.General practitioner, hospital and education records of young people in Wales between 1999 and 2014 were linked and analysed using Cox regression.Linked records were available for 652 903 young people and of these 33 498 (5.1%) developed depression and 15 946 (2.4%) self-harmed after the age of 12 but before the age of 20. Young people who developed depression over the study period were more likely to have achieved key stage 1 (age 7 years) but not key stage 2 (age 11) (hazard ratio (HR) = 0.79, 95% CI 0.74–0.84) milestones, indicating that they were declining in academic attainment during primary school. Conversely, those who self-harmed were achieving as well as those who did not self-harm in primary school, but showed a severe decline in their attainment during secondary school .Long-term declining educational attainment in primary and secondary school was associated with development of depression in the teenage years. Self-harm was associated with declining educational attainment during secondary school only. Incorporating information on academic decline with other known risk factors for depression/self-harm  may improve risk profiling methods. For early identification and prevention strategies to be effective they need to be informed by an understanding of how the disorder first develops. Although it is recognised that mental health disorders involve multiple causal factors , several studies have identified low levels of educational attainment as an important association with depression and self-harm during childhood and adolescence.,http://www.farrinstitute.org/). For each data-set within the SAIL databank, an individual is assigned an anonymised linking field (ALF_E), based on their names, addresses or National Health Service (NHS) numbers, which is employed to link across data-sets. All data within the SAIL gateway is treated in accordance with the Data Protection Act 1998. To date, the SAIL databank incorporates over 10 billion records from multiple health and social care events and at the time of analysis, received data from 70% (328/468) of the general practitioner (GP) practices in Wales and all hospital admissions. The education database is available for all children in school between the years 2005 and 2014. Therefore, the study population consisted of children with a GP record  and linkage to the educational data-set (for example children of school age between the years 2005 and 2014).The population we selected from consisted of all children and young people (aged 5–20) born or living in Wales who had at least 1 year in education at school in Wales between the years 1990 to 2014. Education records were linked with mortality data, hospital admissions data and general practice records. The linkage and hosting of this data were through the SAIL (Secure Anonymised Information Linkage) databank.,https://doi.org/10.1192/bjp.2017.96 for the Read codes and ICD-10 codes used to identify diagnosis).The SAIL databank was queried using IBM DB2 9.7 SQL. Statistical analyses were conducted using Stata version 13. Exposure was attainment in education at the key stages within the education data-set. Mental health as an outcome was examined through looking at diagnosis and symptom codes for depression and self-harm in GP data in those aged ≥12,The diagnosis of depression included: single or recurrent major depressive episode and symptom codes for depression such as depressed mood. The diagnosis for self-harm included: self-inflicted, intentional codes and injury undetermined intent codes (see Supplementary File 1). Undetermined intent codes are included as this is what is recommended in the literature because of some suicides being recorded as ‘undetermined intent’.Outcomes assessed were time to event between the ages of 12 and 20 in the in-patients' data-set and visits to the GP. Analysis was conducted for each outcome separately  and Cox GP data in the UK are coded using Read codes, which contain some 300 000 codes for symptoms, diagnosis, treatment and management. Data within the hospital admission system are recorded using ICD-10 codes.The study design uses anonymised data and therefore the need for ethical approval was waived by the approving institutional review board. The independent Information Governance Review Panel, which contains members from the UK National Health Service Research Ethics Service, approved the study.There were approximately 1 million children born and subsequently living in Wales between 1 January 1990 and 31 December 2014 . Of these, 829 590 could be linked to the education data-set  that was available for children in school between 2005 and 2014. The education database contains the school attainment results. This data-set contains results for; key stage 1 (KS1) that covers national tests in mathematics and English/Welsh language at age 6/7; key stage 2 (KS2) that covers national tests in the core subjects of mathematics, English/Welsh and science at ages 10/11; key stage 3 (KS3) that covers national tests at ages 13/14, including both core and non-core subjects; and key stage 4 (KS4) that covers a range of subjects at age 15/16.In this linked data-set of 829 590, there were 627 423 (76%) children who were over the age of 5 years  and had at least one result in KS1 through to KS4. An individual was considered to have achieved their key stage if they passed mathematics and English/Welsh to the accepted national curriculum level. If they did not achieve the accepted level in the core subjects (mathematics or language (English/Welsh)) they were assigned an overall ‘not achieved’.v. 3.27%, difference: 4.2%, 95% CI 4.1–4.3) and were more likely to have been prescribed an antidepressant drug   were excluded as we were using educational attainment as the exposure to predict future mental health conditions. Girls were more likely to be diagnosed with depression than boys (7.49 3.5–3.7) . The cru3.5–3.7) . Adjusti3.5–3.7) . Thus, cDepression is predominantly occurring in the later teenage years and therefore there is a long time lag between poor education attainment in primary school and diagnosis of depression in later adolescence .Table 5There were 15 946 (2.4%) individuals with a record of self-harm in