Chimeric antigen receptor T cell therapy (CAR-T) represents a promising and exciting new therapy for hematologic malignancies, where prognosis for relapsed/refractory patients remains poor. Encouraging results from clinical trials have often been tempered by heterogeneity in response to treatment among patients, as well as safety concerns including cytokine release syndrome. The identification of specific patient or treatment-specific factors underlying this heterogeneity may provide the key to the long-term sustainability of this complex and expensive therapy. An individual patient data meta-analysis (IPMDA) may provide potential explanations for the high degree of heterogeneity. Therefore, our objective is to perform a systematic review and IPDMA of CAR-T cell therapy in patients with hematologic malignancies to explore potential effect modifiers of CAR-T cell therapy.We will search MEDLINE, Embase, and the Cochrane Central Register of Controlled Clinical Trials. Studies will be screened in duplicate at the abstract level, then at the full-text level by two independent reviewers. We will include any prospective clinical trial of CAR-T cell therapy in patients with hematologic malignancies. Our primary outcome is complete response, while secondary outcomes of interest include overall response, progression-free survival, overall survival, and safety. IPD will be collected from each included trial and, in the case of missing data, corresponding authors/study sponsors will be contacted. Standard aggregate meta-analyses will be performed, followed by the IPD meta-analysis using a one-stage approach. A modified Institute of Health Economics tool will be used to evaluate the risk of bias of included studies.Identifying characteristics that may act as modifiers of CAR-T cell efficacy is of paramount importance and can help shape future clinical trials in the field. Results from this study will be submitted for publication in a peer-reviewed scientific journal, presented at relevant conferences and shared with relevant stakeholders.The online version contains supplementary material available at 10.1186/s13643-022-02158-1. Patients with CD19+ hematologic malignancies have a very poor prognosis in the relapsed or refractory setting. For example, patients with relapsed diffuse large B cell lymphoma after autologous stem cell transplant have a median survival of 10 months . ChimeriAlthough most clinical trials using CD19 CAR-T cells have generally been relatively small, evidence to date has demonstrated durable responses, suggesting that many patients who respond are cured of their underlying malignancy –9. These5 to 1 × 1010 cells/kg. Using individual patient data (IPD) meta-analyses may present an opportunity to examine patient-level characteristics which may modify the effect of CAR-T cell therapy.Our previous systematic review explored the efficacy and safety of CAR-T cell therapy in patients with any form of malignancy . Sixty sIn the last two decades, the use of IPD has become increasingly popular as it provides many statistical and clinical  advantages over traditional, aggregate-level data meta-analyses . IPD metTherefore, we believe an IPD approach has the potential to identify important subgroups of patients that may be more responsive to the therapeutic efficacy of CAR-T cell therapy. Our objective is to conduct a systematic review and individual patient data meta-analysis of CAR-T cell therapy in patients with hematologic malignancies to explore potential effect modifiers of CAR-T cell therapy.This systematic review protocol follows the Preferred Reporting Items for Systematic reviews and Meta-Analysis Protocol (PRIMSA-P) guideline  ; therefoOur intervention is chimeric antigen receptor T cell therapy. There will be no restrictions based on therapeutic dose, the number of therapeutic administrations, CAR-T target, CAR-T co-stimulatory domain, etc.Studies with or without comparators will be included.The primary outcome of interest is complete response. Secondary outcomes include overall response, disease progression, relapse, overall survival, and adverse events . Tertiary outcomes of interest include patient experience, health-related quality of life, and health utility measures.We will include all interventional studies. Observational studies  will be excluded.Searches will be conducted in the MEDLINE , Embase (OVID interface), and the Cochrane Central Register of Controlled Trials (Wiley interface) databases from October 2017 to present. This represents the date at which the search from our previous review was last run . We willThe literature search used in our previous review will be used as a guide . The fieResults of the literature search will be uploaded to Distiller Systematic Review Software . The titles and abstracts will be independently reviewed by two reviewers using the predefined inclusion criteria as described above. To refine the screening question and to establish a high level of inter-rater correlation (kappa > 0.8), a calibration test involving ten studies will be performed before screening begins formally. The full text will be accessed for all titles that meet the inclusion criteria or in case of uncertainty. Two review authors will assess the full reports for eligibility. A third-party member will be consulted in order to resolve disagreements. The reasons for excluding studies will be recorded. For non-English full text articles, we will contract Ottawa Hospital faculty or employees with fluency in the language of the article to assist in determining article eligibility. The study selection process will be documented and reported using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flow diagram.Data extraction forms will be developed in DistillerSR® by the study team in order to capture all relevant information from each included study. Two reviewers will extract all relevant data from the included studies using this extraction form. Five studies will be used for calibration, and the review team will also be consulted for guidance if the data extraction form needs to be revised. Any disagreements will be reconciled through consensus and, if necessary, a third party will make a final decision. Where uncertainty is identified, or data of interest is not reported, study authors will be contacted for more information.We will collect basic study characteristics , study-level patient data , and intervention characteristics will be similar to our previous review  . In this case, complete response rates at the longest follow-up provided will be extracted and analyzed. The duration of the complete response will be collected. Secondary outcomes include overall response, progression-free survival, relapse, overall survival, and adverse events . Overall response will be defined as the sum of partial and complete responses. Tertiary outcomes of interest include patient experience, health-related quality of life, and health utility measures.We will use a modified version of the Institute of Health Economics tool to assess risk of bias , 29. ThiI2 statistic will be used to assess statistical heterogeneity. Alternative funnel plots (specific to single-arm studies) will be used to assess publication bias [Our data analysis will consist of two approaches. First, we will perform the traditional, aggregate data approach. Briefly, dichotomous data  will be analyzed and presented in a proportion (truncated between 0 and 1) with 95% confidence intervals. Using Comprehensive Meta-Analysis , we will use a random-effects model (DerSimonian and Laird) to pool outcomes. The Cochrane ion bias . The quaion bias .Second, we will perform an IPDMA, which will be used to explore the effect of patient-level characteristics on our identified outcome measures. For the IPDMA, a one-stage approach will be used, which synthesizes the IPD from all included studies in a single step, while simultaneously accounting for the clustering of patients within studies . SpecifiNext, we will perform subgroup analyses at the patient-level, as subgroup exploration at the patient-level is the primary purpose of our study. We will explore the effects of patient-level covariates on the efficacy (complete response) and safety (adverse events) of CAR-T cell therapy. Covariates of interest include sex, age, cancer type, cancer stage, previous number of treatments, use of lymphodepletion, use of bridging therapy, follow-up period, duration of response, CAR-T dose, number of CAR-T cell infusions, time between leukapheresis and infusion, CAR-T source , CAR-T formulation, and co-stimulatory domain used. These covariates of interest have been chosen based on findings from our previous systematic review of CAR-T cell therapy, as well as discussions with clinical experts on the review team , 35. CanInstitutional ethics approval is not required for this study. Results from this review will be published in a peer-reviewed scientific journal and presented at appropriate scientific conferences. The final reporting of this manuscript will follow the guidance set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses IPD statement . FinallyIn developing this protocol, patients and members of the public were not involved. However, we have an ongoing relationship with two patient partners for CAR-T research, and we plan to involve our patient partners going forward in the project, specifically around the interpretation and disseminate of results. Our group has had a fruitful relationship with patient partners in the past for CAR-T-related research , involviThe results from our project will have the potential to shape future treatment and research in the field of CAR-T cell therapy. The heterogeneity seen in efficacy both between and within clinical trials has been a detriment to the advancement of the field of CAR-T cell therapy as the variability in patient and therapeutic characteristics limited our ability to draw certain conclusions and to evaluate the impact of important clinical and intervention characteristics such as patient sex and age or dosing characteristics. By using individual patient data, as opposed to data aggregated at the study level, we are increasing our ability to identify important characteristics which may be modifying the efficacy of CAR-T cell therapy. The impacts of IPD meta-analyses on trial design can range from comparator selection, to population and outcome definition , 19, to Additional file 1. PRISMA-P  2015 checklist.Additional file 2. Sample Search Strategy.


Integrating magnetic resonance (MR) into radiotherapy planning has several advantages. This report details the clinical implementation of an MR simulation (MR-planning) program for external beam radiotherapy (EBRT) in one of North America's largest radiotherapy programs.An MR radiotherapy planning program was developed and implemented at Sunnybrook Health Sciences Center in 2016 with two dedicated wide-bore MR platforms (1.5 and 3.0 Tesla). Planning MR was sequentially implemented every 3 months for separate treatment sites, including the central nervous system (CNS), gynecologic (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus. Essential protocols and processes were detailed in this report, including clinical workflow, optimized MR-image acquisition protocols, MR-adapted patient setup, strategies to overcome risks and challenges, and an MR-planning quality assurance program. This study retrospectively reviewed simulation site data for all MR-planning sessions performed for EBRT over the past 5 years.From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all computer tomography (CT) simulations (CT-planning) performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of planning MR/CT increased from 3% of all planning sessions in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%).Detailed clinical processes and protocols of our MR-planning program were presented, which have been improved over more than 5 years of robust experience. Strategies to overcome risks and challenges in the implementation process are highlighted. Our work provides details that can be used by institutions interested in implementing an MR-planning program.The online version contains supplementary material available at 10.1186/s13014-023-02209-4. The evolution of radiotherapy in recent decades has been driven by increases in target dose, target conformity, and delivery accuracy made possible by the introduction of planning computed tomography (CT). That shift from 2D X-ray-based planning, approximately 20 years ago, gave way to subsequent implementation of intensity-modulated radiation therapy (IMRT), image-guided radiation therapy (IGRT), and high-dose stereotactic body radiotherapy (SBRT) . DespiteMR offers several advantages over CT scanning and other image modalities. This includes superior soft-tissue contrast from T1 and T2-weighted imaging, the capacity to assess tumour extent and perfusion with gadolinium-based contrast imaging, and the ability to carry out specialized MR-based imaging such as magnetization-transfer and contrast-enhanced saturation transfer (CEST) imaging for metabolic assessments of tumour extent and response . In geneFor the purposes of radiation planning, in most radiation oncology workflows, a diagnostic MR (secondary image) is registered to a planning CT (primary image) using rigid and deformable fusion methods as needed. This process, however, is subject to co-registration errors, where possible sources of registration error include differences in patient positioning, short term physiologically-expected changes in organ shape (such as due to respiratory motion or bladder filling), or target tumour size changes due to the time elapsed between the diagnostic MR and planning CT , 6. OtheOne of the best alternatives to optimize the use of MR for radiotherapy planning is integrating MR into the planning workflow, known as MR-simulation or MR-planning . ImplemeIn the last 5 years, two dedicated MR platforms (1.5 and 3.0 Tesla) were installed in the Radiation Oncology Department of the Sunnybrook Health Sciences Center, and an MR-planning program was developed and implemented. This report aims to describe in detail the experience in the clinical implementation of MR-planning for external beam radiotherapy (EBRT) and highlight the strategies to overcome encountered risks and challenges so it can be implemented by interested institutions.An MR-planning program was developed and implemented from 2016 to 2021 at the Radiation Oncology Department of the Sunnybrook Health Sciences Center. The clinical implementation is detailed here, including developed workflow, optimized MR image acquisition protocols, MR-adapted patient setup, radiofrequency (RF) coil placement, strategies employed to overcome the encountered risks and challenges, and an MR-planning quality assurance (QA) program. Data on planning site were collected from the treatment planning system (TPS) for all the MR-planning activities for EBRT from July 2016 to December 2021.For MR-planning, two dedicated MR machines were used. The first was a Philips Ingenia system with a magnetic field of 1.5 T, and the second a Philips Ingenia Elition X system with a magnetic field of 3.0 T. Both scanners were equipped with a 70 cm bore, external laser systems for registration with CT-coordinate systems, and flat and curved tabletops. For MR-safety purposes, the American College of Radiology (ACR) safety zones II-IV were instituted with badge-access required, and a 5-gauss line was demarcated inside scan rooms.A workflow was implemented in which the radiation oncologist assigns a care plan (CP) in a patient's chart using MOSAIQ Oncology Information Systems . The CP automatically generates a set of pre-defined quality checklists (QCLs) specific for each treatment  and contains the entire workflow for planning and treatment delivery. Along with the CP, the Radiation Oncologist completes custom fields that include CT/MR-planning scheduling, MR-safety screening, dose/fractionation, and patient setup. A QCL is automatically forwarded to the radiation department that then schedules the CT simulation (CT-planning) and MR-planning, preferably immediately consecutively.The CT-planning is then carried out according to the physician's order and institutional protocols, ensuring MR-compatible immobilization devices. The MR safety form is re-checked before MR-planning with patients since all patients are required to pass a screening process at least twice. After MR-planning, the radiation therapist proceeds with the CT-MR co-registration, which is later re-checked by the radiation oncologist and/or medical physicist.The important sequences for planning MR scans were selected for each anatomical and disease simulation site. The pulse sequence parameters were optimized to meet radiation planning needs, including reducing the voxel size to maximize spatial resolution, reducing slice thickness for optimal resolution, removing or minimizing gaps between slices, and increasing the field-of-view (FOV) for specific protocols  , 9. AddiTherapists with dual certification for radiation therapy and MR performed all MR scans. Central nervous system  was the first site to be implemented because it encompassed the highest volume of patients that would benefit from the MR-planning and had the least complex MR imaging process. After sufficient clinical experience with the CNS planning process, gynecology (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus MR-planning were sequentially implemented every 2–3 months.The goal of planning MR scans was to replicate the patient's setup on the planning CT. In cases where this is not possible, for instance, due to the limitation of accessories, the patient's positioning and immobilization on MR-planning were made as similar as possible to the CT-planning. Site-specific setups are detailed in Table It was identified that MR-planning was sometimes performed without a prior diagnostic MR and some sequences that could have been useful for diagnostic purposes were eventually absent. To overcome this limitation, additional sequences were added incrementally in the MR-planning protocols  for differential diagnosis purposes. As these sequences are not routinely required for planning, they were not detailed.Patients were positioned with no immobilization devices on a curved MR tabletop, using a head coil, similar to the usual diagnostic setup. A hybrid 3-point thermoplastic mask was customized for immobilization for the CT-planning but not used for MR-planning, as the skull allows perfect CT-MR co-registration. This is supported by the literature as there is no difference in image quality or movement artifacts when comparing mask immobilization versus standard diagnostic setup . All theThis section describes the MR-planning of the head and neck, cervical and high thoracic spine, upper esophagus (T5 and above), and brachial plexus. Patients were routinely immobilized for CT-planning with a 5-point thermoplastic mask and arms facing down. This accessory was perfectly compatible with MR-planning, and therefore the setup was identical for both. The posterior, anterior, and flex coils were used for HN, upper esophagus, and brachial plexus, and the posterior and flex coils were used for the cervical and upper thoracic spine.For spine SBRT, the radiation oncologist defined MR scan limits, which generally included 1–2 vertebrae above and below the target. MR-planning was routinely performed with no contrast; however, it was used in selected cases  at the physician's discretion.For brachial plexus imaging, patients were shifted toward the contralateral side, whenever possible, to bring the ipsilateral brachial plexus closer to the MR isocentre. Contrast was not routinely required for brachial plexus contouring, but it could be considered for improving tumour delineation at the physician's discretion.The MR-planning reproduces the same setup as CT-planning. Patients were positioned supine on a flat tabletop with arms above the head supported by a vacuum cushion . However, the Vac-Lok was omitted in circumstances where it did not fit inside the bore due to patient’s physical habitus. Alignment was based on the skin marks, and flex and posterior coils were used.This section describes the MR-planning of SBRT treatments of the thoracic, lumbar, and sacral spine, abdomen, and pelvic bones. Patients are routinely immobilized for CT-planning with a whole-body vacuum cushion , head support, and arms above the head. This setup, however, was not fully compatible with MR-planning because the Body FIX is too wide and long to fit inside the bore. Therefore, MR-planning was carried out with the patient using no immobilization accessories, with arms above the head. A curved tabletop was used to mimic the shape of the patient's back on the Body FIX and to approximate the patient to the posterior coil, which was especially important for spine SBRT. The posterior coil was used for the spine, while the anterior coil was added for abdominal and pelvic bones SBRT.As previously stated, contrast was not routinely necessary for spine and pelvic bones but could be used with paraspinal disease at the physician's discretion. Additionally, MR imaging was acquired on free-breath for abdominal tumours to match tomography acquisition.This topic describes the MR-planning of non-SBRT treatments of the lower esophagus (T6 and below) and abdomen. Patients were generally positioned for CT-planning and MR-planning with head support, arms above the head, flat tabletop, and knee-fix in place. The patient's tattoos were aligned to ensure the same setup. Given that most patients with abdominal tumours underwent planning with four dimensions-CT (4D-CT) and treatment with free-breathing, the MR-planning scan was acquired using free-breathing in order to mimic the averaged scan of the 4D-CT. Anterior and posterior coils were used.This topic describes the MR-planning of gynecologic, prostate, rectal, and