adolescence. In addition, there were 692 excluded who had a record of self-harm in primary school, these children were more often boys. The crude hazard ratio (HR) of demonstrating self-harm behaviours (years of follow up 11 467 479) if not achieving KS2 (age 11) was 1.38 (95% CI 1.31–1.43) and the adjusted HR was 1.03 (95% CI 0.94–1.12) . HoweverThis study found that the association between educational attainment and depression may differ from the association seen with self-harm. The young people who went on to receive a diagnosis of depression/symptoms of depression were already declining in educational attainment at school for a number of years before the diagnosis was made. The peak period of incidence for depression in this study was 18–19 years but a decline in academic attainment was apparent from primary school and through secondary school .However, among those who self-harm there was no evidence of a decline in educational attainment in primary school. In fact, the children who self-harmed in the teenage years were improving in primary school, being less likely to achieve at age 7 (HR=1.17) but just as able at age 11 as those who do not self-harm. The young people who self-harm started declining in education attainment in secondary school almost concurrently with their self-harming behaviour, for example the peak time of self-harm behaviour was aged 15  and thisA survey of 12- to 15-year-olds in school in Australia and the USA found self-harming behaviour to be particularly related to late or completed puberty, girls and self-cutting.,,–The study results suggest a temporal association between academic attainment and subsequent depression in children and young people. In addition, our study data raises the possibility that depression symptoms and low mood are being missed in primary school, possibly because the adults around them are not recognising their depressive symptoms. Indeed, epidemiological cohort studies illustrate that most depression goes unrecognised and untreated in young people despite the fact that rapid early specialist treatment ameliorates later outcomes.This study has important implications suggesting declining academic attainment may be an indicator that interventions aimed at emotional and social development could improve and potentially reduce the development of future mental health problems. Depression occurs through multiple pathways and one route is the ‘failure’ route whereby social and academic problems affect an individual's self-perceptions and increase vulnerability to depression.This study is novel in bringing together education data and health data on a national level to give a large sample that can look at the temporal relationship between academic attainment and depression, and provides a longitudinal cohort of real-world observational data. However, it must be recognised that data was not collected originally for research and this means diagnosis and data collection is not consistent in all periods of time and across all areas. Differences in coding with time and with GP practice will affect prevalence levels of outcomes and confounders with time. Healthcare and education standards change with time, and these changes are not reflected or accounted for in these results. For example, recent changes in mental health awareness and provision of school counsellors in the UK and other interventions will mean children in secondary school in 2014 will have a different experience from those in secondary school in the mid-1990s. This is an observational study and as such the findings would need to be repeated in other populations to confirm validity and repeatability. Importantly, this study did not examine undiagnosed depression or self-harm and so the findings are only relevant to those who present at services with depression or self-harm. This raises an obvious limitation in terms of predicting future events using only diagnosed disease when it is known that the majority of depression in childhood/adolescence is untreated and undiagnosed. Therefore, the strength of the association of decline in educational attainment at school and depression may be underestimated with this study.In addition, this study does not attempt to look at the severity or length of time a person has depression or have been self-harming. We did not examine how severe the depression is that is associated with educational decline. We did not impute missing data for educational attainment as the available data did not give good estimates of attainment because the data known to be good predictors of child attainment, such as maternal education and mobility, were unavailable. The data-set we were using was large, comprising over 800 000 children and adolescents and it was therefore assumed that the majority of data was missing at random (for example living in England at time of exam) and so we have made the assumption that excluding those with missing education data will not bias the findings. The results of the current study reflect presentation to primary care, recognition by GPs and the way in which depression and self-harm in children and young people is recorded in primary care. However, this is likely to be an underestimation since routine data does not capture individuals with whom depression or self-harm is discussed, but not recorded. This is common feature of all routinely collected database studies.Finally, children born in the early 1990s will not have their key stage 1 (age 7) and key stage 2 (age 11) records included in the educational data-set, which only started in 2005. Their data will not be included in analysis looking at key stage 1 and 2 but their data will be included in analysis looking at a later key stage where data is captured. Therefore, the later key stage analysis will contain a different mix of children compared with the earlier key stage analysis.In summary, impaired academic performance precedes overt clinical symptoms of depression. The findings from this study show that this decline may be seen as early as primary school and imply that preventing these children becoming disengaged from the educational system may be critical in modifying the development of mental disorder and, perhaps economic inactivity.