anal cancer. Patients receiving pelvic radiation were positioned similarly for CT-planning and MR-planning. The setup consisted of head support, arms on the chest, and W foam on a flat tabletop. The MR-planning was carried out immediately after CT-planning in order to minimize time elapsed between scans and avoid bladder or rectum filling which would lead to volume differences. Posterior and anterior coils were used.Particular attention was given to gynecologic and anal tumours. CT-scans of uterine malignancies were acquired with full bladder and MR with both full and empty bladder to account for the dependence of uterus positioning on bladder filling. Patients with vulvar and anal canal neoplasms were positioned on CT-planning with a vacuum cushion for the legs in a frog-leg position, and the MR-planning should replicate the frog-leg position as much as possible. In most cases, this configuration was fully compatible with the MR-planning as the cushion was used on the distal part of the patient's body. The scan typically extended beyond external genitalia inferiorly.An initial limitation of implementing MR-planning was a shortage of radiation therapists with clinical MR experience, specifically those holding dual MR and radiation therapy certification. Most radiation therapy training programs in Canada still provide only CT-based training; consequently, more than 90% of the department was unfamiliar with MR platforms and did not have any MR background. In order to overcome this challenge, specific recruitment and intensive training were put in place by setting up small learning groups targeted toward each treatment site to address MR knowledge gaps. In the first year of implementation, work was carried out by a limited number of experienced MR technologists with radiation planning background (10 + years) and then supported by newly recruited radiotherapy staff with MR certification but limited MR experience.Another challenge from a staff perspective was shifting physicians’ culture and mindset from CT-based to MR-based planning. Certain site groups familiar with contouring on MR imaging were more enthusiastic and moved quickly to adopt MR-planning . In contrast, other groups used to contouring on CT imaging only were relatively later adopters due to the learning curve of a newly implemented method. Radiation oncologists not habituated to MR images needed specific training in interpreting multiple MR sequences and using them for contouring purposes, which was initially perceived as an increased physician contouring workload. However, this barrier was overcome as they became comfortable delineating on MR imaging, and the benefits of MR-planning became more evident.We identified a lack of MR safety knowledge among the members of our department. Thus, an MR-safety program was established following the American College of Radiology and Canadian Association of Radiology guidelines. A dual-certified therapist (MR-Radiotherapy) was assigned the departmental role of MR safety officer after acquiring certification from the American Board of Magnetic Resonance Safety. In addition, two Radiation Oncologists acquired formal certification from the American Board of Magnetic Resonance Safety and became MR-Medical Doctor Directors supporting the MR safety program in our department.We encountered challenges due to the incompatibility of some immobilization accessories, which limited the reproducibility of selected CT-planning setups. For example, the Body Fix is one of the most used accessories for SBRT immobilization, but it is not compatible with MR-planning due to its shape and size. Besides compromising image quality by elevating the patient some centimeters away from the posterior coil and the MR isocenter, the Body Fix is too long and wide to fit inside the bore and under the anterior coil. Smaller vacuum cushions  can be used as an alternative to the Body Fix, but still, the setup is highly dependent on the patient’s physical habitus. In cases where the MR-planning setup was not identical to the CT-planning, we adapted the patient’s positioning in the MR to be as close as possible to the CT, as detailed above and in Table And lastly, the MR coil selection was challenging when standard uses of coils in a diagnostic imaging department were incompatible with the CT-planning setup. Therefore, in these circumstances, the MR-planning was adapted using non-standard coil configurations to ensure compatibility with the radiotherapy setup and, at the same time, produce diagnostic-quality images. Breast planning is an example that was carried out without a conventional coil placement, as patients need to be prone to use the MR breast coil. Instead, patients were positioned in the supine radiation treatment position with the extremity (flex) coils placed over the breasts. For HN cancer patients, extremity (flex) coils were used along with a torso coil placed on a bridge (holder) above the patient's head, neck, and upper torso to be compatible with the thermoplastic masks. And for prostate cancer, planning was carried out without an endorectal coil.Claustrophobia is the most common challenge for patients undergoing MR imaging. Sublingual benzodiazepines are very helpful in facilitating the procedure; however, some patients may have problem completing the planning session despite taking the prescribed medication.Pain is another prominent issue, as patients can have difficulty maintaining motionless or even completing the MR planning session. This occasionally happens in patients with locally advanced head and neck cancer as they need to stay immobilized in a tight 5-point thermoplastic mask for over 30 min, or with bulky bone metastases. Our policy is to prescribe these patients potent analgesics to provide pain relief. Moreover, MR-planning may be longer than the respective diagnostic MR imaging, which could be challenging for patients in pain. The longer scan times result from thinner slices and higher resolution for MR planning. Therefore, one alternative for patients struggling to complete MR-planning despite analgesics is to streamline MR sequences essential for contouring  to shorten the image acquisition time.From the technical aspect, about one-third of our patients have internal medical devices, and often the implant model and MR-safety profile are unknown. When a medical device is present within the patient’s anatomy, we proceed with a cautionary risk–benefit analysis with a multi-disciplinary group of experts (including MR physicists and the radiology department), acknowledging that the main risks include imaging artifacts or implant motion/malfunctioning due to the magnetic field. In situations where MR is essential  but could be associated with patient harm, alternatives are considered not to delay immediate treatment. In the case of a not MR-conditional pacemaker, such alternatives can include changing the patient’s device or scanning the patient with constant monitoring in the presence of a cardiology and pacemaker team. Nevertheless, in our experience, most internal medical devices were successfully managed, and the MR-plannings were carried out safely with adequate MR images for contouring purposes.An MR-planning machine QA program was implemented to ensure safety, operability, and high-clinical performance. Our QA program is aligned with the recommendations of the latest MR-safety guidelines   were scanner script-driven and performed weekly. The analysis was automated, requiring only 15 min per session while meeting the National Electrical Manufacturers Association (NEMA) MR standards. ACR large phantom tests were carried out monthly as an independent alternative to PIQT. For monthly 3D geometric uncertainty measurements, evaluations alternated between the Philips Geometric QA phantom and an independent option . Relative changes in system performance were observed by tracking these data and investigating measurements that were outside of nominal readings. The detailed QA tests and frequency are described in Additional file From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all planning CT performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of MR/CT-planning sessions increased from 3% of all simulations in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%). Figure We described the clinical implementation of MR-planning for several treatment sites along with relevant technical details. Our study is significant as it details protocols and processes developed in-house to deliver radiation planning scans at diagnostic quality, improved over 5 years of experience, and with almost nominally nine-thousand MR scans. Although there are guidelines and recommendations for the development and implementation of a MR-planning program , 9, 13, Our report is unique in addressing protocols for planning MR of sites that are not commonly detailed in the literature, such as breast or brachial plexus, and covering almost all tumour locations in the body. Even though planning MR is not routinely used for adjuvant breast radiotherapy, there has been growing interest in MR for partial breast irradiation, breast SBRT, and brachial plexus recurrences , 24–26. One of the strengths of our methodology was the sequential implementation of a single treatment site every 2–3 months, starting with the most straightforward planning processes and progressively moving towards more complex ones. This allowed the department and staff members to gain expertise and adjust strategies longitudinally. For each scan protocol, the reconstructed MR slice thickness was set up for optimal signal-to-noise ratio and time using standard MR-scanner interpolation to avoid gaps between the slices and to permit compatibility for co-registration. Moreover, the radiology department was consulted as needed to ensure that the pulse parameters being implemented for MR-planning were at the same time optimized for radiation purposes and met diagnostic quality requirements.There are several benefits of implementing an MR-planning session , 29, 30.Additionally, incorporating MR in planning workflow goes beyond improving contouring. Recently, MR has been integrated into radiotherapy platforms in place of the cone-beam-CT, namely MR-Guided Linear Accelerators (MR-LINAC), and treatment delivery on such technology has become online MR-guided , 31, 32.As radiotherapy progressively moves towards MR-based treatment, the next step would be to eliminate the planning CT in cases where it is not needed for target definition. The greatest challenge would be using MR alone for dose distribution calculation. The solution relies on algorithms developed to generate a synthetic CT (pseudo-CT) from MR-planning scans for dosimetric calculation purposes, a process known as MR-only workflow . The gaiIn conclusion, we describe processes and protocols developed in-house for the clinical implementation of an MR-planning program for several sites, which has been improved over 5 years of robust experience. Finally, the strategies to overcome the challenges were addressed, and the strengths of our process were discussed. Our work provides details that can be used by institutions interested in implementing an MR-planning program.Additional file 1. Table S1: Quality Assurance Program for MR-Planning. Abbreviations: PIQT, Periodic Image Quality Test; SNR, NEMA, National Electrical Manufacturers Association; ACR, American College of Radiology; MR, magnetic resonance; RF, radiofrequency.


The CRdb database comprised a total of 647 CRs and 2,591 ChIP-seq samples from more than 300 human tissues and cell types. These samples have been manually curated from NCBI GEO/SRA and ENCODE. Importantly, CRdb provided the abundant and detailed genetic annotations in CR-binding regions based on ChIP-seq. Furthermore, CRdb supported various functional annotations and upstream regulatory information on CRs. In particular, it embedded four types of CR regulatory analyses: CR gene set enrichment, CR-binding genomic region annotation, CR-TF co-occupancy analysis, and CR regulatory axis analysis. CRdb is a useful and powerful resource that can help in exploring the potential functions of CRs and their regulatory mechanism in diseases and biological processes.Chromatin regulators (CRs) regulate epigenetic patterns on a partial or global scale, playing a critical role in affecting multi-target gene expression. As chromatin immunoprecipitation sequencing (ChIP-seq) data associated with CRs are rapidly accumulating, a comprehensive resource of CRs needs to be built urgently for collecting, integrating, and processing these data, which can provide abundant annotated information on CR upstream and downstream regulatory analyses as well as CR-related analysis functions. This study established an integrative CR resource, named CRdb ( In the past biological studies, developments in epigenetics have significantly changed our understanding of the mechanisms that regulate physiological or pathological signals ,2. AberrSeveral databases associated with CRs have been developed by previous studies, which provide worthwhile information on the biological functions of CRs. For example, CR2Cancer  comprisehttp://cr.liclab.net/crdb/), which aimed to record massive available resources for anthropic CRs and provide substantial annotations and analysis functions of CRs. The current version of the CRdb database comprised a total of 647 CRs and more than 2,500 CR-associated ChIP-seq samples from more than 300 human tissues and cell types, while the ChIP-seq samples are nearly twice as many as the other databases. This study analyzed the ChIP-seq data and identified CR-binding regions. CRdb emphatically provided the circumstantial and numerous (epi) genetic annotations in CR-binding regions by processing and integrating large-scale high/low-throughput experimental data, including super-enhancers, enhancers, whole-genome shotgun bisulfite sequencing (WGBS), single-nucleotide polymorphism (common SNP), risk SNPs, linkage disequilibrium (LD) SNPs, expression quantitative trait locus (eQTL), topologically associated domain (TAD), chromatin accessibility (ATAC), DNase I hypersensitive signal (DHS), clustered regularly interspaced short palindromic repeats (CRISPR) and 3D chromatin interactions. The downstream target genes of CRs could also be found by five calculative methods in CRdb. Furthermore, CRdb supported upstream regulatory information and various functional annotations of CRs, including Gene Ontology (GO)   terms, pogy (GO) . CRdb caWe collected a list of human CRs from the database and literature ,18,20–22CR ChIP-seq samples were identified from NCBI Gene Expression Omnibus (GEO)  and EncyThe quality control for the CR ChIP-seq data was important because CR ChIP-seq samples were obtained from different source. For each ChIP-seq sample, we provided seven different quality metrics, such as number of sample reads within analyzed chromosomes, the estimated fragment length by cross-coverage method, SSD score RIP, and so on using the ChIPQC. We provided a link to display the detailed ChIP-seq quality in each CR ChIP-seq sample page for the convenience of the users. This quality control was used to evaluate the data for users, not strictly for classifying samples as pass or fail.CRs are crucial regulators of gene transcription, which can link regulatory cues from enhancers to promoters. Numerous genomic annotations on the regulatory element regions were collected as regulatory cues of CRs, including enhancers, super-enhancers, accessible chromatin, 3D chromatin interaction, DNA methylation, CRISPR and TAD. Besides, SNP on the CR-binding regions might affect the binding of various regulators, affecting the activity of the regulatory elements. Therefore, the information on common SNP, risk SNP, LD SNPs and eQTL was collected.For obtaining the regions of enhancers, we collected enhancer datasets from ENdb , EnhanceThe super-enhancer datasets were obtained from SEdb , which wEmerging evidence has revealed that CR-binding regions have high chromatin openness scores, which are useful for recruiting TFs and other transcription regulators. ATAC-seq and DNase-seq are extensively used to identify accessible chromatin regions across the genome . We downA complex relationship existed between the CR-binding regions and TAD/3D chromatin interaction. The disruption of chromatin interactive structure could lead to the dysregulation of downstream genes. To better understand whether CR-binding regions were TADs, we obtained TADs for 21 tissue types from 3D Genome Browser , and theA total of 37,302,778 human common SNPs were acquired from dbSNP . VCFToolDNA sequence that targets the CRISPR RNA sequences and the transcriptional region within 200 bp of the genomic region was shown by annotation of the CRISPR/Cas9 target sites ,50. The Overall, 32,099,123 methylation sites were downloaded from 450K array of ENCODE . We alsoCRs maintain chromatin structure and function by binding or catalyzing histone modifications, thereby affecting the transcriptional process of their downstream target genes. For identifying the downstream target genes of CRs, five different methods were used: (i) the BETA algorithm  was direExcept for the annotations of CR regulatory elements, the additional annotations of CRs  were obtained from various sources for the purpose of elucidating the biological function of CRs. The experimentally-supported CR-disease correlations in human were obtained from GAD  and DisGCRdb is a powerful and comprehensive platform for users to browse, query, analyze, visualize and download the basic and annotated information about CR of interest, and for biologists to explore the underlying functions and regulatory mechanisms of CR in disease and biological processes Figures  and 2A.The ‘Data-browse’ page in the CRdb database allows users to quickly search for CR using two different methods. Users can retrieve the corresponding CR by selecting ‘Function Type of CR’ , ‘Histone modification’ and/or ‘DNA methylation’  via the navigation bar on the left side of the page. Moreover, the right side of this page is an interactive table presenting the retrieval results from the alphabetical sorting function, and each CR in the table is hyperlinked to an individual CR page for further information Figure . AdditioCR overview. Users can obtain general information on the searched CR, including the CR name, uniport accession, protein names, the aliases, functional type of CR , number of diseases, number of pathways, upstream super-enhancer/enhancer/promoter region of CR, PMID of the study related to CR, and network consisting of CR and its regulated genes .s Figure Ci.ChIP-seq samples of CR. We used a list to present the basic information about these CR ChIP-seq smaples, including Sample ID, CR name, Biosample type, File accession and Source . Users can select a ‘Sample ID’ of interest to view the details about the ChIP-seq sample . For ChIP-seq peak annotation, the interactive table represents the peak ID, genome location, size, and detailed genetic and epigenetic information in the CR ChIP-seq regions. CRdb visualizes ChIP-seq peaks through ChIPseeker . In particular, the target gene weightiness of CRs, as a measure of the potential relationship between the CR and the target genes, was defined by calculating the sum of the prediction. This section could help researchers in judging the regulatory relation between CR and the target genes from multiple perspectives .s Figure Ciii.Upstream regulatory details of CR. For the details of upstream regulation, the table describes the information on the upstream regulatory regions of CR  and information on microRNA with a targeted relationship to the CR. By integrating the upstream and downstream regulatory information, users can establish a regulatory axis of upstream regulatory element-CR-downstream target genes .s Figure Civ.Additional information on CRs. The extra information included CR-related PPI, functional annotation, TCGA cancer survival map, disease information and expression  .) Figure Cv.CRdb provides a personalized and powerful genome browser through JBrowse v2.0.0 that helps users visualize regulatory information about human CRs by customizing traces of interest, including CR ChIP-seq regions, genes, SNP, super-enhancers, TAD, and so on.On the Search page, CRdb offers five query methods: ‘Search by CR’, ‘Search by CR function type’, ‘Search by target gene’, ‘Search by genomic region’ and ‘Search by Biosample term name’ Figure .‘Search by CR’ query, users can query multiple CRs via different IDs, including symbol, ENTREZ GENE ID, protein name and uniprot accession, and so on. Users can get a result table for the CRs of interest, showing the basic information of CRs. By selecting a CR name in the result table, users can obtain detailed information about the CR. In the ‘Search by genome region’ query, by inputting a genomic region, CRdb identifies the CR ChIP-seq peak regions overlapping with the submitted region, and then outputs a result table. Specifically, even if the ChIP-seq peak region of the CR intersects with only one base of the user-submitted region, that will also be displayed in the result table. Users can select ‘Peak ID’ in the result page, obtaining detailed information about the peak. In the ‘Search by target gene’ query, by submitting a gene of interest and selecting a target gene prediction method , and CRdb will extract all the CRs that may regulate this gene in the upstream region in the outcome table. Users can also select ‘the function type of CR’ and ‘the idiographic type’ in the ‘Search by CR function type’ query. CRs are divided into three major classes  based on the regulatory roles in epigenetics, and then histone modifiers and DNA methylators are further grouped into erasers, writers and readers according to their modification .In the fication ,75,76. C‘CR gene set enrichment’ analysis, users can submit a set of genes and set the threshold value of P-value/FDR, and then CRdb identifies the significantly enriched CR using the hypergeometric test. The background set for enrichment analysis has two options  that enable users to select different background sets for enrichment analysis. The experimentally validated CR target gene set obtained from TRRUST was used as the default background set for enrichment analysis, so as to improve the reliability of enrichment analysis. In the ‘CR-binding genomic region annotation’ analysis, when the user inputs the genomic region of interest (in .bed format), the CRdb identifies the CR that can be combined with the input genomic region. Particularly, users can customize the minimum proportion of the input genome region overlapping with the CR region in the analysis. After choosing one of CR, users can acquire the comprehensive annotation for its overlapping peaks. In the ‘CR-TF co-occupancy analysis’, users can obtain the number of co-binding peaks for the CR-TF pairs by inputting multiple CRs and TFs. Similarly, users can also input CR(s)/TF(s) to find all TFs/CRs that have a co-localization relationship with it. By clicking on the ‘Details’ button, users can obtain the detailed result containing Peak ID, Sample ID, Sample name, region, P-value, score and the sequence. In the ‘CR regulatory axis analysis’, users can submit a gene set of interest