Von Hippel-Lindau (VHL) disease is an inherited syndrome manifested as a benign and malignant tumor. It is an autosomal dominant syndrome diagnosed approximately in 1 in 36,000 people.We report a case where male siblings presented with the involvement of bilateral kidneys and the multi-cystic lesion on the pancreas in both. Reverse transcription polymerase chain reaction (RT-PCR) was conducted to detect the VHL gene, which turned out to be a significant finding in our study. The rare involvement of both pancreas and kidneys was noted in the siblings with VHL in the present study.In patients with VHL-associated tumour presentations, the most frequent detection of pathogenic variants in the VHL gene is the result of directed genetic testing or inherited cancer gene panels. The presence of renal and pancreatic involvement is rare but a significant finding present within the family member who needs to be screened. Von Hippel-Lindau (VHL) syndrome is an inherited syndrome manifested as a benign and malignant tumor. It is an autosomal dominant syndrome diagnosed approximately in 1 in 36,000 people . The speA 32-year-old male presented with a history of fever and abdominal pain particularly over the epigastric region. On examination, a palpable lump was appreciated in the epigastric region. On further examination, it was found that subtle hematuria was present on urine analysis, and the presence of hypertension was detected on physical examination. The patient was subjected to further radiological evaluations. The abdominal ultrasonography (USG) and CT were performed. They showed a significant disease extensive with a multitude of pancreatic cystic lesions. The largest measured 12.6x11.8x11.7 cm noted with few septations showing the focal calcification in the body of pancreas Figure , 1B. TheVHL gene is mapped to chromosome 3p25 and was cloned in the year 1990s, with further research into the knowledge about the gene function extending over the next twenty years. The VHL gene products function as a tumor suppressor protein [Data conflict with the link of particular germline mutations and the occurrence of renal cell carcinoma. For example, according to the analysis, the total risk of renal cell carcinoma in 138 families with VHL disease was comparable in those with significant deletions and mutations in the VHL gene relative to those with missense mutations . On the In patients with VHL-associated tumour presentations, the most frequent detection of pathogenic variants in the VHL gene is the result of directed genetic testing or inherited cancer gene panels. The American College of Medical Genetics and Genomics (ACMG) publishes guidelines for disclosing incidental findings (now referred to as secondary findings) while conducting complete exome or genome sequencing -7.Families with VHL have been divided into type 1 and 2 based on the likelihood of developing pheochromocytoma. Type 1 disease has a lower risk of developing pheochromocytomas (type 1A) and also a lower risk of pheochromocytomas and RCC (type 1B). Whereas type 2 disease has a higher risk for developing pheochromocytoma. The type 2A and 2B families have a low and higher risk of RCC, respectively, in them. However, type 2C are characterised by the development of pheochromocytomas only with no evidence of RCC or hemangioblastoma in them . PancreaSurveillance protocols focus on hemangioblastomas , RCCs, pheochromocytomas, and audiology, given the increased risk of endolymphatic sac tumors (ELST) in patients with VHL. Surveillance recommendations may need to be adapted to the individual patient, taking into account the patient’s current or prior tumor diagnoses. However, all individuals with VHL, even if currently asymptomatic, should understand that they may develop manifestations of VHL disease and will benefit from following surveillance guidelines. Several organisations have revised surveillance protocols for contemporary imaging and laboratory diagnostic approaches. The International Committee of Clinicians Caring for Children with VHL was assembled in 2016 as part of the American Association for Cancer Research (AACR) Childhood Cancer Predisposition Workshop. The panel reviewed both the American and European VHL regimens and issued surveillance guidelines, including enhanced strength and early initiation (Table In this case, however, the diagnosis of VHL was done by contrast-enhanced computed tomography and was subsequently confirmed by RT-PCR amplification.VHL continues for the entire course of life. Patients should be screened for tumours and cysts that develop at different sites along with suitable intervention whenever required. Patients with VHL suffer from trouble caused by multiple tumours and cysts involving various organs, most commonly, brain, kidney, and pancreas. A bright prospect for this disease is the innovation of molecular targeting anti-angiogenic drugs in the future. Patients must be cared for by well-trained specialists throughout their lives to improve the prognosis caused by the above-mentioned conditions.