and select at least one pathway database , while also selecting the P-value/FDR, and CRdb will identify pathways significantly enriched for these genes using hypergeometric tests. Moreover, it can identify CRs on the downstream of pathway, thus providing regulatory information about these CRs.We designed and provided four analytical methods for biologists to elucidate the functional mechanisms of CR Figure . Gene seAll CR-related files  are supported for download on the ‘Download’ page. Users can promptly retrieve and download associated information Figure . MeanwhiUsers can share their CR-related ChIP-seq data in the CRdb. For ensuring the data quality control, CRdb recommends that users submit the corresponding GEO/SRA series number or the corresponding accessible URL for the raw data on the ‘Submit’ page. Moreover, the submitter is required to fill in the relevant information  for the submitted data, as well as the user's e-mail, to facilitate subsequent contact. We will determine the data-update time dynamically based on the sample size submitted by the user, ensuring the timely release of the data.EZH2 has been demonstrated to be a member of the Polycomb-group (PcG) family, forming multimeric protein complexes, which are involved in maintaining the transcriptionally repressive state of genes over successive cell generations. The EZH2 expression has been found to be altered in multiple cancers, such as breast cancer, esophageal cancer, liver cancer and so on. The expression level of EZH2 is closely related to the malignancy degree, treatment and prognosis of the tumor . EZH2 waet al. revealed that TF OCT1 occupied the binding site of EZH2 in an anoxic environment, a common condition of tumors, activating the expression of epithelial-mesenchymal transition (EMT) genes  genes . This deT) genes   genes . AccordiAtherosclerosis is a chronic inflammatory disease characterized by lipid deposition in the arterial wall. Atherosclerotic cardiovascular disease has been a major cause of morbidity and mortality worldwide . IncreasP-value, sequence information, type and cell line. Particularly, we found that EP300 cooperated with NF-ĸB was similar in the two HUAEC  samples that are most associated with atherosclerosis (Figure In the ‘CR-TF co-localization analysis’, EP300 and NFKB1 were used to explore the synergistic regulatory mechanisms and further verify the function of the CRdb Figure . We obses Figure . We seles Figure . STAT6 is Figure ,97. In as Figure . Meanwhis Figure . ConsequCRs are a class of specialized domain-containing enzymes that recognize, form and maintain an epigenetic state in a cell-context-dependent manner. It has been proved that the abnormal expression of CRs is related to multiple biological processes, and the dysregulation of CRs can lead to the occurrence, progression or deterioration of various diseases, such as cancer, inflammation and so on. Meanwhile, CR transcriptional activity was also governed by numerous of upstream regulators, such as TFs and cis-regulatory elements. Large number of studies demonstrated that CRs can regulate panoramic epigenetic patterns to influence multiple target genes simultaneously. Aberrant CRs provided disease cells an efficient mechanism to rewire pathological transcriptional regulatory circuits. Thus, deciphering CR-mediated transcriptional regulatory network is essential for understanding the molecular mechanisms of pathological and physiological processes. For instance, EP300 is largely acknowledged in cancer therapy for its advanced roles in SE organization and oncogenes transcription regulation. CR-Cistrome , CR2CancThe CRdb is the first comprehensive resource focusing on systematically revealing the regulatory mechanisms of CRs Table . ResearcIn the current version of CRdb, we integrated and processed a great number of CR-related ChIP-seq datasets and embedded abundant annotation information on CRs, which filled the gap of the precise identification of CR-related regulatory mechanisms in complex diseases or biological processes. CRdb showed numerous advantages of information and functions compared with other CR-associated databases Table . Neverthhttp://cr.liclab.net/crdb/.The research community can access information freely in the CRdb without registration or logging in. The URL for CRdb is gkac960_Supplemental_FilesClick here for additional data file.


The specific role and prognostic value of DNA repair and replication-associated miRNAs in gastric cancer (GC) have not been clearly elucidated. Therefore, comprehensive analysis of miRNAs in GC is crucial for proposing therapeutic strategies and survival prediction.  Firstly, clinical information and transcriptome data of TCGA-GC were downloaded from the database. In the entire cohort, we performed differential analysis in all miRNAs and support vector machine (SVM) was used to eliminate redundant miRNAs. Subsequently, we combined survival data and cox regression analysis to construct a miRNA signature in the training cohort. In addition, we used PCA, Kaplan-Meier, and ROC analysis to explore the prognosis value of risk score in the training and testing cohort. It is worth noting that multiple algorithms were used to evaluate difference of immune microenvironment (TME), microsatellite instability (MSI), tumor mutational burden (TMB), and immunotherapy in different risk groups. Finally, we investigated the potential mechanism about miRNA signature.  We constructed miRNA signature based on the following 4 miRNAs: hsa-miR-139-5p, hsa-miR-139-3p, hsa-miR-146b-5p, and hsa-miR-181a-3p. Univariate and multivariate Cox regression analyses suggested that risk score is a risk factor and an independent prognostic factor in GC patients. The AUC value of ROC analysis showed a robust prediction accuracy in each cohort. Moreover, significant differences in immune functions, immune cell content, immune checkpoint, MSI status, and TMB score were excavated in different groups distinguished by risk score. Finally, based on the above four miRNA target genes, we revealed that the signature was enriched in DNA repair and replication.  We have developed a robust risk-formula based on 4 miRNAs that provides accurate risk stratification and prognostic prediction for GC patients. In addition, different risk subgroups may potentially guide the choice of targeted therapy. Gastric cancer (GC) is one of the most common causes of death across the world . Its oveMeanwhile, miRNAs are endogenous noncoding RNAs ranging in length from 17 to 25 nucleotides that influence gene expression posttranscriptionally . IncreasAlthough there are a large number of studies based on Cox and LASSO regression analysis to identify risk signatures, there are fewer studies on signature in GC patients with the SVM method. In order to obtain robust and stable results, we used SVM and Cox regression analysis to construct a miRNA signature. In conclusion, the construction of a novel miRNA signature is critical for the prognosis prediction of GC patients with the goal of exploring potential effects of miRNAs on immunotherapy, TME, biological processes, and MSI status.The Cancer Genome Atlas (TCGA) database was searched for transcriptome data and included 45 normal samples and 389 GC samples. The UCSC Xena Browser contains clinical data on TCGA-GC. Their survival information, clinicopathology, and genetics were retrieved and analyzed further. TCGA-GC cohort was randomly divided into 1 : 1 and represented as training set and testing set. The RNA-seq transcriptome data in CPM format and corresponding clinical data of GC patients were extracted from the database, and only genes with CPM greater than 1 were considered.p value less than 0.05 to undertake multivariate Cox regression analysis. The expression levels of the miRNAs and coefficients were then used to construct risk signature. The following formula was used to calculate the risk score for each patient:Clinical data from GC cases in TCGA cohort were used to screen prognostic miRNAs linked with OS using univariate Cox regression analysis, and support vector machine (SVM) was used to eliminate redundant miRNAs. We selected miRNAs with We calculated the median score in TCGA-GC cohort to divide patients into two groups and identify the most significant differences in prognosis between the risk subgroups. To analyze the prediction performance of prognostic features on overall survival, Kaplan-Meier survival curves and ROC curves were used.Differential expression analysis (mRNAs and miRNAs) was performed using the limma package. TargetScan, miRTarBase, and miRDB tools were used to screen out target mRNAs. We overlapped target mRNAs and differential expression mRNAs. Finally, the above genes were analyzed for gene enrichment.p values and Pearson correlation coefficients were obtained based on the study. Immune checkpoint-related gene and human leukocyte antigen (HLA) gene expression levels may be linked to immune checkpoint inhibitor therapy response. We explored the difference in gene expression levels between the two groups.We used ssGSEA, XCELL, TIMER, QUANTISEQ, MCPCOUNT, EPIC, CIBERSORT, CIBERSORT-ABS, ESTIMETA, and TIDE algorithms for estimating the abundance of immune cells, immune-related pathway, immunotherapeutic response, and microsatellite instability (MSI) status. Using 45 normal samples as a control, we revealed that 138 were upregulated miRNAs and 60 were downregulated miRNAs. The volcano plot and heat map showed the 198 miRNA expression landscape Figures . In addip < 0.05). The results showed that the OS of patients with low risk was better than those of high-risk patients in the entire cohort (p < 0.001).To better evaluate the prognostic value of risk score, we performed ROC analysis, and the AUC value showed a robust prediction accuracy (AUC > 0.7) in each cohort, as shown in Figures e cohort , trainine cohort , and tese cohort . To detee cohort  and an ie cohort . SpecifiWe further analyzed the relationship between risk score and somatic mutation. The waterfall plot showed that patients in the low-risk group exhibited a wider range of mutations Figures . HoweverWe performed ANOVA for different risk patients and immune subtypes, and the differences were statistically significant . We alsoTargetScan, miRTarBase, and miRDB tools were used to screen out target mRNAs in 4 miRNAs participating in signature. Subsequently, we overlapped target mRNAs and differential expression mRNAs. Finally, a potential functional regulation network is constructed . To bettGastric cancer (GC) is widely regarded as one of the most common malignant tumors of the digestive system, with high morbidity and mortality, and has attracted more and more attention. A series of discoveries of miRNAs have made significant progress in the field of cancer, especially in immune . In rece+ T lymphocytes have also been demonstrated to cause lipid peroxidation in cancer cells and make cells more susceptible to ferrogenesis by releasing IFN [The four miRNAs involved in the modeling have been studied in gastric cancer. For example, SNHG3 functions in an oncogenic manner to drive GC proliferation, migration, and invasion by regulating the miR-139-5p/MYB axis . In addising IFN . As a reIn conclusion, this study utilized comprehensive bioinformatics to analyze and establish 4-miRNA risk score formula, including hsa-miR-139-5p, hsa-miR-139-3p, hsa-miR-146b-5p, and hsa-miR-181a-3p, ultimately to identify potential biomarkers for predicting GC progression. And further analysis and study finally revealed the functions and mechanisms of these miRNAs. Due to the small sample size of the control group used for miRNA analysis in this study, only limited data can be presented in the paper. In summary, our data need to be further investigated and validated in a larger patient population and explored in future research together.