This work combines single cell Raman spectroscopy (RS) with group and basis restricted non-negative matrix factorisation (GBR-NMF) to identify individual biochemical changes associated with radiation exposure in three human cancer cell lines. The cell lines analysed were derived from lung (H460), breast (MCF7) and prostate (LNCaP) tissue and are known to display varying degrees of radio sensitivity due to the inherent properties of each cell type. The GBR-NMF approach involves the deconstruction of Raman spectra into component biochemical bases using a library of Raman spectra of known biochemicals present in the cells. Subsequently, scores are obtained on each of these bases which can be directly correlated with the contribution of each chemical to the overall Raman spectrum. We validated GBR-NMF through the correlation of GBR-NMF-derived glycogen scores with scores that were previously observed using principal component analysis (PCA). Phosphatidylcholine, glucose, arginine and asparagine showed a distinct differential score pattern between radio-resistant and radio-sensitive cell types. In summary, the GBR-NMF approach allows for the monitoring of individual biochemical radiation-response dynamics previously unattainable with more traditional PCA-based approaches. Altered cellular metabolism is a hallmark of tumour cells4 and a contributing factor in tumour cell resistance to both radiation therapy and anti-cancer drugs. This has created significant interest in the development of more personalised and effective methods of radiation treatment delivery. To develop treatment plans which are specific to tumour type and environment, a better understanding of the radiation-induced biochemical changes which take place within the tumour environment is required.It is estimated that radiation therapy (RT) is used to treat 6. In this study, three human tumour cell lines were irradiated and analysed using RS. The cells were derived from human lung (H460), breast (MCF7) and prostate (LNCaP) tumour cell lines. Previous studies have shown that both MCF7 and H460 cells display a radiation-induced accumulation of glycogen which is correlated with radiation resistance7. The metabolism of glycogen involves an array of complex signalling pathways, many of which can be directly related to tumour progression12. Increase in glycogen content within tumour cells post radiation treatment is thought to provide metabolic precursors which protect against hypoxia and other forms of stress13.Raman spectroscopy (RS) is a non-invasive, label-free optical spectroscopic technique which can be used to obtain spectral information pertaining to the biochemicals present in live cells both pre and post radiation treatment. As a result, specific radiation induced responses can be monitored within a given cell population and potential therapeutic targets identified7 identified metformin, a drug widely used to treat type-2 diabetes, as a potential candidate for use in combination with radiation therapy. Specifically, 5 mM metformin was shown to reverse the glycogen accumulation observed in MCF7 breast cancer cells after treatment with small doses of radiation. As a result, the previously radio-resistant cells displayed enhanced levels of radio-sensitivity. These results support the possibility that manipulation of metabolic pathways could provide a therapeutic strategy to enhance sensitivity to RT.Identifying metabolites which are associated with tumour progression and treatment resistance enable the development of more personalised, cancer-specific treatment options. Matthews et al.14.In much of the literature exploring radiation response using RS, principal component analysis (PCA) has been used as the primary data analytic tool. The main drawback of using dimensionality reducing techniques such as PCA in combination with RS is the difficulty often encountered when interpreting the relationship between positive and negative attributes of principal components and how these can be correlated with individual biochemical responses within cells and tumours. Aside from the drawbacks of PCA allowing components to assume negative values, which is an incorrect representation of spectroscopic data, there is also a constraint of orthogonality within the principal components, which can restrict our interpretation of the features which are responsible for the variance within the dataset. Additionally, principal components are often combinations of spectral features relating to multiple cellular bio-components which can confound identification of specific biochemicals15 to provide an additive, parts-based representation of a non-negative data matrix. A data matrix 16, the We therefore report an alternate