Recent studies indicate that bladder cancer is among the top 10 most common cancers in the world . Bladder cancer frequently reoccurs, and prognostic judgments may vary among clinicians. As a favorable prognosis may help to inform less aggressive treatment plans, classification of histopathology slides is essential for the accurate prognosis and effective treatment of bladder cancer patients. Developing automated and accurate histopathology image analysis methods can help pathologists determine the prognosis of patients with bladder cancer.https://www.cancer.gov/tcga).In this study, we introduced Bladder4Net, a deep learning pipeline, to classify whole-slide histopathology images of bladder cancer into two classes: low-risk (combination of PUNLMP and low-grade tumors) and high-risk (combination of high-grade and invasive tumors). This pipeline consists of four convolutional neural network (CNN)-based classifiers to address the difficulties of identifying PUNLMP and invasive classes. We evaluated our pipeline on 182 independent whole-slide images from the New Hampshire Bladder Cancer Study (NHBCS)  collected from 1994 to 2004 and 378 external digitized slides from The Cancer Genome Atlas (TCGA) database : 0.86–0.94) on the NHBCS dataset and 0.99 (95% CI: 0.97–1.00) on the TCGA dataset. Additionally, we computed Kaplan–Meier survival curves for patients who were predicted as high risk versus those predicted as low risk. For the NHBCS test set, patients predicted as high risk had worse overall survival than those predicted as low risk, with a log-rank p-value of 0.004.If validated through prospective trials, our model could be used in clinical settings to improve patient care. The cancer stage consists of the location of the cancer cells and how far they have grown. Higher stages indicate whether the tumor has grown away from the surface. Urothelial carcinoma pathologic stages are named Ta (papillary tumor without invasion), TIS (carcinoma in situ (CIS)), T1 (tumor invades the connective tissue under the surface lining), T2 (tumor invades the muscle layer), T3 , and T4 . According to the WHO 2016 classification, NMIBC is divided into three groups: Ta, TIS, and T1, while MIBC is divided into T2, T3, and T4. In low-grade cancer cases, the cancer cells show morphology with less atypia, more closely resemble normal urothelial cells, and grow slowly. Clinical research has demonstrated that the most common bladder tumors are low-grade tumors.Papillary urothelial neoplasm of low malignant potential (PUNLMP) was first introduced by the WHO/ISUP in 1998 as a new entity of bladder cancer.The histological classification of bladder cancer has significant implications for the prognosis and treatment of patients. Moreover, detecting and classifying histologic patterns such as PUNLMP and low-grade urothelial carcinoma under the microscope is a time-consuming and challenging task for pathologists. Manual classification of bladder cancer histological patterns has a high error rate due to the similarity of histological features. Therefore, clinical information such as the cancer stage is commonly used for a more accurate prognosis. Automated image analysis using deep learning techniques can assist pathologists in providing faster and more consistent results. Additionally, these techniques can be improved by providing new data and associated annotated labels by several pathologists so that the model can be trained based on the expert opinion of multiple pathologists.,Automated image analysis methods to classify and visualize various cancer patterns in high-resolution whole-slide images can help pathologists avoid errors and reduce their assessment time.For the model development and evaluation, we used images from the New Hampshire Bladder Cancer Study or NHBCS.This dataset contains 838 whole-slide images from 1994 to 2004 as part of the NHBCS.We normalized the color intensity of patches and applied standard data augmentation methods, including random horizontal and vertical flips, random 90° rotations, and color jittering.We collected 378 whole-slide images from TCGA for external validation. The distribution of these whole-slide images used in this study is summarized in The tumor histologic subtypes in the NHBCS dataset were independently confirmed by two expert genitourinary pathologists from the Department of Pathology and Laboratory Medicine at Dartmouth–Hitchcock Medical Center (DHMC) based on a standard histopathology review. In the NHBCS dataset, 637 whole-slide images were categorized into papillary urothelial neoplasm of low malignant potential (PUNLMP), low-grade papillary urothelial carcinoma , high-grade papillary urothelial carcinoma , and invasive urothelial carcinoma (IUC). Among these slides, 34 were classified as carcinoma in situ (CIS). Because of the small number of available CIS cases, we removed them from our study. In addition, 31 cases were labeled as others, which were excluded from our study. We used 607 whole slides from four classes  in our analysis. We combined PUNLMP and low-grade whole-slide image cases into a single class because of their similarity, as they are both noninvasive and low-risk cancers. Additionally, high-grade and IUC cases were merged into one group because they are considered high-risk cancers.We considered the grade heterogeneity during the annotation of the WSI of the urothelial lesions, especially the noninvasive low and high-grade papillary urothelial carcinoma. The criteria of WHO classification of low and high-grade papillary urothelial carcinomaTwo pathologists manually annotated the whole-slide images in our internal NHBCS training set using the Automated Slide Analysis Platform (ASAP).In this study, we developed a deep learning-based model to distinguish between low- and high-risk bladder cancer cases, where the low-risk class includes PUNLMP and low-grade cases, and the high-risk class includes high-grade and invasive cases. This deep learning pipeline, named Bladder4Net, is shown in Analyzing large histology images using deep learning models requires substantial memory resources. Therefore, we split each whole-slide image into fixed-size patches (224 × 224 pixels) with 1/3 overlap. ResNet-18 is a light deep learning architecture. Therefore, it requires fewer computational resources to train, is faster during the inference time on large whole-slide images and is less prone to over-fitting. The Bladder4Net pipeline consists of four binary ResNet-18y-axis represents the prediction ratio, the x-axis represents each WSI sample, and the bar colors are related to predicting classes. In other words, this figure illustrates how prediction aggregations are performed; for example, when a WSI contains the PUNLMP class, the ratio of predictions is expected to be higher for its class.To classify whole-slide images, we aggregated patch-level prediction outputs. For each whole-slide image, we preprocessed the image by removing the white background and color markers. To aggregate the patch-level predictions, the ratio of patches from each class to the total number of patches from a slide was computed per whole-slide image. Bladder cancer is progressive, and there are mixed types of cancer cells in many whole slides. Therefore, there were some low-risk patches in high-risk whole-slide images. We used a Gaussian process classifier for whole-slide inferencing. This classifier was trained on the patch ratios of whole-slide images from the training set and evaluated on the same validation set used in the patch-level analysis. The patch ratios of each classifier were given as input to the whole-slide inference classifier. Low-risk images usually have a higher ratio of patches labeled as PUNLMP and low-grade patches. High-risk images typically have a higher ratio of high-grade and invasive patches. Moreover, we integrated the output of four binary patch-level classifiers to keep high-confidence patches and exclude low-confidence and normal patches in the whole-slide inference step. This process in our proposed pipeline is shown in We analyzed the survival time of patients for low- and high-risk classes. Survival time was calculated from the date of diagnosis to the date of death for patients who did not survive or to the date when the Death Master File was queried for patients who survived.To measure the efficacy and generalizability of our approach, we evaluated our trained model on 182 independent whole-slide images (WSIs) from the NHBCS dataset and 378 WSIs from the TCGA dataset. We used precision, recall, and the F1-score as evaluation metrics. The confusion matrix was also generated for error analysis. In addition, 95% confidence intervals were computed using the bootstrapping method with 10 000 iterations for all the metrics.In For the internal NHBCS test set, patients predicted as high risk had worse overall survival than those predicted as low risk, with a log-rank p-value of 0.004 . AdditioAmong 378 patients from the TCGA dataset, 367 were predicted to be high risk, and 11 were predicted to be low risk. Due to the small number of low-risk patients and the limited follow-up time, we limited our survival analysis to the first 24 months after the initial diagnosis. There was no death event reported during the follow-up for the low-risk group, and 35 death events were reported in the high-risk group in the first 24 months of follow-up, with a log-rank P-value of 0.04 . NotablyFor the NHBCS test set, patients predicted as high risk had worse overall survival than those predicted as low risk, with a log-rank p-value of 0.004 . The pat,,The WHO has updated its bladder cancer grading guidelines several times since 1973 to align them more closely with disease recurrence and progression.In recent years, deep learning models, such as convolutional neural networks or CNNs, have been applied to a variety of computer vision tasks as well as biomedical applications.As part of this study, we investigated the development of a multiclass CNN model with