approach, wherein a variant of non-negative matrix factorisation (NMF) is used to identify radiation induced responses specific to a known library of chemical bases. NMF was originally developed by Lee and Seung17. Biochemicals which are not represented by the constrained bases, should be accounted for in the unconstrained component of the model. Spectra can be added or removed to the model, dependent on the biochemical make up of the samples and components which may be of particular interest. Raman spectra for each cell line, acquired subsequent to treatment with clinically relevant doses of ionising radiation (2–10 Gy) and 0 Gy controls, on days 1–3 post treatment were the input data. The GBR-NMF model then produced scores on each of the 30 biochemical bases spectra, for each cell type, under each condition described above. The scores obtained are similar in nature to PCA scores, which correlate how much a sample spectrum can be described by the positive and negative features of the principal component output by the model19. However, as GBR-NMF is a semi-supervised approach, the scores obtained correlate directly with the contributions of the biochemical bases to the sample spectrum. These scores allow us to identify biochemical score patterns (expression dynamics) with respect to the conditions under which the initial input data was obtained—for example: cell type, radiation dose, time post radiation treatment.In this model, a library consisting of 30 Raman spectra of the biochemicals  is a supervised learning method which can be used for classification or regression. Random forests are generated by constructing a large number of decision trees, which when their predictions are systematically combined have strong predictive power21. An advantage of this type of machine learning is that it allows us to measure the importance of the features in the model based on the classifications provided and the success of the classification23. There are two main ways that this is often measured in classification RF: mean decrease accuracy (MDA) and mean node impurity (MNI). MDA measures the decrease in accuracy of the model when the observations on the variable in question are randomly permuted. The greater the decrease in accuracy due to the permuting of each variable, the greater the importance of that variable in correctly classifying the data. In our applications, the MDA and MNI measures provided very similar results, and so we will only discuss MDA in this work. Combining GBR-NMF with RF allows us to discern the important biochemicals which contribute to the classification of the three cell types, H460, MCF7 and LNCaP, as radio-sensitive or radio-resistant.The GBR-NMF model produces scores on biochemicals which can also be used in conjunction with other machine learning techniques. Random forest6. Each cell line was exposed to single fractions of 0, 2, 4, 6, 8 and 10 Gy radiation. Single cell Raman spectra were obtained on days 1, 2 and 3 post-irradiation, as described by Matthews et al.7 Prior to GBR-NMF, PCA was carried out on the entire data set, wherein the first principal component (PC1) very closely resembled that of a pure glycogen spectrum  and non-small cell lung tumour cell line (H460). A human prostate tumour cell line (LNCaP) was also examined as this cell line is known to be radio-sensitive7 have previously shown that both radio-resistant cell lines (MCF7 and H460) show a trend pertaining to increased glycogen accumulation with respect to radiation dose received. The H460 and MCF7 cell line displayed a statistically significant  and radio-sensitive (LNCaP). The data was randomly split into a training set  and a testing set . The resultant MDA values for each of the 31 variables  are shown in Fig Analysis of the MDA of each variable revealed phosphatidylcholine to be the most important variable in correctly classifying the data as radiation resistant or radiation sensitive. This was unexpected as PCA analysis had shown glycogen to be a major biochemical which showed distinctly different expression patterns between radiation resistant and radiation sensitive cell types. However, it is shown in Fig The GBR-NMF approach also allows us to visualise possible relationships between the input chemicals, for example, glucose and glycogen. The scores for each cell line, H460 (pink), MCF7 (yellow) and LNCaP (blue) from the ten most important chemicals  staining for metabolic enzymes, which is both time consuming and can often be subjective27. Another advantage of the GBR-NMF method is the distinct absence of negative features in the bases spectra, which can often be a problem when analysing PCA score trends relating to PCs with both positive and negative features. Additionally, as the model is semi-supervised and therefore each base is constrained to contain only one chemical spectrum, score trends can be directly related to the