four labels, including PUNLMP, low-grade, high-grade, and invasive cases. Although this model achieved a reasonable performance at the patch level , some classes, such as PUNLMP and invasive cases, achieved suboptimal results. This outcome indicates that a single multiclass model cannot effectively handle the complexities of this task and achieve good performance and generalization for all four classes. Notably, differentiating between PUNLMP and low-grade types has the lowest accuracy rate among clinicians due to their morphological similarities.As the primary whole-slide level classification outcomes, we focused on identifying low- and high-risk groups for bladder cancer based on histology slides, where the low-risk class includes PUNLMP, and low-grade cases and the high-risk class includes high-grade and invasive cases. The differentiation between these two risk groups has a significant clinical impact on patient prognosis and treatment. For whole-slide inferencing, we built a Gaussian process classifier based on the distribution of the classified patches from each slide.To demonstrate the generalizability of our model,The earlier study on 838 whole-slide images from NHBCSFinally, we computed Kaplan–Meier survival curves for patients predicted as high risk versus those predicted as low risk for both the NHBCS and TCGA test sets. Patients predicted as high risk had worse overall survival than those predicted as low risk, with log-rank p-values of 0.004 and 0.039 on the NHBCS and TCGA test sets, respectively. Additionally, our predicted high-risk group in the NHBCS test had an estimated hazard ratio of 1.958  compared to the predicted low-risk group, which was slightly higher than the hazard ratio using the labels defined by the WHO/ISUP grading.Of note, we did not sub-classify the high-grade lesions further based on the percentage of high-grade areas or the low- to the high-grade ratio in the current study. However, for future research, we plan to evaluate the performance of our model for borderline lesions . The nested variant of urothelial carcinoma was classified as invasive urothelial carcinoma in high-risk cases. Our model classifies invasive urothelial carcinoma based on not only the cytological features but also other histologic features, such as the growth pattern and the stromal reaction. In this study, we did not annotate invasive urothelial carcinoma with histologic subtypes due to the limited number of cases for these variants. In future work, we plan to evaluate the performance of our model for different histologic subtypes of invasive urothelial carcinoma. Finally, we plan to include additional relevant variants and factors in our pipeline, deploy our developed approach as part of a clinical decision-support system in clinical settings, and conduct a follow-up prospective clinical trial with appropriate clinical metrics to evaluate the clinical impact of this work on pathologist performance and patient health outcomes. We envision the deep learning model could provide a second opinion to the pathologists while reviewing the bladder cancer specimens, enhance the accuracy and efficiency of their performance, and improve patient outcomes.Our implementation achieved the weighted average F1-score of 0.91 (95% CI: 0.86–0.94) for the internal NHBCS test set and 0.99 (95% CI: 0.97–1.00) on the external TCGA test set, which implies that is possible to leverage Bladder cancer recognition using whole slide images. In future work, we plan to expand our model to distinguish between high-grade invasive and high-grade noninvasive classes, which is clinically helpful to determine the progression and reoccurrence of bladder cancer. Because we had a limited number of muscle-invasive cases in our datasets, building such a model for this differentiation was not feasible in the current study. We plan to collect additional data and develop new data augmentation techniques, such as generative adversarial networks (GANs), to tackle the dataset imbalance. Such techniques can mitigate the effects of unbalanced data by preventing overfitting and thus improving overall performance.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Human-Computer Interaction Serious Games (HCI-SGs) set a novel domain in understanding player motivations in gaming, behavioral implications of game play, game adaptation to player preferences and need for increased engaging experiences. When the latter relate to health status, HCI-SGs can become a part of daily life as assistive health status monitoring and enhancement systems , we are delighted to announce that eight papers were accepted after a peer review process that included contributions of more than 20 high-quality international external reviewers and guest editors with expertise in the field of Human-Media Interaction. The accepted manuscripts highlight contributions and advances in the current literature, setting future avenues of research within the HCI-SGs domain, as presented in the next section.The current collection of articles provides validated research, including results from experiments, European projects and real-life applications, based on theories and game applications, in the specific field of HCI-SGs toward behavioral change, covering areas like psychology, (open) education, gamification, rehabilitation, wellbeing, physical and mental health, modeling, machine learning, mobile technology, disability, design process, adaptation, personalization, HCI, co-creation, and emotional intelligence see .Huang and Chen propose a game-based situational learning system as an anti-drug experiment with 53 junior middle school students (aged 13–15), to explore whether different personality traits result in different anti-drug responses. The authors collected 95 sets of codes  from students during the period of using the serious game-based situational learning system. The codes allowed the authors to extrapolate a behavioral transition diagram via Lag Sequential Analysis (LSA) using Generalized Sequential Querier (GSEQ 5.1) software. Different behavioral patterns  were identified, providing important guidelines for designing adaptive anti-drug education programs.Fernández-Avilés et al. applied results from the 82-item Motivational Trait Questionnaire (MTQ-long version) and the 3D Motivational Traits Game-based Objective Test (MT-GOT) to evaluate motivational traits. To assess the validity of the results of the measured motivational traits using the objective behavioral test 31 participants (with an average of 40 games per participant), whose motivational traits were evaluated and compared using these two methods, were recruited. The results from the statistical analysis suggest that the objective MT-GOT game can be a useful application to assess motivational traits as an alternative to the self-report MTQ questionnaire.Padilla-Zea et al. present the “Catch the Open!,” a 2D virtual web-based game, targeting Educators who intend to learn or have more knowledge about Open Education (OE) and Open Educational Practices (OEP) within a particular Higher Education Institution (HEI). The educational content integrated in the Catch the Open! Game was based on the OE framework, as an extension of an Erasmus+ OpenGame project. Involving 153 Educators from six HEIs, several tests and pilot studies were performed, both internally (in the consortium) and with potential end-users. Overall, the results show that the “Catch the Open!” game helped in learning more about OE and the gamified web-based interactive application was mostly rated to be useful for its purpose.Tlili et al. conducted a systematic review to critically explore and better understand the effects of game-based learning applications for learners with disabilities. Content analysis from 96 empirical studies showed important information related to each AT construct. The authors identified relevant gaps in this field, suggesting, that general and domain-specific recommendations/challenges to support practitioners that intend to use game-based learning for learners with disabilities.Using the Activity Theory (AT) approach, Menychtas et al. introduces a gamified design process for a mobile application (MediLudus) targeting patients in rehabilitation and aiming to maintain and improve their mental and physical health. The authors critically discuss key performance indicators  that are important to consider during the early evaluation phase of the application in terms of patient progress, including in particular motivation, interest, and degree of adherence to exercise programs.Theodoropoulos and Lepouras explore the effects of different high school programming environments, by developing games considering gender and personality characteristics. Three groups were considered in this study according to the use of Scratch, App Inventor and Alice 3D, in order to find potential biases based on gender, learning perception, usage and student personalities in the three experimental conditions. Data were collected using pre-/post-activity questionnaires, involving 163 students (aged 14–15 years). The authors found that all programming settings reveal different gender-, personality-, and emotion-related effects on students.Jimoyiannis et al.. Data from 92 Greek university students' attitudes to European identity, before and after playing the “RUEU?” game, were collected. The results show that both instructional interventions were effective to deliver academic content, but also to promote students' reflection at an attitudinal and emotional level.An interesting experimental study designed to explore the effectiveness of the educational “RUEU?” game, and to support higher education students in understanding the key socio-political issues regarding European identity was performed by Mahboobeh et al. address important insights, regarding the use of ICT-based tools for capturing the status of Parkinson's disease (PD) patients. Data derived from 27 PD patients at Stage 1 and 3 were analyzed regarding their interaction with the Personalized Serious Game Suite (PGS) and intelligent Motor Assessment Tests (iMAT) gamified environments. Five feature vector (FV) scenarios were fed into machine learning classifiers , in order to infer the stage of each PD patient. A Leave-One-Out Cross-Validation (LOOCV) method was adopted, and the experimental results revealed that a high (> 90%) classification accuracy can be achieved from both data sources (PGS/iMAT), showing the effectiveness of PGS/iMAT to efficiently reflect the motor skill status of PD patients. This further potentiates PGS/iMAT enhancement with machine learning techniques to infer the stage of PD patients.This Research Topic clearly shows that HCI-SGs can be transferable and applicable to several fields, such as education, rehabilitation, and training, as they can potentiate the (re)education and improve/sustain heath status of the end-users. The eight papers presented here are based on well-established theories/perspectives , showing that HCI-SGs can be specially designed to better support player's active learning, engagement and critical thinking within the game. However, in order to develop new applications, more innovative HCI tools and corresponding methodologies are required in the field. For example, the integration of artificial intelligence within the game co-design/development, including adaptation algorithms, has the capability to change/re-adapt the HCI-SGs at different levels of interaction.Finally, it is our hope that the scientific community and industry can benefit from the theoretical and practical contributions of this Research Topic, boosting further the field of HCI-SGs and emerging related-areas.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Physicists became interested in understanding how complex biological systems work from their basic building blocks, individual biomolecules. How they fold, move, interact, and how they enable the complex life forms on Earth. They brought in tools from physics, such as microscopes, lasers, photonic detectors, and numerous numerical methods. A new area of biology emerged, known as the single-molecule biophysics, where scientists can now see and manipulate individual biomolecules. The single-molecule toolbox has been applied to study the molecules of life, proteins, lipids, DNA, RNA, and their interactions, literally one molecule at a time, from single cells to complex organisms. These methods have opened new dimensions in our understanding of contemporary biology. In the last decade, it has been possible to do experiments that were fanciful hopes only a couple of decades ago. Investigating one molecule at a time provides clear insights into mechanistic details of the molecular machinery that were previously unattainable due to average blurring in traditional ensemble-averaged bulk studies. Single-molecule methods can provide detailed information about highly dynamic processes, short-lived or transient states, rare molecular events, molecular sub-populations, and non-uniform kinetics in individual molecules. Kinetics is also coming into focus as scientists begin to understand how biological processes are kinetically controlled, as they are more energy-efficient than overcoming considerable thermodynamic energy barriers of stable conformational changes. With advancements in bio-nanotechnology, understanding and manipulating such kinetically controlled systems have become more critical. Single-molecule methods are now widely adopted as an integral approach to contemporary biology.Bandyopadhyay and Mishra, in their comprehensive review, described how smFRET was applied to examine the secondary structures of DNA, such as hairpin, Holliday Junction (HJ), G-quadruplex (GQ), and i-motif. Just as a few examples, smFRET helped reveal the folding kinetics and conformational fluctuations of DNA hairpins. Similarly, it enabled studies of HJ dynamics, branch migration, and binding to branch migration enzymes such as the resolvase at the single-molecule level. Additionally, smFRET has helped reveal the multiple conformational states of GQs, their interconversion kinetics and interaction with helicases. Moving to larger DNA nanostructures, Pal, in their mini-review, described the application using smFRET to study the structural dynamics of DNA-based biosensors, drug delivery vehicles, nano-tweezers, walkers, and other bioassays. The large DNA nanostructures described here go beyond a single secondary structure and combine structural motifs and DNA origami structures.Single-molecule FRET (smFRET) is a powerful method to observe large conformational dynamics of DNA nanostructures on the order of 3–10 nm. Spinks et al. dived deep into the single-molecule insight into the dynamics of replicative helicases. The dynamics of helicases have been studied by a broad range of single-molecule methods, including optical traps, magnetic tweezers, smFRET, single-molecule fluorescence recovery after photobleaching (FRAP), and single-molecule fluorescence loss in photobleaching (FLIP). These single-molecule investigations revealed the intermediate states during unwinding and their dynamic interactions within the replisome–processes that ensemble methods cannot uncover. The review provided an overview of model replisome systems and their helicases from phages, prokaryotic, and eukaryotic cells, and how various single-molecule methods provided novel insights into helicase mechanism, including the active translocation and passive unwinding of DNA, the coordination of their subunits, the processivity and step sizes, as well as their interactions with the replisome.Helicases are motor proteins that translocate on single-stranded DNA to unwind double-stranded DNA during DNA replication. The comprehensive review from Kim et al. described how cell spreading on anisotropic nanopatterns depends on the molecular tension. The authors used the molecular tension probe on the anisotropic nanopatterns (800 nm ridge × 800 nm groove × 600 nm height) to elucidate how cells react to topographical cues and generate forces. Their experiment compared cellular morphology and distribution of adhesion strength. The DNA-based molecular tension probe labelled with ligand and fluorophore visualizes the forces generated by the receptor through DNA duplex rupture. The probes with different rupture thresholds were applied to two cancer cell lines. The highly invasive cancer cells exhibit significant morphological change and increased force generation, while the non-invasive cells showed fewer alterations in morphological and mechanical properties. Their findings revealed that topographical cues could affect the force applied by integrin at the subcellular level by different types of cell lines.One of the applications of DNA nanotechnology in a biological system is the molecular tension probes. The research report from Dey et al. described a new technique called Q-SLIP (Quenching-induced Step Length Increase in Photobleaching), which combines single-molecule photobleaching and fluorescence quenching to measure the solvent accessibility of proteins and their conformational states. The authors used tryptophan in solution as quenchers for rhodamine-B labelled peptides to study its interaction with a lipid membrane. When the residue labelled by the fluorophore becomes solvent-exposed, its lifetime increases due to exposure to quenchers, and vice versa when the residue becomes embedded within the bilayer. This was observed and quantified in single-molecule photobleaching experiments, providing insight into how the peptide is oriented and embedded in the lipid bilayer.New single-molecule methods open opportunities to investigate new biological problems. In their research paper, As advanced cutting-edge methods are being developed, single-molecule techniques will continue to make breakthroughs in molecular and cellular biology and decipher even more complex biological processes. However, it is even more fascinating to see the adoption of single-molecule techniques for highly sensitive clinical diagnostics and therapeutics. Single-molecule detection of individual biomarkers can improve disease diagnosis and treatment. The development of single-molecule biosensors opens up opportunities to monitor disease by uncovering hidden properties of individual molecules even at ultralow levels of biomarkers. We are on the verge of a new era of sensitive “at-home” testing devices and personalized medicine involving sophisticated single-molecule techniques.


The average fat mass in adults increases dramatically with age, and older people often suffer from visceral obesity and related adverse metabolic disorders. Unfortunately, how aging leads to fat accumulation is poorly understood. It is known that fat cell (adipocyte) turnover is very low in young mice, similar to that in young humans. Here, we find that mice mimic age-related fat expansion in humans. In vivo lineage tracing shows that massive adipogenesis (the generation of new adipocytes), especially in the visceral fat, is triggered during aging. Thus, in contrast to most types of adult stem cells that exhibit a reduced ability to proliferate and differentiate, the adipogenic potential of adipocyte progenitor cells (APCs) is unlocked by aging. In vivo transplantation and 3D imaging of transplants show that APCs in aged mice cell-autonomously gain high adipogenic capacity. Single-cell RNA sequencing analyses reveal that aging globally remodels APCs. Herein, we identify a novel committed preadipocyte population that is age-specific (CP-A), existing both in mice and humans, with a global activation of proliferation and adipogenesis pathways. CP-A cells display high proliferation and adipogenesis activity, both in vivo and in vitro. LIFR serves as a functional maker of CP-A, which promotes CP-A proliferation. Together, these findings define a new fundamental mechanism involved in fat tissue aging and offer prospects for preventing and treating age-related metabolic disorders.