input chemical base. This is not often the case when PCA modelling is used as PCs often contain spectral features from multiple biochemicals, again making interpretation difficult and subjective18.We have demonstrated, as proof of concept, the capabilities of a GBR-NMF model using a spectral library of 30 biochemicals as a method of identifying radiation response profiles across three different cancerous cell lines. Previously discovered PCA-based trends in glycogen expression due to radiation exposure were replicated using the GBR-NMF model. Matthews et al.28. Although not an entirely linear relationship, both H460 and MCF7 cells displayed decreasing glucose scores as glycogen scores increased, a pattern not observed for LNCaP cells. It is to be expected that glucose content would decrease with increasing glycogen content as glycogen is a polymer of glucose residues linked together by 29 and in several recent studies31. The difference in mean glucose scores in the 0 Gy controls across the three cell types could be due to many factors including cell type32 and aggressiveness of proliferation rates33.Glucose and glycogen scores were plotted for all three cell lines for unirradiated controls and doses 2–10 Gy on days 1, 2 and 3 post irradiation. The relationship between glucose and glycogen scores were as expected for each cell line34. This finding is supported by multiple theories which suggest the re-programming of lipid metabolism as an important feature in promoting malignant growth of cells37. Previous work in our group has used standard NMF algorithms to identify lipid like spectra as factors which displayed unique score patterns with respect to radio-sensitivity and dose of radiation received38. By constraining the bases in the Each of the biochemicals listed in Table 40. The reason for the differences in score plots for H460 and LNCaP cells can likely be attributed to the presence of various other spectral features within PC2  and MCF7 (day 1–3) cells exhibited a significant decrease in citric acid score compared with unirradiated controls on the same day. This finding implies that the radio-resistant cell types (H460 and MCF7) displayed a different pattern in mean score of citric acid when compared with radio-sensitive LNCaP cells. More recently, there has been significant interest in the citric acid cycle (TCA) and its potential as a therapeutic target for certain types of cancersAs with asparagine, H460 cells were the only cell type to display a significant change in lactose score for all doses (2–10 Gy) when compared with unirradiated controls on the same day post treatment. Lactose was identified as an important variable in distinguishing between the three cell types using unirradiated controls. Therefore, it is possible that high lactose content is inherent to H460 cells, irrespective of radiation, however there appears to be a relationship with mean lactose score and radiation dose received by H460 cells . Identification of radiation induced metabolic processes, which may ultimately lead to radio-resistance within certain cell types, has the potential to aid in the development of new combination therapies wherein radio-sensitising drugs can be used alongside radiation treatment and ultimately lead to better outcomes for patients undergoing radiation therapy.7. All media components were purchased from Hyclone Laboratories Inc..H460 (ATCC# HTB-177), MCF7(ATCC# HTB-22) and LNCaP (ATCC# CRL-1740) cells were obtained as stock solutions from American Type Culture Collection . Cells were cultured as monolayers, at Cells were harvested and equivalent aliquots were incubated for 4 days at an initial cell density determined to achieve 50% confluency at time of irradiation. One hour prior to irradiation, culture media was replaced fresh media . Cell monolayers were irradiated with a single fraction of 6 MV photons from a Varian 21 EX linear accelerator  at a dose rate 6 Gy/minute. Single fractions of 0, 2, 4, 6, 8, and 10 Gy were delivered to 3 cultures per dose.7. Briefly, cells were washed with PBS, harvested with trypsin and centrifuged into a pellet. Pellets were transferred to a 5 mm thick magnesium fluoride window  and allowed to air dry for 5 min before spectral acquisition.Cell preparation for Raman spectral acquisition and processing was performed as described previouslyRaman spectra were acquired from 20 individual cells from each sample (20 spectra per sample at the radiation doses indicated) over 3 days of analysis performed in triplicate for all 3 cell lines. Cells for analysis were chosen at random from the top layer of the cell pellet. Spectral acquisition was performed with an inVia Raman microscope  with a 100X dry objective (Group and basis restricted non-negative matrix factorisation (GBR-NMF) was performed on the spectra in order to decompose the data matrix, mentclass2pt{minimSupplementary Information.


Perisynaptic Schwann cells (PSCs) are specialized, non-myelinating, synaptic glia of the neuromuscular junction (NMJ), that participate in synapse development, function, maintenance, and repair. The study of PSCs has relied on an anatomy-based approach, as the identities of cell-specific PSC molecular markers have remained elusive. This limited approach has precluded our ability to isolate and genetically manipulate PSCs in a cell specific manner. We have identified neuron-glia antigen 2 (NG2) as a unique molecular marker of S100β+ PSCs in skeletal muscle. NG2 is expressed in Schwann cells already associated with the NMJ, indicating that it is a marker of differentiated PSCs. Using a newly generated transgenic mouse in which PSCs are specifically labeled, we show that PSCs have a unique molecular signature that includes genes known to play critical roles in PSCs and synapses. These findings will serve as a springboard for revealing drivers of PSC differentiation and function. The neuromuscular junction (NMJ) is a tripartite synapse comprised of an α-motor neuron (the presynapse), extrafusal muscle fiber (the postsynapse), and specialized synaptic glia called perisynaptic Schwann cells (PSCs) or terminal Schwann cells. Due to its large size and accessibility, extensive research of the NMJ has been essential to the discovery of the fundamental mechanisms that govern synaptic function, including the concepts of neurotransmitter release, quantal transmission, and active zones, among others . LikewisWhile great progress has been made in understanding the cellular and physiological characteristics of PSCs, very little is known about the molecular composition of these cells . This haA growing number of molecular markers that recognize subsets of glial cells throughout the nervous system have been identified . Therefo+) and GFP labeled all Schwann cells (referred herein as S100β-GFP+)  it has been found to be co-expressed with S100β, a classical marker of all Schwann cells, in a subset of glial cells in the developing brain ; 2) publ0β-GFP+)  in skele0β-GFP+) . Based oWe next evaluated whether the S100β-GFP;NG2-dsRed mouse line serves as a reliable model to study PSCs and their roles at NMJs. In healthy young adult muscle, we observed the same number of PSCs at NMJs in the EDL muscle of S100β-GFP and S100β-GFP;NG2-dsRed mice . The morG93A mouse line,  with 100% of NMJs having at least one S100β-GFP+ cell by post-natal day 9  and absence of single labeled NG2-dsRed+ cells at NMJs at every observed developmental time point  analysis. This analysis measures the linear distance between neighboring cells in order to determine the regularity of spacing , quantif+;NG2-dsRed+ PSCs, single-labeled S100β-GFP+ Schwann cells, and single-labeled NG2-dsRed+ cells  to separately isolate double labeled S100β-GFPor cells ) from ju+;NG2-dsRed+ PSCs that were previously shown to be associated with PSCs  and genes previously shown to be enriched (BChE  1) Introduction, last paragraph and Results, first paragraph. The authors may like to comment on whether they are the first group to show NG2 at PSCs and/or how they came up with the idea of combining both S100B and NG2 for their approach to identify PSCs. It would also be useful to comment/speculate the potential function of NG2 and other genes such as Ajap1 in PSCs.We thank the reviewer for pointing out this important omission. This manuscript concerns the discovery of new molecular markers, and we failed to explain in sufficient detail how that discovery was made. We have updated the text to rectify this mistake . We have also expanded the text to include a more detailed discussion of the possible roles of NG2 in NMJ development .2) Results, first paragraph, Figure 1F. The authors use the AChR fragmentation index to assess if NMJ deterioration occurs in their transgenic mouse line. It would be more sensitive and informative by also labeling the presynaptic nerve terminals to check if there is denervation. In addition, it is desirable to examine the quantal contents to confirm if indeed there are no functional deficits at the NMJ in their transgenic mice.+ animals and NG2dsRed+/S100B-GFP+ animals, such as overall health or basic motor capacity . We have also added a sentence that discusses this particular limitation of the study. Additionally, we see no changes in PSC number  between NG2-dsRed+ and NG2-dsRed- animals.We agree with the reviewer that analysis of presynaptic nerve terminals and quantal content would contribute to our analysis here, and we cannot discount the possibility that there are currently unidentified negative consequences of the co-expression of GFP and dsRed in PSCs. Unfortunately, performing these additional analyses would take a great deal of time and resources, and would be difficult to complete in a timely manner as long as COVID-19 restrictions persist. In this revision, we have added that we see no discernible differences between general features of S100B-GFP3) It is unclear about the statement, "we failed to find.… throughout the course of embryonic and postnatal development." But NG2 is expressed at least partially starting from P0 . The authors may also like to comment/speculate on the reason/significance for NG2 expression only for mature differentiated PSCs.We agree with the reviewer that we were unclear in the quoted section of the text. We have updated the text to clarify when NG2 appears in PSCs. Additionally, we included text describing the possible function of NG2 at the NMJ .+;NG2-dsRed+ PSCs from skeletal muscles to analyze the PSC transcriptome. However, it appears that NG2 expresses only in PSCs after birth and in mature PSCs . It is also not known whether denervation after nerve injury and subsequent repair would alter the expression of NG2. If NG2 is downregulated or absent in denervated PSCs, their new probes for PSCs and associated genes might not be able to address the role of PSCs after nerve injury. It would be desirable to perform a relatively straightforward experiment by simply examining NG2 staining after nerve injury. This additional experiment would broaden the applications of using their transgenic line to address a key role of PSCs in synaptic repair in future studies. Otherwise, their approaches would be somewhat limited to studying only the mature PSCs in intact muscles.4) The authors used FACS to isolate S100B-GFPWe agree with the reviewer and have added additional data and information that demonstrate the wide-spread utility of these markers to study PSCs at NMJs under various stressors . This includes data showing that PSCs continue to be the only cells expressing both GFP and dsRed (proxies for S100B and NG2) after crushing innervating motor axons and during the symptomatic stage of ALS in a mouse model of the disease characterized by significant destruction of NMJs . These data strongly indicate that these markers will be sufficient to study PSCs in diseases, injury and potentially during aging.Reviewer #3:The paper by Castro et al. describes the use of combined S100b and NG2 to identify perisynaptic  Schwann cells at the neuromuscular junction. Besides the identification of this marker combination, the most significant results presented are the transcriptional profile of these cells isolated by flow cytometry from muscle. Given the long-standing interest in identifying specific markers of PSCs to allow their isolation and manipulation, these findings are important for the field. The image quality in the paper is excellent, and the quantification and statistics are rigorous and convincing. A few items would further improve the manuscript and data presentation.+ cells in muscle may be (recognizing there may be multiple cell types). This would help in future studies attempting to use a similar intersectional approach to study PSCs and also in the interpretation of the current RNA-seq data from this population .The authors should comment on what the other NG2We agree, see response to Essential revisions.+/NG2+ cells versus either single marker is a potentially very useful resource for the field. As such, it should include some additional information to help rank candidates of interest, including read count and fold change .The list of genes in Supplementary file 1 that also show enrichment in the S100bWe agree, see response to Essential revisions.There is a lot of future potential to be based on this work . Addition of such studies would strengthen this paper, but also require significant time and effort and exactly which of these studies would be most important and most informative is hard to predict. Therefore, the intrinsic value of publishing the identification of these markers and the list of PSC-enriched genes is noted as it will allow the field to subsequently pursue these additional experiments.